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PMC517723
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Background
==========
*Nicotiana attenuata*Torr. ex Watson (Solanaceae) (synonymous with *N. torreyana*Nelson and Macbr.) is an annual native to the Great Basin Desert of California, Nevada, Idaho, and Utah (USA) \[[@B1]-[@B3]\] and primarily occurs in large ephemeral populations (typically for less than 3 growing seasons) after fire in sagebrush and pinyon-juniper ecosystems, in small persistent (for \>3 growing seasons) populations in isolated washes, and as a roadside weed after new construction in a previously undisturbed area \[[@B2],[@B4]-[@B9]\]. Positive and negative control by environmental signals over germination from long-lived seed banks (estimated to be minimally 150 y \[[@B10]\] can account for its occurrence in these habitats. Specifically, dormant *N. attenuata*seeds are stimulated to germinate by unidentified factors in wood smoke \[[@B9]\] but are inhibited by factors, including ABA and 4 terpenes (bornane-2,5-dione, 1,8-cineole, β-thujaplicin and camphor \[[@B11]\] which leach from the litter of the dominant vegetation. Genotypes of *N. attenuata*produce seeds that vary in their genetically-determined primary dormancy \[[@B9]\]. Regardless of their degree of primary dormancy, seeds that are shed in unburned habitats with significant accumulations of litter develop strong secondary dormancy in response to the negative germination cues. If the seeds are shed into habitats without significant litter accumulations (e.g. in washes or roadside habitats), seeds without dormancy germinate. When fires pyrolyze the litter layer, removing the germination inhibitors and saturating the soils with smoke-derived germination stimulants, the seed bank responds with a dramatic, synchronized germination response the following growing season during favorable moisture and thermal regimes.
This well-characterized germination behavior likely affects the genetic structure of this potential annual. Genetic structure of a population results from mutations, gene flow (as mediated by pollen and seed dispersal), drift, and selection, all acting in the context of an organism\'s life history traits \[[@B12]\]. Genetic differentiation may be more prevalent between primarily dormant and non-dormant populations, namely between plants found ephemerally (in burns) and those occurring more persistently (in washes). Within the ephemeral populations, the number of plants in the population will vary in relation to the size of the burn and the distribution of the seed bank. Because pollinators must locate these ephemeral populations in a landscape that may be largely composed of other plant associations, out-crossing may not be prevalent. Flowers of *N. attenuata*are self-compatible and outcrossing does not significantly affect seed production, seed mass or viability \[[@B13]\] indicating that this species relies on selfing as its primary form of reproduction. Selfing may keep genetic variation low, especially within populations. Persistent populations are more likely to experience outcrossing, owing to their predictability. These considerations in combination with the annual life cycle of plants in washes in contrast to the 7 -- 150 year life cycle of plants growing in burns may increase the genetic differences among populations found in burns and washes.
Here we examine the genetic structure of *N. attenuata*plants from wash and burn populations in the SW Utah (Fig. [1](#F1){ref-type="fig"}; Table [1](#T1){ref-type="table"}) to determine if the particular germination behavior of this species has left signatures in the plant\'s population structure. We use an AFLP (amplified fragment length polymorphism) analysis, based on the selective polymerase chain reaction (PCR) amplification of restriction fragments from a total digest of genomic DNA \[[@B14]\] and an ISSR (inter-simple sequence repeats) analysis in which bands are generated by single primer PCR that amplifies products between two simple sequence repeats \[[@B15]\]. Both procedures produce reproducible markers useful for the quantification of genetic polymorphism within species \[[@B16]\].
::: {#F1 .fig}
Figure 1
::: {.caption}
######
**Location of *Nicotiana attenuata*populations from which seeds were collected between 1988--1999 in Southwestern Utah**. See Table 1 for number of plants grown for DNA extraction from each location for the AFLP and ISSR analysis. Locations labeled with circles represent single-site or -time collections, while squares signify multiple-site or -time collections
:::
:::
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Number of individual-plant DNA samples harvested for AFLP and ISSR analysis of plants grown from seed collected from: A) six sites within Utah collected over multiple years; B) three burns and 4 roadside washes within Utah collected in 1999; C) 3 non-Utah collections.(Codes identify samples in Fig. 3 and Table 5 \[see Additional file 1\]
:::
**Location** **Seed collection Year** **Codes** **SET I Used for only AFLP** **SET II Used for ISSR & AFLP** **Burn(B) or Wash (W)**
------------------------------------------------------------------ -------------------------- ----------- ------------------------------ --------------------------------- -------------------------
**A. Time series from the following Utah sites:1**
1\. Motoqua roadside wash and burn (fire in 1994)
Wash 1990 M1 4 W
Lower Burn 1995 M2 3 B
Middle burn 1995 M3 3 B
Middle burn 1996 M4 8 4 B
Lower Burn 1996 M5 3 3 B
Wash 1999 M6 4 8 W
2\. DI Ranch burns (yearly fires at garbage dump)
1988 D1 4 B
1990 D2 1 B
1992 D3 6 B
1993 D4 2 B
1995 D5 4 4 B
3\. Goldstrike roadside washes
\#2 1990 2 W
\#5 1990 1 W
\#2 1993 G1 5 5 W
\#4 1993 G2 2 2 W
\#5 1993 G3 1 1 W
4\. Shivwits Reservation roadside wash \# 1
1988 1 W
1990 2 W
1992 1 W
1993 4 W
1995 1 W
1999 B7 8 8 W
5\. Shivwits Reservation roadside wash \# 2
1992 B1 1 W
1993 B2 3 W
1995 B3 4 W
1996 B4 5 W
1999 B5 9 8 W
1999 B6 1 W
6\. Pahcoon Spring roadside wash
1990 1 W
1999 P9 9 8 W
**B) Burn and roadside wash populations collected in Utah 1999**
1\. Pahcoon Spring Burn (fire in 1998)
Burn transect 1 1999 P1 9 6 B
Burn transect 2 1999 P2 7 5 B
Burn transect 3 1999 P3 9 8 B
Burn transect 4 1999 P4 10 8 B
Burn area 1 1999 P5 9 8 B
Burn area 2 1999 P6 9 8 B
Burn area 3 1999 P7 9 7 B
Burn area 4 1999 P8 8 8 B
2\. Rt 91 Burn (fire in 1998)
Burn area 1 1999 R1 8 6 B
Burn area 2 1999 R2 8 8 B
3\. Single collection roadside washes and burns
Shivwits Reservation 4 1999 B8 9 8 W
Rt-91 1999 R3 9 7 W
Lytle Ranch Preserve 1999 L1 10 10 W
Jackson Spring 1999 J1 10 10 W
Cedar Pockets 1999 C1 10 10 B
C\) Non-Utah collections
Arizona 1996 3 3
Oregon 1994 2 2
California 1999 2 2
Total plants 244 175
:::
Specifically, we compare plants growing from seeds collected from 11 large populations after fires, from small populations in 10 washes, from plants in transects across 5 large burns, and from plants growing in specific areas over 10 years during which a small wash population erupted into a large burn population as a result of a fire and returned to become a small wash population. By analyzing the genetic diversity across these *N. attenuata*populations, we aimed to answer the following questions: 1) Are plants growing in burn and wash populations genetically distinct? 2) Are plants growing in the same washes genetically similar through different years? 3) What is the genetic makeup of plants found growing across large burns and geographically adjacent populations? While genetic diversity among the various *Nicotiana*species has been studied with RAPD \[[@B17]\] and AFLP \[[@B18]\] markers, and with peroxidase isozymes \[[@B19]\], this is the first effort to study the spatial and temporal population structure of a native *Nicotiana*species.
Results
=======
SET-I
-----
Set I (Table [1](#T1){ref-type="table"}) consisting of 244 individuals, which was used only for AFLP analysis, produced a total of 207 loci (data not shown). This data was used for separate dendrogram and [p]{.underline}rinciple [c]{.underline}o-[o]{.underline}rdinate (PCO) analyses. The Jaccard similarity index \[[@B20]\] based on [u]{.underline}nweighted [p]{.underline}air [g]{.underline}roup [m]{.underline}ethod [a]{.underline}verage (UPGMA) dendrogram revealed a lack of distinct spatial or temporal structure and had brush- or star-structures with nodal bootstrap values of less than 60% (data not shown). The samples collected from the greatest spatial distances, namely California, Oregon and Arizona, did not form separate clusters from any of the Utah populations. A cluster analysis of 10 wash and 5 burn populations all grown from seed collected in 1999 (Table [1](#T1){ref-type="table"}) revealed no clustering based either on type of population (wash or burn) or geographic location (data not shown).. Some structure was identified when each time series at particular locations (Motoqua, DI Ranch, Shivwits Reservation) were analyzed separately (Fig. [2A,2B,2C](#F2){ref-type="fig"}), but the nodes did not correspond to a particular growing season. No genetic differentiation was observed from a cluster analysis of plants collected from Motoqua before (1990) during (1995--1996) and after (1999) a fire-associated population explosion (Fig. [2B](#F2){ref-type="fig"}). A similar lack of structure was found in the time series analysis from the DI Ranch (Fig. [2A](#F2){ref-type="fig"}) and Shivwits roadside washes (Fig. [2C](#F2){ref-type="fig"}). Similarly, the PCO did not yield any apparent population structure or site- or population- specific grouping associations.
::: {#F2 .fig}
Figure 2
::: {.caption}
######
**UPGMA dendrograms based on the Jaccard similarity index calculated from an AFLP analysis of *N. attenuata*populations collected at three different sites.**A: DI Ranch (17 individuals); B: Motoqua Burn and Wash (25 individuals); C: Shivwits Reservation (23 individuals) collected over a number of different years. Sample codes are given in Table 1. While substantial genetic variation was found, this variation was not organized in time.
:::
:::
SET-II
------
Set II (Table [1](#T1){ref-type="table"}) is a subset of Set I (Table [1](#T1){ref-type="table"}) and consists of 175 individuals analyzed by AFLP and ISSR (either combined or separate) and this dataset was used for dendrogram and PCO analyses. Combined (AFLP + ISSR) analysis revealed a total of 286 loci of which 268 were polymorphic (93.70%). Here, the AFLP analysis showed higher percent polymorphic loci than did the ISSR analysis (96.1% and 87.5%, respectively; Table [2](#T2){ref-type="table"}). Interestingly in the AFLP analysis, the primer and the restriction enzyme combinations that produced the lowest number of loci also delivered the highest rate of polymorphism (Table [2](#T2){ref-type="table"}). It produced an average of 68.7 loci per primer combination with a high percentage of unique bands (65 in the 0--10% frequency class; Fig. [3](#F3){ref-type="fig"}) and a high frequency of commonly shared loci (42 in the 91--100% frequency class; Fig. [3](#F3){ref-type="fig"}). The ISSR analysis, on the other hand, produced 16 loci per primer with a predominance of commonly shared loci (29 in the 91--100% frequency class as compared to 14 in the 0--10% frequency class; Fig. [3](#F3){ref-type="fig"}). Dendrograms and PCO produced from this data set had the same overall characteristics as those produced from showed same structure nature Set I.
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
AFLP and ISSR primers, total number of loci, polymorphic loci and percentage polymorphism.
:::
**AFLP and ISSR Primer sequences (restriction enzymes)** **Total loci** **Nr. Polymorphic loci** **% Polymorphism**
---------------------------------------------------------- ---------------- -------------------------- --------------------
**AFLP**
Eco-AGC\\Mse-CAG 66 61 88.4
Eco-AAC\\Mse-CCG 59 59 100.0
Eco-ACC\\Mse-CCT 81 78 96.3
Total 206 198 96.1
**ISSR**
(AG)~8~T 16 13 81.3
(GA)~8~T 13 11 84.6
(CT)~8~A 16 12 75.0
(CT)~8~G 26 25 96.2
(CA)~8~G 9 9 100.0
Total 80 70 87.5
Total of ISSR and AFLP 286 268 93.7
:::
::: {#F3 .fig}
Figure 3
::: {.caption}
######
Locus frequency class distribution of 206 AFLP-(open) and 80 ISSR-(solid) loci from 175 ecotypes of *Nicotiana attenuata*.
:::
:::
Heterozygosity
--------------
A Bayesian approach \[[@B21]\] was used for heterozygosity calculations. The total heterozygosity as measured from the combined AFLP and ISSR data set of Utah collections (SET-II, Table [1](#T1){ref-type="table"}: the 168 individuals from Utah without, Arizona California and Oregon) was 0.2771 ± 0.0018. The plants from Arizona California and Oregon were not included for heterozygosity and AMOVA analyses due to insufficient sampling of these populations. Different primer combinations produced different values; in particular, in the ISSR analysis, the (CA)~8~A primer produced comparatively high heterozygosity values. In contrast, the AFLP primers produced values that are more similar. Different regions had different measures of total heterozygosity with plants growing at the Lytle Ranch Preserve being the lowest (0.1881 ± 0.0052) and plants from Pahcoon, the highest (0.2043 ± 0.0027) (Table [3](#T3){ref-type="table"}).
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Heterozygosity estimated using Bayesian approach within *N. attenuata*populations from different AFLP / ISSR primer combinations, total AFLP/ISSR heterozygosity and θ~B~estimates.
:::
Pahcoon Rt 91 Motoqua Lytle Ranch Preserve Cedar Pockets Jackson Spring Shivwits Reserve DI Ranch Goldstrike Washes Total Fst (θ~B~)
----------------- ----------------- ----------------- ----------------- ---------------------- ----------------- ----------------- ------------------ ----------------- ------------------- ----------------- -----------------
**AFLP**
E-AGC/M-CAG 0.1906 ± 0.0053 0.1975 ± 0.0079 0.2010 ± 0.0084 0.2135 ± 0.0091 0.2096 ± 0.0094 0.2233 ± 0.0090 0.1978 ± 0.0075 0.2055 ± 0.0103 0.2026 ± 0.0095 0.2152 ± 0.0044 0.0545 ± 0.0097
E-AAC/M-CCG 0.2224 ± 0.0059 0.2371 ± 0.0087 0.2334 ± 0.0094 0.2206 ± 0.0103 0.2363 ± 0.0103 0.2415 ± 0.0102 0.2176 ± 0.0087 0.2405 ± 0.0116 0.2269 ± 0.0109 0.2438 ± 0.0048 0.0598 ± 0.0095
E-ACC/M-CCT 0.2335 ± 0.0049 0.2370 ± 0.0071 0.2490 ± 0.0074 0.2531 ± 0.0083 0.2558 ± 0.0082 0.2453 ± 0.0082 0.2481 ± 0.0064 0.2530 ± 0.0092 0.2537 ± 0.0085 0.2606 ± 0.0041 0.0556 ± 0.0077
Total 0.2185 ± 0.0030 0.2260 ± 0.0044 0.2311 ± 0.0047 0.2332 ± 0.0052 0.2376 ± 0.0053 0.2387 ± 0.0053 0.2254 ± 0.0043 0.2357 ± 0.0058 0.2319 ± 0.0054 0.2432 ± 0.0024 0.0549 ± 0.0050
**ISSR**
(AG)~8~GT 0.1969 ± 0.0139 0.1552 ± 0.0276 0.1644 ± 0.0277 0.1391 ± 0.0265 0.2211 ± 0.0237 0.2301 ± 0.0309 0.2384 ± 0.0156 0.1841 ± 0.0354 0.1252 ± 0.0301 0.2546 ± 0.0098 0.3250 ± 0.0591
(GA)~8~AT 0.1890 ± 0.0230 0.2007 ± 0.0285 0.1650 ± 0.0368 0.1554 ± 0.0372 0.1822 ± 0.0323 0.1597 ± 0.0389 0.2556 ± 0.0226 0.1669 ± 0.0421 0.1688 ± 0.0332 0.2517 ± 0.0179 0.3064 ± 0.0553
(CT)~8~A 0.3017 ± 0.0302 0.2816 ± 0.0345 0.3414 ± 0.0254 0.3659 ± 0.0258 0.3246 ± 0.0311 0.2701 ± 0.0346 0.2786 ± 0.0196 0.2850 ± 0.0393 0.2348 ± 0.0438 0.3600 ± 0.0167 0.1931 ± 0.0380
(CT)~8~G 0.2086 ± 0.0099 0.2172 ± 0.0139 0.2219 ± 0.0159 0.2135 ± 0.0160 0.2122 ± 0.0167 0.2220 ± 0.0157 0.2121 ± 0.0138 0.2235 ± 0.0181 0.2266 ± 0.0160 0.2284 ± 0.0099 0.0508 ± 0.0128
(CA)~8~G 0.2086 ± 0.0099 0.2172 ± 0.0139 0.2219 ± 0.0159 0.2135 ± 0.0160 0.2122 ± 0.0167 0.2220 ± 0.0157 0.2121 ± 0.0138 0.2235 ± 0.0181 0.2266 ± 0.0160 0.2284 ± 0.0099 0.1059 ± 0.0341
Total 0.2309 ± 0.0088 0.2190 ± 0.0100 0.2185 ± 0.0104 0.2145 ± 0.0109 0.2166 ± 0.0111 0.2188 ± 0.0118 0.2145 ± 0.0088 0.2190 ± 0.0131 0.2024 ± 0.0124 0.2452 ± 0.0056 0.1180 ± 0.0132
**AFLP + ISSR**
**Total** 0.2043 ± 0.0027 0.1885 ± 0.0040 0.1916 ± 0.0044 0.1881 ± 0.0052 0.2001 ± 0.0053 0.2007 ± 0.0052 0.1919 ± 0.0036 0.1884 ± 0.0069 0.1844 ± 0.0056 0.2771 ± 0.0018 0.3305 ± 0.0088
:::
AMOVA
-----
AMOVA analysis was performed separately for AFLP, ISSR and combined analysis of plants collected from Utah (168 individuals from SET-II, Tables [1](#T1){ref-type="table"}, [4](#T4){ref-type="table"}). The combined data set was also used to partition variation between wash and burn populations and to examine the effects of the collection year. In separate analyses, ISSR revealed higher variance than did the AFLP in the among-sites, among-population, and within-site categories; whereas, variation in the within-population category from the AFLP analysis was higher than that from the ISSR analysis (Table [4](#T4){ref-type="table"}). All values except the among-site category in the AFLP analysis (*p*\< 0.05) revealed highly significant differences at *p*\< 0.001. AFLP and ISSR data was combined for an AMOVA analysis of all analyzed Utah populations. From this analysis, all three Φ categories were highly significant (*p*\< 0.001; Table [4](#T4){ref-type="table"}) among sites (Φct), among populations within sites (Φsc) and within populations (Φst) values were 0.046, 0.116, and 0.156, respectively. Table [4](#T4){ref-type="table"} reveals low genetic differentiation among sites and a relatively high genetic differentiation within populations. Pair-wise genetic distances (pair-wise Φst) were calculated from the AMOVA. Of the 300 comparisons from the 25 populations, 220 showed highly significant differences and 29 were significant at the p = 0.05 level (Table 5) \[see [Additional file 1](#S1){ref-type="supplementary-material"}\]. Very low among-site variation (0.18 %) was obtained when samples were compared as being derived from either burn or wash populations (Table [4](#T4){ref-type="table"}). To determine the effect of collection year, all individuals were grouped according to their collection year; an AMOVA analysis revealed low (3.77 %) variance within years at p \< 0.5 significance level (Table [4](#T4){ref-type="table"}).
::: {#T4 .table-wrap}
Table 4
::: {.caption}
######
Summary of AMOVA analysis for 168 samples of *Nicotiana attenuata*individuals representing 25 populations from Utah region. Level of significance is based on 1000 iteration.
:::
Level of variation df Absolute Percent Φ values *p*
------------------ -------------------------------- ----- ---------- --------- ------------- ---------
Utah (AFLP+ISSR) Among sites 8 1.38 4.59 Φct = 0.046 \<0.001
Among populations within sites 16 3.33 11.05 Φsc = 0.116 \<0.001
Within populations 143 25.44 84.36 Φst = 0.156 \<0.001
AFLP Among sites 8 0.59 2.72 Φct = 0.027 \<0.05
Among populations within sites 16 1.89 8.72 Φsc = 0.090 \<0.001
Within populations 143 19.17 88.55 Φst = 0.114 \<0.001
ISSR Among sites 8 0.79 9.38 Φct = 0.093 \<0.001
Among populations within sites 16 1.44 16.98 Φsc = 0.187 \<0.001
Within populations 143 6.27 73.68 Φst = 0.263 \<0.001
Burn and wash Among sites 1 0.05 0.18 Φct = 0.002 NS
Among populations within sites 23 4.45 14.85 Φsc = 0.149 \<0.001
Within populations 143 25.44 84.97 Φst = 0.150 \<0.001
Time Among years 3 1.16 3.77 Φct = 0.038 \<0.05
Among populations within years 21 4.70 13.56 Φsc = 0.141 \<0.001
Within populations 143 25.44 82.66 Φst = 0.173 \<0.001
Goldstrike among populations 2 0.06 0.23 Φst = 0.002 NS
within populations 5 25.86 99.77
Motoqua among populations 2 4.81 16.48 Φst = 0.165 \<0.001
within populations 12 24.39 83.52
Pahcoon among populations 8 3.19 12.06 Φst = 0.121 \<0.001
within populations 57 23.25 87.94
Rt91 among populations 2 2.07 7.57 Φst = 0.076 \<0.01
within populations 18 25.27 92.43
Shivwits among populations 2 5.42 18.80 Φst = 0.188 \<0.001
within populations 21 23.39 81.20
NS = Not significant
:::
The AMOVA analysis had sufficient statistical power to detect small differences among populations, which accounted for 0.23 to 16.48 % of the variation, but this was dwarfed by the much larger genetic variation within populations, which ranged from 81.20 to 99.77 % (Table [4](#T4){ref-type="table"}). This dramatic high degree of within-population variance was found in all populations. Again, populations from Goldstrike Canyon had the lowest among-population variance (0.23%) and highest within population variance (99.77%; Table [4](#T4){ref-type="table"}). The Goldstrike populations were located in a narrow canyon produced by a stream and in this region seeds are likely transported among the populations during spring floods.
The Φ-statistic is an analogue of the F-statistic \[[@B22]\]. This analysis revealed that the Φct (i.e. among site variation) values were 0.046, 0.027 and 0.093 for the AFLP + ISSR, AFLP and ISSR analyses, respectively (Table [4](#T4){ref-type="table"}). When these sites were grouped by burn and wash populations, very little genetic differentiation was observed (Φct 0.002). Interestingly, Φst (within population variation) was always comparatively high in all analyses (Table [4](#T4){ref-type="table"}). Substantially higher Fst values were estimated by the program Hickory (Ver 1.0) \[[@B23]\] as θ~B~for the combined AFLP + ISSR analysis (0.3305 ± 0.0088) (Table [3](#T3){ref-type="table"}), but surprisingly, the individual data set θ~B~values were lower (AFLP: 0.0549 ± 0.0050; ISSR :0.1180 ± 0.0132; Table [3](#T3){ref-type="table"}).
Mantel test were conducted to analyze isolation by distance using pair-wise Φst values obtained by AMOVA (ver 1.55). The Φst values from the AFLP, ISSR and the combined data sets were separately correlated with geographical distance and all revealed non significant correlations (AFLP, r = 0.099, p = 0.81; ISSR, r = 0.122, p = 0.89 and AFLP + ISSR, r = 0.019, p = 0.63)
Discussion
==========
The analysis revealed high levels of heterozygosity, with total heterozygosity from all populations (0.2771 ± 0.0018) being higher than that from comparable analyses of self-pollinating annual plants (0.131) \[[@B24]\]. The ISSR analysis (0.2452 ± 0.0056) yielded estimates of heterozygosity that were comparable with the AFLP analysis (0.2432 ± 0.0024) (Table [3](#T3){ref-type="table"}) despite the basic difference in the logic of the two procedures. ISSRs are designed to span a repeat region of the genome whereas AFLP is designed to randomly sample the full genome \[[@B16]\] and most plant genomes are thought to evolve faster in the repeat regions \[[@B25]\]. However, despite the differences in absolute estimates of genetic variation, both procedures produced the same conclusion.
The principle conclusion of this study is that large amount of genetic variation measured by AMOVA, within populations at a particular area significantly dwarfed that observed among sites, among populations growing in burns or washes, or collected during subsequent years growing at a given site. The conclusion that the genetic variation between neighbors is greater than that found between temporally- or spatially-separated populations, is dramatically reflected in the plants sampled along transects through the Pahcoon Springs burn. Only a small fraction (12.6%) of the total genetic variance is found among the 8 sub-samples from the extreme corners of this burn that covered more than 5000 hectares \[[@B26]\], while the majority (87.94 %) was found among plants growing within 10 m^2^of each other. Pahcoon, was the site from which highest number of populations were analyzed. (9 populations), whereas, from other sites smaller numbers of populations were analyzed.
F-statistic was estimated by using Bayesian approach with an analogue of the F-statistic, the Φ-statistic. Low but significant genetic differentiation was estimated among sites (Φct) from AFLP (0.027), ISSR (0.093) and AFLP + ISSR (0.046) data sets, whereas within populations, the Φst values were very high (Table [3](#T3){ref-type="table"}). In *Platanthera leucophaea,*Holsinger *et. al*\[[@B21]\] showed that θ~B~is substantially larger than the estimates from the AMOVA analyses (θ~B~= 0.392 Vs Φst = 0,252). In our study, AFLP + ISSR analysis also showed such difference (θ~B~= 0.3305 Vs Φst = 0.156) whereas, exactly opposite values were found separate analysis of AFLP and ISSR data sets (AFLP. θ~B~0.0594 Vs Φst= 0.114; ISSR θ~B~= 0.1180 Vs Φst = 0.263).
A number of factors, including *N. attenuata*\'s unusual seed germination mechanisms and the irregular nature of fires, natural selection, gene flow mediated by pollination or the relocation of seeds via mammal-vectored transport could account for the lack of population structure and each deserve further discussion.
Dormancy is a major adaptive response of native plants that allows them to cope with environmental variation and provide a means of habitat selection \[[@B27]-[@B29]\]. Moreover, dormancy is likely to influence the genetic structure of populations\[[@B30],[@B31]\]. Seed banks serve as repositories of genetic diversity for most species. Many seeds use cues as general as temperature, photoperiod, moisture, or their own age to trigger germination and initiate vegetative growth \[[@B32],[@B33]\]. To cope with the lack of reliability of these proximate signals and the unpredictability of the post-germination environment, some species may have evolved \"bet-hedging\" strategies, whereby only a certain fraction of the dormant seed bank germinates under favorable conditions. This has been experimentally shown by various researchers. In *Plantago lanceolata*\[[@B30]\], *Calluna vulgaris*\[[@B34]\], *Clarkia springvillensis*\[[@B35]\] and *Lesquerella fendleri*\[[@B36]\] it has been demonstrated that the seed banks have less genetic differentiation than do the adults of a given population. This strategy provides a statistical solution to the problem of cueing germination with unreliable signals \[[@B37],[@B38]\]. Other species, however, use specific signals to time their germination with particular niches. Those species that specialize in the immediate post-fire habitat are a particular case in point \[[@B39]\]. Studies on another fire-dependant plant, *Grevillea macleayana*\[[@B40]\], which also has a long-lived seed bank, showed Fst (0.218) that were comparable to those measured in this study for *N. attenuata*, but had variable heterozygosity (H ~obs~= 0.248 - 0.523). Another major difference from the current study was that *G. macleayana*showed significant isolation by distance.
Seed dormancy increases the effective generation time of this annual plant and by doing so, prevents genetic decay and inhibits the formation of spatial structure between geographically distinct populations \[[@B12]\]. Additionally, a long-lived seed bank results in the overlap of generations \[[@B41]\], which has similar effects and additionally reduces the ability of genetic drift to drive unique alleles to fixation. Operating under the assumption that the synchronized germination response observed after fires represents a synchronized germination of cohorts from the seed bank, we examined populations that occurred over a 6--11 year interval at the same location (Fig. [2A,2B,2C](#F2){ref-type="fig"}) to determine if temporally-defined genetic structure occurred in the populations, but none were found. This suggests that seed banks have a more complicated germination response whereby only fractions of a cohort may germinate at any particular interval and hence may represent a combination of \"bet-hedging\" \[[@B33]\] and the chemically-cued germination of the seed bank.
*N. attenuata*has all the characteristics of species pollinated by moths at night (white fragrant flowers scenting and becoming receptive at night) but day-active humming birds (*Selaphorus*sp.) and bumblebees (*Bombus*sp.) are also known to visit the flowers \[[@B42]\]. Despite these traits that are thought to facilitate out-crossing, 16 years of field work with the Utah populations have revealed that the vast majority of seeds produced are the result of self-pollination. No evidence exists for inbreeding depression in plants self-pollinated for more than 20 generations (I. T. Baldwin, unpublished results). However, the plant species likely enjoys sporadic bursts of cross pollination during the rare outbreaks of hawk moths (*Hyles lineata*and *Manduca*species(observed once in 16 years of observation at the study sites\[[@B43]\]. The amount and distance of gene flow that occurs during these rare events is not known. In the wind pollinated species such as *Zea mays*maximum distance of pollen dispersal was observed to be 18 m achieving outcrossing rate of not more than 1%; insect pollination does not substantially increase this rate \[[@B44]\]. Hence in comparison to seed dispersal these events are likely to have a minor effect on the homogeneity of populations \[[@B12]\].
Seeds of *N. attenuata*are small (160 μg) and could be dispersed by wind, water transport and animals, but none of these mechanisms are well documented. The seeds are eaten by various ground squirrels \[[@B45]\] but are not known to survive a transit through the digestive track. The greater heterogeneity within populations and low genetic differentiation among populations found along the stream in the Goldstrike canyon (Table 5) \[see [Additional file 1](#S1){ref-type="supplementary-material"}\] suggests water transport may not be important. While seeds tend to be dispersed from the plant upon maturation of the seed capsules, the *N. attenuata*calyx is sticky and glandular and could be dispersed by adhering to animals. However, the plants ability to produce the defense secondary metabolite nicotine in substantial quantities in its calyx \[[@B9]\] may be a much more important determinant of its long distance transport. Native Americans are known to have smoked leaves and seed capsules for recreational and medicinal purposes, buried their dead with leather pouches containing *N. attenuata*seeds, burned the sagebrush to promote its growth and are likely to have transported seeds throughout its range in North America \[[@B46]\]. Hence, movement of *N. attenuata*genotypes across the landscape by humans who were smoking this plant may have contributed to the lack of correlation between geographical and pair wise Φst values, as reflected by Mantel test for isolation by distance.
In summary, we conclude that the unusual nature of the *N. attenuata*populations from Utah revealed by AFLP and ISSR analysis is a likely result of combination of random dispersal by humans and its seed dormancy.
Conclusions
===========
We conclude that the genetic structure of *N. attenuata*populations in Utah showed: 1) high similarity across collection sites; 2) small difference between populations growing in burns or washes; 3) small differences between growing seasons; and 4) large difference between individuals growing within populations.
Methods
=======
Seed sources
------------
Seeds were from individual- and multiple-plant samples collected from 1988--1999 from the southwestern USA (Table [1](#T1){ref-type="table"}; Fig. [1](#F1){ref-type="fig"}). A majority of the seed collections (244) originated from a 1500 km^2^region of the SW corner of Utah (T38S R10W-T43S R19WUSA). Collections from Arizona (Flagstaff), Oregon (Eugene) and California (Sequoia Natl. Park) served as out-groups. In Utah, seeds were collected from plants growing at 6 locations for a number of years and were used for a time series analysis (Table [1](#T1){ref-type="table"}). One of these areas (Motoqua), the region surrounding a small wash population that had been sampled in 1990, was struck by lightening at the end of the growing season in 1994 (August) and 1163 hectares were burned. During the 1995--6 growing seasons, large populations of more than 100,000 plants were found, but by 1999 only a small population remained in the original wash. At this site, seeds were collected during the population explosion as well during the contraction of the population at this site (Table [1](#T1){ref-type="table"}). A fire during the 1998 growing season at Pahcoon Springs created a large population (covering more than 5,000 hectares) in the 1999 growing season which was sampled in 8 locations: seeds from 10 individual plants growing along each of 4 line-transects with an inter-plant distance of 10 m and 10 plants growing within a 10 m^2^area at 4 locations were sampled to provide a small-scale spatial analysis of genetic variation for this population.
Plant material
--------------
Seeds (10 seeds per plant collected) were exposed for 1 h to 100 μL liquid smoke (House of Herbs INC., Passaic, NJ, USA): water (1:300, v/v) in 1-mL shell vials and 5 seedlings were planted in soil and grown to the rosette-stage in a glasshouse. Leaves from one plant randomly selected plant from each collection were harvested for DNA extraction.
DNA extraction
--------------
Leaves were flash-frozen in liquid nitrogen, ground to powder and suspended in 750 μL of 100 mM Tris/50 mM EDTA (pH 8.0), containing 250 μg/mL RNase A. Eight μL liquid laundry detergent (Ariel, Procter & Gamble, Schwalbach, Germany) were added. After 60 min incubation at 60°C and subsequent addition of 80 μL of 5 M NaCl, the suspension was centrifuged for 5 min at 16,000 × g. The supernatant was removed and extracted with phenol/chloroform. The DNA was precipitated with 600 μL isopropanol, pelleted by centrifugation at 16,000 × g for 5 min, washed with 200 μL 70% ethanol and dissolved in 50 μL of water. The purity and concentration of the extracted DNA were assessed by electrophoresis on a 1% agarose gel and optical density spectrometric measurements. Both AFLP and ISSR procedures were performed on the same DNA samples.
AFLP procedure
--------------
The four-step AFLP marker production procedure of Sharbel \[[@B47]\] was followed with minor modifications: (1) *Restriction*. The enzyme combination EcoRI/MseI was used to restrict 500 ng of genomic DNA per sample. A 10 μL digestion mix (*2 μL NEB Buffer \#2, 2 μL 10 × BSA, 1.25 μL Mse I, 0.25 μL Eco RI, 4.5 μL water*) was added to 10 μL preparation of genomic DNA and incubated at 37°C for 3 h. (2) *Ligation of adaptators*. The double stranded EcoRI and MseI adaptator sequences designed by Zabeau and Vos \[[@B48]\] were ligated to the restriction fragments. A 40 μL ligation mix {6 μL ligase buffer (10 × Buffer for T4 DNA ligase)}, 4 pmol \"EcoRI-adaptor\", 2 pmol \"Mse-adaptor\", 0.6 μL T4 DNA ligase, water) was added to the 20 μL ligation reaction and incubated 19°C for 12 to 16 h. (3) *Pre-amplification*. Primers designed by Vos \[[@B14]\] complementary to a strand of each of the two adaptors with an additional selective nucleotide extension (\"EcoRI-A\" and \"Mse-C\") were used for an initial PCR pre-amplification step. An aliquot (17.5 μL) of a pre-amplification mix (2 μL 10 × Taq Buffer, 0.5 μL dNTP\'s (10 mM), 50 ng primer Mse-C (1μg/μL solution), 50 ng primer Eco-A (1μg/μL solution), water (grade III), and 0.1 μL Taq Polymerase B (5 U/μL)) was added to 2.5 μL of the digestion-ligation reaction in 0.2-mL PCR tubes. The PCR cycles are described in Sharbel \[[@B47]\]. (4) *Amplification*. Three 6-selective nucleotide EcoRI and MseI primer combinations, also designed by Vos \[[@B14]\] and demonstrated to be useful in *Nicotiana tabacum*by Ren & Timco \[[@B18]\], were used in the subsequent PCR amplifications. The primer combinations EcoRI-AGC/MseI-CAG; EcoRI-AAC/Mse-CCG; EcoRI-ACC/MseI-CCT were chosen with the help of successful studies by Ren & Timko \[[@B18]\]. Each of the three Eco RI-NNN primer types manufactured by Perkin-Elmer was labeled with a distinct fluorescent dye (either JOE, NED or HEX) at the 3\' end to a ratio of 1:5. The following procedure was used for each of the three PCR reactions: 18 μL of amplification mix \[2 μL 10 × Taq Puffer, 0.4 μL dNTP\'s (10 mM), 30 ng primer \"EcoRI-NNN\", 30 ng primer \"Mse-NNN,\" water, and 0.1 μL Taq Polymerase B (5 U/μL)\] was added to 2μL of the pre-amplification PCR product. PCR cycles were the same as in Sharbel \[[@B47]\].
The separate PCR amplification products generated by each of the three primer combinations were loaded together with a ROX 500 GeneScan size standard onto the ABI Prism 310 automated genetic analysis system as described in the manufacturer\'s instructions. The samples were run with the following GeneScan settings: \"GS STR POP 4 (1 mL) D\" module; 150000 V run Voltage; 5 second sample injection; 60°C gel temperature, and 9 m Watt\'s laser power. The distinct emission spectra of the three fluorescently labeled Eco RI-primer types made it possible to distinguish the DNA fragments resulting from each of the different primer combinations separately while the samples were being separated in the same electrophoresis capillary.
Collection of raw data and size alignment of the AFLP fragments was performed with ABI Prism GeneScan Analysis Software (Applied Biosystems) with the internal standard. Aligned data were subsequently imported into Genographer \[[@B49]\] for band calling. Each AFLP locus with an intensity ≥ 150 fluorescence units was scored with the \'thumbnail\' option of genographer and converted into a 1/0 binary data matrix, which was used for further analysis.
ISSR procedure
--------------
The PCR reaction (25 μL) contained 20 ng genomic DNA, buffer (10 mM Tris-HCl pH 8.3, 50 mM KCl, 1.5 mM MgCl~2~) 0.8 U *Taq*DNA polymerase (Eppendorf) 0.1 mM dNTPs, 0.3 μM primer. After 5 min initial denaturation at 94°C, 45 cycles of 1 min denaturation, 45 s annealing at 50°C, and 2 min for extension at 72°C, were followed by 5 min final extension in the PCR cycling program. A total of 55 primers were screened and 5 primers (Table [2](#T2){ref-type="table"}) were selected because they reproducibly produced distinct banding patterns. The amplified products were separated on 2.0% agarose gel (28 samples plus 2-1 Kb ladder standards on each gel) in 0.5 × TAE buffer and bands were detected by ethidium bromide staining. The PCR reaction and separation of PCR products was carried out in duplicate for each DNA sample and only reproducible bands were scored manually as present (1) and absent (0).
Data analysis
-------------
Pair-wise genetic similarity was calculated with the Jaccard coefficient \[[@B20]\]. The resulting matrix was processed for dendrogram construction using the UPGMA ([u]{.underline}nweighted [p]{.underline}air [g]{.underline}roup [m]{.underline}ethod [a]{.underline}verage) clustering method and PCO ([p]{.underline}rinciple [c]{.underline}o-[o]{.underline}rdinate analysis) options of software MVSP (Multi-Variate Statistical Package ver 3.13: \[[@B50]\]) program. The entire AFLP (244 individuals. SET-I) and ISSR+AFLP (175 individuals, SET II) data sets were analyzed individually and the 175 individuals (Table [1](#T1){ref-type="table"}) those were used in both procedures were combined for clustering analysis. Subsequently, the SET I data was analyzed for each time series separately (Fig. [2](#F2){ref-type="fig"})
Genetic diversity was estimated for SET II (without Oregon, Arizona and California individuals) (168 individuals) as heterozygosity using the Bayesian approach of Holsinger et. al\[[@B21]\]. For this analysis, the analysis program, Hickory (ver 1.0) \[[@B23]\], was used with the full model. Several runs were carried out with default sampling parameters (burn-in = 50,000, sample = 250,000 and thin 50) to ensure consistency of results. Since, dominant markers (AFLP and ISSR) are used in conjunction with a largely sefling species, we used an approach that does not assume Hardy Weinberg equilibrium (Holsinger \[[@B21]\]).
The SET II was used to calculate molecular variance from the combined and separate AFLP and ISSR data sets (168 individuals) as partitioned into individual and population components with an AMOVA (ver1.55: \[[@B51]\]). We also calculated variation between different locations, burns and washes, by collection year and population, separately. Φ values generated by the AMOVA program were used to estimate pair-wise genetic diversity, which is an analogue of the F-statistic. The Mantel permutation test was used to correlate pair-wise Φst values obtained by separate analyses of the AFLP, ISSR and combined data sets with geographic distance.
Authors\' contributions
=======================
RB carried out the entire ISSR analysis, the analysis of the AFLP data and contributed to writing the manuscript. DS grew the plants, extracted the DNA and conducted the AFLP analysis. CAP collected seeds, grew the plants and extracted the DNA. ITB was responsible for coordinating the study, collecting seeds for the analysis, and wrote the manuscript.
Supplementary Material
======================
::: {.caption}
###### Additional File 1
Table 5 Pair-wise genetic difference (Φ st Lower diagonal of the matrix) among 25 populations of *Nicotiana attenuata*. Levels of significance are given in the upper diagonal of the matrix: \**p*\< 0.05, \*\**p*\< 0.01, \*\*\**p*\< 0.001 and NS, Non Significant at *p*\< 0.05. *p*-value Indicates the probability that a random genetic distance (Φst) is larger than observed distance and are based on 1000 iterations steps.
:::
::: {.caption}
######
Click here for file
:::
Acknowledgements
================
We thank Dr. Tim Sharbel for generous assistance with all aspects of the AFLP analysis and Dr. Klaus Gase and Susan Kutschbach for assistance with the DNA extraction procedure and the Max Planck Society and Dartmouth College for financial support. We also thank Prof. Willi Nagl from The University of Konstanz for help with the statistical analysis.
|
PubMed Central
|
2024-06-05T03:55:47.756124
|
2004-9-6
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517723/",
"journal": "BMC Ecol. 2004 Sep 6; 4:12",
"authors": [
{
"first": "Rahul A",
"last": "Bahulikar"
},
{
"first": "Dominic",
"last": "Stanculescu"
},
{
"first": "Catherine A",
"last": "Preston"
},
{
"first": "Ian T",
"last": "Baldwin"
}
]
}
|
PMC517724
|
Background
==========
Depressive disorders are very common in clinical practice, with approximately 11.3% of all adults afflicted during any one year \[[@B1]\]. The majority of patients suffer from mild to moderate forms and are treated in primary care settings. Such patients are often reluctant to take synthetic antidepressants in their appropriate doses due to their anticipated side effects including inability to drive a car, dry mouth, constipation and sexual dysfunction. As a therapeutic alternative, effective herbal drugs may offer advantages in terms of safety and tolerability, possibly also improving patient compliance \[[@B2],[@B3]\]. The advent of the first antidepressants- the Monoamine Oxidase Inhibitors (MAOIs) and Tricyclic Antidepressants (TCAs) in the 1950s and 1960s represented a dramatic leap forward in the clinical management of depression. The subsequent development of the Selective Serotonin Reuptake Inhibitors (SSRIs) and the Serotonin Norepinephrine Reuptake Inhibitor (SNRI) venlafaxine in the past decade and a half has greatly enhanced the treatment of depression by offering patients medications that are as effective as the older agents but are generally more tolerable and safer in an overdose \[[@B4],[@B5]\]. The introduction of atypical antidepressants, such as bupropion, nefazadone, and mirtazapine, has added substantially to the available pharmacopoeia for depression. Nonetheless, rates of remission tend to be low and the risk of relapse and recurrence remains high \[[@B2],[@B4]\]. Thus, there is a need for more effective and less toxic agents. Plants extracts are some of the most attractive sources of new drugs, and have been shown to produce promising results for the treatment of depression \[[@B6],[@B7]\].
Saffron is produced from the tiny, dried stigma of lily-like *Crocus sativus*blossom, genuine saffron is worth its weight in gold. This plant belongs to the Iridaceae family. Although once considered a remedy for digestive problems, saffron is no longer used medicinally in the West \[[@B8]\]. In Asian medicine and in particular Persian traditional medicine, it is used to treat menstrual disorder, difficult labor, inflammation, vomiting, and throat diseases \[[@B8]-[@B10]\]. Recent studies indicate its potential as an anti cancer and memory enhancer agent as well \[[@B11],[@B12]\]. Although medicinal plants are used for a wide variety of physical ailments, but often there is limited research supporting these practices. *Crocus sativus*is also used to treat depression \[[@B9]\]. Many Persian medicinal plants textbooks refer to this usage whereas there is no evidence-based document. Our objective was to compare the efficacy of *Crocus sativus*with imipramine in the treatment of mild to moderate depression in a 6-week double blind randomized trial.
Methods
=======
This was a 6-week randomized and double blind clinical trial. The investigation was conducted in the outpatient clinic of Roozbeh Psychiatric Hospital between January 2002 and February 2004.
Patients
--------
Thirty adult outpatients who met the Diagnostic and Statistical Manual of Mental Disorders, 4^th^edition (DSM IV) \[[@B13]\] for major depression based on the structured clinical interview for DSM IV, participated in the trial. Patients have a baseline Hamilton Rating Scale for Depression (HAM-D 17-item) \[[@B14]\] score of at least 18. Prospective participants with the following DSM IV diagnosis were excluded: current cognitive disorder in the last year; or current or past history of bipolar disorder, schizophrenia and schizotypal personality disorder. Patients were required to be free of all psychotropic medications for at least 4 weeks before study entry. Patients were selected to range in age from 18 to 55 years of age. As depression is a serious and potentially life threatening condition and the participants were outpatients so extensive safeguards were needed. Patients were excluded if they posed a significant risk of suicide at any time during participation. Persons who scored greater than 2 on the suicide item of the HAM-D, or who were judged to have significant suicidal ideation or potential in the view of an investigator were excluded. Further, any clinically significant deterioration in the condition of the subject from baseline would result in exclusion. Those who left the study before completion were offered alternative and standard care immediately. Pregnant women or women not using medically accepted means of birth control were excluded. All participants provided written informed consent, and the protocol satisfied the Tehran University of Medical Sciences Ethics Committee requirements.
Saffron capsule preparation
---------------------------
The saffron was used in this study was dedicated by Novin Zaferan Co (Mashhad, Iran) and was identified by the Department of Cultivation and Development of Institute of Medicinal Plants, Tehran, Iran. The stigma\'s extract was prepared as follow: 120 g of dried and milled stigmas was extracted with 1800 ml ethanol (80%) by percolation procedure in three steps then the ethanolic extract was dried by evaporation in temperature between 35--40°C. Each capsule had dried extract of saffron (10 mg), lactose (filler), magnesium stearate (lubricant), and sodium starch glycolate (disintegrant).
Study design
------------
Patients underwent a standard clinical assessment comprising a psychiatric evaluation, a structured diagnostic interview and a medical history. Patients were randomized to receive capsule of saffron or capsule of imipramine in a 1: 1 ratio using a computer-generated code. The investigation preparations were administrated in red capsules whole indistinguishable in color, size, form and taste. The assignments were kept in sealed, opaque envelopes until the point of allocation. The randomization and allocation process was done by the pharmacist of the Roozbeh Hospital. In this double-blind, single-center trial, patients were randomly assigned to receive capsule saffron 30 mg/day (TDS)(Group A) or capsule imipramine 100 mg/day (TDS) for a 6-week study. The dose of saffron was calculated according to a recent published animal study \[[@B9]\]. All patients completed the trial. Patients were assessed by a third year resident of psychiatry at baseline and after 1, 2, 3, 4 and 6 weeks after the medication started. The principal measure of the outcome was the 17-item HAM-D. The rater used standardized instructions in the use of HAM-D. The mean decrease in HAM-D score from baseline was used as the main outcome measure of response of depression to treatment. Throughout the study the person who administrated the medications, rater and patients were blind to assignments.
Side effects
------------
Side effects were systematically recorded throughout the study and were assessed using a checklist administered by a resident of psychiatry on day 3, 7, 14, 21, 28 and 42 (Table [2](#T2){ref-type="table"}).
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Clinical complications and side effects were reported as number per group.
:::
**Side Effects** **Saffron** **Imipramine** **P**
------------------------ ------------- ---------------- ----------
**Anxiety** 4 1 0.32
**Decreased Appetite** 2 0 0.48
**Increased Appetite** 1 5 0.16
**Sedation** 0 6 **0.01**
**Nausea** 2 1 1.00
**Headache** 3 2 1.00
**Dry Mouth** 1 7 **0.03**
**Hypomania** 2 1 1.00
**Constipation** 2 5 038
**Urinary Retention** 1 5 0.16
:::
Statistical analysis
--------------------
A two-way repeated measures analysis of variance (time-treatment interaction) was used. The two groups as a between-subjects factor (group) and the six weekly measurements during treatment as the within-subjects factor (time) were considered. This was done for HAM-D total scores. In addition, a one-way repeated measures analysis of variance with a two-tailed post hoc Tukey mean comparison test were performed in the change from baseline for HAM-D scores in each group. To compare the two groups at baseline and the outcome of two groups at the end of the trial, an unpaired Student\'s t-test with a two-sided P value was used. Results are presented as mean ± S.E.M. Differences were considered significant with P \< 0.05. To compare the demographic data and frequency of side effects between the protocols, Fisher\'s exact test (two sided) was performed. To consider, a = 0.05, β = 0.2, the final difference between the two groups at least score of 5 on the HAM-D total scores that is clinically detectable, S = 5 and power = 80%, the sample size was calculated at least 15 in each group.
Results
=======
No significant differences were identified between patients randomly assigned to the group 1 or 2 conditions with regard to basic demographic data including age and gender (Table [1](#T1){ref-type="table"}).
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Baseline data
:::
**Saffron Group** **Imipramine Group**
----------------------------- ---------------------- ----------------------
**Women** 9 8
**Man** 6 7
**Age (Mean ± SD)** 35.53 ± 10.28 (year) 32.53 ± 8.10 (year)
**Baseline Hamilton Score** 19.20 ± 0.42 19.00 ± 0.44
:::
Efficacy: Saffron versus imipramine
-----------------------------------
The mean ± SEM scores of groups 1 and 2 are shown in Fig. [1](#F1){ref-type="fig"}. There were no significant differences between the two groups at week 0 (baseline) on the HAM-D (d.f. = 28, P = 0.43). Both groups showed a significant improvement over the 6 weeks of treatment (P \< 0.0001). The difference between the two protocols was not significant as indicated by the effect of group, the between-subjects factor (F = 2.91, d.f. = 1, P = 0.09). The behavior of the two treatment groups was homogeneous across the trial (groups-by-time interaction, F = 0.83, d.f. = 3.44, P = 0.49). In addition, the difference between the two protocols was not significant at week 6 (d.f. = 28, P = 0.33).
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Mean ± SEM scores of two groups of patients on the Hamilton Depression Rating Scale. ns = non-significant, \*\* = P \< 0.01 and \*\*\* = P \< 0.001. The horizontal symbols (\*\* and \*\*\*) were used to express statistical significance versus their respective baseline value and ns symbols are for between group comparisons.
:::
:::
Clinical complications and side-effects
---------------------------------------
A number of probable side effects were studied (Table [2](#T2){ref-type="table"}). Dry mouth and sedation were observed more often in the imipramine group.
Discussion
==========
The current therapeutic goal in the treatment of major depression is to improve the quality of life by normalizing mood, increasing awareness of personal pleasures and interests, and reversing the functional and social disabilities associated with depression, as well as to reduce suicide rates \[[@B1]\]. Saffron is used in folk medicine as an antispasmodic, eupeptic, gingival, sedative, anticatarrhal, nerve sedative, carminative, diaphoteric, expectorant, stimulant, stomachic, aphrodisiac, antidepressant and emmenagogue \[[@B8]\]. Furthermore, modern pharmacological studies have demonstrated that saffron extract has an anti tumor effect, radical scavenger property and hypolipaemic effect \[[@B11]\]. The present study was carried out to investigate the possible antidepressant effect of saffron compared with imipramine that has already shown to be significantly more efficacious than placebo in the treatment of major depression \[[@B2]\].
In this small preliminary double-blind and randomized comparison of saffron and imipramine in the treatment of mild to moderate depression, saffron at this dose was found to be effective similar to imipramine. Our results are in the line with a recent published animal study that *Crocus sativus*extracts showed antidepressant effect \[[@B9]\]. In addition, in the imipramine group anticholinergic effects such as dry mouth and sedation were observed more often that was predictable. Saffron at this dose did not induce any abnormal bleeding that is one of the reported side effects of it. It has been reported that saffron inhibits platelet adhesion so its use is contraindicated in pregnancy \[[@B9]\]. In addition, it has been suggested that crocin and safranal two major components of saffron inhibit reuptake of dopamine, norepinephrine and serotonin \[[@B9]\]. The limitations of the present study, including lack of a placebo group, using only a fixed dose of saffron, the small number of participants and short period of follow up should be considered so further research in this area is needed. Indeed, patients and their families may view alternative medicine that is, those treatments that are not traditionally taught in medical schools or generally practiced by clinicians, as being complementary or even superior to conventional medicine. In majority of cases there are no evidence-based documents for them. Therefore, the search for new and more effective therapeutic agents includes the scientific study of plants used in traditional medicine systems to treat mental disorders. The main overall finding from this study is that saffron may be of therapeutic benefit in the treatment of mild to moderate depression. A large-scale trial with placebo control is warranted.
Competing Interest
==================
None declared.
Authors\' contribution
======================
SA was the principal investigator and performed statistical analysis. HF and KA were the trialist. AHJ and FKC were the pharmacognosists of this study. All authors read and approved the final manuscript.
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1472-6882/4/12/prepub>
Acknowledgements
================
This study was supported by two grants from the Iranian National Research Center of Medical Sciences and Red Crescent to Dr. Shahin Akhondzadeh. The saffron was used in this study was dedicated by Novin Zaferan Co.
|
PubMed Central
|
2024-06-05T03:55:47.763185
|
2004-9-2
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517724/",
"journal": "BMC Complement Altern Med. 2004 Sep 2; 4:12",
"authors": [
{
"first": "Shahin",
"last": "Akhondzadeh"
},
{
"first": "Hasan",
"last": "Fallah-Pour"
},
{
"first": "Khosro",
"last": "Afkham"
},
{
"first": "Amir-Hossein",
"last": "Jamshidi"
},
{
"first": "Farahnaz",
"last": "Khalighi-Cigaroudi"
}
]
}
|
PMC517725
|
Background
==========
Recombinant DNA technology made available several simple techniques for transferring and efficiently expressing desired genes in a foreign cell. Thus, it was thought that unlimited and inexpensive sources of otherwise rare proteins would become accessible. It soon was observed that the host cell had a great influence on the quality and quantity of the produced recombinant protein. For example, recombinant protein production in mammalian cells yields a biologically active protein with all the required posttranslational modifications. However, mammalian cell cultivation is characterized by low volumetric yields of the recombinant protein, long cultivation times and requirements for expensive bioreactors and medium components. All these points have a great impact on the production costs. On the other hand, bacterial cultivation processes are based on inexpensive media in which fast growth and high cell concentrations can be obtained. These high cell concentrations combined with higher production rates of the bacterial expression system result in higher volumetric productivities. However, the production of recombinant proteins in bacteria such as *Escherichia coli*frequently yields an inactive protein, aggregated in the form of so-called inclusion bodies.
Though, producing an inactive target protein in the form of inclusion bodies is an important drawback, it also has several advantages such as the high degree of purity of the target protein in the aggregate fraction and the increased protection from proteolytic degradation compared to the soluble counterpart. Inclusion bodies have long been considered completely inert towards *in vivo*dissolution; only recently it was shown that proteins can be resolubilized *in vivo*from inclusion body deposits \[[@B1]\]. Although inclusion bodies in general consist of inactive proteins, *E. coli*can be the superior expression system compared to eukaryotic expression systems when the activity of the recombinant protein can be regained through refolding from the produced inclusion bodies. However, one needs to consider that the decision to select a specific expression system frequently is based on more trivial reasons such as staff knowledge and available equipment and facilities of the producing company/institute.
A good example to demonstrate the diverse routes that can be used for recombinant protein production is the manufacturing of tissue-type plasminogen activator (tPA). This protein enables the dissolution of blood clots and is used therapeutically for the treatment of myocardial infarction, thrombosis, pulmonary embolism, and strokes. To assure sufficient tPA for such a widespread application, an economic production process is a necessity. From the beginning, both the mammalian as well as the microbial route were explored for the production of tPA \[[@B2]\]. tPA is a fairly large (527 amino acids) monomeric protein containing 17 disulfide bridges. Because of this complexity, tPA was first produced in *E. coli*in the form of inclusion bodies while the mammalian expression system yielded an active protein that was secreted into the culture medium. More recently, obtaining active tPA through secretion into the periplasm of *E. coli*was attempted \[[@B3]-[@B5]\]. The early unsatisfactory yields have been improved \[[@B6],[@B7]\] rendering the *E. coli*secretion system as a future potential alternative route to generate functional tPA. Other recombinant organisms such as yeast \[[@B8]\], fungi \[[@B9]\] or insect cells \[[@B10]\] have not yet been considered as industrial producers for this protein.
Initially, the recombinant tPA introduced into the market was obtained from genetically engineered mammalian cells \[[@B2]\]. At that time, generating biologically active tPA from *E. coli*produced material was a process with a poor overall yield \[[@B2]\]. Today, the majority of commercial tPA (alteplase, Activase^®^) is still produced using a mammalian expression system (Genentech: <http://www.gene.com/gene/products/information/cardiovascular/activase/>). In addition, an amino substituted tPA produced by the mammalian expression system with increased half-life (tenecteplase) was developed. Alternatively, a non-glycosylated, truncated tPA (reteplase, Retavase^®^) produced in *E. coli*in form of inclusion bodies and afterwards refolded to its biologically active form is now on the market (Centocor: <http://www.retavase.com/>) and apparently gains market share at the cost of the mammalian-derived product(s) (see Genentech 2004 First Quarter Report).
Thus, continuous research effort focused on developing new refolding techniques or improving existing ones by including novel refolding aiding agents can make the bacterial inclusion body system an excellent alternative to the mammalian expression system or other expression systems that can directly generate active proteins with a complex disulfide bond structure. The foremost aim in improving protein refolding from *E. coli*produced inclusion bodies is to increase both the allowed protein concentrations during the refolding process and the final refolding yield. Recent advances in this area are summarized in conjunction with a short overview on inclusion body isolation and solubilization procedures. Moreover, the different techniques are discussed regarding their applicability for large-scale production processes or high-throughput screening procedures.
Isolation and solubilization of inclusion bodies
------------------------------------------------
A high degree of purification of the recombinant protein can be achieved by inclusion body isolation \[for recent reviews on various aspects of inclusion body formation and renaturation of inclusion body proteins please refer also to \[[@B11]-[@B18]\]\]. Inclusion bodies are in general recovered by low speed centrifugation of bacterial cells mechanically disrupted either by using ultrasonication for small, French press for medium, or high pressure homogenization for large scale. Main protein contaminants in the crude inclusion body fraction are proteins from the cell envelope, the outer membrane proteins \[[@B19]\]. These proteins are not integral inclusion body contaminants but coprecipitate together with other insoluble cell material during inclusion body recovery. Lysozyme-EDTA treatment before cell homogenization facilitates cell disruption. Addition of detergents such as Triton X-100 and/or low concentrations of chaotropic compounds either prior to mechanical cell breakage or for washing crude inclusion body preparations allow the removal of membrane proteins or other nonspecifically adsorbed cell material \[[@B11]-[@B14]\].
After their isolation, inclusion bodies are commonly solubilized by high concentrations of chaotropic agents such as guanidinium hydrochloride or urea. Although expensive, guanidinium hydrochloride is in general preferred due to its superior chaotropic properties. Moreover, urea solutions may contain and spontaneously produce cyanate \[[@B20]\], which can carbamylate the amino groups of the protein \[[@B21]\]. In addition, inclusion body solubilization by urea is pH dependent and optimum pH conditions must be determined for each protein \[[@B22]\]. There are also reports that inclusion bodies can be solubilized at extreme pH in the presence or absence of low concentrations of denaturants \[[@B23]-[@B25]\]. However, extreme pH treatments can result in irreversible protein modifications such as deamidation and alkaline desulfuration of cysteine residues \[[@B26]\]. Finally, inclusion bodies can be solubilized with different types of detergents \[[@B27],[@B28]\], low concentrations of denaturants \[[@B29],[@B30]\], or even by utilization of the aggregation suppressor arginine \[[@B29]\]. Inclusion body proteins solubilized under these mild conditions can possess a native-like secondary structure \[[@B28]-[@B30]\], and may even reveal some biological activity \[[@B29],[@B31]\]. It has also been demonstrated that the utilization of milder solubilization conditions can lead to higher final refolding yields compared to solubilization by high concentrations of guanidinium hydrochloride or urea \[[@B27]\].
In addition to the solubilizing agent, the presence of low molecular weight thiol reagents such as dithiothreitol (DTT) or 2-mercaptoethanol is generally required. These substances will reduce nonnative inter- and intramolecular disulfide bonds possibly formed by air oxidation during cell disruption and will also keep the cysteines in their reduced state \[[@B14],[@B15]\]. Optimum conditions for disruption of existing disulfide bonds are found at mild alkaline pH since the nucleophilic attack on the disulfide bond is carried out by the thiolate anion. Residual concentrations of reducing substances can negatively affect the refolding process, thus, they are frequently removed (*e.g*. by dialysis) before starting the refolding procedure. As an alternative, immobilized reducing agents (*e.g*. DTT; VectraPrime™, Biovectra) could simplify reducing agent removal by centrifugation after the solubilization process. Finally, the pH must be reduced before the removal of the reducing agent from the solution containing the solubilized protein to prevent the formation of undesired disulfide bonds.
Principles of refolding solubilized and unfolded proteins
---------------------------------------------------------
### Correct refolding versus aggregation
In general, the methods used for inclusion body solubilization result in a soluble protein that is devoid of its native conformation. This protein must then be transferred into conditions that allow the formation of the native structure (*e.g*. low denaturant concentration). Moreover, appropriate redox conditions have to be established when the protein contains disulfide bonds in the native state. When proper conditions for refolding are identified, the refolding process can require a few seconds or several days. During this period, the correct refolding pathway competes, often in disadvantage, with misfolding and aggregation of the target protein (Figure [1](#F1){ref-type="fig"}). Protein refolding involves intramolecular interactions and follows first order kinetics \[[@B32]-[@B35]\]. Protein aggregation, however, involves intermolecular interactions and, thus, is a kinetic process of second or higher order, which is favored at high protein concentrations \[[@B32]-[@B35]\]. In fact, refolding yields commonly decrease with increasing initial concentrations of the unfolded protein independent of the refolding method applied \[[@B35]-[@B40]\].
Aggregates are formed by nonnative intermolecular hydrophobic interactions between protein folding intermediates, which have not yet buried their hydrophobic amino acid stretches (Figure [1](#F1){ref-type="fig"}). When the refolding process is beyond these aggregation-prone intermediates, the productive folding pathway is favored and aggregation does not occur. Therefore, prevention of hydrophobic intermolecular interaction during the first steps of refolding is crucial to allow successful renaturation at high protein concentrations. Only recently a non-empirical method for predicting the fate of proteins during the refolding process was proposed \[[@B41]\]. It is based on the second viral coefficient, which indicates the magnitude of protein interaction under certain refolding conditions, and thus its tendency to aggregate. However, though being soluble in the refolding buffer is essential for a protein molecule to refold, it does not ensure that it will fold into the native form.
### Are further purification steps required after solubilization of inclusion bodies?
The recombinant target protein represents in general the major fraction of the inclusion body proteins. Therefore, refolding attempts can be undertaken directly after solubilization of the inclusion bodies. Some reports, however, claim higher refolding yields when the solubilized inclusion body proteins are purified prior to the refolding attempt \[[@B36],[@B39],[@B42],[@B43]\]. Additional purification has been recommended when the protein of interest represents less than 2--5% of the total cell protein \[[@B26]\] or less than 2/3 of the total inclusion body protein \[[@B42]\]. The type of contaminants can also be crucial for the success of the refolding process. For example, typical non-proteinaceous contaminants of inclusion body preparations did not affect refolding yields of lysozyme, while proteinaceous contaminants, which have a high tendency towards aggregation significantly reduced refolding yields \[[@B42]\]. Further purification prior to the refolding attempt does not seem to be required, even at low target protein concentrations, when the solubilized inclusion body proteins are subjected to refolding conditions during size exclusion chromatography where refolding and purification can occur simultaneously \[[@B44]\]. All pros and cons of any further purification step have to be carefully evaluated as they cause potential protein loss and additional production costs.
Techniques for protein refolding
--------------------------------
### Direct dilution
The simplest refolding procedure is to dilute the concentrated protein-denaturant solution into a refolding buffer that allows the formation of the native structure of the protein. Most frequently, the final protein concentration after dilution is in the 1--10 μg/ml range in order to favor the productive refolding instead of the unproductive aggregation pathway. Though ideal at laboratory scale, this technique has serious drawbacks during scale-up as huge refolding vessels and additional cost-intensive concentration steps are required after renaturation.
A major improvement of this technique was the development of a method where the solubilized, denatured protein is added in pulses or continuously into the refolding buffer \[[@B37],[@B40],[@B45]-[@B47]\]. This technique still keeps the simplicity of the direct dilution method while considerably increasing the final concentration of the refolded protein. Prerequisite is an appropriate knowledge of the folding kinetics of the target protein. The addition of the concentrated protein-denaturant solution should occur at rates slower than the rate-determining folding step of the target protein, thereby avoiding the accumulation of aggregation-prone folding intermediates \[[@B37],[@B46]\]. For pulse addition it has been recommended that 80% of the maximum refolding yield should be reached before adding the next pulse \[[@B14]\]. Other factors to be considered are the increasing residual concentration of the denaturant with each pulse, which should not surpass concentrations that affect the refolding of the protein, and the amount of protein added per pulse, which should be optimized in batch experiments to minimize aggregation \[[@B14]\].
### Membrane controlled denaturant removal
Another technique to transfer the solubilized and unfolded protein to conditions allowing the formation of the native structure is the utilization of dialysis and diafiltration systems for denaturant removal \[*e.g*. \[[@B48]-[@B51]\]\]. In contrast to the direct dilution method, the change from denaturing to native buffer conditions occurs gradually. Thus, the protein passes through different regimes of denaturant concentrations, where folding intermediates that are prone to aggregation may become populated. Most often, these techniques cause more aggregation during refolding compared to the direct dilution method \[*e.g*. \[[@B52]\]\]. Additionally, refolding yields can be negatively affected by non-specific adsorption of protein to the membrane. However, for some proteins and with the appropriate denaturant removal rates, adapted to the requirements of the target protein, high refolding yields at high protein concentrations can be obtained \[[@B50]-[@B53]\]. A fairly simple device was recently introduced allowing continuous or pulse refolding in a similar way as in the direct dilution method \[[@B54]\].
### Chromatographic methods for protein refolding
#### Protein refolding based on size exclusion chromatography
Buffer exchange for denaturant removal can also be carried out by using size exclusion chromatography (SEC). Most frequently, the denaturant-protein solution is injected into a column previously equilibrated with the refolding buffer \[[@B44],[@B55]-[@B58]\]. Subsequent elution with the refolding buffer results in a refolded protein in the eluate fraction with a considerably higher concentration compared to concentrations that can be reached by the simple dilution technique \[[@B44],[@B56],[@B58]\]. Protein refolding may be completed in the column or for proteins with slow folding kinetics the final folding steps may occur in the eluate fraction \[[@B44]\]. Aggregate formation is supposed to be reduced either by physical separation of aggregation-prone folding intermediates in the porous structures of the gel \[[@B56]\] or, more likely, by resolubilization of formed aggregates through the delayed running front of the denaturant, which gives the solubilized aggregates another opportunity to refold \[[@B14]\]. For proteins, which exhibit superior refolding yields during gradual denaturant removal, such as lysozyme, elution during SEC is preferably performed by using a decreasing denaturant gradient \[[@B38],[@B52],[@B59]\]. In specific cases, the denaturant removal can be accompanied with other changes in the buffer composition (*i.e*. pH) for further optimization of refolding conditions \[[@B52]\]. An additional advantage of this chromatographic method is the concomitant purification of the target protein during the refolding process \[[@B44]\]. Furthermore, some recent applications have shown the feasibility of using SEC for continuous processes of protein refolding \[[@B60],[@B61]\]. Also, SEC in combination with the use of an annular chromatography system can be coupled to an ultrafiltration and recycling unit for reinjection of resolubilized aggregates, which may form during the refolding process \[[@B60]\].
Some parameters for refolding using SEC are of key importance. For example, protein aggregation during sample injection can cause low refolding yields \[[@B62]\]; injecting the sample followed by an additional small volume of denaturant solution solves this problem \[[@B44],[@B52],[@B62]\]. Also, optimum results can only be reached when the properties of the chromatographic resin allow efficient separation of the renatured target protein from different folding intermediates, misfolded protein, and aggregates that might form during the refolding process \[[@B59],[@B63],[@B64]\]. In general, lower refolding yields are obtained by injecting the denatured protein at high concentrations \[[@B38],[@B58],[@B60],[@B61],[@B64]\] and/or by elution at high rates \[[@B52],[@B62],[@B64]\]. Both conditions result in poor separation among different folding intermediates thereby boosting protein precipitation.
#### Matrix-assisted protein refolding
Attaching the solubilized and unfolded protein to a solid support prior to changing from denaturing to native buffer conditions is another approach to avoid the unwanted intermolecular interaction between aggregation-prone folding intermediates. Binding of the solubilized and unfolded protein to the matrix requires the formation of a stable protein-matrix complex withstanding the presence of chaotropic agents. However, after changing to native buffer conditions, the detachment of the refolded target protein from the matrix should easily be accomplished. Several combinations of binding motives and matrices have been employed for binding the unfolded protein to the solid support. For example, proteins with a natural occurring charged patch in the unfolded chain, which binds to ion exchange resins \[[@B59],[@B65]-[@B67]\], or proteins containing artificially engineered peptide tags such as the hexahistidine tag, which binds to immobilized metal ions \[[@B59],[@B68]-[@B70]\], or N- or C-terminal hexaarginine tags binding to a polyanionic support \[[@B71]\], or protein fusions with denaturant-resistant binding domains, such as a glutathione S-transferase fragment, which binds to an anion exchange matrix \[[@B72]\] or the cellulose binding domain of the cellulose degrading multienzyme complex of the thermophilic bacterium *Clostridium thermocellum*, which binds to a cellulose matrix \[[@B73]\], have been employed. After binding, the matrix-protein complex is brought to refolding conditions by any of the above-mentioned techniques such as dilution \[[@B71]\], dialysis \[[@B68],[@B73]\], or buffer exchange through chromatography \[[@B59],[@B66],[@B69],[@B70],[@B72]\]. Finally, the refolded protein can be detached from the matrix, *e.g*. in the case hexahistidine-tagged proteins by elution with EDTA \[[@B69]\] or imidazole \[[@B59],[@B70]\] or by buffers with high ionic strength in the case of proteins bound by ionic interactions \[[@B59],[@B65],[@B66],[@B71],[@B72]\]. Due to the selective binding, matrix-assisted refolding can combine the renaturation of the target protein along with its purification from host cell protein contaminants \[[@B69],[@B70],[@B72]\].
#### Refolding using hydrophobic interaction chromatography
Hydrophobic interaction chromatography (HIC) has also been successfully used for protein refolding with concomitant removal of contaminating proteins during the renaturation process \[[@B74]-[@B78]\]. Unfolded proteins are applied to the column at high salt concentrations and refolded and eluted with a decreasing salt gradient. In contrast to the above-mentioned chromatographic methods there is no requirement for typical refolding aiding agents such as arginine during the in-column refolding process. Moreover, refolding of the disulfide containing protein proinsulin was even obtained in the absence of a redox system in the mobile phase \[[@B76]\].
It has been proposed that refolding is facilitated during HIC because unfolded proteins adsorb at high salt concentrations to the hydrophobic matrix and, thus, are not prone to aggregation. Additionally, hydrophobic regions of the protein that adsorb to the HIC matrix form microdomains around which native structure elements can form. During migration through the column, the protein will pass through several steps of adsorption and desorption, controlled by the salt concentration and hydrophobicity of the intermediate(s), resulting finally in the formation of the native structure \[[@B75]\].
Physical and chemical features improving protein refolding yields
-----------------------------------------------------------------
Apart from any of the above-mentioned techniques for protein refolding, there are physical and chemical variables that have a great impact on the final yield of biologically active protein. For example, temperature as well as the composition of the refolding buffer are important variables influencing the final refolding yield.
### Physical variables aiding protein refolding
The most important physical variable influencing the refolding yield is the temperature \[[@B40],[@B45],[@B50],[@B51]\]. Temperature has a dual effect on the refolding process. On one side, it influences the speed of folding and on the other it influences the propensity towards aggregation of folding intermediates with exposed hydrophobic patches. Also, there is limited temperature range in which each protein is thermodynamically stable in a given buffer system \[[@B79]\]. In general, low temperatures support the productive folding pathway as hydrophobic aggregation is suppressed. However, low temperatures also slow down the folding rates, thus increasing the time required for renaturation \[[@B51]\]. For refolding attempts of a new protein, 15°C has been proposed as a good starting point \[[@B14]\].
Pressure was identified as another important physical variable affecting protein structure as well as protein refolding processes \[[@B80]\]. It was shown that high pressure up to 3 kbar can disrupt oligomeric protein structures \[[@B80]\] and can dissolve protein aggregates and inclusion bodies \[[@B81],[@B82]\]. The disassembled protein monomers retain native-like secondary structure up to 5 kbar \[[@B80]\]. After gradual depressurization, they can reach their native state even at high protein concentrations, because folding intermediates prone to aggregate at atmospheric pressure are prevented from aggregation by high pressure \[[@B81]-[@B83]\].
### Chemicals aiding protein refolding
Certainly, L-arginine is nowadays the most commonly used refolding aiding agent \[[@B14]\]. It impedes aggregate formation by enhancing the solubility of folding intermediates, presumably by shielding hydrophobic regions of partially folded chains. In addition, it has been shown that numerous other low molecular weight additives such as detergents, protein-stabilizing agents such as glycerol or even low residual concentrations of denaturants improve refolding yields by suppressing aggregation \[[@B14]\]. In addition, high-molecular weight additives such as polyethylene glycol were used successfully for enhancing protein refolding yields \[[@B84]\]. More recently, low-molecular weight non-detergent zwitterionic agents such as sulfobetaines, substituted pyridines and pyrroles and acid substituted aminocyclohexanes have been employed successfully for protein renaturation \[[@B40],[@B85]-[@B87]\]. Moreover, polymers with temperature-dependent hydrophobicity were effectively applied for protein refolding at higher temperatures \[[@B88],[@B89]\]. The benefit of each of these refolding aiding agents for a given renaturation system has to be elucidated experimentally, as they are not equally advantageous for all proteins. The mechanisms of interactions of these refolding aiding agents with the folding intermediates remain often obscure although it is clear that all these substances suppress aggregation in favor of the productive folding pathway \[[@B90]\].
### Micelles and liposomes as protein refolding aiding systems
Detergents \[[@B91],[@B92]\] and phospholipids \[[@B93],[@B94]\], in the form of micelles and liposomes \[[@B95]\], respectively, as well as mixed micelle systems formed by phospholipids and detergents \[[@B92],[@B95],[@B96]\] have shown potential to aid protein refolding. Most likely, illegitimate hydrophobic interactions between folding intermediates are suppressed by transient nonpolar interactions between the protein and the micelle or liposome \[[@B91]-[@B93]\]. Additional transient polar interactions in mixed micelles are supposed to be responsible for higher refolding yields compared to only detergent-based micelle systems \[[@B92],[@B96]\]. Moreover, liposomes linked covalently to chromatographic resins have potential to combine renaturation and separation of the refolded target protein \[[@B93],[@B94]\].
Reversed micelles, formed when an aqueous detergent solution is mixed with an organic solvent, can also facilitate protein refolding by avoiding aggregate formation \[[@B97]\]. The denatured protein, once transferred to this solution, tries to avoid the organic phase, and, after reaching the hydrophilic core of the reversed micelle, can refold as a single molecule \[[@B97]\]. Recently, it was demonstrated that protein precipitates can be solubilized by direct addition into the reversed micellar system allowing refolding with high yields at high protein concentrations \[[@B98]-[@B100]\]. Yet, direct solubilization of inclusion bodies in reversed micellar systems has not been reported. In addition, recovery of refolded protein from these micellar structures is not easily accomplished \[[@B97],[@B99]\].
Chemical and biological protein refolding aiding agents mimicking *in vivo*folding conditions
---------------------------------------------------------------------------------------------
### Natural chaperones
Chaperones are a group of proteins conserved in all kingdoms, which play a key role in assisting *in vivo*protein folding and protecting cellular proteins from different types of environmental stress by suppressing protein aggregation. For example, the major *E. coli*chaperonin GroEL is involved in the *in vivo*folding of 10% of all newly synthesized proteins at normal growing conditions, and of 30% under stress conditions \[[@B101]\]. GroEL assists protein folding by a first capturing step of aggregation-prone folding intermediates \[[@B102]\]. The release of the folding-competent form is then accomplished in an ATP-dependent fashion through the action of the cochaperonin GroES \[[@B102]\].
Natural chaperones have also been applied successfully to refold various proteins *in vitro*\[[@B103]\]. However, their routine application is limited by their cost, the relatively high chaperone concentration required (at least equimolar to the target protein) and the need for their removal after the refolding procedure \[[@B103],[@B104]\]. Some procedures have tried to overcome these limitations by utilizing immobilized and reusable (mini)-chaperone systems \[[@B104]-[@B106]\]. Nevertheless, chaperone-based refolding processes are not robust enough for large-scale processes \[[@B14]\].
### Artificial chaperones
A further development of the detergent-based micellar system mimics the two-step mechanism of chaperone-assisted protein folding. The capturing step is performed by diluting the denatured protein into a detergent solution, which prevents protein aggregation through the formation of mixed protein-detergent micelles \[[@B107]-[@B110]\]. Aqueous solutions of hydrogel nanoparticles (*e.g*. self-assembly of hydrophobized polysaccharides such as cholesterol-bearing pullulan) have been also used for the capturing step \[[@B111]\]. The release of the folding-competent protein is subsequently initiated by the addition of cyclodextrins \[[@B107]-[@B112]\]. They are added in excess to the capturing agent and strip the detergent from the protein-detergent micelles through the formation of a tight detergent-cyclodextrin complex. Long cyclodextrin polymers as striping agent were reported to result in higher refolding yields compared to monomeric cyclodextrins \[[@B113]\]. Also, rapid addition of soluble cyclodextrins is thought to result in higher refolding yields compared to slow addition \[[@B108],[@B109]\] or the utilization of immobilized cyclodextrins \[[@B108],[@B109]\]. However, at least for α-glucosidase similar refolding yields were reported by stripping the detergent either with soluble or immobilized cyclodextrins \[[@B114]\]. The utilization of these cyclodextrin polymer beads allows simple removal of the cyclodextrin-detergent complex by centrifugation and, moreover, these beads can be used in expanded-bed columns in semicontinuous refolding processes \[[@B114]\].
### Liquid paraffin as pseudolipid bilayer membrane
*In vivo*, many proteins are transported through bilayered membranes in an extended and partially unfolded form either simultaneously or after their synthesis \[[@B115]\]. A rather peculiar protein refolding procedure mimicking the effect of a bilayered membrane was carried out in a three-phase liquid system built up in a centrifugation tube \[[@B116]\]. The upper phase contained an organic solution, which was separated from the aqueous refolding buffer by liquid paraffin. The protein, in an aggregated and denatured form, was added to the organic phase and forced to pass through the paraffin film into the refolding buffer by centrifugation. This procedure was successfully applied for the refolding of aggregated and denatured preparations of the model proteins RNase A and BSA.
### Template-assisted protein folding
Several proteins are synthesized in their natural environment with amino-terminal propeptides usually located between a signal sequence and the mature part of the protein. *In vivo*, these propeptides are known to play a key role in assisting the correct folding of the mature part of the protein \[[@B117]\]. *In vitro*studies have demonstrated that they can facilitate the refolding in *cis*, when the denatured mature protein is still linked to its propeptide prior to the transfer into the refolding buffer, or in *trans*by including the isolated propeptide into the refolding buffer \[[@B118]-[@B120]\]. This propeptide assisted protein refolding can be exploited for the renaturation of inclusion body proteins either by synthesizing the mature part linked to its propeptide, thus allowing later facilitated refolding \[[@B121],[@B122]\], or by synthesizing the mature protein and then including the appropriate propeptide into the refolding buffer \[[@B123]\].
Another method of template-assisted protein refolding exploits the specific binding properties of monoclonal antibodies to the target protein to reduce the time required for protein refolding and to enhance the final refolding yield \[[@B124],[@B125]\]. This procedure does not work with all antibodies and depends on the availability of specific antibody clones. Thus, it represents more a proof-of-principle rather than a practical approach to generate active proteins through refolding of inclusion body proteins.
Proteins containing disulfide bonds: special requirements
---------------------------------------------------------
In general, solubilization of inclusion body proteins by chaotropic agents is carried out in the presence of reducing agents such as dithiothreitol or β-mercaptoethanol to allow the disruption of nonnative disulfide bonds. Following solubilization, naturally disulfide-bonded proteins have to be refolded under conditions, which permit the formation of their native disulfide bonds. In the simplest way, free cysteine residues can be oxidized by molecular oxygen, a redox reaction catalyzed by Cu^2+^ions \[[@B126],[@B127]\]. Though a cheap option, air oxidation is slow, often results in mismatched disulfides, and is not suitable for disulfide-bonded proteins, which also have free cysteines \[[@B26]\].
Disulfide bonds are more efficiently formed when a mixture of low molecular weight thiols (*e.g*. glutathione) in their reduced and oxidized state is added to the refolding buffer \[[@B126],[@B128]\]. Best conditions for refolding of disulfide-bonded proteins are commonly established when the reduced form is present in excess and the pH is slightly alkaline. These conditions allow rapid disulfide exchange reactions until the protein reaches the most stable disulfide-bonded configuration, in general the native state of the protein \[[@B26],[@B126],[@B128]-[@B130]\]. Recently, a novel generation of aromatic thiols was developed which have lower p*K*~a~values as the aliphatic thiols thus enabling disulfide-bond formation at lower pH values \[[@B131],[@B132]\]. These thiol reagents might be useful for the refolding of proteins with limited stability at alkaline conditions. Also, an immobilized disulfide-reshuffling system based on thiol-carrying latex particles has recently been successfully applied for the refolding of RNase A \[[@B133],[@B134]\].
Naturally disulfide-bonded proteins in their reduced states are often very unstable and exhibit a high tendency towards aggregation, especially during the early stages of refolding \[[@B128]\]. These problems can be overcome by modifying the reduced thiol groups in the unfolded protein, either by S-sulfonation \[[@B39],[@B128],[@B135],[@B136]\] or by transforming the free cysteines into mixed disulfides with the oxidized form of a thiol reagent (*e.g*. glutathione) \[[@B128],[@B137]\]. These chemical modifications introduce numerous charged residues into the protein, which prevent the intermolecular interactions responsible for aggregation. The chemically modified protein is then transferred to refolding conditions. Correct disulfide bond formation for S-sulfonated proteins is initiated by supplementing the refolding buffer with the appropriate redox system \[[@B39],[@B128],[@B135],[@B136]\], or, for proteins with mixed disulfides by adding trace amounts of the reduced form of the thiol reagent \[[@B128],[@B137]\].
Improvements of refolding yields of disulfide-bonded proteins have also been achieved by using protein disulfide isomerase (PDI) in combination with a redox system. PDI is a folding catalyst that assists disulfide bond formation *in vivo*\[[@B138]\] and was successfully implemented for aiding disulfide bond formation during *in vitro*protein refolding \[[@B139],[@B140]\]. In some cases PDI did not show significant effects on the refolding yield but significantly increased the refolding rate \[[@B141]\]. However, residual concentrations of chaotropic agents in the refolding buffer, especially guanidinium hydrochloride, can drastically reduce PDI activity \[[@B142]\]. Traces of small peptides containing the active site of PDI \[[@B143]\] and chemically synthesized dithiol molecules mimicking PDI function \[[@B144]-[@B146]\] have also shown potential to increase the *in vitro*refolding yields generally obtained with the common redox systems \[[@B143],[@B146]\].
Process integration
-------------------
Published refolding processes are often composed of numerous and cumbersome steps, both downstream (*e.g*. cell disruption, inclusion body isolation and purification by several centrifugation and washing steps followed by a final solubilization procedure) and upstream of the renaturation process (*e.g*. removal of aggregates and misfolded protein and final purification of the correctly refolded target protein). Scale-up problems can arise when some of these steps are not transferable to larger scale processes. As an alternative to the common downstream process, inclusion bodies can directly be solubilized from chemically treated *E. coli*cells \[[@B147]-[@B150]\] or in combination with mechanical treatments \[[@B72]\]. Even more, inclusion body solubilization directly from cells in the cultivation broth is feasible as was shown for periplasmic \[[@B147]\] as well as for cytoplasmic inclusion bodies \[[@B151]\]. A high degree of purification, removal of cell debris and *E. coli*host cell proteins, can be achieved by selective extraction of inclusion body proteins combined with diafiltration \[[@B148]\], aqueous two-phase extraction \[[@B147]\] or selective capture by either expanded bed chromatography \[[@B72],[@B149],[@B151]\] or by attachment to magnetic particles recoverable in high gradient magnetic fields \[[@B152]\]. Major difficulties often arise by the increase of broth viscosity due to release of DNA after chemical treatment requiring its selective removal *e.g*. by precipitation through spermidine addition \[[@B149],[@B151]\] or preferably by treatment with DNA-degrading enzymes \[[@B153]\]. Afterwards, the prepurified and solubilized target protein can be subjected to refolding conditions using any of the above-mentioned methods. Moreover, there are reports on integrated processes where solubilization of the target protein from chemically treated cells is followed by a chromatographic process in which the capturing step and removal of *E. coli*contaminants is followed directly and in the same operation unit by refolding and subsequent purification \[[@B72],[@B74]\]. Utilization of refolding methods based on chromatographic processes is additionally advantageous as they combine refolding with an at least partial purification of the target protein \[[@B44],[@B69]-[@B72]\]. In addition, aggregates formed during the refolding process can also be removed through chromatographic processes as they have a different retention time compared to the correctly folded protein \[[@B56],[@B64],[@B67]\]. Finally, chromatographic processes can be performed continuously \[[@B60],[@B61]\] with the possibility to recycle aggregates formed during the refolding process thus leading to processes with refolding yields up to 100% \[[@B60]\].
Perspectives
============
After the first enthusiasm about protein production using recombinant microorganisms, it was promptly understood that obtaining an active form of the desired protein was not a simple task. Many proteins form nonnative precipitates in form of inclusion bodies when synthesized in bacteria and there is no universal refolding recipe for the generation of native protein from solubilized inclusion bodies. For any given protein, the best refolding conditions still have to be determined empirically. Among a lot of experience and \"a good feeling for the best way\", the use of experimental design methodologies \[[@B154],[@B155]\] and further improvements in predicting the likelihood of aggregation \[[@B41],[@B156]\] may increase the speed for finding the optimal refolding conditions for a given protein. Also, less-established and new techniques as well as new refolding aiding additives may become more widely used in the near future. However, these techniques or new protein refolding aiding substances await rigorous testing for refolding of not only easy-going model proteins such as RNase A but also for more recalcitrant inclusion body proteins. Moreover, refolding strategies also have to be adapted to the required quantity and final use of the refolded protein. For therapeutic proteins needed in great quantities more effort can be undertaken to identify the best refolding conditions leading to high yields of the correctly folded protein. For a protein where just a few milligrams are required for biochemical and/or structural studies process optimization with respect to high yields is not such a necessity. Also, special demands for high throughput refolding screening arising from structural genomic projects require robust strategies that will lead to monodisperse refolded protein samples \[[@B157]\]. In this case, the direct dilution method in combination with variations in temperature and buffer composition is still the best approach. Altogether, new strategies need to increase the robustness of refolding processes and/or decrease the costs to find acceptance for broader applications.
Acknowledgments
===============
This study was carried out in the context of a grant of the Deutsche Forschungsgemeinschaft (SFB 578 \"Vom Gen zum Produkt\", Project B1).
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Simplified model of correct folding versus misfolding and aggregation. The correct protein folding pathway (1) often competes with misfolding (2) and aggregation (3). Aggregation occurs among intermediates with exposed hydrophobic patches, which are buried in the correctly folded protein (blue lines, hydrophilic solvent-exposed parts of the protein; red lines: hydrophobic patches).
:::
:::
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PubMed Central
|
2024-06-05T03:55:47.764825
|
2004-9-2
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517725/",
"journal": "Microb Cell Fact. 2004 Sep 2; 3:11",
"authors": [
{
"first": "Luis Felipe",
"last": "Vallejo"
},
{
"first": "Ursula",
"last": "Rinas"
}
]
}
|
PMC517726
|
Background
==========
Arrhythmias, a significant direct cause of death in heart diseases, are emergent and evolvable events that come with little prior warnings and allow limited response time \[[@B1]\]. Although ECG waveforms -- the mapping of body surface potentials of cardiac cells -- have routinely been used to diagnose arrhythmias, as integrated signals they tell us little about what happen at cell and ionic channel levels. They therefore are only marginally useful in guiding the clinical use of anti-arrhythmic drugs to treat disturbed cardioelectrical activity at cell and channel levels. Many of such drugs used today are ionic channel blocking agents \[[@B2]\].
To overcome the inherent limitations of clinical investigation, computational modeling and simulation has been widely recognized as a valuable alternative approach. Traditionally, cardiac modeling has centered on ECG simulation. Using the finite element method (FEM), the virtual heart and whole chest are partitioned into numerous elements representing a group of cells. The ECG is then simulated, based on computing the body surface potential of each cardiac element \[[@B3]-[@B5]\]. Basically, this method does not concentrate on cellular electrophysiological issues at the channel level, and thus fails to precisely associate macro level phenomena (ECG waveforms) with micro level activities and to make use of the considerable knowledge of cellular electrophysiology accumulated over the past decades. To improve the understanding of arrhythmias and to find effective perturbations, electrophysiological modeling using membrane equations is required so that mechanisms of arrhythmias at cell, channel, and even molecular levels can be investigated \[[@B6]-[@B8]\].
To study arrhythmias using a large-scale realistic electrophysiological model, two issues need to be effectively resolved: model building and operation. Though the widespread paradigm of modeling with C or C++ remains a workable choice, the huge number of cardiac cells in a realistic three-dimensional (3-D) whole-heart model and the numerous modifications of the model to simulate various pathological conditions, make more desirable efficient modeling based on transparent parallel computing. To build and run a model with parallel computing technologies, two strategies were separately developed in recent years. To provide transparent and parallel descriptions, cellular automata were used \[[@B9]-[@B11],[@B50]\]; for efficient execution, distributed computing was adopted \[[@B12],[@B13]\]. Yet, each strategy alone is not sufficient for the successful simulation of arrhythmias. On the one hand cardiac models built with traditional cellular automata are qualitative, and thus do not use the Hodgkin-Huxley (HH) action potential equations to describe channel electrical activity. Consequently, many arrhythmias, such as those triggered by early-after-depolarization (EAD) and delayed-after-depolarization (DAD), can not be simulated. On the other hand, physical parallelism on parallel computers is also not fully exploited in these cellular automata models. MPI, the programming protocol for distributed-memory multiprocessors (DMP), and OpenMP, the programming protocol for shared-memory multiprocessors (SMP), are not used \[[@B14],[@B15]\]. Partly because of these two issues, arrhythmia simulations with a realistic whole-heart electrophysiological model have not been fruitfully conducted.
There is compelling evidence that cardiomyocytes are not arranged in a uniformly connected continuum, as has often been assumed and simulated in the past. Along with nonlinear ionic channel electrical activity, discontinuous electrical propagation is another key feature of cardioelectrical activity \[[@B16]\]. The former demands a precise membrane equation based description; the latter requires a gap junction based discrete model. To efficiently build heterogeneous models containing different types of cardiomyocytes described by different membrane equation models and connected through different gap junctions remains a major challenge. In the present study, we propose a method using an extended, quantitative cellular automaton to build a discrete whole heart model with the data of the Visible Human Project (VHP) male cadaver \[[@B17]\]. An ECG simulation algorithm based on the membrane potential of each and every cell is designed and validated in a 2-D model built with the same method. Moreover, we combine cellular automata modeling with distributed parallel computing to realize efficient and affordable simulation. The parallel numerical solutions of the HH equations within a large number of cardiac cells are executed in parallel on a cluster with hybrid MPI and OpenMP programming. The parallel programming does not have to be manually coded in models built with the extended cellular automaton, because the modified compiler of the cellular automaton can automatically parallelize the codes, making parallelism fully transparent. The aim of this paper is to introduce the method and the whole-heart electrophysiological model. Results of performance evaluation on a four-node cluster are given. Based on this work, we conclude that quantitative modeling using extended and cluster computing enabled cellular automata is feasible and efficient, seamlessly binding conceptual and physical parallel computation. This method is suitable for a variety of computational intensive, tissue level modeling and simulation.
Methods
=======
Cellular automata style quantitative computing
----------------------------------------------
Cellular automata were first introduced by John von Neumann and Stanislaw Ulam in the 1940s, and gradually used to solve a wide range of problems, including multicellular biological modeling in which a natural correspondence between each automaton cell and each biological cell is assumed \[[@B18]-[@B21]\]. Simple local interaction producing complex global behavior is common to a variety of natural phenomena, including cardioelectrical activity. Though traditionally cellular automata are regarded as discrete parallel systems, new functions can be obtained with non-standard implementations \[[@B22],[@B23]\]. For language-based cellular automata, a program encoded in a language instead of a rule is shared by all cells and describes the behavior of each cell. A compiler translates the cell program into executable files. To enhance the portability of the language, a two-step compilation is usually adopted, with C/C++ files being the intermediate codes, allowing the extension of such cellular automata systems.
*Cellular*is a cellular automata system based on the language *Cellang*\[[@B23]\], whose cell program comprises three parts: constant declarations, a cell declaration, and statements. The cell declaration defines a set of fields to store states of each cell between successive steps of computation. The cell array is described in a separate data file, whose output is piped to the cell program to provide the value of fields in each cell so as to enable computation. A predefined unchangeable variable *time* synchronizes the running of all cells. By conventions, in cellular automata computation quantitative computing is not fully supported and function call is not allowed. To overcome this inherent inadequacy of *Cellang*in quantitative computing and enable it to solve HH type membrane equations, we have added new language facilities, including the floating-point data type and the mathematical functions provided in the C libraries. Thus, *Cellang*is able to encode numerical solutions of the HH equations (Figure [1](#F1){ref-type="fig"}). A built-in function position() is also added to specify the global coordinates of the currently running cell. This function, in combination with the if-then statement, allows position-and time-dependent runtime perturbations to any cells, a function valuable for arrhythmia simulation. Viewing facilities are also extended to monitor and display simulation of electrical activitys at channel, cell, and organ level.
::: {#F1 .fig}
Figure 1
::: {.caption}
######
**Quantitative cellular automata with different neighborhoods.**(a) Moor neighborhood. (b) A user-defined neighborhood. The radius in both cases is 1.
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Running a model may be no easier than building it. The large number of cells, the small time step Δt and the long running time for arrhythmia simulation make it impractical to run a whole heart model on any low-end computer. Since large-scale SMP machines are extremely expensive, the prevailing parallel computing platforms are clusters of small-scale SMP or DMP, and the protocols of programming in Fortran, C, and C++ on such computers are OpenMP and MPI. First, an endless *while*loop is used to realize iterative computation. Second, since for an *n*-dimensional model each field in the cell program is translated into an *n*-dimensional data array in the intermediate C program, within the *while*loop *n*successive *for*loops are employed to traverse the *n*dimensional cell space. Only the codes within the *for*loops, which are statements in the cell program, need to be parallelized. Instead of defining one data array with an offset for each field in the original *Cellular*system, we use two data arrays in a flip-flop manner to support parallel write operation. OpenMP provides a group of directives to be inserted into the C program to tell the compiler the region to be executed in parallel. Such directives appear before the *for*loops to dispatch the outermost *for*loop into a group of threads, whose number is set dynamically according to the available CPUs. The simulation of cellular activity is thus implicitly parallelized in a shared memory space. To parallelize a *Cellang*program on a platform with distributed memory, explicit cell space decomposition is inevitable. Every data array is equally divided into several subsets located in distributed memory bodies, and computed by autonomous computing nodes that communicate each other through MPI. Since a cell needs to access its neighboring cells over the maximal radius *m*to compute transjunctional currents, each subset should enclose *m*extra layers of cells on each side to ensure that cells at the boundary layer(s) can access correct neighbors that are located in the outermost *m*layers of the two neighboring subsets, respectively. Field values of cells in these extra layers should be swapped between neighboring subsets after each round of computation to ensure that cells access updated data. Such data exchange is the major factor for the excessive time needed by cellular automata models running on distributed memory platforms. If cells have many fields, the time spent on such operations may even offset the benefits of parallelism.
To reach the maximal flexibility and portability for MPI-parallelization, a *master-slave*program structure is adopted (Figure [2](#F2){ref-type="fig"}). The number of *slaves*is set in the compilation command with an argument. The *master*is responsible for:
::: {#F2 .fig}
Figure 2
::: {.caption}
######
The master-slave structure of distributed computing with MPI programming.
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• Reading data from the data file into the cell space and dispatching the cell space at time step 0;
• collecting the value of a selected field in each cell from all *slaves*and displaying them at each time step;
• updating the variable *time*and sending its new value to every *slave*to trigger the next round of computation;
• doing some global, non-cellular automata style computing such as ECG simulation;
Each *slave*process is responsible for:
• receiving a subset of the cell space at time 0;
• exchanging the boundary layers with neighboring *slaves*at each time step;
• executing the cell program of cells in its subset at each time step;
• sending the value of a selected field to the *master*at each time step for display;
• receiving the new value of *time*at each time step.
Finally, to run the model on a cluster of SMP nodes, a two-tier parallelism -- a coarse-grained setting among nodes and a fine-grained setting within nodes -- is applied. The hybrid programming is straightforward -- insert OpenMP directives into the *master*and *slaves*, as in the case of pure OpenMP programming to spawn a group of threads within each node to implement cell level parallelism. Due to the stereotyped appearance of these codes, we let the compiler generate them each time we compile a model, leaving the number of *slaves*and threads within each *slave*as command line arguments, so as to make parallel computation entirely transparent to users.
Construction of the anatomical model of the heart
-------------------------------------------------
The anatomical model, which is a data file describing the distribution of the cell array and the initial value of fields in each cell, is independent of the cell program. The data file can be manually edited or generated by a program coded in C/C++. Due to the correspondence between each automaton cell and each biological cell, the building of the anatomical model is straightforward, even if a model has an irregular structure and a heterogeneous cell population. Usually, the Moore neighborhood is adopted, as is the case in our model.
The data used to build the 3-D heart model are the axial images of the Visible Human Project (VHP) digital male cadaver \[[@B17]\], which contains about 125 thoracic slices at a 1 mm interval. Using an image processing program we developed, we enter a 128 × 128 coordinate system on each slice and use a computer mouse to mark the cells of different tissue with different colors (Figure [3](#F3){ref-type="fig"}). This process digitalizes each slice into a data file that reports the coordinates and type of each cell. The current heart model contains six kinds of cardiac tissues: sinoatrial node (SAN), atrioventricular node (AVN), atrium (AT), ventricle (VT), and trunk conduction bundle in the atrium (CBA) and in the ventricle (CBV). The distribution of trunk conduction bundles in each slice is determined by clinical experts, but the terminal distribution of the Purkinje fibers is generated by an algorithm at runtime. After processing all 125 slices, we use a program to merge the generated 2-D data files into a 3-D data file, which constitutes the anatomical model of the heart that occupies about 280,000 cells in the 128 × 128 × 128 cellular automata cell space. We also build an illustrative 2-D model containing the same kinds of cells and the same action potential models to evaluate the ECG simulation algorithms (Figure [6](#F6){ref-type="fig"}). The simulated normal and some abnormal ECG waveforms support the validity of the algorithm (Figure [7](#F7){ref-type="fig"}).
::: {#F3 .fig}
Figure 3
::: {.caption}
######
**Digitalizing slices of the digital male cadaver.**Yellow color indicates ventricular tissue, and pink color indicates atrial tissue.
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::: {#F6 .fig}
Figure 6
::: {.caption}
######
**The stratified heart walls.**(a) The stratified 2-D model. (b) The epicardium-to-endocardium repolarization in the 2-D model based on stratified cardiac walls. Different color indicates different transmembrane potential. (c) Two ischemia areas based on stratified cardiac walls. (d) The stratified 3-D model (a section).
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::: {#F7 .fig}
Figure 7
::: {.caption}
######
**The simulated ECGs with the 2-D model.**(a) The normal ECG; two leads are at the middle of left and right chests (\<190,50 \> and \<-80,50 \>). (b) The normal ECG; two leads are in the cardiac cavities (\<75,50 \> and \<32,50 \>). (c) The ECG of endocardial ischemia (top line) and epicardial ischemia (bottom line); two leads are at the same positions as in (A). Two ischemia areas are shown in Figure 6(c).
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Heterogeneity, anisotropy and inhomogeneity
-------------------------------------------
The heterogeneity of a model is described in two ways. First, a specific field *type*, indicating cell type, is defined in the cell program, but whose value is initially stipulated in the anatomical model when we process tissue slices, such as:
\[x, y, z\] = type, \...\...
x, y, and z are the coordinates. Values of other fields can be defined or not in the data file. With a nested *if-then*statement on the value of *type,*the cell program is divided into several parts, each being executed by cells of the specific type. Second, *type*can be modified at runtime to simulate pathological changes. After a cell type is changed, its program and therefore its behavior also change.
In a tissue or organ, aside from heterogeneity, cells often show anisotropy and inhomogeneity that cannot be conveniently described while processing the raw data. To describe these two properties needs a bit of pattern formation programming \[[@B24]\], an interesting and challenging issue of biological modeling with cellular automata. In building the whole-heart model, the first relevant issue is cells at different layers in cardiac walls have different electrical properties \[[@B16],[@B25]\]. To express this inhomogeneity, we developed a resolution-and dimension-independent algorithm to stratify cardiac walls into layers at the initial stage of runtime. The algorithm is comprised of three steps, and is run by all cells:
Let the layer number of SAN cells (at least one SAN cell is on the epicardium) be 0 and the layer number of AVN cells (at least one AVN cell is on the endocardium) be 50.
• If the current cell is neither a ventricular nor an atrial cell, then: if it connects to a cell whose layer is 0, its layer is 0; if it connects to a cell whose layer is 50, its layer is 50.
• If the current cell is a ventricular or an atrial cell, then: visit all its neighboring cells and find out their minimal layer number, *Min*. The layer of this cell is *Min+1*.
A slice of the stratified 3-D model and of the stratified 2-D model is shown in Figure [6](#F6){ref-type="fig"}. After stratification, the layer number of each ventricular cell is added to its HH equations as a special parameter to control and adjust its action potential duration (we do not use the layer number of atrial cells). This procedure ensures that epicardial cells have shorter action potential duration than endocardial cells, and the epicardium-to-endocardium repolarization is naturally and faithfully established. By assigning a large layer number to cells in the middle layers of the ventricular walls, an unusually long action potential duration is created, and the specific electrical property of M cells can be naturally simulated \[[@B25]\].
The slices of the digital cadaver do not provide any useful information on the distribution of terminal Purkinje fibers. Even if we know that most of them are located in the subendocardium, it is impractical to make a slice-by-slice manual description. Based on the stratified cardiac walls, this issue can be easily solved by using a lateral inhibition algorithm applied to cells on the ventricle subendocardium to generate a mesh-like Purkinje network. On completion of running the algorithm, some of the cell types are changed from ventricular cell to Purkinje cell.
The more difficult engineering issue is the fine structure of cardiac cells and conduction fibers. Simulation with the 2-D model demonstrates that, even if the HH action potential model of Purkinje cells produces a very fast upstroke, which means a quick transjunctional conduction, yet a one-cell by one-cell conduction can never give normal propagation profiles as observed in Durrer\'s experiment, due to a too long transjunctional delay \[[@B26]\]. Nevertheless, our simulation shows that the rapid conduction in conduction fibers can be implemented by *n*-by-*n*cell communication among automaton cells of conduction fibers without physically building the fiber structure; *n*= 4 gives very satisfactory simulation results. Again, we propose that by using a pattern formation algorithm the physical construction of fiber structures is also feasible. In this scenario, a fiber is assembled by *n*successive automaton cells sharing the same, unique identity number, among which there is no conduction delay. Currently, with the 2-D model we find that even if letting each automaton cell stand for a discrete ventricular cell, the model works quite well in ECG simulation.
Computation within and between cells
------------------------------------
Each automaton cell is a computing unit for action potential and ECG simulation. The electrical activity of each automaton cell of a specific cell type is described by the corresponding HH type action potential model. Five action potential models are employed to simulate activities of different cardiac cells (The cells of trunk conduction fiber in atriuma and ventricles use the action potential model of the Purkinje cell) \[[@B27]-[@B31]\]. Since the models are based on experimental data from different animal species, parameters of K^+^channels are slightly changed to produce action potential duration of human cardiac cells. Time constraints are the only reason for us to adopt early published, simpler action potential models. In the given simulations, all action potential models are solved using explicit Euler integration with a time step, Δt, of 0.01 ms \[[@B32]\]. An asynchronous adaptive time step method has also been developed to speed up simulation \[[@B49]\]. Electrical activities at channel (Figure [4](#F4){ref-type="fig"}), cell (Figure [5](#F5){ref-type="fig"}), and organ (Figures [6](#F6){ref-type="fig"}, and [7](#F7){ref-type="fig"}) levels are monitored and captured at runtime.
::: {#F4 .fig}
Figure 4
::: {.caption}
######
**The channel level electrical activities of a ventricular cell.**(a) The transjunctional currents from eight neighboring cells. (b) The state of gating variables. (c) The transmembrane ionic currents.
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::: {#F5 .fig}
Figure 5
::: {.caption}
######
**The cell level electrical activities of a ventricular cell.**The top line is the transmembrane potential; the middle line is the transmembrane current; the bottom line is the stimulating current received from neighboring cells. The cell is under progressive ischemia, which can be reflected in the change of action potential.
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Each automaton cell in the 3-D model has 26 neighbors, linked by gap junctions. When a cell depolarizes, driven by the potential difference between it and its neighboring cells, transjunctional currents generate and propagate to neighbors through gap junctions. Simulations with the 2-D model show that the simple static gap junction model, in which the resistance of the gap junction is a constant and the transjunctional current follows Ohm\'s law, works quite well. The dynamic gap junction models, in which the resistance of gap junction changes in a nonlinear manner with membrane potential, will significantly increase computational time \[[@B33],[@B34]\] and create an extra burden for large-scale modeling.
Values of gap junction resistance between different cells and in different directions are initially set according to available experimental data, and then tuned via simulation according to Durrer\'s experimental observations \[[@B26]\]. Excitation conduction between cells of the same layer follows an end-to-end propagation, and between cells of different layers is a side-to-side process. Parameters are also adjusted to fix the ratio of side-to-side conduction speed vs. end-to-end conduction speed to be one-third in ventricular cells and one-tenth in atrial cells \[[@B35]\]. Gap junction resistance can be modified at runtime to examine its effect on excitation propagation. For each cell in each round of computation, before solving the HH equations, the transmembrane potentials of all neighboring cells are checked and the transjunctional currents computed and summed to get the stimulating current, *I*~*stim*~, that the cell receives. The direction and speed of electrical propagation within the heart are jointly controlled by: (1) the stratification of the ventricular walls, (2) the speed of end-to-end and side-to-side conduction, (3) the ratio of end-to-end conduction speed to side-to-side conduction speed, and (4) the distribution of the trunk conduction bundle.
Description of pathological activity
------------------------------------
In the cardiac model built with the extended cellular automata, abnormal electrical activities are grouped into four classes. The first class is based on anatomical defects in the heart that can be described by changing the type of some cells, either in the anatomical model or in the cell program. The Wolff-Parkinson-White syndrome caused by atrium-ventricle bypasses is a representative case. The second class is resulted from aberrant environments, especially abnormal ionic concentration (e.g. hyperkalemia) which significantly influences action potential. Abnormality of transjunctional conduction constitutes the third class, and the fourth class is is comprised of anomalous dynamics of cellular electrical activity itself. Changes in the HH equations can simulate these aberrations. In most cases, pathological changes affect more than one aspect. For example, in addition to providing an abnormal cell environment, ischemia also results in changed cellular electrical activity and altered gap junction resistance. To simulate the effect of ischemia, a special field *blood,*with normal value 1.0 is defined in the cell program, and introduced as an extra parameter in action potential and in gap junction models. To multiply the conductivity of the gap junction by an abnormal value of *blood*(e.g., *blood* 0.7) can simulate a lowered gap junction conduction speed. A small value for *blood*, when inserted into the equation computing Ca^++^current, affects the generation of the action potential. Dynamically modified *blood*can naturally simulate progressive ischemia (Figure [5](#F5){ref-type="fig"} and Figure [7](#F7){ref-type="fig"}) \[[@B36],[@B37]\].
Combining these factors, a variety of arrhythmias can be simulated. For example, by partially or completely blocking the activity of cells, or the conduction of gap junctions at specific locations, various conduction blocks such as AV (atrium-ventricle) block, LBBB (left bundle branch block) and RBBB (right bundle branch block) can be conveniently simulated. Many rapid arrhythmias are triggered by successive ectopic beats. Such abnormal beats can be produced in the model by providing cells at specific locations with extra stimulation or by changing them from atrial/ventricular to SAN cells. For abnormal propagations such as long QT syndrome, caused by the extra long refractory period of M cells, we can adjust, either dynamically or statically, the layer number of cells at the middle layers of the ventricular walls. Complex spatiotemporal patterns of arrhythmias are formed through discrete cell-cell communication. By these means, arrhythmic electrical activities can be simulated in flexible ways, different from those models created by cable equations or other partial differential equations (PDE).
ECG simulation by computing field potential of every cell
---------------------------------------------------------
Linking ECG simulation directly with cellular and channel electrical activity is crucial for the understanding and treatment of arrhythmias. Since each automaton cell in our model is a computing unit, a cell level ECG simulation algorithm is developed to compute each cell\'s field point potential. The algorithm, implemented as a backend function coded in C language, shows strengths, because such cell level simulation builds a link between the action potentials of cells and the ECG waveforms. The limitation here is that this heart model does not include the chest, so that the contribution of thoracic tissues to body surface potential is much simplified. The model reads the membrane potential of every automaton cell and computes its field potentials at the standard lead locations.
Several assumptions are made in the computations on account of established physical laws. (a) Each (automaton) cell has a spherical shape. Thus, the transmembrane potential, *V*~*m*~, is uniform on all parts of the cell membrane, except at gap junctions. (b) Gap junctions occupy the same area and are symmetrically distributed on each cell. (c) The distance from cell to field point is long enough so that the two solid angles subtended by the positive and negative sides of a cell membrane to a field point are equal. (d) Dielectric effects on field potential are neglected. σ~*media*~is the average conductivity of the 1-D tissues between a source cell and a field point; σ~e~the conductivity of the intercellular matrix; and σ~*i*~the conductivity of the intracellular cytoplasm. (e) For any neighboring cells, *j*and *k*, σ~je~= σ~ke~, σ~ji~= σ~ki~and φ~je~= φ~ke~, φ~e~is the potential in intercellular space. For convenience, we present the algorithm for the 2-D model here; the 3-D case is similar. The equation computing the field potential of an isolated cell at field point P is \[[@B38]\]
σ~i~φ~i~- σ~e~φ~e~is the double layer strength of the cell membrane. When there is no propagation on the cell membrane, the field potential is zero. If the cell connects with eight adjacent cells, equation (1) becomes:
Here, σ~i~φ~i~- σ~ji~φ~ji~is the double layer strength of the gap junction between the cell and its *j*th neighbor. The transjunctional potential difference between the two cells then becomes:
φ~i~- φ~ji~= φ~i~- φ~e~+ φ~e~- φ~ji~= φ~i~- φ~e~+ φ~je~- φ~ji~= V~m~- V~jm~ (3)
S1 to S8 are areas of the eight gap junctions; Ω~1~to Ω~8~are solid angles subtended by them; and S0 denotes the remaining part of the cell membrane (Figure [8](#F8){ref-type="fig"}). Let the membrane area positive to P be S~B~and the area negative to P be S~A~. If: (a) S~B~= S~A~, (b) the same and even number gap junctions distribute symmetrically on S~B~and S~A~, and (c) all gap junctions have an equal area, then it can be proved that:
::: {#F8 .fig}
Figure 8
::: {.caption}
######
**Computing the field potential of single connected cells.**This figure shows the distribution of gap junctions on the membrane of cells in a 2-D cell array and how gap junctions contribute to field potential. φ~*i*~is the potential within the current cell; φ~1*i*~is the potential within the first neighboring cell;  is the normal direction of the transjunctional potential difference between the current cell and its first neighboring cell; \... Ω is the solid angle subtended by the current cell at field point P.
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Here, Σ K~A~is the sum of areas of gap junctions on S~A~, and Σ K~B~is the sum of areas on S~B~. In this circumstance, the first term in equation (2) is zero, and only the second term makes a contribution to field potential. The equation now becomes:
Considering all Sj (j = 1\...8) to be equal, and cos α~1~= cos α~5~= cos 90° = 0, we have:
Here,  is a constant that affects only the baseline, but not the shape of the ECG waveform. The field potential at point P, generated by the whole heart, is the superposition of all cells\' contributions:
Here, *n*is the number of automaton cells, and φ~j~(P) is computed with equation (5).
Due to the time needed for the numerical solution of massive HH equations, the computing of σ~media~R^2^has to be much simplified, as described in equation (7), where σ~media\_i~is the conductivity of tissue *i*, and R~i~is the length of tissue *i*on the line between the source cell and the field point P.
As noted above, both the boundary effect and order of dielectric distribution are neglected. The 2-D (3-D) boundary between two tissues is treated as a 1-D boundary, and the ordered dielectric distribution is treated as an unordered distribution. Because of the huge number of cardiac cells and various possible field points on body surface, epicardium, endocardium and cardiac cavities, it is impossible to deal with numerous situations of boundary conditions between cells and field points. The method we adopt here is to make a runtime traverse from the source cell to the field point and meanwhile check the conductivity of each tissue and determine the 1-D space it occupies. The scaled distance is 1.0 between two perpendicular-connected cells, and 1.414 between two oblique-connected cells. Although the electrical property of non-cardiac tissues is much simplified, the electrical property of cardiac cells is intensively considered. Cardiac cells under different conditions have different conductivity \[[@B39]\]. It is σ~Depo~= 0.4 mhos/m in depolarization, σ~Repo~= 0.25 mhos/m in repolarization, σ~Rest~= 0.2 mhos/m in resting state, σ~Infarct~= 0.1 mhos/m in acute infarcted area, and σ~Ischemia~= 0.16 mhos/m in ischemic area. We let σ~Blood~= 0.6 and σ~Chest~= 0.1 be the average conductivity of tissues in chest \[[@B40],[@B41]\]. We find ECG simulation is not clearly impaired by this simplified dielectric description, but benefits from the intensified cardiac tissue description.
Results
=======
Factors that influence performance of the parallelized cellular automata model
------------------------------------------------------------------------------
For the physically parallelized whole-heart electrophysiological model built with the extended cellular automata, several factors impair the simulation efficiency on a cluster of SMP.
The first difficulty is the graphic display of the simulation. The main display window, as the critical resource in the parallelized program, can only be sequentially accessed by the cells. Thus, to display the updated state of all cells leads to a significant decrease of running speed. We mitigate this problem by displaying the cell state every 20 or even 50 steps, instead of every single step. The second problem is the overhead of communication among *slaves*located on different nodes. The time cost of communication, spent on the exchange of boundary sheets between neighboring *slaves*in each round, rises with the increase of *slave*number. An extreme case for a 128 × 128 × 128 model is that there are 128 nodes, and each *slave*deals with just one sheet, requiring every sheet to be exchanged in each round. The physical link between nodes also significantly affects performance. An additional limitation is that the overhead of *fork/join*operations in the OpenMP parallelized program degrades performance, although not very significantly. The OpenMP directive *parallel*can be inserted either before the endless *while*loop, or more simply, before the three *for*loops. If it is inserted before the *for*loops, the *fork*and *join*operations, which create and delete threads and allocate and collect memory for temporary variables in each thread, will be repeatedly executed in each round. The preferable way, which eliminates this unnecessary expenditure, is to insert the directive *omp parallel*before the *while*loop, and the directive *omp for*before the *for*loops. Between the *omp parallel*and the *omp for*,*omp master*is used to limit parallelism to only the cell program part. Finally, load balance becomes a limitation when a model has an irregular and/or heterogeneous structure. The heart, with four chambers and an uneven shape, is a typical case. Usually, on a cluster consisting of *m*identical nodes each containing *n*CPUs, a program is evenly dispatched to distribute the cell space across all nodes. We find that using this strategy, the 3-D heart model cannot reach the best load balance and performance because different nodes deal with different numbers of cardiac cells. Furthermore, even if each node contains the same number of cardiac cells, since different cells run different action potential models, the burden of computation remains unequal. Only a solid cubic model with homogeneous cells occupying the full cell space can ensure a best performance. Thus, if a model needs to run many simulations, an important issue is to find the best cell space partition.
Evaluation of the 3-D cardiac model
-----------------------------------
Pilot runs with the 3-D model have been made on a 4-node SUN computer cluster. The head node has eight UltraSparc CPUs, and the other nodes each have four identical CPUs. Five processes, 1 *master*and 4 *slaves*, are created at each run. The *master*and a *slave*are assigned to the head node, and each remaining *slave*is assigned to a node. Within each *slave*, four threads are created using the OpenMP *parallel*directive. Figure [9](#F9){ref-type="fig"} gives the performance results for an even partition strategy. With this partition, due to the irregular structure of the heart and the heterogeneity of cardiac cells, the combination of 4 *slaves*-4 threads does not give the best performance. The 4 *slaves-*2 threads setting behaves better because the overall cost is lower. . However, when the whole cell space is occupied by ventricular cells, the 4 *slaves*-4 threads version provides the best performance, as predicted.
::: {#F9 .fig}
Figure 9
::: {.caption}
######
**The performance of running the 3-D model on a cluster of SMP nodes.**(a) When the 3-D cell space is sparsely occupied by the heart model (left), the evenly dispatch strategy does not produce the best performance. (b) When the cell space is fully occupied by ventricular cells (right), the best performance is guaranteed.
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Discussion
==========
Arrhythmias are a group of complex syndromes not well understood. Many difficult issues exist when investigating arrhythmias through computational modeling. We cover here only a few relating to model building and running.
We adopt early published action potential models in the current 3-D model because they are simpler and more computationally affordable. In the first version of the Luo-Rudy model \[[@B30]\], there are six ionic channels, and the fluctuation of ionic concentration is not described. In the second version, there are many more channels, and the dynamic ion concentrations are described by another large group of ODEs \[[@B42]\]. It is straightforward to upgrade the cardiac model by replacing old action potential modelswith new ones. However, action potential models are not the whole story for a cardiac model. One has to make a compromise between the complexity of action potential models and the resolution of the cardiac model, because the computational burden also is due to the latter. Pollard *et al*. \[[@B43]\] in 1993 reported a cardiac model containing 400,000 computing nodes, but a much simplified action potential model was used \[[@B44]\]. This strategy was also adopted by other modelers \[[@B45]\]. We argue that full action potential models are important for modeling and understanding arrhythmias, especially those triggered by abnormal ionic electrical activities. However, to simulate more complex spatio-temporal cardioelectrical activities such as spiral waves in fibrillation, the current resolution of the model is undoubtedly insufficient. Technically, it is not difficult to adopt a higher resolution with more precise data, such as the digital female cadaver slices, which have an interval of 0.33 mm \[[@B17]\]. To double the resolution using a 256 × 256 × 256 coordinate system is another choice. By either method, the cell program, the pattern formation algorithms, and the ECG simulation algorithm remain the same -- they are resolution-independent. This is a prominent and beneficial feature of such cellular automata modeling.
Although experimental evidence show that fiber orientation takes a role in arrhythmia generation \[[@B46],[@B47]\], to implement a highly realistic description of fiber orientation is expensive because of the difficulty in acquiring sufficient validated data \[[@B48]\]. Encoding these data into models is also quite complex, requiring the use of complex mathematical tools such as tensors. In our model, a new approach is proposed for stratifying heart walls. If fibers are simply built with cells of the same layer, they automatically acquire an arc shape (Figure [6d](#F6){ref-type="fig"}) that can assume various orientations. Comparison of effectiveness between the two methods is currently not available due to the lack of sufficient simulations.
Another issue relates to ECG simulation. Although simulation results of the 3-D model have not been acquired thus far, the simulated ECGs with the 2-D model in different lead locations and under physiological and pathological conditions are impressive and qualitatively agree with recorded ECGs, supporting the validity of the algorithm. Theoretically, the boundary effect of dielectrics is not negligible for field potential computing; yet in practice simplifications are often inevitable. So far we find that our simplified treatment of boundary effect on field potential does not visibly affect ECG simulation. There may be two reasons for this. First, the conductivity of the tissues (not including the heart) in the chest may not be significantly different. Second, the boundaries among different tissues are so irregular that the net boundary effect may be effectively neutralized. On the other hand, we find that to let cardiac cells under different conditions (depolarization, repolarization, resting state, and ischemia) have different conductivity can improve the ECG quality, indicating that the precise description of the source may be more important than the precise description of the dielectric.
Finally, we point out that, as in single cell models where adaptive time steps can greatly improve the running performance, this same strategy can produce the same results in multicellular models built with this cellular automaton \[[@B49]\]. Simulation with the 2-D model shows that an overall speed improvement of 4.5 is reached.
Conclusions
===========
Effective simulation of arrhythmias needs a whole-heart model, differential description of electrical properties of cardiac cells, membrane equation based computation, association between cellular activities and ECG generation, flexible description of pathological conditions, and long running time. To comprehensively address these issues, we develop a method based on cellular automata and parallel computing technologies to build large-scale electrophysiological models with extended cellular automata, and run such models on clusters of shared memory machines. The dynamically traced and captured electrical activities at channel, cell, and organ levels can substantially help us understand abnormal cardioelectrical activities through simulation. Simulation results with the 2-D model support the validity of the ECG simulation algorithm. Transparent cluster computing is a convenient and effective solution to the excessive time consumption of computational intensive simulation.
In addition to reaching a mechanistic understanding of arrhythmias, an important goal of *in silico*research is to facilitate the discovery and evaluation of drugs. This helps to reduce the risk and cost of clinical trials, shorten the cycle of development, and remove randomness in candidate screening. A whole-heart electrophysiological model that links electrical activities at channel, cell, and organ levels can help achieve this result. The modeling method described in this paper shows the advantages of precisely linking cell and organ activities, exploiting the intrinsic parallelism in tissue/organ level biological activities. Besides modeling electrical activity, the method is also applicable to many other multicellular models in which quantitative description is required.
Authors\' contributions
=======================
HZ develops the methods and built the initial 3-D model. AM provides data of conduction system distribution in ventricles. YS and GR help solve some technical issues. PD is responsible for the project.
Acknowledgements
================
The authors wish to extend their sincere appreciation to our funding agency, Agency of Science, Technology and Research (A-STAR), Singapore for supporting the present work.
|
PubMed Central
|
2024-06-05T03:55:47.768591
|
2004-8-30
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517726/",
"journal": "Biomed Eng Online. 2004 Aug 30; 3:29",
"authors": [
{
"first": "Hao",
"last": "Zhu"
},
{
"first": "Yan",
"last": "Sun"
},
{
"first": "Gunaretnam",
"last": "Rajagopal"
},
{
"first": "Adrian",
"last": "Mondry"
},
{
"first": "Pawan",
"last": "Dhar"
}
]
}
|
PMC517727
|
Background
==========
A number of previous reports have indicated an excess of leukaemia in Broome County, New York, particularly in the Town of Union \[[@B1]-[@B5]\]. The Broome County Health Department in conjunction with the New York State Department of Health (NYSDOH) conducted a study of cancer incidence among residents of several communities in Broome County for the years 1976--1980 and found a significant excess of leukaemia among males in the village of Endicott, which is located in the Town of Union \[[@B1]\]. In a follow up study, NYSDOH investigated cancer incidence for the years 1981--1990 \[[@B2]\]. As in the previous study, leukaemia was elevated among males in the Village of Endicott, although the findings were not statistically significant. When data were evaluated for the neighbouring village of Johnson City as well as for the entire Town of Union, significantly elevated rates of leukaemia were observed among males in both areas (unpublished data). When the data were examined more closely, it was noted that the majority of the leukaemia excess was limited to males ages 65 and older (Table [1](#T1){ref-type="table"}). In addition, an atlas of cancer incidence in New York State between 1992 and 1996 shows that Broome County continues to have a statistically significant elevation of leukaemia among males \[[@B3]\].
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Leukaemia incidence by age among males in the Town of Union, Broome County, NY: 1981--90.
:::
**Age Group** **Number of cases** **SIR** **95% C. I.**^a^
--------------- --------------------- ------------- ------------------ ---------- ----------
Observed Expected^b^ Lower CI Upper CI
0--44 6 7.5 0.80 0.29 1.75
45--64 7 10.0 0.70 0.28 1.44
65--74 21 10.1 2.09 1.29 3.19
75+ 20 12.7 1.57 0.96 2.42
Total 54 40.4 1.34 1.01 1.75
^a^Exact 95% confidence intervals calculated for the Poisson distribution^30^.
^b^Expected numbers based on the NYSDOH Bureau of Cancer Epidemiology Cancer Incidence Standard: 1983--1987, which includes age and sex specific cancer rates for population density Quintile III (suburban). Population of the study area based on 1986 estimated population of the Town of Union based on linear interpolation between 1980 and 1990 Census population estimates.
:::
Spatial analysis techniques have also been used to investigate clustering of leukaemia within central New York \[[@B4],[@B5]\]. Analysis of this well studied data set of 592 leukaemia cases has generally shown an area of increased risk in the Town of Union although the increase has not been statistically significant in all analyses.
The International Agency on Cancer Research (IARC) has classified employment in the boot and shoe manufacturing industry as a Group 1 risk factor, meaning there is sufficient evidence that the exposure or setting is carcinogenic to humans \[[@B6]\]. A number of chemicals used in the shoe and boot manufacturing industry including chlorophenols, hexavalent chromium, aniline and azo dyes and benzene are known or suspected carcinogens. Of these, benzene has most often been implicated as a likely etiologic agent in the development of leukaemia among workers in the industry. IARC has classified benzene exposure as a Group 1 carcinogen \[[@B7]\] and the United States Environmental Protection Agency has also characterized benzene as a known human carcinogen for all routes of exposure based upon convincing evidence from human studies and supporting evidence from animal studies \[[@B8],[@B9]\]. Exposure to benzene has been most strongly associated with acute myeloid leukaemia, the most common type of leukaemia in adults \[[@B7],[@B9]\].
A number of epidemiological reports have shown an association between employment in the shoe and boot manufacturing industry and an increased risk of leukaemia mortality among workers in Italy, Turkey and Great Britain \[[@B10]-[@B15]\]. The workers found to be most at risk were those who worked in specific jobs where exposure to solvents and glues containing high levels of benzene was common. In Great Britain, elevated mortality rates were found only among workers in the departments where solvents and glues were used to attach soles to the upper parts of shoes, and exposure to benzene occurred \[[@B12]\]. In Italy there was also evidence that the elevated risk of leukaemia was highest among workers who began work prior to 1963, after which time glues containing high levels of benzene were banned by law \[[@B13],[@B14]\]. A follow-up of the Italian cohort of workers found that the risk of leukaemia increased with increasing cumulative exposure to benzene \[[@B15]\]. Similar results, however, have not been reported in studies of mortality among workers in shoe and boot manufacturing in the United States \[[@B16]-[@B19]\].
The Endicott Johnson Company was the major employer in the Town of Union between 1930 and 1960 \[[@B20]\]. The company manufactured shoes and boots in the Endicott and Johnson City area beginning shortly before the turn of the century. At the peak of its activity, in the 1950\'s, the company employed approximately 20,000 workers in leather tanning and shoe production at numerous factories throughout the Town of Union and neighbouring communities. Beginning in the mid 1960\'s the company began shifting its manufacturing facilities to areas of the southern United States and eventually overseas. Shoe manufacturing in the Endicott and Johnson City areas continued to decline in 1970\'s and 1980\'s as the company focused more on retail sales and eventually ceased production in the mid 1990\'s.
The objective of the current study is to investigate the association between leukaemia incidence and employment in the Endicott Johnson tanneries and shoe and boot manufacturing facilities, in the Town of Union, Broome County, New York.
Methods
=======
Study Population
----------------
A matched case-control study was conducted to investigate the association between leukaemia incidence among males 65 and older and employment in the shoe and boot manufacturing industry. The New York State Cancer Registry served as the source for the leukaemia cases. Because the excess of leukaemia was limited primarily to males 65 and older, the selection of cases was restricted to males aged 65 and over with a primary diagnosis of leukaemia (ICD9 204--208) occurring between the years of 1981--1990 and residing in the Town of Union, Broome County, NY at the time of diagnosis. In addition, all cases must have been deceased as of August 1997 and a resident of the Town of Union at the time of death. Since acute myeloid leukaemia (AML) has been most closely associated with exposure to benzene, a subset of the original cases, which included only cases of AML (ICD9 205.0), was also examined. Once the cases were identified from the Cancer Registry, death certificates for each were obtained from the NYSDOH Vital Records Section.
Death certificates for controls were obtained from the NYSDOH Vital Records Section. Four controls meeting the following criteria were selected at random for each case. Controls were restricted to males 65 years and older who resided in the Town of Union at the time of death. In addition, controls were matched to cases on year of death and year of birth +/- 1 year. Matching on dates of birth and death was done to control for potential confounding due to age and to ensure that the cases and controls had a similar opportunity of being exposed (i.e. to work at Endicott Johnson). Additionally, the controls must not have had leukaemia listed as either a cause of death or a contributing cause of death on their death certificates.
Of the 41 leukaemia cases among males 65 and older listed in Table [1](#T1){ref-type="table"}, thirty-six cases were identified that met the study criteria; these were matched to 144 controls. Five of the 41 incident cases were eliminated because they were not known to be deceased at the start of the study. For one control the employer could not be identified from any field on the death certificate. A new control was chosen using the predefined restriction and matching criteria. Twelve cases of acute myeloid leukaemia were identified among the 36 leukaemia cases.
Assessment of Occupation/Exposure
---------------------------------
Occupation was determined from information on the death certificate because this represented the most readily available source of occupational information. No company or union records were easily available to determine employment or job status. The company has not allowed previous researches access to company records for occupational health studies \[[@B18]\]. In addition, because of a fairly generous benefits package, labour unions were never able to organize most of the workers under investigation thus union records could not be used as a source of information. \[[@B20]\].
For the purpose of this study an individual was considered exposed if Endicott Johnson was listed on the death certificate under \"Name and locality of firm or company\". If this field was blank or the employer could not be determined, the fields \"usual occupation\" and \"kind of business\" were examined to see if the employer could be determined. The individual responsible for assigning exposure was blinded to case or control status of the study subjects. Because of the ambiguity of many of the listings of occupation on the death certificates, it was not possible to subdivide Endicott Johnson employees further by occupation in order to exclude those employees who had no exposure to carcinogenic chemicals or processes. Therefore all workers in the shoe and boot making factories as well as workers from the nearby Endicott Johnson tanneries were included among the group considered to be exposed.
Statistical testing
-------------------
Crude odds ratios (OR) were first calculated for \"exposed\" versus \"non-exposed\" groups. However, since each case was individually matched to a set of four controls, the matched sets were analyzed as individual strata. An adjusted OR was therefore calculated taking into account just the contribution of the discordant pairs within each stratum \[[@B21]\]. The SAS Software System V8 was used to calculate the adjusted odds ratios using conditional logistic regression \[[@B22]\]. These data were analyzed separately for all leukaemia cases and their matched controls combined as well as for just cases of AML and their matched controls.
Results
=======
Approximately 29% of the study subjects (cases and controls) were employed by Endicott Johnson. This was more than the next 5 largest employers in the area combined. Table [2](#T2){ref-type="table"} gives a comparison of the cases and controls according to usual employment at Endicott Johnson. The crude odds ratio for leukaemia among those employed at Endicott Johnson vs. not employed at Endicott Johnson was 1.52 (95%CI 0.70 -- 3.30), while the adjusted odds ratio was 1.47 (95%CI 0.70, 3.09). When analysis was restricted to include only those cases of AML, the crude OR was 1.21 (95%CI 0.31, 4.69), while the adjusted odds ratio was 1.19 (95%CI 0.33, 4.28) (Table [3](#T3){ref-type="table"}).
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Crude and adjusted risk of leukemia among males 65 and older, by usual employer.
:::
**Employer** **Cases** **Controls** **Total** **Crude OR (95%CI)** **Adjusted OR (95%CI)\***
------------------ ----------- -------------- ----------- ---------------------- ---------------------------
Endicott Johnson 13 (36%) 39 (27%) 52 1.52 (0.70 -- 3.30) 1.47 (0.70 -- 3.09)
Other Employer 23 (64%) 105 (73%) 128 **-** **-**
Total 36 144 180
\*Adjusted Odds Ratio and 95% Confidence Intervals calculated using conditional logistic regression to account for matching on date of birth and age.
:::
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Crude and adjusted risk of AML among males 65 and older, by usual employer.
:::
**Employer** **Cases** **Controls** **Total** **Crude OR (95%CI)** **Adjusted OR (95%CI)\***
------------------ ----------- -------------- ----------- ---------------------- ---------------------------
Endicott Johnson 4 (33%) 14 (29%) 18 1.21 (0.31 -- 4.69) 1.19 (0.33 -- 4.28)
Other Employer 8 (67%) 34 (71%) 42 **-** **-**
Total 12 48 60
\*Adjusted Odds Ratio and 95% Confidence Intervals calculated using conditional logistic regression to account for matching on date of birth and age.
:::
Four study subjects (1 case and 3 controls) had shoe worker as their occupation but their employers were companies other than Endicott Johnson. Odds ratios and confidence intervals were calculated with the subjects considered both as exposed and unexposed. The results of the study were not significantly different. For the results presented here the four subjects were considered as not working for Endicott Johnson (i.e. unexposed). None of these study subjects were part of the AML subgroup.
Discussion
==========
Overall those whose death certificates indicated that they worked at Endicott Johnson had approximately a 50% higher risk of developing leukaemia than those who did not work for the company; however, there was not enough evidence to rule out the possibility that the observed results were due to chance alone. Among the types of leukaemia, occupational exposures have been most closely associated with acute myeloid leukaemia; thus we might have expected to observe a greater risk of AML among Endicott Johnson workers. This was not the case, however, as the risk of AML was slightly less than that observed for all leukaemias.
Previous studies of workers employed in the shoe and boot manufacturing industry in the United States have failed to find an elevated risk for leukaemia mortality \[[@B16]-[@B19]\]. In contrast, several occupational studies in Italy and Great Britain have reported an elevated risk of leukaemia mortality among shoe and boot workers \[[@B12]-[@B15]\]. While we did observe an elevated risk of leukaemia among workers in the current study, the excess was not statistically significant. Differences in study design may have accounted for some of the variation in results observed between the European and US studies. The British and Italian studies were retrospective cohort studies, whereas three of the four US studies were proportional mortality studies. The use of a cohort study design allows better exposure assessment and control for confounding. The only US cohort study was of shoe workers in a factory where benzene was never used as a solvent in glues as it had been in the European factories \[[@B19]\]. Although the current study used a case control study design, many of the limitations of the proportional mortality studies also existed in the current study.
Limitations that may have prevented the observance of more conclusive findings including small sample size, limited work history, no exposure assessment and limited control of confounding factors. Table [4](#T4){ref-type="table"} describes several potential sources of bias in the study and how they may have affected the results.
::: {#T4 .table-wrap}
Table 4
::: {.caption}
######
Potential forms of bias and the direction that they may have influenced the results.
:::
**Cause or Source of Bias** **Direction of the Effect**
------------------------------------------------------- --------------------------------------
Accuracy of \"Usual Occupation\" on Death Certificate Either (most likely toward the null)
Only deceased individuals eligible as controls Toward the null
Lack of specific job titles Toward the null
Migration into and out of region Toward the null
No information on length of employment Toward the null
No information on specific chemicals used Toward the null
:::
The power to detect a true increase in risk was limited by the population size of the study. Because this study was a follow-up to a previous study, the population was limited by the constraints of the previous study. Leukaemia is a relatively rare disease and the population of white males over 65 in the study area was only approximately 3,500. For the current study the power to detect an increased risk of 50% (similar to the observed risk for leukaemia) with a 95% confidence interval was only 20%. In order to achieve a power of 80% the study population would have had to have been approximately eight times as large. This could have been achieved by either increasing the study area to include neighbouring communities or by increasing the period under observation. However, as mentioned previously we were limited by the parameters of the previous study.
The accuracy of occupation and industry data found on death certificates has been examined in a number of studies \[[@B23]-[@B27]\] and their value in epidemiological studies has been questioned by some \[[@B26],[@B28]\]. Studies have generally found industry listed on the death certificate to be accurate between 50% and 80% of the time when compared to data collected from the next of kin or from company records. The accuracy of occupation/industry information of death certificates used in the current study, however, was probably in the higher end of those ranges for several reasons. The current study was limited to white males and previous studies on the accuracy of industry and occupation on death certificates have found a higher concordance with other data sources among whites compared to blacks \[[@B26]\]. Since we were seeking information on employer and industry not on specific occupations, we also believe this lead to greater accuracy. Concordance between \"company\" found on death certificates compared to work histories has been found to be accurate 81% of the time while among those retired at the time of death 91% concordance has been reported \[[@B27]\]. In addition, because Endicott Johnson was the major employer in the area at the time, it was more likely to be known by the next of kin. Nonetheless it is likely there was some misclassification of employer on the death certificates. Usual occupation as listed on the death certificate may not have been accurate for workers who switched jobs late in life. However, this type of misclassification has been found to occur in a random manner, thus, it would have likely biased the results slightly toward the null \[[@B25]\].
In addition, only dead individuals were eligible as controls in the study. Since working in the shoe and boot manufacturing industry is associated with other kinds of types of cancer, such as lung and bladder cancer, in addition to leukaemia, this may have artificially increased the prevalence among controls. This would also bias the odds ratio towards the null.
A major limitation in this study was the assessment of exposure. Because death certificates were used to identify usual employer and occupation, information on specific jobs worked was fairly limited and often missing completely. Even when the employer was known to be Endicott Johnson, a nondescript job title such as \"shoe worker\", \"Endicott Johnson worker\", or \"labourer\" was often given for occupation. Because of this, any mention on the death certificate of having worked at Endicott Johnson was used as a surrogate for exposure. The effect of including every Endicott Johnson worker in the exposed group may have biased the odds ratio toward the null due to the large variety of jobs within each factory. In addition to all workers in the shoe and boot making factories, workers from the nearby Endicott Johnson tanneries were also included among the group considered to be exposed, further diluting the effect. Previous studies have found an increase in leukaemia mortality only among men in departments where shoes were assembled \[[@B12]-[@B15]\].
Additionally, it was not known what chemicals were used in the production of shoes at the Endicott Johnson facilities. Therefore, it is difficult to know if the lack of an association between leukaemia and employment for Endicott Johnson may have been a result of poor exposure assessment or a result of no exposure to certain carcinogens.
The length of employment and timing of the exposure were also not taken into account. However, the \"usual occupation\" as listed on the death certificate is most likely to represent long-term, stable employment. In Italy, the highest leukaemia rates were found among workers who worked in the industry prior to 1963 \[[@B13]\]. Estimates for the latency between occupational exposure to carcinogens and the development of leukaemia range from 2 to 20 years. Therefore, the temporality of the exposure and disease development suggests that many of the cases would have occurred before our study period. In addition, previous studies have found that the biggest increase in leukaemia mortality occurred among male workers less than 50 \[[@B9]\]. In the current study we focused exclusively on males over 65 because rates among males less than 50 were not significantly elevated.
Migration is a problem when investigating diseases such as cancer that have a long latency period. In the current study this may have been compounded by the fact that the workforce at Endicott Johnson has been declining since the mid 1950\'s as the company slowly scaled back and eventually eliminated its production facilities in the area. In addition, both cases and controls may have retired and moved out of the area. Overall, however, it is felt that those males age 65 and older in this region represent a fairly stable population. Nonetheless, any misclassification due to migration would certainly bias the results toward the null since it is unlikely that any cases who recently moved into the area would have worked for Endicott Johnson.
Most types of bias identified in this study would tend to lead to an underestimation of the true risk (i.e. bias the results toward the null). A summary of the types of biases identified and their effects is given in Table [4](#T4){ref-type="table"}. Because most would lead to an underestimation of risk it is likely that the true association between working for Endicott Johnson and the risk of leukaemia is somewhat higher than indicated. However to fully evaluate these biases a more thorough study design is needed.
In the study only age, gender and date of birth were controlled. Because of the study design, other possible confounders could not be taken into account. For instance, cigarette smoking has been associated with several forms of leukaemia, however no attempt was made to determine smoking status in the current study \[[@B29]\].
Conclusions
===========
The incidence of leukaemia was of interest in this community because a number of previous cancer investigations in the area have found an increase in leukaemia incidence. In addition, several studies have found an association between leukaemia and employment in the shoe and boot manufacturing industry, which was predominant in the town for most of the past century. In the current study, a positive association between the risk of leukaemia and working at Endicott Johnson was observed; however, the small population size prevented us from determining whether the results could be due to chance alone. Serious limitations may have prevented the observance of more conclusive findings in this study. Better exposure assessment, information on length of exposure and types of job held, control of confounding factors and information on chemicals used by this company would strengthen any future investigations. However, many of the most carcinogenic chemicals, which at one time were used in the industry, have not been used for several decades. In addition, since the company no longer manufactures shoes and boots, there is no current or future exposure among this particular group. Nonetheless, lessons learned from retrospective analyses of disease among workers in American industries may be applicable to overseas industries, particularly in developing nations, where many of the safeguards and restrictions that have been in place for decades in the US and Europe have not yet been adopted.
List of Abbreviations
=====================
AML, acute myeloid leukaemia
CI, confidence interval
IARC, International Agency on Cancer Research
ICD, International Classification of Diseases
NYSDOH, New York State Department of Health
OR, odds ratio
Competing interests
===================
None declared.
Authors\' contributions
=======================
Not applicable.
Acknowledgements
================
Supported in part by a grant from the Agency for Toxic Substances and Disease Registry (U50/ATU200002-13). The author wishes to thank John Camadine for death certificate abstraction; Gwen Babcock for statistical assistance; and Thomas Talbot and Syni-An Hwang for review and comment on the manuscript.
|
PubMed Central
|
2024-06-05T03:55:47.772794
|
2004-8-30
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517727/",
"journal": "Environ Health. 2004 Aug 30; 3:7",
"authors": [
{
"first": "Steven P",
"last": "Forand"
}
]
}
|
PMC517728
|
Background
==========
Otitis media (OM) is an inflammation of the middle ear, often seen in children younger than six year of age. OM is caused by infection of nasopharyngeal cells by the bacterium *Haemophilus influenzae*(HI). Complications of OM include permanent hearing loss and perforation of the tympanic membrane.
Generally, OM is treated with antibiotics such as penicillin derivatives. However, in spite of the effectiveness of antibiotic prophylaxis, the increasing bacterial resistance to antibiotics has caused some concerns. This has prompted the development of anti-adhesive agents against HI infection \[[@B1]\]. Today, several anti-adhesive agents such as xylitol and oligosaccharides have been studied in clinical trials \[[@B2]-[@B5]\]. Human casein has been shown to have an inhibitory effect on the adhesion of HI to human respiratory tract epithelial cells \[[@B6]\], but the active factor(s) has not been characterized. Recently, we have discovered that certain rice flour extract inhibits HI adhesion \[[@B7]\]. Results from the preliminary purification process indicated that the active factor(s) in the rice flour extract was amphiphilic and structurally resemble to the phosphoinositides. To verify this view, we examined in this study the anti-adhesion activities of phosphoinositides against HI using the models of human pharynx carcinoma (DT 562) cells and neonatal rats.
Results and Discussion
======================
Bioactivity of polyphosphoinositides
------------------------------------
The attachment (adhesion) of bacteria to a mammal\'s nasopharynx area is believed to be the first stage of the bacterial infection, which can lead to OM and other disorders and diseases caused by HI. For this study, *in vitro*effect of various phosphoinositides on the attachment of HI to nasopharyx was evaluated. The activity was defined as the percent of inhibition of HI adhesion to human pharynx carcinoma cells as compared to the control. Results in Table [1](#T1){ref-type="table"} show that four phosphoinositides, i.e., Ins-1,2,6-PPP, Ins-1,3,4-PPP, GPI and PI at a concentration of 0.1 mg/mL exerted no effect on HI adhesion to the human pharynx cell cultures. On the other hand, PI-3-P and PI-4-P showed 24% inhibition of HI adhesion. More, PI-3,4-PP at the same concentration showed 74% inhibition against HI adhesion. A dose-dependent inhibition of HI adhesion by PI-3,4-PP was observed between 0.006 and 0.1 mg/mL, which exerted 31 to 81% inhibition (Figure [1](#F1){ref-type="fig"}).
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Bioactivities (% inhibition) of phosphoinositides against the adhesion by *Haemophilus influenzae*
:::
Compound \% Inhibition Dose (mg/mL)
--------------- --------------- --------------
Ins-1,2,6-PPP 6^a^ 0.1
Ins-1,3,4-PPP -1 0.1
GPI -3 0.5
PI -2 0.1
Pl-3-P 24 0.1
Pl-4-P 24 0.1
PI-3,4-PP 74 0.1
^a^Within statistical error; thus no activity is presumed.
:::
::: {#F1 .fig}
Figure 1
::: {.caption}
######
The dose response curve of PI-3,4-PP against the adhesion by *H. Influenzae*.
:::
:::
In Vivo Activity of PI-3,4-PP
-----------------------------
The inhibitory activity of PI-3,4-PP against the attachment of nontypeable HI was further demonstrated in two trials using a neonatal rat model. Figure [2](#F2){ref-type="fig"} shows the average inoculum dose (cfu) and the average number (log~10~\[cfu/mL\]) of HI recovered for a total of 10 rat pups for each treatment. In trial 1, at the inoculum dose of approximately 100 cfu/pup, the treated group (PI-3,4-PP) containing 1 mg/mL of PI-3,4-PP showed an 80-fold (1.9 logs) reduction in the number of bacteria recovered 24 hours post-inoculation as compared to the control group (HBSS). In trial 2, the rat pups were exposed to much higher doses (approximately 700 cfu/pup) of bacteria. The treated group (PI-3,4-PP), which was protected by the same level of PI-3,4-PP, showed a 4-fold (0.6 log) reduction in the number of bacteria recovered. The result demonstrates that PI-3,4-PP can inhibit the attachment and thus the growth of nontypeable HI in the nasopharynx of neonatal rats.
::: {#F2 .fig}
Figure 2
::: {.caption}
######
*In vivo*activity of 1 mg/mL of PI-3,4-PP against the adhesion by *H. influenzae*.
:::
:::
The exact mechanism for the anti-adhesion activity of the phosphoinositides is not known at this time. However, the anti-adhesion activity may be associated with the structures of the phosphoinositides. Molecules containing no phosphatidyl group such as Ins-1,2,6-P, Ins-1,3,4-P and GPI, exerted no effects on adhesion. PI, which contains a phosphatidyl group, also had no activity. In addition to the presence of a phosphatidyl group, phosphorylation of inositol seems to be required for the bioactivity. Since PI-3,4-PP had a higher anti-adhesion activity than PI-3-P and PI-4-P, it is possible that the presence of extra phosphate groups at the positions 3 and 4 of the inositol moiety may exert an even greater effect. Results from a preliminary study (Jeffrey Baxter, personal communication) showed the presence of multi-phosphate groups in a molecule (such as phytate, inositol phosphate, and phosvitin) were inhibitory to HI adhesion. On the other hand, results from our study showed that PI-3,4-PP was more active than phytate (a *myo*-inositol hexaphosphate), *myo*-inositol penta-and tetra-phosphates (data not shown). Taken together, these results suggests that the presence of both a phosphatidyl group and an additional phosphate group is essential for the high anti-adhesion activity of PI-3,4-PP as compared to PI-3-P and PI-4-P.
It is known that bacterial adhesion involves specific recognition of carbohydrate receptors by pathogen proteins \[[@B4]\]. This specificity is probably one of the main factors that dictate in which tissue that pathogen species can successfully colonize. Previously, the anti-adhesion effect of some oligosaccahrides has been attributed to their bindings to the specific binding sites of pathogen\'s proteins \[[@B4]\]. These oligosaccharides serve as decoys and occupy bacteria\'s carbohydrate-binding proteins, and thus reduce the binding of pathogens to the native carbohydrate in epithelial cell membrane. Similarly, polyphosphoinositides present in inner ear tissue and kidney \[[@B8],[@B9]\] and other tissues have been postulated as *in vivo*receptor for aminoglycoside antibiotics \[[@B10]\]. It is possible that phosphorylated phosphatidylinositol such as PI-3-P, PI-4-P, and PI-3,4-PP may serve as decoys by occupying the binding sites in bacteria and prevent their attachment to the epithelial cells. It has also been reported that phosphatidylinositides can bind to mCD14, a cell-surface receptor on the membrane of monocytes and neutrophils \[[@B11]\]. Among those tested phosphatidylinositides, PI-3-P, PI-4-P, PI-3,4-PP, and PI-4,5-PP display the highest affinities for mCD14. Recently, non-typeable HI have been shown to adhere to human bronchial epithelial cells through the lipooligosaccharide (LOS) on the cell surface of the bacteria \[[@B12]\], and LOS further interacts with the platelet-activating factor (PAF) receptor to initiate host cell signal cascade and bacterial invasion \[[@B13]\]. It is then possible that phosphatidylinositides occupy the binding sites of the bronchial epithelial cells through binding to the membrane of these cells, thus reducing the number of binding sites available for HI attachment. By suppressing the binding of HI to the cell membrane, phosphatidylinositides prevents the replication of the bacteria.
Conclusions
===========
In conclusion, the PI-3,4-PP suppressed the adhesion of nontypeable HI to nasopharyngeal cells of neonatal rats, and thus preventing the replication of the bacteria in the animal. The results suggest that the phosphoinositides may be used to formulate pharmaceutical and nutritional compositions for prophylactic treatments of OM and other infections caused by HI.
Materials and Methods
=====================
Phosphoinositides
-----------------
Five different classes (I through V) of phosphoinositides were used for this study (Figure [3](#F3){ref-type="fig"}). Class I included 1-D-*myo*-inositol-1,2,6-triphosphate sodium salt (Ins-1,2,6-PPP) and 1-D-*myo*-inositol-1,3,4-triphosphate sodium salt (Ins-1,3,4-PPP) (Figure [3A](#F3){ref-type="fig"}). Class II included 1-(α-glycerophosphoryl)-D-*myo*-inositol lithium salt (GPI), class III L-α-phosphatidylinositol ammonium salt (PI), class IV dipalmitoylphosphatidyl-inositol-3-phosphate ammonium salt (PI-3-P), and L-α-phosphatidylinositol-4-monophosphate sodium salt (PI-4-P), and class V dipalmitoylphosphatidylinositol-3,4-diphosphate ammonium salt (PI-3,4-PP) (Figure [3B](#F3){ref-type="fig"}). Ins-1,2,6-PPP, Ins-1,3,4-PPP, PI-3-P, and PI-3,4-PP were obtained from Matreya Inc. (Pleasant Gap, PA), GPI from Calbiochem-Novabiochem Corp. (La Jolla, CA), and PI and PI-4-P from Sigma Chemical Co. (St. Louis, MO). All chemicals are reagent grade with purity greater than 99%.
::: {#F3 .fig}
Figure 3
::: {.caption}
######
Structural formulas of the five (I through V) classes of phosphoinositides.
:::
:::
Cell Cultures
-------------
The Detroit 562 human pharynx carcinoma cell line (DT 562) was obtained from the American Culture Type Collection. The DT 562 cells were seeded into Costar 96-well plates (Corning Life Science, Acton, MA) at a density of 20,000 to 25,000 cells per well, and cultured in Dulbeco\'s modified Eagle Medium (GIBCO, Grand Island, NY) supplemented with 10% fetal bovine serum (FBS) (Hyclone, Logan, UT). The plates were incubated in a humidified atmosphere of 95% air: 5% CO~2~at 37°C until reaching at least 90% confluency. Plates were washed three times with 20 mL of Hanks Balanced Saline Solution (HBSS) (Sigma Chemical Company, St. Louis, MO) to remove serum proteins.
Radiolabeling of HI bacteria
----------------------------
For the adhesion study, an HI nontypeable bacterial strain was used. The HI isolated from the middle ear of an infected child was a gift from Dr. Lauren Bakaletz of The Ohio State University, Columbus, Ohio. HI was streaked onto Chocolate agar plates (Becto Dickinson Diagnostic Instrument System, Sparks, MD) from frozen aliquots of a low passage number. The plates were then incubated at 37°C in a humidified atmosphere of 95% air: 5% CO~2~for 18 hours. Bacteria were then harvested in phosphate buffered solution (PBS) supplemented with 0.05% bovine serum albumin (BSA) (Miles Inc., Kankakee, Ill.). After centrifugation, the cell pellets were resuspended in a volume of PBS/BSA yielding an optical density of 2.4 at a wavelength of 660 nm. The bacteria were then radiolabelled with ^111-^Indium-oxine (^111-^In), a high energy, short-lived tracer. Fifty μCi of ^111-^In solution was added to 2.5 mL of the bacterial suspension and incubated for 20 minutes at 37°C. The radiolabeled bacteria were then washed two times with 10 mL HBSS and unbound ^111-^In were removed by centrifugation. The bacteria pellets were then resuspended in 5 mL HBSS supplemented with 30 mM 2-hydroxyethyl-piperazine-N\'-2-ethane sulfonic acid buffer (Life Technologies, Calsbad, CA).
Adhesion Quantitation
---------------------
Prior to adhesion test, aliquots (25 μL) of the ^111-^In-labeled bacterial suspension were pre-incubated with 25 μL of the test chemical (containing various phosphoinositides) in a Costar polypropylene 96-well plate for 15 minutes at 37°C to allow binding of the test agent to the HI. For adhesion quantitation, aliquots (25 μL) of the pre-incubated mixture were pipetted into the wells of an assay plate containing the DT 562 human pharynx carcinoma cells. The assay plate was incubated for about 15 to 20 minutes at 37°C to allow adhesion of the bacteria to the cell monolayer. Nonadherent bacteria were removed by washing the plate three times with HBSS. The cell monolayer and the adhering of the HI cells were disrupted by the addition of 100 μL of 0.05 N sodium hydroxide. The contents of each well were placed in Cobra polypropylene tubes and the radioactivity counted on a Cobra Gamma Counter (Packard Instrument Co., Meriden, CT). After calibration of the background, the average radiation count of four replicates (per sample) was calculated. The percents of inhibition of bacterial adhesion, as compared to bacterial attachment in control wells containing no test chemical were then calculated.
In Vivo Activity
----------------
A neonatal rat model \[[@B14],[@B15]\] was modified for testing the *in vivo*activity of PI-3,4-PP against nontypeable HI. Prior to the test, overnight cultures of nontypeable HI were prepared, washed twice and diluted with HBSS to obtain a bacterial suspension of less than 10^5^colony-forming-units (cfu) per mL. Three different test chemicals were prepared for this test: (i) HI + PI-3,4-PP, an aliquot (0.5 mL) of PI-3,4-PP (2 mg/mL in HBSS) mixed with 0.5 mL of the diluted bacterial suspension (5 × 10^4^cfu/mL) and incubated for one hour at 37°C; (ii) HI + HBSS, This bacterial control prepared by mixing and incubating 0.5 mL HBSS with 0.5 mL of the diluted bacterial suspension; and (iii) HBSS, the solvent blank prepared by incubating 1 mL of HBSS under the same conditions. A 10 μL of the test material was used to inoculate 24-hour-old or younger Sprague Dawley rats (Charles River, Portage, MI) by intranasal administration. Twenty-four hours after the inoculation, samples of nasopharyngeal fluid were collected by the slow instillation of 25 μL of HBSS into the left naris, and the initial 10-μL discharge from the right naris was collected for plate count. This procedure insured that the fluid had passed through the nasopharynx. The nasal wash was then spread (or diluted and then spread), onto Chocolate agar plates. The plates were incubated at 37°C overnight and counted for the number of cfu\'s, an indicator of the number of viable bacteria.
Authors\' contributions
=======================
YSH conceived of the study. JWL screened and identified the phosphoinositides, and drafted the manuscript. SNA carried out cell adhesion assay. JM carried out assay for in vivo activity. SMH and PM participated in experiment coordination.
Acknowledgements
================
We thank Dr. Lauren Bakaletz of The Ohio State University (Columbus, Ohio) for the gift of the *Haemophilus influenzae*non-typeable bacterium strain, and Linda A. Harvey for her technical assistance.
|
PubMed Central
|
2024-06-05T03:55:47.775165
|
2004-9-3
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517728/",
"journal": "Lipids Health Dis. 2004 Sep 3; 3:20",
"authors": [
{
"first": "Jim-Wen R",
"last": "Liu"
},
{
"first": "Steve N",
"last": "Anderson"
},
{
"first": "Jonathan A",
"last": "Meulbroek"
},
{
"first": "Shie-Ming",
"last": "Hwang"
},
{
"first": "Pradip",
"last": "Mukerji"
},
{
"first": "Yung-Sheng",
"last": "Huang"
}
]
}
|
PMC517729
|
Background
==========
Although dental problems are widespread in number and impose a large burden on society in terms of lost production, pain and suffering, and health expenditure there is a tendency to underestimate their importance due to the generally non-fatal nature of most oral diseases and complacency arising from acknowledged improvements in oral health, such as trends toward lower caries levels among children and decreased edentulism in adults. Australians spend \$2.6 billion on dental services, some 5.4% of recurrent health expenditure for 1998--99 \[[@B1]\]. While dental diseases are not usually life-threatening, the importance of delivering services needs to be considered in view of the repetitive and ubiquitous nature of dental problems which combine to create a large burden. For example, dental problems were ranked as the fourth most frequent illness condition, behind headache, hypertension and colds in a two week survey period \[[@B2]\], dental caries (decay) has been ranked as the highest diet-related disease in Australia in terms of both total costs and health care costs \[[@B3]\], and periodontal (gum) disease has been reported to be the fifth most prevalent health condition in Australia \[[@B4]\].
The disability-adjusted life year or DALY \[[@B5],[@B6]\] provides a summary measure of population health that combines information on the impact of premature death and of disability and other non-fatal health outcomes. The Australian Burden of Disease and Injury Study used the DALY approach to assess the magnitude and impact of health problems in Australia \[[@B7]\]. This burden of disease methodology is designed to inform health policy in relation to the prevention and treatment of health problems. This provides a different picture to traditional approaches that take into account deaths, but not disability. However, the authors acknowledge that further work is required to refine and develop the data and methods.
Estimates of DALYs are limited by inadequate information on the distribution of severity of disease and the course of a disease. Due to limitations in the data many of the disease models are necessarily simple and approximate, with their precision reflecting the source and nature of the data underlying the model. Also, the lack of Australian disease weights may mean that they are not completely representative of Australian societal preferences \[[@B7]\]. Hence the estimates of YLD (Years Lost due to Disability) and DALYs (Disability-Adjusted Life Years) should be regarded as provisional and developmental.
The DALY estimates for oral health in the Australian Burden of Disease and Injury Study seemed inconsistently low with other reports of the high prevalence and incidence of oral health conditions such as dental caries and periodontal disease \[[@B4]\]. There are a number of specific problems associated with estimating oral health DALYs. There is a lack of recent national data on oral health. Just one national oral health survey (NOHSA) has been performed in Australia, which was conducted in 1987--88 \[[@B8]\] and hence is now out of date. Data from other sources \[[@B9]\] indicates that oral health status in Australia is changing, which makes it difficult to estimate disease models for caries and periodontal disease based on data from NOHSA. Sequelae need to be included in disease models, for example disease models should account for sequelae of caries such as pulpal/periapical infection. Oral health estimates need to include a fuller range of oral conditions such as cuspal fractures. Edentulism estimates were based on self-reported data, and may be under-estimates if edentulous persons are less likely to participate in population surveys of oral health. The disease models were based on assumptions regarding severity and duration of symptoms that may require quantitative confirmation and revision.
The broad aims of the project were to evaluate methods used to measure the burden of disease associated with oral conditions in Australia. The specific aims were to obtain measures of burden of disease related to specific oral conditions, measure these in terms of the nature, severity and duration of symptoms, and calculate disability weights from these measures.
Methods
=======
Design
------
The study was conducted using a 2-stage sampling design whereby dentists were randomly sampled from the South Australian Dental Register, randomised into one of seven equal-sized study groups and sent a mailed self-complete dentist questionnaire along with up to five self-complete patient questionnaires depending on the study group. Dentists were provided with a practitioner logbook in which to record for the first 1 to 5 adult patients (depending on study group assignment of dentist) of a random clinical day the treatment they performed and diagnosis of the oral disease or condition treated. At the conclusion of treatment the practitioner passed on a survey kit to their sampled patient(s) containing a patient questionnaire, cover letter and explanation sheet. Sampled patients completing the patient questionnaire recording basic socio-demographic characteristics and data concerning the nature, severity and duration of their symptoms. The patient questionnaires were identified using the practitioner identification number allowing linkage between the practitioner logbook data and patient questionnaire data, but maintaining the anonymity of each patient to the investigators.
Sampling and data collection
----------------------------
The emphasis of the project was to obtain precise estimates of the component measures of the burden of oral disease. These are typically expressed as percentages, such as the percentage of persons or percentage of time experiencing symptoms of a given degree of severity. Taking a parameter size of 10% as a reference estimate for any given measure, in order to achieve a level of precision of 20% or less relative standard error, a minimum target sample of 225 patients was required. This would provide an acceptable minimum level of precision for estimates as low as 10% in size, and better precision for any estimates larger than 10% in size.
Data were collected during 2001--2 with a primary approach letter sent initially to each dentist, followed a week later by the survey materials, with a reminder card two weeks later, and up to four follow-up mailings of survey materials to dentists who had not yet responded in order to ensure higher response rates \[[@B10]\].
Data items
----------
Dentists recorded the details of the dental conditions that patients had, and patients recorded their experience of those dental conditions. Diagnosis of dental conditions was collected from dentists using an open-ended question in the dentist questionnaire and coded using the coding scheme adopted in the Longitudinal Study of Dentists\' Practice Activity \[[@B11]\]. Data on dental conditions in both the practitioner logbook and patient questionnaire were collected for the main dental condition that was currently being treated, another dental condition being treated besides the main condition, and for dental conditions that were not currently treated. In the patient questionnaire, patients were asked if the dental conditions had caused problems in each of six health state dimensions, the severity of the problem (prevalence and percent of time that problems were experienced in relation to each health state dimension) and duration of problems in each dimension. The six health state dimensions were: mobility (e.g, walking about), self-care (e.g, washing, dressing), usual activities (e.g., work, study, housework, family or leisure), pain/discomfort, anxiety/depression and cognition (e.g, memory, concentration, coherence, IQ). They were measured using the European Quality of Life indicator or EuroQol (EQ-5D+) instrument \[[@B12]\]. The EuroQol measures each of these six dimensions according to a 3-level response grading from 1 = no problems, 2 = some / moderate problems and 3 = extreme problems.
Data analysis
-------------
Following descriptive analysis of response rates and characteristics of respondents, the distribution of dental conditions was examined for the 11 most common dental conditions. These dental conditions were then examined in terms of the nature, severity and duration of each condition. Disability weights were then calculated for each dental condition by using a health state valuation algorithm based on UK population data \[[@B13]\]. A patient could have more than one dental condition and hence have more than one disability weight. This initial disability weight was then adjusted by multiplying the coefficients from the health state valuation by the percentage of time affected by the problem. A final adjustment to the disability weights was performed by subtracting the intercept term from the health state valuation equation from the disability weight that had been adjusted by the percentage of time affected by the problem (see appendix 1: [additional file 1](#S1){ref-type="supplementary-material"} for details), as there was some conjecture as to how such an intercept term should be interpreted \[[@B13]\]. For each type of disability weight (i.e., unadjusted and adjusted) a dental condition-specific weight was calculated as the average of the weights for each patient that had reported having that specific dental condition. Results are reported adjusted for the survey design effect of clustering of patient observations within the primary sampling unit of dentists \[[@B14]\]. Disability weights were also calculated using the multiplicative EQ-5D+ regression model from the Australian Burden of Disease and Injury Study \[[@B7]\] as a form of cross-validation of the approach (see appendix 2: [additional file 1](#S1){ref-type="supplementary-material"} for details).
Results
=======
Response
--------
A total of 378 dentists responded to the survey (response rate = 60%). Response rates between study groups ranged from 49% to 70% and tended to be higher in study groups that required dentists to sample less patients, but the effect was not monotonic (Table [1](#T1){ref-type="table"}). Data were available for 375 patients from the patient questionnaire, comprising a response rate of 72% of patients sampled, with response rates between study groups ranging from 69% to 92%.
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Response to the practitioner logbook and patient questionnaires.
:::
Practitioner logbook Patient questionnaire
---------------- --- ---------------------- ----------------------- ----- --------- ----- --------- ------
Pilot study 5 60 (65) 135 (17.9) 93 (24.8) (69)
Main study (a) 0 61 (70) 237 (31.4) \- (-) (-)
Main study (b) 1 56 (62) 37 (4.9) 29 (7.7) (78)
Main study (c) 2 54 (60) 49 (6.5) 45 (12.0) (92)
Main study (d) 3 43 (49) 61 (8.1) 41 (10.9) (67)
Main study (e) 4 50 (58) 118 (15.6) 84 (22.4) (71)
Main study (f) 5 54 (57) 119 (15.7) 83 (22.1) (70)
Total 378 (60) 756 (100.0) 375 (100.0) (72)
:::
Characteristics of patients
---------------------------
The characteristics of patients are presented in Table [2](#T2){ref-type="table"} where data from private general practice \[[@B11]\] and Australian population estimates \[[@B15],[@B16]\] are presented for comparison. The majority of patients were female (59.5%), born in Australia (75.5%), had dental insurance (64.8%) and had visited a dentist in the last 12 months (65.3%). The main reason for dental visiting was for other dental problems not involving relief of pain (46.7%), followed by check-ups (35.2%) and emergency visits involving relief of pain (18.1%).
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Characteristics of patients in the Burden of Oral Disease Study compared with private general practice and Australian population estimates.
:::
Burden of Oral Disease Study Private General Practice ^(a)^ Australian Population
------------------------------ ------------------------------ -------------------------------- -----------------------
\% \% \%
Sex
% Female 59.5 54.9 ^(b)^50.4
Place of birth
% Australian 75.5 n.a. ^(b)^76.4
Dental insurance status
% Insured 64.8 47.8 ^(c)^34.8
Reason for dental visit
Check-up 35.2 41.1 ^(c)^45.1
Emergency 18.1 28.6 n.a.
Other dental problem 46.7 30.8 n.a.
Time since last dental visit
% visited in last 12 months 65.3 n.a. ^(c)^61.3
(a): Longitudinal Study of Dentists\' Practice Activity 1998--99
(b): Australian Bureau of Statistics 2002
(c): National Dental Telephone Interview Survey 1999
n.a. : denotes data not available
:::
Dental condition
----------------
The distribution of dental conditions is presented in Fig [1](#F1){ref-type="fig"} for the 11 most common conditions. Recall/maintenance (26.7%) and caries (23.7%) were the most common conditions followed by tooth fracture (18.4%), failed restorations (14.9%), pulpal infection and denture problems (both 12.3%), and periodontal disease (11.2%). Further analysis assumes zero disability weights for the conditions of recall/maintenance care and oral hygiene conditions due to the lack of symptoms associated with them, and therefore excludes each of these conditions from further consideration.
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Distribution of dental conditions (% of patients ± SE).
:::
:::
Dental conditions by health state dimensions and duration
---------------------------------------------------------
Dental conditions are presented in Table [3](#T3){ref-type="table"} by health state dimensions and duration. A high percentage of patients reported problems (defined as level 2 = some/moderate or level 3 = extreme) with the dimension of pain or discomfort for problems such as pulpal infection (63%), dentinal sensitivity (55%), tooth wear (40%), caries and denture problems (both 38%) and tooth fracture and periodontal disease (both 35%). A high percentage of patients also reported problems with the dimension of anxiety or depression for problems such as periodontal disease (32%), tooth wear (30%) and dentinal sensitivity (27%). The percentage of time affected by dental conditions was generally high for most dimensions for dental conditions such as caries, tooth fracture, and denture problems, and for the dimensions of pain or discomfort and anxiety or depression for dental problems such as failed restoration, periodontal disease and pulpal infection. Aesthetics had the longest duration among dental conditions, however aesthetic problems comprised relatively low percentages of total conditions (as shown in Fig [1](#F1){ref-type="fig"}). Among the more common conditions caries and denture problems had long durations (ranging between 66 and 81 weeks).
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Distribution of health state dimensions (± SE) by dental conditions.
:::
Duration (weeks) Health state dimensions
--------------------- ------------------ ------------------ ------------------------- ------------ -------------- -------------- -------------- --------------
Caries 81 ± 18 Prevalence ^(a)^ ^(3)^4 ± 2 ^(3)^3 ± 2 14 ± 4 38 ± 6 19 ± 5 ^(1)^10 ± 3
Time ^(b)^ ^(3)^25 ± 14 33 ± 8 26 ± 6 42 ± 7 34 ± 9 29 ± 8
Fracture ^(1)^27 ± 9 Prevalence ^(a)^ ^(3)^3 ± 2 ^(3)^3 ± 3 ^(3)^3 ± 2 35 ± 6 18 ± 5 ^(2)^10 ± 4
Time ^(b)^ †10 \- †50 28 ± 7 ^(3)^20 ± 14 ^(3)^55 ± 45
Denture problem ^(1)^66 ± 24 Prevalence ^(a)^ ^(2)^13 ± 6 ^(3)^3 ± 3 ^(2)^16 ± 7 38 ± 10 ^(1)^22 ± 7 ^(1)^19 ± 7
Time ^(b)^ ^(3)^28 ± 24 †100 ^(3)^40 ± 23 33 ± 6 ^(1)^34 ± 10 ^(3)^25 ± 14
Failed restoration 15 ± 4 Prevalence ^(a)^ 0 0 ^(3)^2 ± 2 27 ± 6 ^(2)^10 ± 4 ^(3)^4 ± 3
Time ^(b)^ \- \- \- 29 ± 8 ^(2)^23 ± 11 ^(3)^10 ± 10
Periodontal disease ^(1)^49 ± 19 Prevalence ^(a)^ ^(3)^3 ± 3 0 ^(3)^3 ± 3 35 ± 8 32 ± 9 ^(3)^3 ± 3
Time ^(b)^ \- \- \- 32 ± 7 28 ± 7 \-
Pulpal infection 31 ± 8 Prevalence ^(a)^ ^(3)^2 ± 2 0 ^(3)^12 ± 6 63 ± 8 ^(1)^22 ± 7 ^(1)^10 ± 5
Time ^(b)^ †10 \- 32 ± 9 46 ± 6 41 ± 6 ^(1)^30 ± 12
Wear ^(1)^69 ± 23 Prevalence ^(a)^ 0 0 0 ^(2)^40 ± 16 ^(3)^30 ± 15 ^(3)^10 ± 10
Time ^(b)^ \- \- \- ^(2)^9 ± 4 ^(3)^33 ± 17 †50
Sensitivity ^(2)^21 ± 9 Prevalence ^(a)^ 0 0 0 55 ± 16 ^(3)^27 ± 14 0
Time ^(b)^ \- \- \- ^(3)^21 ± 12 ^(3)^28 ± 23 \-
Aesthetics ^(2)^118 ± 51 Prevalence ^(a)^ 0 0 0 ^(3)^27 ± 19 ^(3)^9 ± 9 ^(3)^9 ± 9
Time ^(b)^ \- \- \- ^(3)^5 ± 3 †5 †25
\(a) Percentage of patients reporting problems (at level 2 = some/moderate or level 3 = extreme) with a health state dimension related to the dental condition
\(b) Percentage of time during the period that the patient had experienced reported symptoms or problems related to the dental problem
-: denotes no observations
†: denotes one observation only
(1): Relative standard error = 30--39%
(2): Relative standard error = 40--49%
(3): Relative standard error = 50--59%
:::
Dental conditions by disability weights
---------------------------------------
Unadjusted disability weights derived from the additive model (DW~a~) were highest for pulpal infection, dentinal sensitivity and caries, followed by denture problems, periodontal disease, tooth wear and tooth fractures (Table [4](#T4){ref-type="table"}). When adjusted by the percentage of time that dental conditions were experienced all disability weights (DW~b~) were reduced. Pulpal infection remained the highest adjusted disability weight, followed by caries and dentinal sensitivity, followed by denture problems, periodontal disease and failed restorations. Subtracting the intercept from the unadjusted disability weight reduced all weights (DW~c~) by a constant amount.
::: {#T4 .table-wrap}
Table 4
::: {.caption}
######
Disability weights (95% CI) by dental problem -- derived from additive model.
:::
Unadjusted Disability Weight (DW~a~) Disability Weight (DW~b~) adjusted by % time experienced problems Disability Weight (DW~c~) adjusted by % time experienced problems minus intercept‡
--------------------- -------------------------------------- ------------------------------------------------------------------- ------------------------------------------------------------------------------------
Caries 0.185 (0.143--0.226) 0.125 (0.094--0.157) 0.044 (0.013--0.076)
Fracture 0.150 (0.123--0.178) 0.095 (0.085--0.105) 0.014 (0.004--0.024)
Denture problem 0.163 (0.124--0.200) 0.107 (0.084--0.130) 0.026 (0.003--0.049)
Failed restoration 0.136 (0.105--0.166) 0.100 (0.081--0.118) 0.019 (0.0001--0.037)
Periodontal disease 0.158 (0.123--0.194) 0.104 (0.090--0.119) 0.023 (0.009--0.038)
Pulpal infection 0.210 (0.162--0.258) 0.150 (0.110--0.191) 0.069 (0.029--0.110)
Wear 0.152 (0.093--0.210) 0.092 (0.078--0.107) †0.011 (0.000--0.026)
Sensitivity 0.191 (0.102--0.281) 0.121 (0.045--0.198) †0.040 (0.000--0.118)
Aesthetics 0.121 (0.067--0.175) 0.083 (0.080--0.086) †0.002 (0.000--0.005)
† confidence interval truncated at zero
‡ standard error for DW~c~is the same as DW~b~due to transformation by a constant
:::
The disability weights derived from the multiplicative model are presented in Table [5](#T5){ref-type="table"}. The unadjusted disability weights derived from the multiplicative model (DW~d~) followed a similar rank order as for the unadjusted disability weights derived from the additive model (DW~a~), being highest for pulpal infection with caries ranked second-highest, but with some re-ordering of the next highest conditions (i.e., denture problems were ranked second rather than fourth, while dentinal sensitivity was ranked fourth rather than second, then followed in the same order by periodontal disease and tooth wear). When adjusted by the percent of time that dental conditions were experienced all disability weights derived from the multiplicative model (DW~e~) were reduced, with pulpal infection ranked highest, followed by caries, dentinal sensitivity, denture problems, tooth wear and periodontal disease.
::: {#T5 .table-wrap}
Table 5
::: {.caption}
######
Disability weights (95% CI) by dental problem -- derived from multiplicative model.
:::
Unadjusted Disability Weight (DW~d~) Disability Weight (DW~e~) adjusted by % time experienced problems
--------------------- -------------------------------------- -------------------------------------------------------------------
Caries 0.121 (0.073--0.170) 0.059 (0.022--0.095)
Fracture 0.091 (0.050--0.132) 0.021 (0.006--0.035)
Denture problem 0.124 (0.070--0.179) 0.041 (0.007--0.075)
Failed restoration 0.065 (0.028--0.102) 0.030 (0.005--0.054)
Periodontal disease 0.106 (0.056--0.156) 0.034 (0.017--0.052)
Pulpal infection 0.128 (0.067--0.191) 0.076 (0.028--0.123)
Wear 0.099 (0.005--0.193) †0.036 (0.000--0.083)
Sensitivity 0.112 (0.007--0.218) †0.048 (0.000--0.138)
Aesthetics †0.050 (0.000--0.110) †0.002 (0.000--0.005)
† confidence interval truncated at zero
:::
The final adjusted disability weights derived from the additive (DW~c~) and multiplicative (DW~e~) models were similar in rank ordering, with pulpal infection, caries, dentinal sensitivity and denture problems ranked highest. While the adjusted disability weights derived from both models were also similar in magnitude those derived from the additive model were lower for all oral conditions except aesthetics, which was identical for both models. In the remainder of the paper the final adjusted disability weights derived from the additive model (DW~c~) will be presented, as this provided the most conservative estimate.
Comparison of disability weights
--------------------------------
The disability weights for oral conditions are presented in Table [6](#T6){ref-type="table"} along with the weights for oral conditions from the Australian Burden of Disease and Injury Study \[[@B7]\]. Comparing edentulism with denture problems shows a higher disability weight in the Burden of Oral Disease Study estimate. For periodontal disease the disability weight estimate from the Burden of Oral Disease Study was higher. For caries, the disability weight was higher for the Burden of Oral Disease Study estimate than either of the two estimates for caries from the Australian Burden of Disease and Injury Study.
::: {#T6 .table-wrap}
Table 6
::: {.caption}
######
Comparison of oral health disability weights by source.
:::
Australian Burden of Disease and Injury Study Burden of Oral Disease Study
----------------------------------------------- ------------------------------ --------------------- -------
Edentulism Denture problems
Edentulism 0.004 Denture problem 0.026
Periodontal disease Periodontal disease
Periodontal disease 0.007 Periodontal disease 0.023
Caries Caries
Caries (filling) 0.005 Caries (all cases) 0.044
Caries (extraction) 0.014
:::
The disparity in disability weights for oral health conditions between the Australian Burden of Disease and Injury Study and the Burden of Oral Disease Study is examined further in Table [7](#T7){ref-type="table"}, which compares the assumptions for oral health disability weights by source. Comparing edentulism estimates with those for denture problems shows a slightly higher estimate for percentage of time affected and a more marked difference in percentage of cases affected in the Burden of Oral Disease Study estimates. For periodontal disease the estimates from the Burden of Oral Disease Study are higher for both percentage of time and percentage of cases. For caries, estimates of percentage of time and duration for moderate pain and moderate anxiety were both higher for the Burden of Oral Disease Study, as was the estimate for extreme pain.
::: {#T7 .table-wrap}
Table 7
::: {.caption}
######
Comparison of assumptions for oral health disability weights by source.
:::
Australian Burden of Disease and Injury Study Burden of Oral Disease Study^(a)^
----------------------------------------------- ----------------------------------- -------------- --------------------- ----------------------- -----------------------
Edentulism \% of time \% of cases Denture problems \%(± se) of time \%(± se) of cases
Moderate pain 25% of time 10% of cases Moderate pain 33 ± 6% of time 38 ± 10% of cases
Moderate anxiety 25% of time 10% of cases Moderate anxiety ^(1)^34 ± 10% of time ^(1)^22 ± 7% of cases
Periodontal disease \% of time \% of cases Periodontal disease \%(± se) of time \%(± se) of cases
Moderate pain 10% of time 10% of cases Moderate pain 30 ± 8% of time 32 ± 8% of cases
Caries \% of time Duration Caries \%(± se) of time Duration (± se)
\(a) filling \(a) all caries
Moderate pain 20% of time 2 months Moderate pain 34 ± 5% of time ^(1)^29 ± 9 months
Moderate anxiety 20% of time 2 months Moderate anxiety 34 ± 10% of time ^(1)^13 ± 5 months
\(b) extraction \(b) all caries
Extreme pain 20% of time 2 weeks Extreme pain 59 ± 14% of time ^(2)^50 ± 23 weeks
Moderate anxiety 20% of time 2 weeks Moderate anxiety 34 ± 10% of time ^(1)^51 ± 18 weeks
(a): Estimates are reported specific to level of problem (eg, moderate), dimension (eg, pain) and condition (eg, caries)
(1): Relative standard error = 30--39%
(2): Relative standard error = 40--49%
:::
For comparison purposes the disability weights for oral conditions are presented in Table [8](#T8){ref-type="table"} along with a range of weights for other health conditions from the Australian Burden of Disease and Injury Study \[[@B7]\] classified into disability classes \[[@B17]\]. Some oral conditions such as dental aesthetics have very low weights, (e.g., 0.002). Conditions such as tooth wear and tooth fracture had weights comparable with moderate anaemia. Denture problems, failed restorations and periodontal disease were lower but comparable with the weight for mild asthma. Dentinal sensitivity and caries were comparable with the weight for an episode of influenza. Pulpal infection, which had the highest weight of all oral conditions, had a weight comparable with acute sinusitis and lower than other conditions such as severe anaemia and gastroenteritis.
::: {#T8 .table-wrap}
Table 8
::: {.caption}
######
Comparison of disability weights for a range of health conditions by source.
:::
Disability class Disability weights Health condition Disability Weight Source Oral/dental conditions
------------------ -------------------- ------------------------------- ------------------- --------------- ------------------------
1 0.00--0.01 Aesthetics (dental) 0.002 Current study Yes
Anaemia (mild) 0.005 ABDS
2 0.01--0.05 Wear (tooth) 0.011 Current study Yes
Anaemia (moderate) 0.011 ABDS
Fracture (tooth) 0.014 Current study Yes
Failed restoration 0.019 Current study Yes
Periodontal disease 0.023 Current study Yes
Denture problem 0.026 Current study Yes
Asthma (mild) 0.030 ABDS
Sensitivity (dentinal) 0.040 Current study Yes
Caries 0.044 Current study Yes
Influenza (episode) 0.047 ABDS
3 0.05--0.10 Chronic back pain (episode) 0.060 ABDS
Sinusitis (acute) 0.061 ABDS
Pulpal infection 0.069 Current study Yes
Anaemia (severe) 0.090 ABDS
Gastroenteritis 0.093 ABDS
4 0.10--0.15 Mild depression (episode) 0.140 ABDS
5 0.15--0.20 Measles 0.152 ABDS
Trachoma (moderate) 0.170 ABDS
Conjunctivitis 0.180 ABDS
6 0.20--0.30 Asthma (severe) 0.230 ABDS
Tuberculosis 0.295 ABDS
7 0.30--0.40 Moderate depression (episode) 0.350 ABDS
8 0.40--0.50 Trachoma (severe) 0.430 ABDS
9 0.50--0.65 Tetanus 0.612 ABDS
10 0.65--0.80 Severe depression (episode) 0.760 ABDS
11 0.80--1.00 Cancer (terminal stage) 0.930 ABDS
ABDS: Australian Burden of Disease and Injury Study
:::
Discussion
==========
Response
--------
Response rates to the survey were adequate for both the dentist and patient questionnaires \[[@B18]\]. Comparison of respondents against estimates for private general practice and the Australian population indicated a slightly higher percentage of female patients compared to the population consistent with higher reported visiting rates by females \[[@B16]\], but both place of birth and time since last visit was similar. While dental insurance was higher, the percentage of check-up visits was lower among patients indicating a higher percentage of dental problems for patients compared to the population. The method of sampling patients showed that response rates tended to be higher among dentists who had to sample fewer patients consistent with a lower response burden, but selection of an optimal collection methodology requires consideration of efficiency of collection as well as response rates.
Burden of disease approach
--------------------------
The burden of disease approach is grounded on the use of the DALY to quantify the burden of disease that treats \'like as like\' within an information set of health conditions of individuals \[[@B19]\]. While use of DALYs has been criticised on the basis of its assumptions and value judgements \[[@B20]\], Murray & Acharya \[[@B19]\] argue that the widespread use of DALYs makes them a convenient tool for comparative burden of disease and cost-effectiveness analyses.
The EuroQol was developed as a standardised non-disease-specific instrument for describing and valuing health-related quality of life \[[@B12]\] and hence represents the best method to quantify DALYs. The EuroQol is intended to complement other forms of quality of life measures and it was purposefully developed to generate a generic index of health. Any classified health state can be valued using preferences elicited from a general population \[[@B12]\], and values can be modelled from such data sets \[[@B13],[@B21]\]. The EuroQol is widely used internationally and reported to have adequate construct and convergent validity, but is highly skewed and has relatively poor sensitivity especially in relation to disease-based outcomes research \[[@B22]\].
The six dimensions of the EuroQol were used as a standardized description of health status in the development of disability weights for the Dutch Disability Weights Study \[[@B17]\]. The Australian Burden of Disease and Injury Study adopted the Dutch weights where possible. While both DALYs and the EuroQol instrument have their critics, if these approaches continue to influence policy decisions as to the scope and importance of oral disease then there will be an increasing need to assess the validity of the estimates and to address any shortcomings that are identified.
Assumptions of disability weights
---------------------------------
Differences in disability weights between the Australian Burden of Disease and Injury Study and this paper probably reflect a lack of quantitative data in the Dutch study related to the nature of symptoms experienced by persons with dental conditions. The data from this paper shows that many common dental conditions are associated with symptoms that on average were more severe and of longer duration than previously assumed by Stouthard et al. \[[@B17]\].
The calculation of disability weights in this paper was based on the use of EuroQol health state descriptions as in the Dutch study, but instead of using a panel approach to elicit valuations we adopted a model-based approach to estimate health state valuations for each individual response and then derive a disability weight as the average of those individual estimates. Such a model-based approach was also used as a source of validation in the original Dutch study but was not developed in detail due to the lack of an adequate statistical model at the time of development \[[@B23]\]. Two strategies are recognised as ways of arriving at a link between epidemiological data and disability weights \[[@B24]\]. The first one is derivation of disease-specific disability weights using health state descriptions with a disease label. The second approach, adopted in this study, is derivation of disability weights using generic descriptions of health states associated with specific diseases. In this study disability associated with oral disease was described using a generic measure (the EuroQol) valued by applying an existing formula \[[@B13]\]. The advantage of this approach is the transparency of the valuation task and the use of the formula provides the facility to cover generic health states without additional valuation studies \[[@B24]\].
Disability weights reflect health state valuations whereby weights are assigned to health states that are worse than ideal health. A range of methods can be used to elicit health state valuations including visual analogue scale, time trade-off and person trade-off. The visual analogue scale method uses a scale anchored by the best imaginable health state at 100 and death at 0, with respondents asked to indicate the exact point on the scale they would place a particular health state relative to the best imaginable health, death and all other health states. Time trade-off methods ask respondents to imagine choosing between the two options of remaining in a particular health state for 10 remaining years of life or be restored to perfect health but live for a shorter time. Person trade-off methods ask respondents to choose between two different programmes, one that would prevent the deaths of 100 perfectly healthy individuals and one that would prevent the onset of a particular health problem in a certain number of healthy people. While there is little agreement as to which method is most appropriate \[[@B25]\], it has been shown that visual analogue scale methods tend to give lower values for particular health states, than time trade-off methods, which give lower health state values than person trade-off methods. The additive model weights in this study were derived from a U.K. study based on valuations produced from visual analogue scale and time trade-off methods \[[@B13]\] whereas the multiplicative model weights were derived from a Dutch study based on visual analogue scale and person trade-off methods \[[@B23]\]. It could be argued that since the Australian Burden of Disease and Injury Study used disability weights based on person trade-off methods and this study used disability weights based on time trade-off methods that any differences between the disability weights from this study with the Australian Burden of Disease and Injury Study could reflect differences in methodology. Also, the Australian Burden of Disease and Injury Study used a multiplicative model fitted to the Dutch weights for 153 disease sequelae or stages as multiplicative multi-attribute functions were preferred for providing better fit to observed preference data than additive models \[[@B7]\]. However, the final adjusted disability weights derived from the additive model produced results that were consistent with, but slightly lower than, the multiplicative model. Therefore methodological issues stemming from valuation and modelling strategies do not seem to explain the differences that were observed.
One consideration arising from the disability weights derived in the present study was the reliance on the use of data from patients seeking care. The experience of dental problems from the perspective of a patient may be different than that from the population as a whole. If the symptoms experienced by patients were more severe compared to the general population then some further adjustment may be required to reduce the disability weights appropriately. However, it would not be right to assume that most patients attending for dental care would be symptomatic as patient-based data have shown that the majority of patients reported no problems on the six EuroQol dimensions (ranging from 69.7% for pain/discomfort to 98.6% for self-care), with 39.6% of patients reporting symptoms on one or more of the six dimensions \[[@B26]\]. Conversely, patients who are unable or unwilling to seek care can be expected to have a longer duration, and perhaps severity of dental symptoms and associated health problems than subjects in this study. There is some evidence of a symptom iceberg with respect to oral and facial pain, with Canadian population data showing that less than one in two who experience such pain consult a dentist or physician \[[@B27]\]. Since there are plausible arguments as to why patient-based estimates might reflect either more severe or less severe conditions the question of possible bias in a patient population remains open and perhaps could be settled by further research. An important design feature of this study was the use of dentists to diagnose the oral health conditions that were subsequently reported on by the patients. Further refinement of these disability weights could be achieved through the use of an oral health survey based on a population sample that also uses a linked questionnaire to survey the experience of oral health problems. It may also be the case that further refinements to the algorithm for estimating disability weights that incorporates the cognitive dimension may also increase the size of weights although oral health conditions related to this dimension were not as prevalent as other dimensions that were included such as pain/discomfort and anxiety/depression. The weights derived from the multiplicative model included the cognitive dimension and this may help explain why they were observed to be slightly larger than the weights derived from the additive model. Detailed prospective data would be required to evaluate whether persons report the experience of their symptoms accurately or are more influenced by the end-stage of their disease experience than by the average experience over the period of their symptoms. Generic measures such as SF-36 have been found to be less sensitive to changes in oral health and to exhibit limited construct validity in comparison to specific measures of oral health \[[@B28]\]. Despite being a generic measure the EuroQol has shown discriminant validity in relation to a range of dental patient, visit and oral health measures \[[@B29]\]. However, in general there can be problems assigning disability weights to diseases with high prevalence and low severity, relating to the lack of differentiation at this low end of the scale \[[@B24]\].
Implications of oral health disability weights
----------------------------------------------
The findings from this study indicate that oral health conditions may account for a considerably higher level of DALYs than previously thought, due to the lack of quantitative data on the nature of dental conditions. While Australia has not had another national oral health survey since the initial survey of 1987--88, there have been other studies that suggest that dental problems are common \[[@B2],[@B4]\], and account for large amounts of health care costs \[[@B3]\]. Further work could be done to incorporate the revised disability weights for oral health into new estimates of the burden of disease in order to estimate the impact that such revisions to the disability weights have on the number of DALYs, and how this affects the ranking of oral health problems in relation to other health conditions.
Conclusions
===========
Compared to the Australian Burden of Disease and Injury Study the adjusted disability weights for oral health conditions in this study were higher for comparable oral conditions of caries (0.044 versus 0.005 for caries involving a filling and 0.014 for caries involving an extraction), periodontal disease (0.023 versus 0.007) and denture problems (0.026 versus 0.004 for edentulism). In addition there were a range of common oral health problems such as pulpal infection, failed restorations and tooth fracture that were not included in the Australian Burden of Disease and Injury Study which had relatively high disability weights. The inclusion of a fuller range of oral health conditions along with revised disability weights would result in oral health accounting for a much larger amount of disability than originally estimated.
Competing interests
===================
None declared.
Authors\' contributions
=======================
DSB and AJS were chief investigators on the grants obtained to fund the study. DSB performed data collection, analysis and drafting of the manuscript. AJS participated in the design and coordination of the study, and completion of the manuscript. All authors read and approved the manuscript.
Supplementary Material
======================
::: {.caption}
###### Additional File 1
Appendix 1: algorithm used to calculate disability weights from the additive model. Appendix 2: algorithm used to calculate disability weights from the multiplicative model
:::
::: {.caption}
######
Click here for file
:::
Acknowledgements
================
This research was performed at the Australian Research Centre for Population Oral Health, Dental School, Faculty of Health Sciences at The University of Adelaide with funding from the Australian Dental Research Foundation and Adelaide University Small Research Grants Scheme. The participation of responding dentists and patients is acknowledged.
|
PubMed Central
|
2024-06-05T03:55:47.776891
|
2004-9-3
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517729/",
"journal": "Popul Health Metr. 2004 Sep 3; 2:7",
"authors": [
{
"first": "David S",
"last": "Brennan"
},
{
"first": "A John",
"last": "Spencer"
}
]
}
|
PMC517808
|
Background
==========
Particle clearance in the airways is dependant on mucus and cilia \[[@B1]\]. The cilia beat frequency, mucus secretion rate and the properties of mucus are variables important in normal and effective mucociliary clearance \[[@B2]\]. However, the study of mucociliary clearance in intact mammalian airways in humans or small mammals is technically difficult. It is worthwhile, therefore, to develop alternate models that, by way of ease of preparation and homology to human conductive airways, can yield important knowledge in understanding the basic mechanisms involved in airway diseases. The bullfrog palate provides an excellent integrated model system for studying all the relevant variables for mucociliary clearance including mucus secretion rate, cilia beat frequency, linear velocity of mucus, the viscoelastic properties of mucus and the transepithelial potential difference, indicative of changes in epithelial ion fluxes and water transport \[[@B2]\].
We have extended the physiological applications of the frog palate model to study the initial events of airway injury. To create an injury model from the fresh frog palate model, a solution of sodium metabisulphite was topically applied to the palate. Sodium metabisulphite has been shown to release sulfur dioxide (SO~2~) on contact with water and has been employed as an aerosol in other airway injury models to study hypersecretion and hyperplasia \[[@B2]-[@B6]\]. In dog studies, chronic exposure to SO~2~produced symptoms similar to chronic bronchitis in humans \[[@B3]\].
We hypothesize that sodium metabisulphite will interfere with mucociliary clearance on the frog palate by disrupting the action of the ciliated epithelium, vital to the process of mucociliary clearance. The objective of this study was to evaluate the effect of sodium metabisulphite on mucociliary clearance on the frog palate. A further objective was to analyze tissue and mucus samples in ultra-structural and molecular studies to characterize the nature of the injury and to assess the potential involvement of matrix metalloproteinases which have been shown to play a role in airway injury and remodeling \[[@B7],[@B8]\] and in cell-signaling pathways \[[@B14]\].
Materials and Methods
=====================
Development of a frog palate injury model
-----------------------------------------
A fresh frog palate was prepared as previously described \[[@B1],[@B2]\]. Briefly, the upper palate of the bullfrog (*Rana catesbiana*) was excised by cutting in the coronal plane from the lateral border of the mouth on one side of the head to the other. The excised palate was placed horizontally on gauze soaked in frog Ringers (2/3 Ringers + 1/3 distilled water, 207 mosml L^-1^) in a Petri dish. The palate was placed in an enclosed chamber (20 × 20 × 30 cm) maintained at a constant temperature (22--24°C) and continuously humidified at 100% with aerosolized frog Ringers generated by a Pari Jet^®^nebulizer at a airflow rate of 8 L/min. The palate was allowed to stabilize for 15--20 min before any procedures were carried out on the palate.
Mucociliary clearance time (MCT) was measured by applying a droplet of mucus collected from the inferior (cut) edge of the palate that was placed at the superior edge of the palate near the midline. The action of cilia carries the mucus toward the inferior edge. The effect of various concentrations of sodium metabisulphite on MCT was measured following topical application on the palate. Frog Ringers was used as a control solution and vehicle for sodium metabisulphite. The volume of solution (either frog Ringers or sodium metabisulphite) that was applied to each palate was normalized among different sized palates according to the area of the palates surface. The area of the palate was approximated by measuring across the lateral-most borders of the jaw at the base of the palate, and calculating the area of the equivalent half-circle. The volume of solution applied was normalized to the area of each palate as shown: area = 3.5 cm^2^(volume applied = 2 μl), 4.5 (3 μl) 5.5 (4 μl) to 6.5 cm^2^(5 μl).
Using bromophenol blue in frog Ringers applied to the palate, it was shown that within two minutes of application, the solution was carried from the superior edge of the palate to the inferior edge by ciliary action. Therefore, when frog Ringers was applied to the palate, two minutes was allowed for the droplet of solution to disperse on the palate. This was followed by the measurement of MCT using a drop of frog mucus collected off the inferior (cut edge) of the palate and marked with carbon particles to enhance its visibility on the palate surface. The movement of the mucus droplet down the palate by ciliary action was observed through a stereomicroscope with a reticulated eyepiece and timed over a set distance of 4 mm, once it reached a steady speed. For each solution tested, five consecutive mucus clearance times were recorded and the average was used as the time point for that particular group of recordings. After a recovery period, sodium metabisulphite 10^-4^M was applied to the palate. After two minutes, another five measurements of MCT were recorded followed by a recovery period. At this point in time (70 min, shown in Figure [1](#F1){ref-type="fig"}), frog Ringers was applied and MCT was measured again. If this value was within 10% of the first application, the palate was considered to have recovered back to the control condition. Sodium metabisulphite 10^-2^M (at 80 min) was applied followed by the measurement of MCT again. This was followed with a recovery period with the measurement of frog Ringers MCT again, which was shown to be not different from the previous controls.
::: {#F1 .fig}
Figure 1
::: {.caption}
######
The effect of sodium metabisulphite on mucociliary clearance time (MCT). The results of seven independent experiments performed on seven different frog palates are shown in real time as displayed on the x-axis of the graph. Application of frog Ringers (FR) is shown by grey bars, while black bars indicate the application of sodium metabisulphite shown by the concentration (10^-4^, 10^-2^or 10^-1^M).
:::
:::
Frog Ringers following each recovery period also represented a timed control prior to each dose of metabisulphite. However, in order to control for deterioration of palate over the course of the experiment, three sets of frog Ringers controls measured before the application of sodium metabisulphite 10 ^-1^M were plotted versus time and a line of best fit was determined (data not shown). No change in the significance of the slope of the line (equal to or close to \'0\') indicated that no significant deterioration of the palate had taken place over time. Within each individual experiment there was, however, some variability in controls. Therefore the control mucociliary clearance times that were used to determine a line of best fit (taken as 100%) were compared to the actual MCT measured at that particular point. Thus for each experiment the actual MCT was expressed as a percentage of the line of best fit of the control time which was extrapolated to the time of application of frog Ringers or sodium metabisulphite to the palate as shown ((actual MCT/predicted control MCT) ×100). Thus, there is variation within and between controls that are shown as a standard deviation for each time point (representing seven independent frog palate experiments).
MCTs for metabisulphite were expressed as a percentage of the line of best fit for frog Ringers controls, extrapolated to the time metabisulphite was applied. An increase in MCT compared to control times, indicated a slowing of the mucociliary clearance time. A minimum of fifteen minutes was allowed after metabisulphite, for MCT to return to the normal range, i.e. within 10% of the frog Ringers MCT, measured prior to metabisulphite. If recovery of MCT had not occurred after twenty minutes to within the range specified, frog Ringers was re-applied and the recovery period was repeated.
Injury to the palate
--------------------
A 50% increase in MCT was established *a priori*as indicative of a quantifiable injury to the mucociliary clearance system. Sodium metabisulphite was applied in progressively increasing concentrations from 10^-4^, 10^-2^and 10^-1^M. Each test solution was alternated with frog Ringers. A higher concentration of metabisulphite was not applied until the MCT had returned to within 10% of the previously measured frog Ringers control. In several experiments, pH was measured on the surface of the frog palate, using a solid-state micro pH electrode (Lazar Research Laboratories, Los Angeles, CA) connected to an Accumet^®^pH meter (Model 925, Fisher Scientific, Nepean, ON, Canada) to continuously monitor changes on the palate surface during the application of sodium metabisulphite.
Scanning electron microscope (SEM) studies
------------------------------------------
Samples of frog palate epithelial tissue and mucus were placed in 2.5% glutaraldehyde solution, immediately after collection and kept in a refrigerator at 4°C until processing. Samples were prepared for the SEM by standard methodology. Briefly samples were post-fixed in 1% osmium tetroxide in Milonig\'s buffer at room temperature for one hour. They were then washed briefly in distilled water and dehydrated in an increasing series of ethanol (50, 80 and 100%), ten minutes at each concentration, followed by two additional periods of absolute ethanol. The samples were further dehydrated by critical point drying at 31°C for 5--10 minutes, and then mounted on a specimen holder for drying overnight in a desiccator. In the final stage of preparation before viewing, the samples were sputter coated with gold (Edwards, Model S150B Sputter Coater) and examined with a Hitachi 2500S scanning electron microscope. High-resolution digital images were acquired directly to a computer for storage and reproduction.
Morphometry
-----------
To quantify the area of cilia loss in fields of view in the electron microscope studies, image files were analyzed using Sigma Scan^®^image analysis software to trace areas of cell loss and determine the areas of loss relative to the field of view. Fifteen fields from 3 samples exposed to sodium metabisulphite 10^-1^M were examined as well as samples from control tissue (exposed only to frog Ringers).
Gelatinase zymography
---------------------
Samples of frog palate epithelial tissue were removed following mucus clearance studies, snap frozen in liquid nitrogen and stored at -80°C until they were prepared for zymography. At that time the tissue samples were ground with a mortar and pestle to a powder, adding liquid nitrogen to the mort to keep the tissue frozen. Homogenization buffer (KCl, ZnCl~2~, EDTA and Tris-HCl) was added to the samples that were sonicated for 30 seconds and then centrifuged at 14,000 rpm for 15 minutes. The supernatant was collected and an aliquot removed for protein assay (BCA protein assay kit, PIERCE).
A 10 μl sample, normalized for protein content, was loaded on a separating gel (acryl amide and gelatin) and run at 120 volts for one hour. After electrophoresis, the gel was washed for one hour in 25% Triton-X100 at room temperature followed by incubation overnight in zymography development buffer (0.15 M NaCl, 0.5 mM CaCl~2~, 0.05% Azide NaN~3~, 50 mM Tris-Cl, 2 M Tris-HCl). The gel was then stained for 2 hours with 0.05 % Coomassie blue (R-250) in methanol: acetic acid: water (2.5:1:6.5) followed by de-staining in 20% isopropanol in 4% ethanol and 8% acetic acid. The presence of gelatinases (MMP 2 and 9) was shown by clear bands (no staining) corresponding to MMP standards (MMP 2 and 9) run in leftmost lane on the gel. Optical density was measured in a Bio-Rad Scanning densitometer.
Statistical treatment of data
-----------------------------
All measurements were expressed as mean ± standard deviation. Overall significance of the MCT results were tested using a one-way analysis of variance in SPSS, with differences among groups (of more than two) evaluated using planned orthogonal comparisons. For comparisons between two groups (density comparisons between control and MB in zymograms), a Student T-test was used. The level of significance was set at p \< 0.05.
Results
=======
Figure [1](#F1){ref-type="fig"} shows the effect of sodium metabisulphite on the MCT expressed as a percent of frog Ringers control times. MCT is shown for frog Ringers, sodium metabisulphite 10^-4^, 10^-2^and 10^-1^M and 3 consecutive recovery periods following sodium metabisulphite 10^-1^M in which frog Ringers was applied to the palate in twenty-minute intervals followed by a measurement of MCT. The average frog Ringers MCT (in 7 frogs) measured initially at 15 minutes following an initial stabilization period was 97.3 ± 6.3 %. No difference in MCT was measured after the application of sodium metabisulphite 10^-4^(30 min) and 10^-2^M (60 min); whereas 10^-1^M sodium metabisulphite (at 100 min) increased MCT by 254.5 ± 57.3% compared to Ringers control MCT (taken as \~100%). Between 10^-4^and 10^-2^M sodium metabisulphite, there was no significant difference compared to control MCTs. This is illustrated by the dotted line in Figure [1](#F1){ref-type="fig"}. However, twenty minutes after sodium metabisulphite 10^-1^M, frog Ringers was applied but MCT did not recover to previous frog Ringers control times. Another twenty minutes of recovery was allowed and frog Ringers MCT was still not recovered. After an additional twenty minutes, frog Ringers MCT was measured for the third consecutive time, showing that after one hour of recovery (\~170 min in the time course of the experiment), the MCT was still significantly different from the initial frog Ringers MCT (140.9 ± 46.3 vs. 97.3 ± 6.3%, p \< 0.001, n = 7).
MCT was significantly increased after sodium metabisulphite 10^-1^M. To determine if this acute effect was due to pH changes, possibly representing altered ion fluxes in the tissue, a micro pH electrode was placed on the palate to measure pH before and after the application of metabisulphite to the palate surface. This is shown in Figure [2](#F2){ref-type="fig"}. Prior to metabisulphite, the pH on the surface was 6.8--7.0 units. The pH was not significantly altered after the application of sodium metabisulphite 10^-4^and 10^-2^M. However, after sodium metabisulphite 10^-1^M, the pH declined within seconds, reaching a nadir at \~60 seconds. After 300 seconds, there was some recovery toward normal, but the pH was still 0.3--0.5 units below the initial control value. As shown in Figure [1](#F1){ref-type="fig"}, MCT recovered somewhat by 20 minutes after sodium metabisulphite 10^-1^M and showed continued (but incomplete) recovery after one hour. No corresponding pH measurements were taken at these time points.
::: {#F2 .fig}
Figure 2
::: {.caption}
######
The effect of sodium metabisulphite on the pH, measured continuously on the surface of the palate, is shown for before and after three concentrations of sodium metabisulphite were applied (vol = 5 μl) to the palate.
:::
:::
Scanning electron microscope studies
------------------------------------
In Figure [3](#F3){ref-type="fig"}, Panel A (X400) shows the normal cilia blanket, with pores of secretory cells visible. Panel B (X400) shows regions of the palate surface devoid of cilia after 10^-1^M sodium metabisulphite was applied. The normal continuous covering of cilia is shown greater detail in Panel C (x3500) and in Panel D after 10^-1^M sodium metabisulphite, where a region of exfoliation is shown more clearly at the higher magnification. The absence of cilia and ciliated epithelial cells is visible, with only the extracellular matrix remaining. Morphometry to quantify the area of exfoliation determined in a five different field from three independent experiments, revealed that after sodium metabisulphite 10^-1^M, there was a 25 ± 11.8% loss of ciliated epithelial cells from these palates compared to none in control palates.
::: {#F3 .fig}
Figure 3
::: {.caption}
######
Scanning electron micrographs of control and MB-treated palates at a magnification of 400× (panels A and B respectively) and at 3500× (panels C and D respectively). In panel A, the ciliated epithelium completely covers the surface of the palate except where the openings to secretory cells are seen. In panel B, it can be seen that the ciliated surface is not continuous, but punctuated with numerous spaces where ciliated cells are not present. Panel C shows the high density of cilia on the palate surface, which under normal transport conditions, beat in a metachronal pattern to move a mucus layer over them. In panel D, the continuity of the ciliated layer is interrupted by spaces where ciliated epithelial cells are no longer present.
:::
:::
SEM of the palate surface following sodium metabisulphite 10^-4^and 10^-2^M, showed no ultra structural changes compared to control palates to which frog Ringers had been applied. Figure [4](#F4){ref-type="fig"} shows a split micrograph of mucus collected from a palate after sodium metabisulphite 10^-1^M. At lower power (X400) a grouping of ciliated cells are visible in the mucus. At the higher power (x2000), intact ciliated epithelial cells are clearly shown.
::: {#F4 .fig}
Figure 4
::: {.caption}
######
A sample of mucus taken off the palate after MB treatment showed groups of intact ciliated cells. This would suggest that the cells, which were exfoliated from the epithelial surface, were carried off the palate in the mucus layer by the process of mucociliary clearance.
:::
:::
Gelatinase zymography
---------------------
Figure [5](#F5){ref-type="fig"} shows two representative zymograms from tissue and mucus. In 5A from tissue, in the left lane, two bands are visible representing MMP-9 (92 kD) and MMP-2 (72 kD) standards. In sodium metabisulphite 10^-1^M treated tissue (two rightmost columns), bands representing MMP 9 activity were seen whereas only faint bands were visible in control tissue. Statistical comparison of densitometry bands showed significant activation (p \< 0.05, n = 3). MMP-2 activity (in the bottom row on the zymogram) may have also increased, but since control tissue showed similar activation these results are inconclusive. A similar state of MMP activation in mucus is shown in Figure [5B](#F5){ref-type="fig"}. Increased activated MMP-9 was observed in the mucus from metabisulphite-treated palates (p \< 0.05, n = 3) compared to mucus from frog Ringers-treated palates. To test if MMP-9 activation was related to sodium metabisulphite concentration, samples of epithelial tissue were treated with sodium metabisulphite 10^-4^, 10^-2^and 10^-1^M, and prepared for zymography (Figure [6](#F6){ref-type="fig"}). Optical density analysis showed that activation of MMP-9 after sodium metabisulphite 10^-2^M was greater than after sodium metabisulphite 10^-1^M (\#, p \< 0.05, n = 3) while both were greater than MMP-9 activation following application of 10^-4^M sodium metabisulphite (\*, p \< 0.05, n = 3).
::: {#F5 .fig}
Figure 5
::: {.caption}
######
Representative zymograms from tissue (A) and mucus (B) shows the standards for MMP9 (top band, \~92 kD, latent size) and MMP2 (lower band, \~72 kD, latent size) in the leftmost lane. To the right of standard in each zymogram, two sets of bands are visible, corresponding to MMP-9 and MMP-2 levels of activity in duplicate samples of control tissue. In the next two lanes are duplicate sets of bands from an experiment which shows increased activated MMP-9 and possibly MMP-2 activity in sodium metabisulphite 10^-1^M treated tissue in both tissue and mucus. The bar graph only shows a comparison of the scanning density of the MMP-9 bands since the MMP-2 control and sodium metabisulphite-treated tissue showed similar activation. A significant increase in activated MMP-9 was seen in sodium metabisulphite-treated mucus and tissue (\* p \< 0.05, n = 3 for each).
:::
:::
::: {#F6 .fig}
Figure 6
::: {.caption}
######
MMP-9 activation in palate tissue is a dose-related effect. The representative zymogram shows bands corresponding to MMP-9 activity in tissue samples treated with MB 10^-1^, 10^-2^and 10^-4^M. The MMP-2 bands have been removed from this gel as no differences were seen. Densitometry of the MMP-9 bands showed that MB 10^-1^M showed less activity than MB 10^-2^M, whereas MB 10^-4^M showed significantly less activation than either of the higher doses. The bar graph shows the average results in tissue from three separate experiments.
:::
:::
Discussion
==========
The important findings of this study are: 1. the development of a model of airway epithelial injury that can be used for study of ultra-structural and molecular events in airway injury that are directly related to the disruption of mucus clearance; 2. that sodium metabisulphite (by releasing SO~2~on contact with water) has an acute effect on mucus clearance followed by incomplete recovery of mucus clearance time; 3. ultra-structural studies showed that areas of ciliated epithelial cells were lost from the palate surface resulting in an incomplete recovery of mucus clearance. Loss of cilia has been previously reported following exposure to SO~2~in dogs \[[@B3]\]. The implication is that loss of cilia may affect mucus clearance in number of airway diseases. The mechanism of this effect requires further study for a more complete understanding of the events involved in this process. Intact ciliated epithelial cells were found in the mucus from 10^-1^M sodium metabisulphite-treated palates but not from frog Ringers-treated control palates; 4. Gelatinase zymography showed increased activity of MMP-9 after sodium metabisulphite (10^-4^to 10^-1^M) and this was shown to be a dose-related effect. It is noteworthy that gelatinase zymography showed increased activity of MMP-9 at each concentration of sodium metabisulphite, whereas ultrastructural damage was only found at the highest concentration; 5. The finding that intact ciliated cells were found in the mucus suggests that the action of activated gelatinases was on cell-cell or cell-matrix attachments resulting in the exfoliation of intact ciliated epithelial cells, which may have contributed to a slowing of mucus clearance over the surface of the palate.
Additional studies are underway in our laboratory to identify possible the role of inflammatory mediators in the activation of matrix metalloproteinases in this model. Sodium metabisulphite may cause the release of oxidants or other mediators by epithelial cells \[[@B10],[@B11]\] or from typical inflammatory cells, possibly activated neutrophils resident in the tissue, although the question of a time frame, related to neutrophil recruitment and activation would need to be clarified \[[@B12]\]. Oxidant products may cause activation of precursor forms of collagenase or gelatinase, leading to breakdown of the extracellular matrix \[[@B14]\]. It has been recently shown that mechanical stress resulted in the expression and release of gelatinases from epithelial and endothelial cells in the rat lung \[[@B7]\]. Further studies need to be undertaken to identify the source of MMP release following sodium metabisulphite and other airway modulating agents.
A high concentration of sodium metabisulphite may not be biologically relevant and represents a practical limitation to the applicability of the model. Nevertheless, a dose-response curve showed little effect on mucus clearance in the frog palate model at lower concentrations of sodium metabisulphite. Our findings suggest that this *ex vivo*model may be particularly useful in characterizing how an initial injury may be induced in ciliated epithelium. The ability to make functional measurements of mucociliary clearance in the *ex vivo*frog palate model allows for a correlation of variables in follow-up *in vitro*studies of tissue and mucus that may be interfering with mucociliary clearance.
Sodium metabisulphite, when applied to the palate is diluted in the periciliary fluid \[[@B9]\]. The dilution in palate surface fluid reduces the concentration of the applied metabisulphite. By approximating the area of the palate as one-half the area of a circle (\~5 cm^2^on average) and assuming a mucus plus periciliary layer of 10 μm, a volume of 5 μl would effectively be diluted by as much as 1--2 orders of magnitude (assuming it spread over at least half the area of the palate). This calculation would suggest that sodium metabisulphite 10^-1^M was effectively and rapidly diluted to 10^-2^M or less. It follows that the lower concentrations of metabisulphite would be effectively less than the stock concentrations. Since, the effective concentration was determined experimentally in a dose-response experiment as that dose that produced a 50% or greater increase in the mucus clearance time, and since only the highest concentration of metabisulphite produced this effect, this concentration became physiological relevant to the outcome of these experiments. Lower concentrations (10^-4^and 10^-2^M) were also used, even though no effect on mucociliary clearance time was observed in the dose-response experiments, to determine if there might be some quantifiable effect at the cellular level, which was not manifested as a decrement in mucociliary clearance.
In several experiments the continuous pH response following the application of sodium metabisulphite 10^-1^M to the palate surface was monitored for 5 minutes. The pH measured on the palate prior to metabisulphite was 6.9 ± 1.4 units. There was a decrease in pH following sodium metabisulphite 10^-1^M, reaching a nadir of 6.4 ± 0.25 pH units after 60 seconds. Sodium metabisulphite 10^-4^and 10^-2^M did not cause any decrease in pH on the palate after application. Although the observed decrease in pH with sodium metabisulphite 10^-1^M is relatively minor (\<0.5 pH units), it may have been sufficient to influence ion channels, possibly disrupting ciliary beating and causing chemical changes such as the induction of inflammatory mediators \[[@B5],[@B15]\]. The dramatic increase in mucus clearance time seen 1--2 minutes after the application of MB 10^-1^M occurred in a similar time frame to the pH changes. After five minutes, the pH was returning toward normal, and within 20 minutes there was some recovery of mucus clearance time. An *in vitro*study \[[@B13]\] examined the effect of pH changes on ciliary beat frequency and found that the beat frequency was stable between 7.5 and 10.5 pH units. A significant decrease in beat frequency was noted at lower pH values. This report is consistent with our study that suggests that the transient decrease in pH caused a transient slowing or even cessation of ciliary beat frequency.
The increase seen in mucus clearance times after 10^-1^M sodium metabisulphite (\~250% compared to control, \~100%) was followed by a recovery (120 to 170 min in Figure [1](#F1){ref-type="fig"}) to \~150% compared to control (still significantly different from control) nevertheless, demonstrated recovery from the acute response. It is possible that recovery could have been attenuated by the inability of the cilia to clear sodium metabisulphite off the palate. Alternately, SE micrographs showed that, in metabisulphite-treated palates, significant areas of exfoliation were present. It was shown by morphometric analysis that areas of the palate were devoid of ciliated cells, compared to an uninterrupted \"carpet\" of cilia in control palates. Although mucus continued to move across the palate, the loss of a significant portion of the ciliary layer, replaced by gaps in the ciliated surface, would contribute to a sustained (non-recoverable) increase in MCT. A further finding of intact, ciliated epithelial cells in mucus, recovered from metabisulphite-treated palates, suggested that exfoliation of intact ciliated cells may involve the action of proteases on cell-cell or cell matrix attachments. Gelatinase zymography showed increased activity of MMP-9 in tissue and mucus from metabisulphite-treated palates compared to controls.
Conclusion
==========
We have shown from the zymographic studies, taken together with the scanning electron microscope studies, that MMP-9 activation was associated with the loss of ciliated cells from the palate. These results suggest the sustained increase in MCT as measured directly on the frog palate may have been due to the action of sodium metabisulphite to activate MMP-9 leading to a loss of ciliated epithelial cells. How this occurs at the cellular level is a question that remains to be answered. Further studies that clarify a site of action of the MMPs and a source of MMPs in this model will be important to determine the mechanism of action of this effect. How MMPs are activated in the tissue is another important question. An understanding of this injury mechanism may lead to ways to intervene in the early stages of airway diseases with symptomatic signs of impaired of mucociliary clearance.
|
PubMed Central
|
2024-06-05T03:55:47.782648
|
2004-8-24
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517808/",
"journal": "Respir Res. 2004 Aug 24; 5(1):10",
"authors": [
{
"first": "Darryl W",
"last": "O'Brien"
},
{
"first": "Melanie I",
"last": "Morris"
},
{
"first": "Jie",
"last": "Ding"
},
{
"first": "J Gustavo",
"last": "Zayas"
},
{
"first": "Shusheng",
"last": "Tai"
},
{
"first": "Malcolm",
"last": "King"
}
]
}
|
PMC517820
|
Introduction {#s1}
============
Sterols are essential in most eukaryotic cells and play a structural role in the architecture of their membranes. They influence the physicochemical properties of membranes, including fluidity and permeability for ions ([@pbio-0020280-Haines1]). Cholesterol, together with glycosphingolipids, is also proposed to organise membrane microdomains (also called "rafts"), which provide platforms for protein sorting or signal transduction ([@pbio-0020280-Simons1]). In addition to this structural role in the membrane, cholesterol is essential for a variety of signalling processes. It is a precursor of important classes of physiologically active compounds such as steroid hormones in mammals or ecdysones in insects. The nematode Caenorhabditis elegans provides a valuable model system to study the orchestration of cholesterol metabolism and function at the level of a whole organism. *C. elegans,* like other nematodes, cannot synthesise sterols de novo ([@pbio-0020280-Hieb1]; [@pbio-0020280-Chitwood1]). Thus, it requires an exogenous source of sterols, which enables (i) analysis of sterol metabolism using labelled precursors and (ii) analysis of sterol functions by feeding normal and mutant worms with cholesterol derivatives and related sterols.
Although worms require exogenous cholesterol for survival, the effects of its depletion are still controversial ([@pbio-0020280-Kurzchalia1]). Worms are routinely grown in the laboratory on agar plates seeded with bacteria and supplemented with 5 μg/ml of cholesterol (Brenner conditions) ([@pbio-0020280-Brenner1]). Omitting sterols from agar has a weak effect on development and growth: Worms can still propagate for many generations, although some larvae fail to shed the old cuticles properly during molting, gonad development is aberrant, and movement is uncoordinated ([@pbio-0020280-Yochem1]; [@pbio-0020280-Shim1]). Under these conditions, the amounts of sterols in both the agar and the bacteria grown on yeast extracts seem to be sufficient to support growth. A stronger phenotype is obtained by using bacteria grown on defined or sterol-extracted media ([@pbio-0020280-Crowder1]; [@pbio-0020280-Merris1]). Results of depletion experiments indicate that although absolutely necessary, sterols are required only in very low amounts. This makes it less likely that they are structural components in worm membranes, and thus the primary role in worms should reside in signalling ([@pbio-0020280-Kurzchalia1]). However, no specific signalling molecules derived from cholesterol, steroid hormones, or ecdysones have been identified yet.
It has been suggested that in worms cholesterol plays a role in the processes of molting and dauer formation. Involvement in molting is based on the roles of the worm homologues of mammalian megalin and insect DHR3. A worm mutant of *lrp-1,* a homologue of mammalian gp330/megalin protein, had a phenotype of defect in shedding of the cuticle, and this phenotype became more apparent upon partial cholesterol depletion ([@pbio-0020280-Yochem1]). Among other functions, megalin in mammals is involved in the uptake of a cholesterol derivative, vitamin D, by kidney absorptive cells ([@pbio-0020280-Willnow1]). Molting in insects is regulated by ecdysones, polyhydroxylated sterols derived from cholesterol, which act via nuclear hormone receptors. The analysis of the C. elegans genome did not reveal a homologue of the ecdysone receptor itself. However, disruption by RNAi of CHR3 *(nhr-23),* a C. elegans homologue of *Drosophila* orphan nuclear receptor (DHR3) that is induced by ecdysone, leads to defective shedding of the old cuticle ([@pbio-0020280-Kostrouchova1], [@pbio-0020280-Kostrouchova2]).
Another process that might involve cholesterol or its derivatives is dauer larva formation. Many genes can mutate to cause constitutive formation of dauer larvae (Daf-c mutants) or to prevent their formation (Daf-d mutants) ([@pbio-0020280-Riddle1]). Genetic studies have revealed that three pathways (TGF-β, cyclic GMP, and insulin-like IGF-1) control the formation of dauer larvae ([@pbio-0020280-Riddle1]). DAF-2 (insulin-like receptor, IGF-1) signals to inhibit the activity of DAF-16, a forkhead domain (FOXO) transcription factor ([@pbio-0020280-Kenyon1]; [@pbio-0020280-Morris1]) that also influences the prolongation of adult life span ([@pbio-0020280-Lin1]; [@pbio-0020280-Ogg1]). Under dauer formation conditions, DAF-16 is activated and translocated into the nucleus, where it may integrate insulin-like and TGF-β signalling pathways ([@pbio-0020280-Henderson1]; [@pbio-0020280-Lee1]; [@pbio-0020280-Lin2]). Genetic epistasis analysis suggests that *daf-16* acts upstream of two other *daf* genes, *daf-9* and *daf-12* ([@pbio-0020280-Gerisch2]; [@pbio-0020280-Jia1]). It was proposed that DAF-16 inhibits the activity of DAF-9 when the dauer formation process is initiated. The integration of all three pathways downstream from *daf-9* occurs at the level of DAF-12, a putative nuclear hormone receptor ([@pbio-0020280-Antebi1], [@pbio-0020280-Antebi2]), suggesting a possible hormonal regulation of dauer larva formation. In addition, *daf-9* has a strong homology to several cytochrome P450s that are involved in steroid metabolism in mammals ([@pbio-0020280-Gerisch2]; [@pbio-0020280-Jia1]). The *daf-9* null mutation leads to constitutive dauer formation, consistent with the scenario where DAF-9 is an enzyme that produces a steroid hormone regulating DAF-12, which in turn ultimately triggers dauer formation.
As a starting point for our investigations on the role of sterols in *C. elegans,* we developed a protocol for strict elimination of sterols in the medium and food. Under sterol-free conditions, the first generation of worms developed from eggs to adults without external cholesterol. In the second generation they become dauer-like larvae but molting was incomplete. We found that replacing cholesterol with its natural metabolite lophenol, a methylated sterol, induced all worms to form regular dauer larvae. Using the effect of lophenol on growth, we could partially purify activity supporting the reproduction and determine the role of sterols during dauer larva formation and longevity. In the absence of this hormone, the nuclear hormone receptor DAF-12 is derepressed and thereby activates the dauer formation program. Active DAF-12 triggers in neurons the nuclear import of DAF-16 that contributes to dauer differentiation. Thus, the effect of lophenol allowed us to reveal a novel function of DAF-16 downstream of DAF-12 that is required for the execution of the dauer program but has no effect on life span.
Results {#s2}
=======
Worms Grown without Cholesterol for Two Generations Become Dauer-Like Larvae with Incomplete Molting {#s2a}
----------------------------------------------------------------------------------------------------
In order to establish sterol-free growth conditions, we extracted traces of sterols from agarose and used defined medium for propagation of Escherichia coli to be fed to worms (see [Materials and Methods](#s4){ref-type="sec"}). When eggs derived from mothers grown on normal plates (5 μg/ml of cholesterol; approximately 13 μM) hatched at low population densities on sterol-free plates seeded with bacteria, the first generation of worms developed from eggs to adults without external cholesterol. These adults, however, laid only about 60% as many eggs as normal, and 17% of the total eggs laid did not hatch ([Figure 1](#pbio-0020280-g001){ref-type="fig"}A). The second-generation larvae completed their L1-to-L2 molt but then all arrested their development ([Figure 1](#pbio-0020280-g001){ref-type="fig"}A, no cholesterol). Previous studies showing a weaker effect of cholesterol depletion in the second generation ([@pbio-0020280-Yochem1]; [@pbio-0020280-Crowder1]; [@pbio-0020280-Shim1]; [@pbio-0020280-Merris1]) might be due to contaminating sterols.
::: {#pbio-0020280-g001 .fig}
Figure 1
::: {.caption}
###### Depletion of Cholesterol Leads to Formation of Dauer-Like Larvae
\(A) For worms grown on plates without cholesterol, the first-generation worms (F1) laid fewer eggs than normal (133 ± 10 versus 210 ± 12) and more eggs failed to hatch. Filled ovals depict unhatched eggs; 17% of eggs laid by cholesterol-depleted worms failed to hatch in comparison to 0.02% of those laid by cholesterol-fed worms. The second generation of worms (F2) arrested after the completion of the L1-to-L2 molt.
\(B) Light micrograph of an arrested L2 larva.
\(C) Electron micrograph of the lateral cuticle of an arrested L2 larva 5 d after arrest, showing two cuticles. The outer cuticle resembles that of an L2, which has no alae, and the inner cuticle resembles the dauer cuticle with its distinctive striated layer (bracket) and an incomplete dauer ala.
\(D) Electron micrograph of an arrested L2 *daf-12* mutant grown without cholesterol. Arrows indicate vesicles beneath the cuticle which are not present in normal larvae.
\(E) Electron micrograph of a wild-type L2 larva grown with normal cholesterol.
:::
:::
[Figure 1](#pbio-0020280-g001){ref-type="fig"}B shows an F2 larva grown on a cholesterol-depleted plate. The arrested larvae are similar in size and appearance to L2 larvae grown on cholesterol. The number of cells in their gonads varied between five and 25 with an average of ten, similar to normally grown L2 larvae ([@pbio-0020280-Kimble1]). These larvae stopped pharyngeal pumping after 3--5 d and became immobile after 7 d. If they were transferred to cholesterol-containing plates within the first 2--3 d, larvae reversed their arrest and matured to fertile adults. The reversal required as low as 20 nM cholesterol.
The arrested larvae had a double cuticle ([Figure 1](#pbio-0020280-g001){ref-type="fig"}C). The outer cuticle looks like a normal L2 cuticle and the inner cuticle has the characteristics of the normal dauer larva cuticle, including partially developed alae (for comparison, see [Figure 3](#pbio-0020280-g003){ref-type="fig"}D) and the distinctive striated layer found only in dauer larvae ([@pbio-0020280-Cassada1]) ([Figure 1](#pbio-0020280-g001){ref-type="fig"}C). Other dauer-like features of these arrested larvae include constriction of the gut and unstained gut granules (unpublished data). Occasionally, animals were found with partially shed cuticles (\<5%; unpublished data). In contrast to normal dauer larvae ([@pbio-0020280-Swanson1]), these arrested larvae were sensitive to treatment with 1% sodium dodecyl sulphate (SDS), perhaps because this shedding defect prevents complete dauer cuticle maturation.
::: {#pbio-0020280-g003 .fig}
Figure 3
::: {.caption}
###### Wild-Type Worms Form Regular Dauer Larvae When Grown with Lophenol Replacing Cholesterol
(A and B) Light microscopy of the second generation of worms grown on lophenol. Note low population density and ample bacteria on the plates (bacteria get swept into piles resembling worm tracks on agarose plates).
(C--E) Electron micrographs of lophenol-grown and *daf-2* dauer larvae. The alae and the striated layer (bracket) are indistinguishable from those of regular dauer larvae, with extended outer projections.
:::
:::
We then asked whether the dauer features of the arrested larvae depend on *daf-12.* In the absence of cholesterol the second generation of *daf-12* worms arrested with only one cuticle similar to that of normal L2 ([Figure 1](#pbio-0020280-g001){ref-type="fig"}D and [1](#pbio-0020280-g001){ref-type="fig"}E). These results show that on noncrowded plates with ample food, the absence of cholesterol causes L2 larvae to enter the normal dauer pathway utilising DAF-12.
In summary, our results imply that cholesterol, or cholesterol derivatives, are essential either for the development of reproductive adults or for the prevention of dauer larva formation. In addition, cholesterol derivatives are needed to shed the L2 cuticle.
Cholesterol Depletion Leads to Reduced Levels of Nonmethylated Sterols and Accumulation of Methylated Sterols {#s2b}
-------------------------------------------------------------------------------------------------------------
We investigated the metabolism of cholesterol in worms under conditions of cholesterol depletion. Eggs derived from mothers fed with radioactive cholesterol were put on cholesterol-depleted plates, where they grew for another generation to finally produce arrested L2/dauer larvae. The metabolism of sterols was followed by thin-layer chromatography (TLC). It has been previously established that C. elegans metabolises exogenously added cholesterol by methylating the A-ring at the fourth position and rearranging the double bond to form lophenol as the major product ([Figure 2](#pbio-0020280-g002){ref-type="fig"}A) ([@pbio-0020280-Chitwood2]). In eggs and L1 larvae of the first generation ([Figure 2](#pbio-0020280-g002){ref-type="fig"}B, lanes 1 and 2, respectively) or under conditions where cholesterol is present in the food permanently (unpublished data), methylated sterols (ms; lophenol and 4α-methyl-Δ8,14-cholestenol) are found in much lower amounts than nonmethylated sterols (nms; cholesterol, 7-dehydrocholesterol, and lathosterol). Quantification of radiographs revealed that under these conditions ms represent only 1%--3% of the total radioactivity. Cholesterol is also metabolised to a number of more hydrophilic derivatives (indicated by a vertical line), the identities of which are still unknown. In eggs derived from the second generation we observed two major changes: (i) The total radioactivity decreased and (ii) the fraction of nms showed a stronger decrease than that of ms ([Figure 2](#pbio-0020280-g002){ref-type="fig"}B). The proportion between ms and nms changed even more dramatically in the L1 larvae of the second generation ([Figure 2](#pbio-0020280-g002){ref-type="fig"}B, lanes 3--6). Here, about 95% of radioactivity was found as ms (lane 6). Note that the total radioactivity is on the limit of detection. Thus, upon cholesterol depletion the relationship between amounts of nms versus ms is altered.
::: {#pbio-0020280-g002 .fig}
Figure 2
::: {.caption}
###### Depletion of Cholesterol Is Associated with a Decrease of Nonmethylated Sterols
\(A) Nematode-specific biosynthesis of 4-methylated sterols from exogenously added cholesterol. Open arrow shows the methylation at the fourth position. A vertical line indicates hydrophilic metabolites of cholesterol.
\(B) Cholesterol metabolism in the first (lanes 1 and 2) and the second (lanes 3--6) generations of worms derived from mothers fed with radioactive cholesterol. CE, cholesteryl esters; mS, methylated sterols (lophenol, 4-methylcholestenol); nmS, nonmethylated sterols (cholesterol, 7-dehydrocholesterol, lathosterol). The position of these compounds on TLC was determined by chromatography of cholesteryl stearate, lophenol, and cholesterol. E, eggs; L1, L1 larvae.
:::
:::
Substitution of Cholesterol by a Methylated Sterol, Lophenol, Leads to Dauer Larva Formation in the Second Generation {#s2c}
---------------------------------------------------------------------------------------------------------------------
To test how nms influence dauer larva formation, we grew worms on plates with all cholesterol replaced by the methylated sterol lophenol ([Figure 2](#pbio-0020280-g002){ref-type="fig"}A). When eggs from normally grown hermaphrodites were placed on lophenol plates, the first generation of worms was indistinguishable from that grown on cholesterol. They had normal brood size and normal morphology. In the second generation, however, the entire population completed two molts and became dauer larvae despite sufficient food and low population density ([Figure 3](#pbio-0020280-g003){ref-type="fig"}A and [3](#pbio-0020280-g003){ref-type="fig"}B). Even on plates with a single worm, the individual developed into a dauer larva. These dauer larvae formed on lophenol plates had the distinct skinny shape, their pharynx was constricted, and they had very rare pharyngeal contractions, as detected earlier for dauer larvae formed by starvation ([@pbio-0020280-Keane1]). Electron microscopy showed that they had the characteristic alae ([Figure 3](#pbio-0020280-g003){ref-type="fig"}C) and striations of the normal dauer cuticle (compare [Figure 3](#pbio-0020280-g003){ref-type="fig"}D and [3](#pbio-0020280-g003){ref-type="fig"}E). They were also resistant to SDS treatment like normal dauer larvae. These results show that, like cholesterol starvation, growth on lophenol leads to dauer larva formation. Unlike cholesterol starvation, however, lophenol allows shedding of the L2 cuticle to form normal dauer larvae.
The formation of dauer larvae by growth on 13 μM lophenol was prevented completely by adding cholesterol or its immediate precursor, lathosterol (see [Figure 2](#pbio-0020280-g002){ref-type="fig"}A), in amounts as low as 20 nM. Under these conditions all the worms matured to fertile adults. The presence of contaminating nms in plates could be the reason why others did not find dauer larvae when worms were grown on lophenol ([@pbio-0020280-Merris1]).
The dauer larvae formed on lophenol plates resumed normal growth when transferred to cholesterol plates, although it required 3--4 d for them to reinitiate development, in contrast to the typical 15 h for normal dauer larvae.
Methylation of the Fourth Position of Sterols Is Not Obligatory for Dauer Larva Formation {#s2d}
-----------------------------------------------------------------------------------------
The observation that small amounts of nms can prevent dauer larva formation on lophenol suggests that the lack of a cholesterol derivative which cannot be produced from lophenol is causing dauer larva formation. However, it is possible that lophenol itself actively induces dauer larva formation and methylation of sterols in the 4α position is necessary for this process. In order to distinguish between these alternatives we synthesised 5α-cholestan-3β-ols with a methyl group or fluorine substituted in 4α position ([Figure 4](#pbio-0020280-g004){ref-type="fig"}) and fed them to worms. We decided to use saturated sterols because they are much more easily accessible for chemical synthesis (for details of synthesis, see [Protocol S1](#sd001){ref-type="supplementary-material"}). Cholestanol ([Figure 4](#pbio-0020280-g004){ref-type="fig"}A) and lophanol ([Figure 4](#pbio-0020280-g004){ref-type="fig"}B) have similar effects on growth as their homologues cholesterol and lophenol, respectively. The former supports reproductive growth, whereas the latter induces dauer formation. Remarkably, when fed with 4αF-cholestanol ([Figure 4](#pbio-0020280-g004){ref-type="fig"}C), worms in the second generation produced dauer larvae. Fluorinated compounds, except in very rare cases, are not susceptible to chemical modifications by living organisms and therefore 4αF-cholestanol cannot be methylated. The fluorine atom is less bulky than the methyl group ([Figure 4](#pbio-0020280-g004){ref-type="fig"}, space-filling models) and differs from the latter in its chemical properties. Thus, it is not the methylation of a sterol in the fourth position per se that is required for the formation of a dauer larva, but rather its accessibility is necessary to prevent this process. We suggest that cholesterol is normally metabolised in two distinct pathways: a pathway forming lophenol, and a pathway forming a steroid hormone. This hormone is required for maintaining reproductive growth and cannot be produced from ms.
::: {#pbio-0020280-g004 .fig}
Figure 4
::: {.caption}
###### Methylation of the Fourth Position of Cholestanol Is Not Required for Dauer Larva Formation
Structural formulae and space-filling models of (A) cholestanol, (B) lophanol, and (C) 4αF-cholestanol. Abilities to support reproductive growth or dauer formation in the second generation are indicated. R, reproduction; D, dauer larva.
:::
:::
Partial Purification of Gamravali, an Activity That Promotes Reproduction {#s2e}
-------------------------------------------------------------------------
The effect of lophenol on growth gave us a unique opportunity to purify the hormone (activity) required for reproductive growth. The rationale of our approach was to rescue the formation of dauer larvae induced in the presence of lophenol by a substance derived from a lipidic extract of worms. Obviously, this substance should differ from cholesterol and its direct metabolites such as 7-dehydrocholesterol and lathosterol. The lipidic extract of worms (see [Materials and Methods](#s4){ref-type="sec"}) was fractionated using high-performance liquid chromatography (HPLC) on a reverse-phase C~18~ column ([Figure 5](#pbio-0020280-g005){ref-type="fig"}A), and fractions mixed with lophenol were fed to L1 larvae of the second generation that were grown on lophenol. As seen in [Figure 5](#pbio-0020280-g005){ref-type="fig"}B, two major peaks of activity rescuing dauer larva formation were detected. The major peak, according to retention times (23--30 min), should contain cholesterol, lathosterol, and 7-dehydrocholesterol. Another peak at the beginning of the gradient, however, is much more hydrophilic than major metabolic sterols. Two observations argue that this fraction is not contaminated by dietary cholesterol: (i) This region of the gradient never displayed activity even if the column was overloaded with cholesterol, and (ii) in contrast to cholesterol, active fraction \#2 did not support reproductive growth alone, and instead many worms engulfed by the old cuticle were observed. This may be because another cholesterol-derived substance responsible for molting was missing.
::: {#pbio-0020280-g005 .fig}
Figure 5
::: {.caption}
###### Partial Purification of Gamravali
\(A) Lipidic extract of worms was separated by HPLC using a C~18~ reverse-phase column. Retention times of (1) 7-dehydrocholesterol, (2) cholesterol/lathosterol, and (3) ecdysone/estradiol/testosterone are indicated with arrows.
\(B) Fractions of 2 min from the chromatography were assayed for the activity to rescue the formation of dauer larvae induced in the presence of lophenol.
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:::
We name this activity gamravali (from gamravleba, which means "reproduction" in Georgian; gamravali means "something supporting the reproduction") because it is required for reproduction in worms. Currently we are attempting to determine the molecular formula of gamravali using mass spectroscopy. This task, however, is very demanding because of the tiny amounts of the substance in worms. Even more demanding will be the final identification of the structure by nuclear magnetic resonance or X-ray analysis. We estimated that the latter might require scaling of the preparation (see [Materials and Methods](#s4){ref-type="sec"}) up to more than two orders of magnitude.
Our data indicate that gamravali is much more hydrophilic than sterols. Remarkably, retention times on the column of many mammalian steroids tested (pregnenolone, β-estradiol, testosterone, etc.) and the insect molting hormone ecdysone are very similar ([Figure 5](#pbio-0020280-g005){ref-type="fig"}A). Thus, gamravali could be a polyhydroxylated sterol such as ecdysone, lack the hydrophobic side chain as in mammalian steroid hormones, or even contain a charged group. However, none of the compounds mentioned above or other commercially available steroids could rescue dauer formation in the presence of lophenol (see a list of tested compounds in [Materials and Methods](#s4){ref-type="sec"}).
A Mutant of *daf-12* Can Grow and Reproduce Normally on Lophenol for Many Generations, Whereas Several Daf-d Mutants Produce Dauer Larvae {#s2f}
-----------------------------------------------------------------------------------------------------------------------------------------
The effect of lophenol on growth also made it possible to identify steps of the dauer formation pathway at which gamravali is required. For this we examined the phenotype of several dauer formation-defective (Daf-d) mutants when grown on lophenol. We assumed that mutants that are defective in metabolism of gamravali and thus act upstream of the hormone receptor should produce dauer larvae on lophenol. Mutants in genes acting downstream of the gamravali action should reproduce normally.
We first investigated the growth of a *daf-12* null mutant with lophenol as the sole source of sterols. DAF-12 as a putative nuclear hormone receptor is a good candidate to be a receptor for gamravali. In contrast to wild-type worms, mutants of *daf-12* grown on lophenol produced no dauer larvae and developed normally for more than seven generations. *daf-12* could also reproduce normally on lophanol and 4αF-cholestanol (see [Figure 4](#pbio-0020280-g004){ref-type="fig"}). Therefore, *daf-12* acts downstream of gamravali depletion to promote dauer formation, leaving open the possibility that gamravali could be a ligand that inhibits the DAF-12. Our data also show that lophenol can substitute for all cholesterol functions except for the promotion of reproductive development.
In contrast to *daf-12,* other Daf-d mutants, such as *daf-22, daf-6, daf-10, daf-3,* and *daf-5* developed into dauer larvae when grown on lophenol. According to genetic studies all these genes are upstream of *daf-12* in the pathway. *daf-22* and *daf-6* cannot produce or sense the dauer-inducing pheromone, respectively ([@pbio-0020280-Golden1]; [@pbio-0020280-Perkins1]). DAF-3 and DAF-5 are SMAD transcription factor and its regulator Ski, which antagonise TGF-β action ([@pbio-0020280-Patterson1]; [@pbio-0020280-Da1]). The functions of these genes could be to inhibit gamravali production when the dauer pathway is initiated by starvation or overcrowding. Growth on lophenol alone would mimic this situation and result in dauer formation since gamravali cannot be made from lophenol.
Mutant *daf-16* Produces Defective Dauer Larvae on Lophenol and the Latter Induces Entry of DAF-16 into Nuclei of Neurons in a DAF-12--Dependent Manner {#s2g}
-------------------------------------------------------------------------------------------------------------------------------------------------------
Somewhat different results were obtained with null mutants of *daf-16* grown on lophenol. In the second generation, neither reproductive adults nor regular dauers were observed. The larvae were fully susceptible to the SDS treatment and their morphology displayed several abnormalities in comparison to regular dauer larvae ([Figure 6](#pbio-0020280-g006){ref-type="fig"}). They did not have alae of normal morphology (compare [Figure 6](#pbio-0020280-g006){ref-type="fig"}A and [3](#pbio-0020280-g003){ref-type="fig"}E), although a striated layer characteristic of the dauer state was visible. The gut was not constricted as in regular dauer larvae ([Figure 6](#pbio-0020280-g006){ref-type="fig"}A). Remarkably, the cuticle displayed annular structures ([Figure 6](#pbio-0020280-g006){ref-type="fig"}B, arrowhead) characteristic of adults but never detected in dauer larvae (compare [Figure 6](#pbio-0020280-g006){ref-type="fig"}B and [6](#pbio-0020280-g006){ref-type="fig"}C). One in about 400 worms would occasionally mature and produce a few eggs that never hatched. Thus, in the absence of DAF-16 only a partial, defective dauer larva can be produced on lophenol. Similar defective dauers (although with very low efficiency) were produced by pheromone-treated *daf-16* ([@pbio-0020280-Vowels1]). Our data indicate that in the absence of cholesterol or its derivatives other than lophenol, *daf-16* is still needed for normal differentiation of dauer larvae. Thus, DAF-16 should have activity downstream of the sterol requirement.
::: {#pbio-0020280-g006 .fig}
Figure 6
::: {.caption}
###### Mutant *daf-16* Worms Grown on Lophenol Form Defective Dauer Larvae
\(A) Low-magnification electron micrograph of lophenol-grown *daf-16*. The alae are defective although the striated layer (bracket) is visible. Note that the gut is not constricted and contains remnants of food.
(B and C) High-magnification electron micrographs of lophenol-grown *daf-16* and wild-type dauer larvae. Arrowhead indicates an annular structure.
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Genetic epistasis analysis suggested that *daf-16* functions upstream of *daf-9,* which in turn acts upstream of *daf-12* ([@pbio-0020280-Gerisch2]; [@pbio-0020280-Jia1]). Moreover, it has been proposed that DAF-16 inhibits DAF-9, a cytochrome P450 that could be involved in the synthesis and/or degradation of a gamravali-like ligand for DAF-12. Consequently, gamravali should be required downstream of DAF-16 function. However, our data ([Figure 6](#pbio-0020280-g006){ref-type="fig"}) imply that, in addition to the regulation of sterol biosynthesis, DAF-16 acts downstream of DAF-12 and is involved in the differentiation of dauer larvae.
Under reproductive conditions, DAF-16 is found in both the cytoplasm and the nucleus, whereas upon activation by the IGF-1 or the TGF-β pathways the protein is accumulated in the nucleus ([@pbio-0020280-Henderson1]; [@pbio-0020280-Lee1]; [@pbio-0020280-Lin2]). We asked whether the growth on lophenol had a similar effect on the cellular distribution of DAF-16. In order to answer this question, we made use of a transgenic line expressing a DAF-16::GFP fusion protein ([@pbio-0020280-Lin2]). In L3 larvae grown on cholesterol, DAF-16::GFP showed diffuse fluorescence throughout many cells, as reported previously ([Figure 7](#pbio-0020280-g007){ref-type="fig"}A). In contrast, in the second generation of worms grown on lophenol, DAF-16::GFP is localised in nuclei of neurons of the pharynx, ventral cord, and tail ([Figure 7](#pbio-0020280-g007){ref-type="fig"}C). Lophenol had a very weak effect on the accumulation of DAF-16 in the nuclei of other cells (e.g., gut or muscles).
::: {#pbio-0020280-g007 .fig}
Figure 7
::: {.caption}
###### Growth on Lophenol Induces the Accumulation of DAF-16 in the Nuclei of Neurons in a DAF-12--Dependent Manner
\(A) When grown on cholesterol, the transgenic line DAF-16a::GFP/b^KO^ displays a diffuse staining in the cytoplasm and nuclei of many cells (only the pharynx region of an L3 larva is shown).
\(B) Staining of a larva of similar age by Hoechst. Note many nuclei in the pharynx.
\(C) The DAF-16a::GFP/b^KO^ line grown on lophenol shows strong staining of nuclei in neurons of the pharynx, tail, and ventral cord of a dauer larva.
\(D) An L3 larva of DAF-16a::GFP/b^KO^ in a *daf-12* null background grown on lophenol. Note the diffuse fluorescence in the pharynx cell similar to that shown in (A).
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:::
Is the nuclear accumulation of DAF-16 upon growth on lophenol dependent on the activation of DAF-12? DAF-16::GFP showed diffuse staining in a *daf-12* null mutant grown on lophenol (compare [Figure 7](#pbio-0020280-g007){ref-type="fig"}D and [7](#pbio-0020280-g007){ref-type="fig"}A). Our data therefore indicate that the activation of DAF-12 induced by the absence of gamravali leads to accumulation of DAF-16 in the nuclei of neurons.
Since the double *daf-16;daf-12* mutant grown on lophenol did not produce dauer larvae and could grow on this sterol for many generations, the phenotype of *daf-16* observed in the absence of hormone (see [Figure 6](#pbio-0020280-g006){ref-type="fig"}A and [6](#pbio-0020280-g006){ref-type="fig"}B) depends on the activity of *daf-12.* These results imply that the dauer formation process is initiated by DAF-12 but needs nuclear import of DAF-16, which in turn contributes to dauer differentiation, presumably through transcriptional regulation in the nucleus.
Growth on Lophenol Does Not Extend the Life Span of Worms {#s2h}
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*daf-2* mutants have a life span that is approximately twice as long as that of the wild-type worms ([@pbio-0020280-Kenyon1]), and in addition mutants display strong intrinsic thermotolerance ([@pbio-0020280-Gems1]). This effect is attributed to the activation of DAF-16 in a *daf-2* mutant, since a double *daf-16;daf-2* mutant suppresses this phenotype. Does the nuclear accumulation of DAF-16 in neurons when grown on lophenol have a similar effect on life span and thermotolerance? In wild-type worms of the first generation grown on cholesterol or lophenol we could not detect significant differences in the mean life span (21.0 ± 1.8 d and 20.3 ± 1.6 d for cholesterol and lophenol, respectively). It must be noted, however, that worms grown in the absence of cholesterol and the presence of lophenol do not have a developmental phenotype in the first generation and therefore may have some maternal rescue of adult life span. Because the second generation does not grow to adulthood (forms dauer larvae), the definitive experiment cannot be performed. Growth on lophenol also had no influence on the intrinsic thermotolerance of worms at 39 °C. Thus, the activation of DAF-16 induced by the absence of gamravali might have different physiological consequences than its activation by diminished IGF-1 signalling.
Discussion {#s3}
==========
Worms Need Tiny Amounts of Sterols for Survival {#s3a}
-----------------------------------------------
In our attempts to understand the role of cholesterol in nematodes we developed strict sterol-free conditions for growth by combination of the extraction of agarose with organic solvents and the growing of bacteria on defined media. Under these conditions, the first generation of worms grew relatively normally and only the second generation arrested as dauer-like larvae. Thus, the amount of sterols deployed by mothers into embryos is sufficient not only for the survival of the first generation but even for the embryonic development of about 130 embryos that reach the L2 stage in the second generation. This makes cholesterol unlikely to be an indispensable structural component in most worm membranes, although it could play a structural role in cell types where it is concentrated ([@pbio-0020280-Matyash1]). These results are difficult to reconcile with the widespread role of cholesterol and other nms as essential structural components of the plasma membrane. Presumably, C. elegans can regulate membrane properties in response to temperature changes by altering fatty acid composition of phospholipids ([@pbio-0020280-Tanaka1]). Future investigations should clarify what components of nematode membranes substitute for structural functions of cholesterol and whether mechanisms exploited by nematodes to control membrane properties are also serving an analogous purpose in higher eukaryotes.
Hormonal Regulation of Dauer Larva Formation: Gamravali versus Lophenol {#s3b}
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Our results obtained by growing wild-type and mutant worms without cholesterol, with cholesterol replaced by lophenol, and with lophenol supplemented by gamravali demonstrate unequivocally that the decision to enter diapause is regulated by a sterol-derived hormone(s). We propose the following model to explain these results ([Figure 8](#pbio-0020280-g008){ref-type="fig"}). Gamravali derived from cholesterol acts to promote reproduction and prevent dauer larva formation by inhibiting the nuclear hormone receptor DAF-12. The effect of external signals that induce dauer formation, starvation, and overcrowding is to prevent gamravali production, thus preventing reproduction and promoting entry into diapause. According to this model, growth on lophenol resembles the absence of gamravali. Although it is formally possible that lophenol or ms derived from it could induce dauer formation, this is unlikely for three reasons: (i) Dauer larvae are not induced in the first generation on lophenol, (ii) cholesterol and gamravali at concentrations less than 1/600 that of lophenol prevent dauer larva formation, and (iii) the 4α-fluoro derivative can substitute for lophenol. It is much more likely that lophenol supports all the functions of cholesterol, structural and hormonal, except promoting reproductive growth, since *daf-12* null mutants grow and reproduce normally on lophenol. The *daf-9* gene, which encodes a cytochrome P450 ([@pbio-0020280-Gerisch2]; [@pbio-0020280-Jia1]), could be involved in the production of gamravali. Remarkably, expression of DAF-9 in *daf-7* and *daf-2* could rescue their Daf-c phenotype ([@pbio-0020280-Gerisch1]; [@pbio-0020280-Mak1]). We did not detect any gross-level changes of cholesterol metabolism in the double null *daf-9 daf-12* strain ([Figure S1](#sg001){ref-type="supplementary-material"}). However, since DAF-9 is expressed predominantly in only a small subset of cells ([@pbio-0020280-Gerisch2]; [@pbio-0020280-Jia1]), differences in overall cholesterol metabolism might be small and require more sensitive assays.
::: {#pbio-0020280-g008 .fig}
Figure 8
::: {.caption}
###### Cross Talk between Two Signalling Pathways in the Process of Dauer Larva Formation
Pheromone accumulated under the conditions of overcrowding or starvation induces the inhibition of gamravali production via the TGF-β pathway. Genes, mutants of which produced dauer larvae on lophenol, are shown in blue. Activated by the absence of gamravali, DAF-12 initiates the process of dauer larva production. One of its activities is to recruit DAF-16 into nuclei of neurons (shown in red). The insulin-like pathway has several physiological functions, among them the regulation of longevity and thermotolerance, and could be involved in the process of dauer formation by regulating the levels of gamravali via DAF-16.
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:::
The Place and Role of *daf-16* in the Dauer Formation Pathway {#s3c}
-------------------------------------------------------------
Our data uncover a dual role for DAF-16, first during the reproductive/dauer decision and second during dauer differentiation. It has been established that DAF-16 acts via the insulin-dependent pathway and is involved in the inhibition of hormone production ([@pbio-0020280-Gerisch2]; [@pbio-0020280-Jia1]), thereby controlling the reproductive/dauer decision ([Figure 8](#pbio-0020280-g008){ref-type="fig"}, right branch). Our results show that, in addition, DAF-16 functions downstream of DAF-12 so that activation of the latter recruits it into neuronal nuclei ([Figure 8](#pbio-0020280-g008){ref-type="fig"}, shown in red). The process of dauer formation, thus, is initiated by DAF-12 but needs DAF-16.
A direct physical interaction between nuclear hormone receptors and forkhead domain (FOXO) transcription factors has recently been reported ([@pbio-0020280-Schuur1]; [@pbio-0020280-Zhao1]; [@pbio-0020280-Dowell1]; [@pbio-0020280-Li1]). It is tempting to speculate that DAF-12 and DAF-16 can interact physically and that the activated DAF-12 can retain DAF-16 in the nucleus. Consistent with this, DAF-12 and DAF-16 have been coimmunoprecipitated in a recent in vitro study ([@pbio-0020280-Dowell1]).
Sterols and Longevity {#s3d}
---------------------
According to a current view, *daf-16* is a major regulator of the longevity process ([@pbio-0020280-Lin1]; [@pbio-0020280-Ogg1]). Reduction of DAF-2/IGF-1 signalling leads to activation of DAF-16 and to near-doubling of the life span of worms ([@pbio-0020280-Kenyon1]; [@pbio-0020280-Morris1]). The inhibition of insulin receptor activity leads to the redistribution of FOXO transcription factors from cytoplasm into the nucleus and thus is a prerequisite for their activity ([@pbio-0020280-Henderson1]; [@pbio-0020280-Lee1]; [@pbio-0020280-Lin2]). Our data show that in worms grown on lophenol, DAF-16 accumulates strongly in neuronal nuclei. The growth on lophenol, however, has no consequences on the length of the life span. A plausible explanation for this observation is that the activity of *daf-16* influencing life span is tissue specific. In a recent study, [@pbio-0020280-Libina1] have expressed DAF-16 in a *daf-16;daf-2* double mutant under different tissue-specific promoters. Whereas expression of DAF-16 in the intestine led to the extension of the life span, expression in the neurons had no effect on longevity. This is consistent with our data showing that the DAF-12--dependent nuclear import of DAF-16 in neurons activates a different program from that in the intestine.
Materials and Methods {#s4}
=====================
{#s4a}
### Materials {#s4a1}
Lophenol was purchased from Research Plus (Manasquan, New Jersey, United States). Electrophoresis-grade ultraPURE agarose was the product of Life Technologies (Paisley, Scotland, United Kingdom). Dulbecco\'s medium (DMEM) was from Invitrogen (Karlsruhe, Germany). Sterols, steroids, and antioxidant BTH were from Sigma (Sigma-Aldrich Chemie, Taufkirchen, Germany).
All mutants except *daf-12 (rh61rh411)* and *daf-9 (dh6) daf-12 (rh61rh411)* were obtained from the *Caenorhabditis* Genetics Center. *daf-12* and the double mutant *daf-9 daf-12* were a kind gift of Adam Antebi (Max Planck Institute for Molecular Genetics, Berlin, Germany). The following mutant strains were used throughout the study: *daf-22 (m130)*II, *daf-6 (e1377)*X, *daf-3 (mgDf90)*X, *daf-5 (e1386)*II, *daf-10 (e1387)*IV, *daf-12 (rh61rh411)*X, *daf-2 (e1370ts)*III, and *daf-16 (mgDf50)*I. For imaging studies strains *daf-16 (mu86)*I; *muIs71*\[*pKL99*(*daf-16a::GFP/bKO*)+*pRF4(rol-6)*\]X and *daf-16 (mu86)*I; *muIs61 (daf-16::GFP (pKL78)+rol-6(pRF4)* were tested. Since the former, *daf-16a::GFP/bKO,* gave a brighter signal, as previously reported ([@pbio-0020280-Henderson1]; [@pbio-0020280-Lee1]; [@pbio-0020280-Lin2]), results obtained with this strain are presented throughout the study.
### Preparation of sterol-depleted and sterol-containing plates for the propagation of worms {#s4a2}
Wild-type N2 Bristol and mutant strains were routinely propagated on NGM-agar plates as described in [@pbio-0020280-Brenner1]. To obtain cholesterol-free conditions, agar was replaced by agarose (extracted three times with chloroform) and peptone was omitted from plates. An overnight culture of the NA22 strain of E. coli was grown on a sterol-free culture medium DMEM. Bacteria were rinsed with M9 medium before use.
For preparation of sterol-containing plates, cholesterol or lophenol was dissolved in methanol to the concentration of 5 mM and mixed 1:1 (v/v) with cholesterol-free bacterial suspension in M9. After evaporation of methanol in SpeedVac, the suspension was mixed with fresh bacteria to obtain the desired end concentration of tested substance. Bacterial suspensions were spread on cholesterol-free agarose plates.
### Light, fluorescence, and electron microscopy {#s4a3}
Light and confocal fluorescence microscopy were done using Zeiss Axioplan and Axiovert LSM 510 microscopes, respectively. For nuclear labelling, larvae were grown on medium containing 5 μg/ml of Hoechst (Molecular Probes, Eugene, Oregon, United States). One hour before imaging, larvae were transferred to medium without Hoechst, washed briefly with M9 medium, anaesthetised with 40 mM sodium azide in M9, and mounted on agarose pads. For electron-microscopic studies arrested larvae were washed two times with M9, harvested by centrifugation, and mixed with an equal volume of 2×Fixative (5% glutaraldehyde, 2% paraformaldehyde in M9). Worms were cut at room temperature with a razor blade on a microscopic slide, transferred to a centrifuge tube, and incubated for 2 h in a refrigerator. Afterwards worms were centrifuged and embedded in EmBed-812 (EMS, Ft. Washington, Pennsylvania, United States). Images were acquired by Tecnai 12 (FEI, Eindhoven, The Netherlands) or Phillips 400 electron microscopes.
### TLC of cholesterol metabolites from *C. elegans* {#s4a4}
To investigate cholesterol metabolism in *C. elegans,* 10-cm NGM agar plates were prepared without cholesterol. A quantity of 300 μl of bacterial suspension containing 13 μM cholesterol was supplemented with 4 μCi of \[^3^H\]-cholesterol (70 Ci/mmol; Amersham Biosciences Europe, Freiburg, Germany). Worms were harvested from the plates with M9 medium and subjected to three cycles of freezing-thawing, and lipids were extracted by the Bligh and Dyer method ([@pbio-0020280-Bligh1]). Eggs derived from mothers fed with radioactivity were put on sterol-free plates and propagated for two generations. Equal amounts of eggs and L1 larvae estimated by counting of aliquots were extracted and analysed by TLC as described above.
TLC was performed on glass-backed plates of silica gel 60 (Merk, Darmstadt, Germany). Solvents used for the separation of cholesterol metabolites were chloroform-methanol (24:1).
After chromatography, plates were sprayed with a scintillator (Lumasafe, Lumac LSC B.V., Groningen, The Netherlands) and exposed to a film (Hyperfilm MP, Amersham Biosciences Europe, Freiburg, Germany).
We quantified relative amounts of ms and nms by scanning films exposed to radioactivity for short time and using Adobe Photoshop software.
### Regio- and stereospecific synthesis of 4α-substituted 5α-cholestan-3β-ols {#s4a5}
The synthesis of 4α-substituted 5α-cholestan-3β-ols is described in the [Supporting Information](#s5){ref-type="sec"}.
### Preparation and HPLC fractionation of a lipidic extract from worms {#s4a6}
Worms of mixed population from 150 15-cm plates were collected by rinsing with ice-cold water and left overnight at 4 °C to sediment. The final volume of the sediment was about 150 ml. After decantation, aliquots of the worm suspension were transferred into 50-ml Falcon tubes and subjected to three cycles of freezing in liquid N~2~ and thawing by sonication in an ultrasound bath at 37 °C. Worm suspension was then transferred into a glass bottle, 19 volumes of methanol containing 10 μg/ml of antioxidant BHT was added, and extraction was performed overnight at room temperature under continuous agitation. Extract was separated from worm remnants by filtration through a Whatman GF/A glass filter and remnants were reextracted with a fresh portion of methanol. Methanol extracts were combined and extracted two times with one volume of hexane. The obtained hexane extract was washed twice with a methanol-water mixture (9:1), dried under N~2~ flow, and dissolved in 7 ml of hexane.
In order to dispose very hydrophobic substances, the extract was subjected to a solid-phase separation. A quantity of 200 μl of the hexane fraction was applied to a 20-ml LC-18-SPE cartridge (SUPELCO, Bellefonte, Pennsylvania, United States) equilibrated with methanol. Twenty millilitres of flow-through methanol was collected, dried under N~2~ flow, and dissolved in 200 μl of methanol. Two preps (400 μl) were subjected to reverse-phase HPLC chromatography on an Alliance 2695 solvent module (Waters GmbH, Eschborn, Germany) linked to a Waters 996 photodiode array detector using an XTerra Prep MS C~18~ 10 μm 10 × 250-mm column (Waters). The elution protocol was as follows: 15% solvent A (20% methanol in water) and 85% solvent B (methanol) for 11 min, a gradient from 85% B to 100% B in 11 min, and 100% B for 18 min. The flow rate was 5 ml/min. Fractions of 2 min were collected, dried, dissolved in 400 μl of isopropanol, and stored at −80 °C until use.
### Assay for gamravali {#s4a7}
Testing of the biological activity of HPLC fractions was performed in 12-well cell culture plates (Nunc, Roskilde, Denmark). Each well contained 1 ml of sterol-free agarose mixed with 0.1% tergitol. A quantity of 100 μl of HPLC fractions was added per well and dried in the laminar flow cabinet. Before seeding worms, 30 μl of sterol-free bacteria containing 10 μM lophenol was added to plates and left to stay overnight at room temperature.
Worms for the bioassay were prepared as follows. The first generation of adult worms grown on lophenol (see above) was bleached, and eggs were placed on sterol-free plates without food and were kept for 3 d to obtain synchronised L1 larvae.
About ten starved L1 larvae were placed in each well with HPLC fractions at room temperature. After 4 d worms were scored and the activity of fractions was represented as the percentage of worms that reached L4 or adult stages. Quadruplicates of each fraction per experiment were analysed.
### Compounds tested to rescue the dauer larva formation in the presence of lophenol {#s4a8}
Pregnenolone, testosterone, estrone, β-estradiol, progesterone, androstenol, vitamin D~3~, ecdysone, 20-hydroxyecdysone, 7α-hydroxycholesterol, 7β-hydroxycholesterol, 19-hydroxycholesterol, 20-hydroxycholesterol, 22-hydroxycholesterol, 24-hydroxycholesterol, 26-hydroxycholesterol, cholic acid, dehydrocholic acid, deoxycholic acid, litocholic acid, taurodeoxycholic acid, and chenodeoxycholic acid were tested. 7α-hydroxycholesterol, 19-hydroxycholesterol, and 26-hydroxycholesterol were from Steraloids (Newport, Rhode Island, United States); all others were from Sigma.
### Generating a double null mutant for *daf-12* and *daf-16* and a transgenic line expressing DAF-16::GFP in *daf-12* null background {#s4a9}
The double mutant *daf-16(mu86)*I; *daf-12 (rh61rh411)*X was generated by crossing *daf-16 (mu86)*I; *muIs71*\[*pKL99(daf-16a::GFP/bKO)*+*pRF4(rol-6)*\]X hermaphrodites with *daf-12 (rh61rh411)* males. Progeny displaying no Roller phenotype and fluorescence and able to grow on lophenol were selected. The *daf-16(mu86)* mutation was identified by PCR. Consequently, the mutations were verified by sequencing.
The double mutant *daf-16(mu86)*I; *daf-1*2 *(rh61rh411)*X was then used to generate *daf-16 (mu86)*I; *daf-12 (rh61rh411) muIs71*\[*pKL99(daf-16a::GFP/bKO)*+*pRF4(rol-6)*\]X worms by backcrossing to the original *daf-16 (mu86)*I; *muIs71*\[*pKL99(daf-16a::GFP/bKO)*+*pRF4(rol-6)*\]X. The mutations were identified and verified in a way similar to that used for the double mutant.
### Life span and thermotolerance {#s4a10}
The life span and thermotolerance of worms were investigated according to the method of [@pbio-0020280-Gems1]. Studies with N2 animals were performed on plates containing cholesterol or lophenol at 20 °C. Day 0 corresponded to L4 stage. The life spans of about 300 worms per condition were investigated.
Supporting Information {#s5}
======================
Figure S1
::: {.caption}
###### Comparison of Cholesterol Metabolism in Wild-Type, *daf-12,* and Double Mutant *daf-9 daf-12* Worms
(3.8 MB PDF).
:::
::: {.caption}
######
Click here for additional data file.
:::
Protocol S1
::: {.caption}
###### Regio- and Stereospecific Synthesis of 4α-Substituted 5α-Cholestan-3β-ols
(114 KB DOC).
:::
::: {.caption}
######
Click here for additional data file.
:::
We thank all members of Kurzchalia Lab for many discussions, Gaspare Benennati (TVK lab) for help in gamravali preparation, and Jana Mäntler for technical support. We are indebted to Marcos González-Gaitán for stimulating discussions in the beginning of the project and his comments on the manuscript. We thank Suzanne Eaton for critical reading of the manuscript. We thank the *Caenorhabditis* Genetics Center (T. Stiernagle) for providing several mutant strains and Adam Antebi (Max Planck Institute for Molecular Genetics, Berlin) for the *daf-12* strain. SW was supported by the Alexander von Humboldt Foundation and NIH grant GM 25243. The synthetic part of the project was supported by the Fonds of Chemical Industry.
**Conflicts of interest.** The authors have declared that no conflicts of interest exist.
**Author contributions.** VM, EVE, HJK, and TVK conceived and designed the experiments. VM, EVE, FM, MWB, AWS, SW, and TVK performed the experiments. CT and HJK contributed reagents/materials/analysis tools. SW and TVK wrote the paper.
Academic Editor: Julie Ahringer, University of Cambridge
Citation: Matyash V, Entchev EV, Mende F, Wilsch-Bräuninger M, Thiele C, et al. (2004) Sterol-derived hormone(s) controls entry into diapause in Caenorhabditis elegans by consecutive activation of DAF-12 and DAF-16. PLoS Biol 2(9): e280.
Daf-d
: dauer formation defective
HPLC
: high-performance liquid chromatography
ms
: methylated sterols
nms
: nonmethylated sterols
SDS
: sodium dodecyl sulphate
TLC
: thin-layer chromatography
|
PubMed Central
|
2024-06-05T03:55:47.785391
|
2004-9-21
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517820/",
"journal": "PLoS Biol. 2004 Oct 21; 2(10):e280",
"authors": [
{
"first": "Vitali",
"last": "Matyash"
},
{
"first": "Eugeni V",
"last": "Entchev"
},
{
"first": "Fanny",
"last": "Mende"
},
{
"first": "Michaela",
"last": "Wilsch-Bräuninger"
},
{
"first": "Christoph",
"last": "Thiele"
},
{
"first": "Arndt W",
"last": "Schmidt"
},
{
"first": "Hans-Joachim",
"last": "Knölker"
},
{
"first": "Samuel",
"last": "Ward"
},
{
"first": "Teymuras V",
"last": "Kurzchalia"
}
]
}
|
PMC517821
|
Introduction {#s1}
============
Methanotrophic bacteria such as Methylococcus capsulatus are responsible for the oxidation of biologically generated methane ([@pbio-0020303-Soehngen1]), and they are therefore of great environmental importance in reducing the amount of this greenhouse gas released to the Earth\'s atmosphere. Atmospheric methane levels have been increasing over the last 300 years, and it is thought that this is mostly due to human activity. Methane is a very effective greenhouse gas; it has been estimated that methane contribution to climate change is about 26 times that of carbon dioxide (mole for mole) ([@pbio-0020303-Ehalt1]; [@pbio-0020303-Ehalt2]; [@pbio-0020303-Lelieveld1]). The effect is further amplified by the reduction of hydroxyl radical concentrations due to increasing atmospheric methane levels; these radicals oxidize methane photochemically, thus their loss from the atmosphere increases the persistence of methane ([@pbio-0020303-Lelieveld1]).
Biological methane oxidation is known to occur aerobically in both terrestrial and aquatic habitats, and anaerobically in sediments and anoxic salt water. It acts on methane biologically generated in situ and on methane scavenged from the atmosphere ([Figure 1](#pbio-0020303-g001){ref-type="fig"}). Deep-sea environments such as cold gas seeps and hydrothermal vents exhibit a photosynthesis-independent food chain based on methanotrophs and chemolithotrophs, some of which form symbiotic partnerships with invertebrates (e.g., [@pbio-0020303-Cavanaugh1]). Methanotrophs are also able to metabolize or co-metabolize xenobiotic compounds, including chlorinated solvents such as trichloroethylene, and hence have potential as bioremediation tools ([@pbio-0020303-Large1]).
::: {#pbio-0020303-g001 .fig}
Figure 1
::: {.caption}
###### Global Methane Cycle
Methane is oxidized either photochemically in the atmosphere or biologically in terrestrial and aquatic systems. The ocean, grasslands, and desert form major methane sinks, whereas wetlands, agricultural and grazing lands, and other anthropogenic sources such as landfills, are major sources. The cow depicted in the figure represents diverse ruminants. Anthropogenic inputs of nitrogen in the form of ammonia compete for MMOs, reducing methane oxidation and leading to the formation of nitrous oxide, another greenhouse gas.
:::
:::
Distribution of methanotrophy within the Bacteria is currently thought to be relatively limited, being found so far in only 11 genera of the Proteobacteria. These methanotrophs are classified into two types, based primarily on their phylogenetic relationships but also on differences in their physiology and internal membrane structure. Type I methanotrophs (including *Methylococcus*), which are all members of the Gammaproteobacteria, utilize ribulose monophosphate (RuMP) as the primary pathway for formaldehyde assimilation, whereas those of type II, which are all Alphaproteobacteria, use the serine pathway ([@pbio-0020303-Hanson1]).
M. capsulatus is classified as an obligate methanotroph ([@pbio-0020303-Whittenbury1]); methane is oxidized via methanol to formaldehyde, which is then assimilated into cellular biomass or further oxidized to formate and CO~2~ for energy production. The conversion of methane to biomass by M. capsulatus has been exploited for large-scale commercial production of microbial proteins by fermentation ([@pbio-0020303-Skrede1]).
The powerful tool of whole-genome sequencing has been applied to microorganisms that carry out other important components of the carbon cycle, such as photosynthesis ([@pbio-0020303-Eisen4]; [@pbio-0020303-Dufresne1]) and methanogenesis ([@pbio-0020303-Bult1]; [@pbio-0020303-Smith1]; [@pbio-0020303-Slesarev1]), but there is a paucity of genomic information on the methanotrophs, which are equally important contributors to global carbon cycles. Many insights into methylotrophy have been gained from the recently available partial genome sequence of Methylobacterium extorquens (AM1) ([@pbio-0020303-Chistoserdova2], [@pbio-0020303-Chistoserdova3]), but this organism, like other nonmethanotrophic methylotrophs, is limited to the oxidation of C1 compounds other than methane. We undertook the whole-genome sequencing of M. capsulatus (Bath) to obtain a better understanding of the genomic basis of methanotrophy, a globally important microbial process.
Results/Discussion {#s2}
==================
Genome Properties {#s2a}
-----------------
The genome of M. capsulatus (Bath) comprises a single circular molecule of 3,304,697 bp. General features of the genome and its 3,120 predicted coding sequences (CDSs) are summarized in [Table 1](#pbio-0020303-t001){ref-type="table"}. GC skew ([@pbio-0020303-Lobry1]) and oligoskew ([@pbio-0020303-Salzberg2]) analyses were used to identify a putative origin of replication, and basepair 1 was assigned upstream of the glucose-inhibited division protein A*(gidA)* gene(MCA0001), adjacent to the chromosome-partitioning proteins encoded by *gidB, parA,* and *parB* and the operon that encodes F~1~F~0~ ATP synthase.
::: {#pbio-0020303-t001 .table-wrap}
Table 1
::: {.caption}
###### General Features of the M. capsulatus (Bath) Genome
:::
EUS, enzymes of unknown specificity
:::
The M. capsulatus (Bath) genome contains 51 identifiable insertion sequence elements from various families ([@pbio-0020303-Chandler1]). As is found in other sequenced bacterial genomes, many of these elements share higher intra- than intergenome similarity. This suggests several possible mechanisms: expansion of these elements since their introduction into the M. capsulatus (Bath) genome, repeated cycles of duplication and subsequent deletion, or gene conversion. Twenty elements belonging to the IS4 family of insertion sequences ([@pbio-0020303-Chandler1]) encode a 366-amino-acid transposase with 100% amino acid sequence conservation between copies. One copy (MCA1197) is found within the soluble methane monooxygenase (sMMO) operon, although not in all sequenced clones, suggesting that this element is highly mobile. Other examples of insertion of this element include disrupted genes encoding tRNA pseudouridine synthase (split into two putative CDS---MCA1311 and MCA1313) and an exopolysaccharide export protein (split into MCA1176 and MCA1178).
Two putative prophages (one of approximately 58.5 Kbp, spanning from MCA2632 to MCA2689 and the other, a Mu-phage-like element of approximately 45 Kbp spanning from MCA2900 to MCA2959) were identified in the genome. The Mu-like prophage is unusual in encoding an intein within F (Mu gp30), a cofactor in head assembly. This intein region is most similar to inteins present in several archaeal translation initiation factor IF-2 sequences from the genera *Pyroccocus* and *Methanococcus,* sharing 41% sequence identity and 62% sequence similarity with the Pyrococcus horikoshii intein. The intein lacks a recognizable endonuclease sequence and appears degenerate compared to the archaeal IF-2 intein, casting doubt on its ability to be mobile. If functional, the presence of the intein in this protein suggests that head morphogenesis could be regulated by conditions that influence the rate of intein excision. Another intein sharing sequence similarity with archaeal inteins was identified in the gene encoding ribonucleotide reductase (MCA2543). Inteins are rare, but when present are often found in genes associated with nucleotide metabolism, such as ribonucleotide reductases.
Bacteriophages have been important tools for genetic manipulation of bacterial genomes, and such tools are currently lacking for M. capsulatus (Bath). The M. capsulatus (Bath) Mu-like prophage could be engineered to resemble the Mu derivatives, which have been excellent tools for random mutagenesis in other species ([@pbio-0020303-Casadaban1]). Conditional protein splicing via inteins is used as a tool for protein engineering, drug therapy, and vaccine development ([@pbio-0020303-Humphries1]; [@pbio-0020303-Mootz1]; [@pbio-0020303-Nyanguile1]). The putative inteins could be designed as a tool either for generating protein material for vaccination of salmon (or other animals feeding on M. capsulatus proteins) or for manipulating M. capsulatus live vaccine vectors.
Metabolism and Transport: Genomic Basis of the Methanotrophic Lifestyle {#s2b}
-----------------------------------------------------------------------
We have attempted to predict central metabolic pathways in M. capsulatus (Bath), including the methane oxidation pathway, mechanisms for carbon fixation, glycolytic and gluconeogenic conversions, and the tricarboxylic acid (TCA) cycle, from analysis of the genome data. These pathways, together with those known from previous studies, are depicted in [Figure 2](#pbio-0020303-g002){ref-type="fig"}, along with the locus numbers for predicted enzymes. Some of these pathways have not been experimentally verified, so we present [Figure 2](#pbio-0020303-g002){ref-type="fig"} as a hypothesis of metabolic activity in M. capsulatus (Bath) that is based on available genome data.
::: {#pbio-0020303-g002 .fig}
Figure 2
::: {.caption}
###### Predicted Central Metabolic Pathways of M. capsulatus
Genomic information was used to predict the flow of carbon from methanotrophy pathways into carbon fixation pathways, and thence into glycolysis/gluconeogenesis and the TCA cycle. Locus names are indicated next to key steps. Some intermediates are omitted.
:::
:::
### Methane oxidation {#s2b1}
Methanotrophs are unique in their possession of methane monooxygenases (MMOs), which catalyze the first step of methane oxidation ([Figure 2](#pbio-0020303-g002){ref-type="fig"}). M. capsulatus is known to possess both a particulate membrane-bound form, pMMO (detected by centrifugation studies and encoded by *pmo*), and a soluble form, sMMO (encoded by *mmo*), and these enzymes have been extensively studied ([@pbio-0020303-Murrell1]; [@pbio-0020303-Nguyen1]; [@pbio-0020303-Stolyar1]; [@pbio-0020303-Coufal1]; [@pbio-0020303-Murrell3], [@pbio-0020303-Murrell4]; [@pbio-0020303-Whittington1]). The pMMO was previously known to consist of three subunits encoded by *pmoCAB* ([@pbio-0020303-Zahn1]); two complete copies of *pmoCAB* and a third copy of *pmoC (pmoC3)* were previously identified ([@pbio-0020303-Stolyar1]). Our genomic analysis suggests the pMMO genes have been recently duplicated ([Table 2](#pbio-0020303-t002){ref-type="table"}). The *pmoC3* gene is located in a putative operon with three additional genes of unknown function, and we can speculate that these three are also related to methane oxidation.
::: {#pbio-0020303-t002 .table-wrap}
Table 2
::: {.caption}
###### Selected Putative Lineage-Specific Gene Duplications in M. capsulatus (Bath)
:::
These genes were identified as those encoding proteins with better BLASTP matches to other proteins in M. capsulatus than to all other complete genomes
:::
Only one chromosomal locus for the components of sMMO was identified (*mmoXYB--*transposase*--mmoZDC--*hypothetical protein*--mmoGQSR* \[MCA1194--1205\]). The transposase (MCA1197) is oriented in the same direction as the *mmo* genes and, thus, may be transcribed under sMMO-promoting growth conditions. The functions of these sMMO components have been previously determined ([@pbio-0020303-Stainthorpe1]; [@pbio-0020303-Nielsen1]; [@pbio-0020303-Coufal1]; [@pbio-0020303-Merkx1]; [@pbio-0020303-Csaki2]).
### Methanol oxidation {#s2b2}
Methanol is available to M. capsulatus from the oxidation of methane and presumably also from exogenous sources (e.g., pectin and lignin degradation) ([@pbio-0020303-Hanson1]), and its oxidation is catalyzed by methanol dehydrogenases ([@pbio-0020303-Anthony1]). We have detected three sets of genes encoding homologs of the structural components of methanol dehydrogenase (homologs of MxaF and MxaI) and the proteins required for its catalytic function *(*homologs of MxaJGRACKLD*)* ([Figure 2](#pbio-0020303-g002){ref-type="fig"}). There is one large cluster of genes (MCA0779--0790) including homologs of *mxaFJGIRACKLD,* which probably encodes a heterodimeric methanol dehydrogenase, as is found in other methylotrophs ([@pbio-0020303-Amaratunga1], [@pbio-0020303-Amaratunga2]). Also like other methylotrophs, M. capsulatus (Bath) contains a second methanol dehydrogenase--like cluster, *mxaFJ,* (MCA0299--0300) lacking a homolog of *mxaI* that normally encodes the small subunit of methanol dehydrogenase. The function of *mxaJ* is unknown, and it is not clear whether this *mxaFJ* cluster encodes components active in methanol oxidation. There is a third cluster of genes required for methanol dehydrogenase synthesis, *mxaACKL* (MCA1527--1530).
### Formaldehyde and formate oxidation {#s2b3}
Formaldehyde is the substrate for carbon fixation through the RuMP pathway in M. capsulatus ([@pbio-0020303-Attwood1]) and thus is an important intermediate in both catabolism and anabolism ([Figure 2](#pbio-0020303-g002){ref-type="fig"}). However, formaldehyde is also highly toxic, and the cell needs to tightly control its production ([@pbio-0020303-Attwood1]). We were able to compare the results of genomic analysis with previously reported pathways for formaldehyde oxidation in M. capsulatus. A membrane-bound pyrroloquinoline quinine protein is known to be the major formaldehyde dehydrogenase under high-copper growth conditions, while a soluble NAD(P)^+^-linked formaldehyde dehydrogenase is active when copper concentrations are low ([@pbio-0020303-Zahn2]). Other previously characterized formaldehyde oxidation pathways in M. capsulatus include the cyclic pathway that uses enzymes of the RuMP pathway ([@pbio-0020303-Strom1]), and the tetrahydromethanopterin (THMPT)-linked pathway ([@pbio-0020303-Vorholt1]).
Genome analysis showed the previously determined N-terminal sequence of the pyrroloquinoline quinine--containing formaldehyde dehydrogenase ([@pbio-0020303-Zahn2]) to match MCA2155, a protein resembling a sulfide-quinone reductase (SQR), on the basis of both its motifs and its phylogenetic relationship to other SQRs. [@pbio-0020303-Zahn2] reported homology of their N-terminal sequenced enzyme with SQRs from other bacteria, but were unable to obtain experimental evidence for quinone reductase activity. In the absence of this evidence, we have annotated the gene as a formaldehyde dehydrogenase.
We found that the previously sequenced 63-kDa subunit of NAD(P)^+^-linked formaldehyde dehydrogenase ([@pbio-0020303-Tate1]) best matches the N-terminal of the large subunit of methanol dehydrogenase (MCA0779), although the sequences differ slightly. The sequence of modifin, the 8.6-kDa subunit thought to confer substrate specificity to the enzyme ([@pbio-0020303-Stirling1]; [@pbio-0020303-Tate1]), could not be clearly identified in the genome. A recent paper ([@pbio-0020303-Adeosun1]) helps resolve this conflict between the genome and these previous results; apparently the NAD(P)^+^-linked activity is due to an artefactual mixture of methanol dehydrogenase and methylene dehydrogenase.
We also identified components of the RuMP (Entner-Douderoff pathway)-linked and THMPT-linked pathways of formaldehyde oxidation ([Figure 2](#pbio-0020303-g002){ref-type="fig"}). In addition to the formaldehyde oxidation systems described above, genome analysis suggests an additional complete tetrahydrofolate (THF)-linked pathway ([Figure 2](#pbio-0020303-g002){ref-type="fig"}) previously undescribed in *M. capsulatus,* as was recently found alongside the THMPT pathway in M. extorquens ([@pbio-0020303-Vorholt1]; [@pbio-0020303-Chistoserdova2]). In M. extorquens, the THF pathway is thought to play a role in assimilation of carbon from both formaldehyde and formate, while THMPT is involved in catabolic oxidation of formaldehyde to formate using the same enzymes used for methanogenesis; free formaldehyde is thought to be the substrate for hexulose-6-phosphate synthase in the RuMP pathway ([@pbio-0020303-Strom1]; [@pbio-0020303-Vorholt1]). M. capsulatus possesses homologs to genes encoding proteins in all of these pathways; therefore, it may have the capability to assimilate/detoxify formaldehyde in the same way.
We have identified three previously undescribed homologs of formate dehydrogenases (MCA2576--2577, MCA1208--1210, and MCA1391--1393). Multiple formate dehydrogenases occur in other bacteria ([@pbio-0020303-Sawers1]; [@pbio-0020303-Chistoserdova3]); in *M. extorquens,* all three are expendable, indicating that this last step in methane oxidation plays a minor role and that formate can be dissimilated in other ways ([@pbio-0020303-Chistoserdova3]). The importance of the formate dehydrogenases in M. capsulatus remains to be determined.
The genomic redundancy in the set of methane oxidation pathways suggests that M. capsulatus exploits different systems under variable environmental conditions (e.g., copper levels). It is plausible that M. capsulatus balances its requirement for formaldehyde-derived carbon and reducing power with the toxicity of formaldehyde by taking advantage of three enzymes for formate oxidation and multiple pathways for formaldehyde oxidation under different environmental conditions. This redundancy has implications for future attempts to manipulate the genes of this pathway; simple knockouts may not be achievable.
### Carbon fixation {#s2b4}
M. capsulatus is known to assimilate formaldehyde through the RuMP pathway ([@pbio-0020303-Strom1]) ([Figure 2](#pbio-0020303-g002){ref-type="fig"}). Genomic analysis suggests that RuMP components have experienced a lineage-specific duplication ([Table 2](#pbio-0020303-t002){ref-type="table"}); there is a 5,267-bp identical direct repeat centered around the transaldolase gene that contains the genes for hexulose-6-phosphate isomerase*,* hexulose-6-phosphate synthase*,* fructose-1,6-phosphate aldolase*,* and transketolase*.* There is evidence that the RuMP pathway is also used for gluconeogenesis (see below); this dual function may have been facilitated by the redundancy resulting from this tandem duplication. The M. capsulatus (Bath) genome appears to contain some parts of the alternative serine pathway of formaldehyde assimilation ([Figure 2](#pbio-0020303-g002){ref-type="fig"}), including a candidate for the key serine cycle enzyme malyl-CoA lyase (MCA1739). Activities associated with this pathway have been reported as "sometimes" present ([@pbio-0020303-Hanson1]). However, the majority of enzymes with a putative role in the serine cycle also have putative roles in other metabolic pathways (e.g., there are candidate genes encoding proteins that may be able convert malate to malyl-CoA---MCA1740--1741 are similar to the two subunits of malate Co-A ligase from M. extorquens \[[@pbio-0020303-Chistoserdova1]\] but are also similar to the two subunits of succinyl Co-A synthases). In addition, the genome apparently lacks any good candidates for other steps in the serine cycle such as the conversion of phosphoenolpyruvate to oxaloacetate (i.e., phosphoenolpyruvate carboxylase). The latter enzyme may be circumvented by a likely oxaloacetate decarboxylase (MCA2479--2481), which converts pyruvate to oxaloacetate ([Figure 2](#pbio-0020303-g002){ref-type="fig"}). It is possible that M. capsulatus fixes formaldehyde through the serine cycle as far as oxaloacetate ([Figure 2](#pbio-0020303-g002){ref-type="fig"}).
It appears that the Calvin cycle operates with transketolase (MCA3040 and MCA3046), reversibly converting glyceraldehyde-3-phosphate to xylulose-5-phosphate, bypassing the typical ribose-5-phosphate to fructose-6-phosphate segment ([Figure 2](#pbio-0020303-g002){ref-type="fig"}); cell suspensions of M. capsulatus grown on methane do not exhibit seduheptulose-1,7-bisphosphatase activity ([@pbio-0020303-Strom1]), and a gene encoding this enzyme was not identified in the genome sequence.
### Redundancy in serine and glycogen biosynthesis pathways {#s2b5}
Serine is an important intermediate in M. capsulatus metabolism, and genomic evidence suggests three potential pathways for serine synthesis not previously described in *M. capsulatus:* a phosphorylated pathway from glycerate-3-phosphate, a nonphosphorylated pathway from glycerate, and a nonphosphorylated pathway from glycolate-2-phosphate ([@pbio-0020303-Ho1]) ([Figure 2](#pbio-0020303-g002){ref-type="fig"}).
Homologs of genes encoding enzymes predicted to catalyze the three steps in the phosphorylated pathway (3-phosphoglycerate dehydrogenase, phosphoserine aminotransferase, and phosphoserine phosphatase) are present, but the latter two may have alternate functions in vitamin B6 biosynthesis ([@pbio-0020303-Lam1]) or as homoserine kinases. Genes normally encoding homoserine kinases *(thrB* and *thrH)* were not identified in the M. capsulatus (Bath) genome, and phosphoserine phosphatase may perform this function as described in Pseudomonas aeruginosa ([@pbio-0020303-Patte1]).
The nonphosphorylated pathway is not well characterized at the molecular level, but it is known to be initialized by the dephosphorylation of phosphoglycerate to glycerate ([@pbio-0020303-Ho1]); subsequently, glycerate is oxidized to hydroxypyruvate and hydroxypyruvate is transaminated to serine ([Figure 2](#pbio-0020303-g002){ref-type="fig"}). The genome encodes a homolog of glycerate kinase, a 2-hydroxyacid dehydrogenase that may function as a hydroxypyruvate reductase, and a serine-glyoxylate aminotransferase, which may also have serine-pyruvate transaminase activity. Genes encoding these three enzymes appear to be organized in an operon (MCA1406--1408), supporting their proposed roles in serine formation from phosphoglycerate. The M. capsulatus (Bath) genome also encodes a putative phosphoglycerate mutase (MCA0753), to interconvert 3- and 2-phosphoglycerate ([Figure 2](#pbio-0020303-g002){ref-type="fig"}), allowing the organism to carry out either the phosphorylated or nonphosphorylated pathway.
In the third pathway, M. capsulatus may derive glycolate-2-phosphate from the oxygenation reaction of ribulose bisphosphate carboxylase (MCA2743--2744, previously identified by [@pbio-0020303-Baxter1]), convert it to glycine, which is split into carbon dioxide, ammonia, and methylene-tetrahydrofolate ([Figure 2](#pbio-0020303-g002){ref-type="fig"}). A second glycine molecule and methylene-tetrahydrofolate ligate to form serine. There is experimental evidence ([@pbio-0020303-Taylor1]) for this pathway of glycolate-2-phosphate assimilation, which resembles that of plants.
### Evidence for novel gluconeogenesis pathways and a complete TCA cycle {#s2b6}
A key enzyme in gluconeogenesis is fructose-1,6-bisphosphatase, which catalyzes the irreversible dephosphorylation of fructose-1,6-phosphate to fructose-6-phosphate; genes encoding this enzyme are absent. However, there are three potential alternative pathways for gluconeogenesis, previously unknown in this organism ([Figure 2](#pbio-0020303-g002){ref-type="fig"}). First, there is a transaldolase homolog (MCA3045) that may convert glyceraldehyde-3-phosphate directly to fructose-6-phosphate. Second, there is a putative phosphoketolase (MCA1587), which can condense pyruvate and glyceraldehyde-3-phosphate into xylulose-5-phosphate, which in turn is fed into the ribulose-5-phosphate pool for eventual formation of glucose-6-phosphate through the pentose phosphate pathway. Third, hydrolysis of fructose-1,6-bisphosphate to fructose-6-phosphate by a pyrophosphate-dependent 6-phosphofructokinase and a pyrophosphatase may occur, as was recently proposed in *Nitrosomonas* ([@pbio-0020303-Chain1]).
An incomplete TCA cycle lacking 2-oxoglutarate dehydrogenase activity has been found in nearly all type I methanotrophs, including M. capsulatus ([@pbio-0020303-Hanson1]). However, genes encoding homologs of 2-oxoglutarate dehydrogenase are present (MCA1952 and MCA1953). Thus, a complete TCA-cycle might operate in M. capsulatus, not under methane oxidation, but under other conditions. Lack of experimental evidence precludes speculation as to the nature of these conditions; however, catabolite repression ([@pbio-0020303-Wood1]) may play a role here. Another type I methylotroph, *Methylomonas* sp. (761), uses a complete TCA cycle to grow on glucose as its sole carbon and energy source ([@pbio-0020303-Zhao1]); M. capsulatus may utilize the same mechanism as carbon is stored as glycogen. Consistent with its autotrophic lifestyle, M. capsulatus possesses only a limited array of membrane transporters for organic carbon compounds. However, although M. capsulatus is not known to utilize any sugars (although in the Texas strain they have been reported to support growth), one complete (MCA1941--1944) and one partial (MCA1924) ATP-binding casette (ABC) family transporter with predicted specificity for sugar uptake were identified. Additionally, components of transporters for peptides (MCA1264 and MCA1268), carboxylates (MCA1872), and a variety of amino acids (e.g., MCA0840) are present.
### Diversity of nitrogen metabolism {#s2b7}
M. capsulatus (Bath) is able to fix atmospheric nitrogen ([@pbio-0020303-Murrell2]), conferring an advantage in environments where fixed nitrogen is limiting, and the structural genes for nitrogenase *(nifH, nifD,* and *nifK)* were previously shown to be contiguous ([@pbio-0020303-Oakley1]), as they are in other nitrogen fixers. Genome analysis extends this contiguous region to include the genes *nifE, nifN,* and *nifX,* which are involved in synthesis of the nitrogenase iron-molybdenum cofactor (MCA0229--0239); this organization has been found in Chlorobium tepidum and some nitrogen-fixing methanogenic Archaea. Two 2Fe-2S ferredoxins (MCA0232 and MCA0238) and two genes identified as conserved hypotheticals (MCA0236--0237) are interspersed with the *nif* genes in the same orientation. The conserved hypothetical genes share the highest sequence similarity with genes from other organisms capable of nitrogen fixation, suggesting that they also have a role in this process.
M. capsulatus exhibits considerable versatility in its combined nitrogen conversions, including nitrification and denitrification. Ammonia is oxidized to nitrite by both pMMO and sMMO because of their lack of substrate specificity ([@pbio-0020303-Colby1]; [@pbio-0020303-Dalton1]); the absence of a separate ammonia monooxygenase, and the redundancy of MMOs, suggests that the MMOs are the sole nitrification enzymes active in M. capsulatus. Four predicted ammonium transporters were identified (MCA0268, MCA0490, MCA1581, and MCA2136), suggesting that ammonium is an important nitrogen source for M. capsulatus. Methane oxidation is inhibited by the presence of ammonia and ammonia oxidation is inhibited by methane ([@pbio-0020303-Whittenbury1]), and input of ammonia to wetland systems (e.g., through fertilizer runoff) may have significant effects on the consumption of biogenic methane by methanotrophs in these systems. It is also interesting to note that, in general, ammonia oxidation produces small amounts of nitrous oxide, which is also a greenhouse gas.
### Electron transport complement suggests unexpected metabolic flexibility {#s2b8}
The M. capsulatus (Bath) genome has a relatively large complement of putative c-type cytochromes; 57 proteins containing a heme-binding motif were identified, and 23 of these contain two or more heme-binding motifs. Analysis of the genome reveals electron transport components previously known to be associated with the methane oxidation pathway, such as cytochrome C~L~ (MCA0781), a specific electron acceptor for methanol dehydrogenase. Other novel electron transport components are encoded in several physical locations on the chromosome; there is genomic evidence for chemolithotrophy and the ability to live at a variety of oxygen tensions.
The genome encodes three predicted hydrogenases: (a) a multisubunit formate hydrogenlyase (MCA1137--1142), most likely involved in the conversion of formate to dihydrogen and carbon dioxide; (b) a soluble cytoplasmic NAD-reducing hydrogenase (MCA2724--2726), which transfers electrons to NAD^+^; and (c) a membrane-bound Ni-Fe hydrogenase (MCA0163--0165). Activity of two hydrogenases (one soluble and one membrane-bound), and the role of molecular hydrogen in driving MMOs, was previously reported ([@pbio-0020303-Hanczar1]). The membrane-bound Ni-Fe hydrogenase was previously sequenced ([@pbio-0020303-Csaki1]). The presence of these two hydrogenases suggests that M. capsulatus is able to capture and oxidize hydrogen that is generated either exogenously or as a by-product of the ATP-dependent reaction of nitrogenase, and recycle it into the electron transport chain. Microorganisms that undergo fermentative metabolism are likely to be encountered in the habitat of M. capsulatus (e.g., soils) and could supply exogenous hydrogen for chemolithotrophic oxidation. The removal of this hydrogen by M. capsulatus metabolism may aid in driving these reactions forward and hence constitute a syntrophic partnership.
Nitrogen fixation requires reducing power, which in aerobes can be supplied by reduced flavodoxin or ferredoxins. There is one candidate flavodoxin present (MCA1697) in the M. capsulatus (Bath) genome; however, two ferredoxins (MCA0238 and MCA0232) physically located within a cluster of genes encoding proteins involved in nitrogen fixation (see Nitrogen Metabolism section above) more likely serve in this capacity. In aerobes, these carriers are usually reduced by NADH/NADPH, although reverse electron transport could be involved in this organism.
The M. capsulatus (Bath) genome encodes homologs of a two-subunit high oxygen-affinity cytochrome d (MCA1105 and MCA1106), which suggests the ability to live under microaerophilic conditions. This evidence for life at low oxygen tensions is supported by the presence of enzymes indicative of fermentative activity ([Table 3](#pbio-0020303-t003){ref-type="table"}). Further support for anaerobiosis is provided by a putative large c-type cytochrome (MCA2189) that contains 17 heme groups and is located adjacent to several hypothetical proteins, including an oxidoreductase and an alkaline phosphatase important to the central metabolism of phosphorous compounds. This cytochrome has significant matches only to high molecular-weight cytochromes in the metal-ion reducers *Shewanella oneidensis, Desulfovibrio vulgaris,* and *Geobacter sulfurreducens,* suggesting that M. capsulatus may have the ability to undergo metabolism at a lower redox potential than previously known. This large protein is most likely localized in the periplasm, as indicated by its signal peptide. The ability to oxidize methane under reduced oxygen tensions would provide an advantage to M. capsulatus in allowing it to be physically closer to environments in which methane is biologically generated.
::: {#pbio-0020303-t003 .table-wrap}
Table 3
::: {.caption}
###### Putative Enzymes Associated with Fermentation
:::
:::
The M. capsulatus (Bath) genome includes a region of approximately 25 kb (MCA0421--0443) encoding novel proteins related to energy metabolism (c-type cytochromes, a c-type cytochrome biogenesis protein, a novel gene possessing a flavodoxin domain, two proteins that may be involved in heme transport, and an undescribed Fe-S binding protein) and hypothetical proteins. The same 25-kb region contains six multiheme c-type cytochromes that are members of the cytochrome c~553o~ family. This previously described family is unique to M. capsulatus (Bath); genome analysis has widened our knowledge of this family from three ([@pbio-0020303-Bergmann1]) to six members (MCA0338, MCA0421, MCA0423, MCA0424, MCA2259, and MCA2160). The redundancy in cytochrome c~553o~ proteins suggests a more complex and plastic electron transport capability than previously known.
A novel monoheme c-type cytochrome (MCA1187) has eight transmembrane-spanning regions and is located near another c-type cytochrome and a proton-translocating pyrophosphatase (a transmembrane-spanning protein pump important in establishing electrochemical gradients). This configuration suggests that the monoheme protein has a role in ATP production via chemiosmosis. Two other monoheme CDSs (MCA2188 and MCA2196) are members of a paralogous family similar to a cytochrome found in *G. sulfurreducens;* one has a signal for twin arginine transport (for export from the cytoplasm) and the second a signature for fumarate lyase. The genome also encodes homologs to the putidaredoxin family of ferredoxins.
### Genomic evidence for anaerobic synthesis of unique fatty acids {#s2b9}
The membrane phospholipids of methanotrophs are unique, with mono-unsaturated fatty acids consisting of a series of even- and odd-numbered positional isomers of both the *cis* and *trans* configuration ([@pbio-0020303-Makula1]). Our analysis supports the existence of an anaerobic mechanism for unsaturated fatty acid synthesis in *M. capsulatus,* as proposed by [@pbio-0020303-Jahnke2] on the basis of biochemical data*.* A predicted enzyme 3-hydroxydecanoyl-ACP-dehydratase (MCA2878) appears to catalyze an alternative dehydratase reaction at the C~10~ level of fatty acid synthesis, followed by a synthase reaction carried out by 3-oxoacyl-acyl carrier protein (ACP) synthase (MCA2879), resulting in *cis*-vaccenate (18:1, *cis*-Δ11). *Trans*-unsaturated acids are obtained by isomerization of preformed *cis*-unsaturated fatty acids, to control membrane fluidity; putative fatty acid *cis*/*trans*-isomerases were identified in the genome (MCA1585 and MCA1806)*.*
### Sterol and hopanoid biosynthesis: evidence for the mevalonate-independent pathway {#s2b10}
M. capsulatus is one of only a few prokaryotes known to synthesize sterols de novo ([@pbio-0020303-Bird1]), and it is thought that they have a role in maintaining membrane fluidity in response to changes in environmental temperature ([@pbio-0020303-Jahnke1]). The main cholesterols in M. capsulatus (Bath) are methylated; genome analysis indicated four putative proteins involved in the conversion of squalene to 4,4-dimethylcholest-8(14)-en-3β-ol (MCA2872, MCA2873, MCA2711, and MCA1404).
Squalene is also a precursor for hopanoid synthesis ([Figure 2](#pbio-0020303-g002){ref-type="fig"}); homologs of squalene hopene cyclase, squalene synthase, and other enzymes leading to hopanoid synthesis were identified (MCA0812, MCA0813, and MCA2873). Acetyl-CoA is usually the starting point for synthesis of hopanoids and sterols. However, with the exception of the final step catalyzed by geranyl-*trans*-transferase, the mechanism for converting acetyl-CoA to squalene (the first major intermediate) is not apparent from genome analysis. Instead, M. capsulatus (Bath) contains genes for the alternative mevalonate-independent pathway from glyceraldehyde-3-phosphate and pyruvate (MCA0817, MCA0573, MCA1055, and MCA2518), so it is possible that the organism employs the same squalene synthesis pathway found in plants and many Gram-negative bacteria ([@pbio-0020303-Rohdich1]).
Environmental Sensing, Response, and Survival {#s2c}
---------------------------------------------
### Copper homeostasis, scavenging, and transport. {#s2c1}
Copper is known to be important in the regulation of MMO activity; high copper concentrations are essential for the formation of extensive intracytoplasmic membranes and pMMO activity, and copper is thought to play an active role in both the catalytic site and the electron transport chain ([@pbio-0020303-Nguyen2]; [@pbio-0020303-Semrau1]; [@pbio-0020303-Basu1]). In contrast, sMMO activity is inhibited by copper; synthesis of sMMO may allow methanotrophs to survive in copper-limited environments where pMMO cannot be active. Two distinct copper transporting systems have been identified in other bacteria, a P-type ATPase (the Cop system) and a resistance/nodulation/cell division (RND)-type copper ion efflux complex (the Cus complex) ([@pbio-0020303-Petersen1]; [@pbio-0020303-Rensing1]; [@pbio-0020303-Franke1]). Analysis of the M. capsulatus (Bath) genome reveals several elements that may relate to processing of copper.
The genome encodes a putative nonribosomal peptide synthetase (NRPS) that may scavenge copper; another methylotrophic bacterium *(Methylosinus)* is known to excrete copper-binding compounds ([@pbio-0020303-DiSpirito1]; [@pbio-0020303-Tellez1]). The NRPS comprises a starting module (MCA2107) containing an adenylation domain (probably recognizing a 5-hydroxy ornithine residue or another derivative of ornithine), a thiolation domain, and an unusual acetyltransferase domain. The starting module may interact with a second module (MCA1883) that contains a condensation domain and a terminal thioesterase needed for peptide release, leading to synthesis of a heavily charged peptide that could be involved in binding/scavenging of copper or other metals.
A single polyketide synthase gene (PKS) (MCA1238) is found adjacent to a gene encoding a sensor protein with diguanylate cyclase and diguanylate phosphodiesterase activities (MCA1237), often found in environmental sensing proteins and H^+^/heavy metal cation antiporters. The two-module and six-domain organization of this PKS is atypical; it contains domains with unknown functions, and its role is difficult to predict. A cation membrane transport system (MCA1900, MCA1907, MCA1911, and MCA1915) is located near the NRPS, and the 4′-phosphopantetheinyl transferase needed for activation of both PKS and NRPS is also present (MCA1522), indicating that these multimodular enzymes may be active.
M. capsulatus (Bath) has a large repertoire of 12 P-type cation ATPases, including multiple predicted copper ion pumps, which correlates with the role of copper in regulation of methane oxidation in this organism. There are also 18 resistance/nodulation/cell division--type metal ion and drug efflux pumps; the large number of these pumps, together with a variety of other metal cation uptake and efflux systems, highlight the significance of metal ion homeostasis in M. capsulatus.
The genome encodes three homologs (MCA0705, MCA0805, and MCA2072) of P-type ATPases with the characteristic copper-binding P-type ATPase motif ([@pbio-0020303-Solioz1]), which makes them likely to function like CopAs from other species. In Escherichia coli, CopA is regulated together with CueO, a multicopper oxidase, by CueR, a member of the MerR-family transcription regulators. No evidence for a CueR homolog was found, indicating a different mechanism of regulation of the *copA* and *cueO* genes in M. capsulatus. The genome encodes one potential *cusCBA* gene cluster (MCA2262--2264), with the *cusA* candidate (encoding the central transport protein CusA) having the same copper-binding and transport motif found in the E. coli gene. No indication of homologs of the CusF periplasmic copper chaperone was found. However, it is interesting to note that the *cusB* candidate (which encodes the CusB outer membrane protein) carries the metal-binding motif typically found in CusF, suggesting that the putative CusB may have a dual function as CusF. No evidence for the CusRS two-component response system regulating the *E. coli cusCFBA* operon was found in M. capsulatus (Bath).
In summary, there are elements of previously studied copper transport and regulation systems in the genome of M. capsulatus (Bath); the lack of the same full complement of genes and identifiable regulators raises questions about the exact operation of copper regulation and suggests future experiments to resolve this central mechanism.
### Possible pathways for capsule biosynthesis. {#s2c2}
As evidenced by its specific epithet, M. capsulatus possesses an insoluble polysaccharide capsule ([@pbio-0020303-Whittenbury1]), the composition of which has not previously been determined. Genome analysis reveals several possible pathways for the synthesis of capsular material, including colanic acid and alginate. The former includes putative colanic acid biosynthesis glycosyl transferases (MCA2124 and MCA1168), the DnaJ-like protein DjlA (MCA0020), which interacts with DnaK to stimulate colanic acid capsule synthesis ([@pbio-0020303-Genevaux1]), and guanine diphosphate-mannose 4,6-dehydratase (MCA1146). Also present are *rfb* genes involved in the synthesis of O antigen; O antigen can serve as capsular material, but given its additional role in lipopolysaccharide synthesis, this cannot be determined with certainty. Colanic acid is generally not produced at temperatures higher than 30 °C in E. coli ([@pbio-0020303-Whitfield1]), so alginate and O antigen may constitute capsular material at the higher growth temperatures favored by *M. capsulatus. M. capsulatus* (Bath) is somewhat desiccation resistant ([@pbio-0020303-Whittenbury1]), and there is evidence that desert soil methanotrophs can survive long periods of water deprivation ([@pbio-0020303-Striegel1]); capsule biosynthesis may aid in this.
### Primitive pathway for asparaginyl- and glutaminyl-tRNA synthesis. {#s2c3}
In common with the genomes of Archaea and some Bacteria, the M. capsulatus (Bath) genome lacks genes for asparaginyl-tRNA synthetase and glutaminyl-tRNA synthetase. However, a heterotrimeric glutamyl-tRNA amidotransferase (MCA0097--0099) is present, suggesting that a single amidotransferase forms asparaginyl-tRNA and glutaminyl-tRNA by transamidation of mischarged aspartyl-tRNA or glutamyl-tRNA, as found previously in many Gram-positive and some Gram-negative bacteria, archaea, and eukaryal organelles ([@pbio-0020303-Ibba1]; [@pbio-0020303-Curnow2]; [@pbio-0020303-Becker1]; [@pbio-0020303-Raczniak1]; [@pbio-0020303-Salazar1]). This indirect transamidation pathway has been proposed as the more ancient route to Gln-tRNA^Gln^ formation ([@pbio-0020303-Curnow1]), because glutamine is thought to be among the last amino acids to be added to the current repertoire of 20 amino acids. It has also been suggested that when this indirect transamidation pathway is the primary source of Gln-tRNA^Gln^ within the cell, it acts as a regulatory mechanism for glutamine metabolism ([@pbio-0020303-Curnow1]).
Evidence for Evolution of Genomic Novelty {#s2d}
-----------------------------------------
### Genomic redundancy. {#s2d1}
The genome of M. capsulatus (Bath) exhibits redundancy in many pathways, as described in more detail in the relevant sections above. The redundant genes fall into two categories. The first category comprises those that appear to be lineage-specific duplications (see [Table 2](#pbio-0020303-t002){ref-type="table"}), identified as genes encoding proteins with better BLASTP matches to other proteins in M. capsulatus (Bath) than to all other complete genomes. In some cases, these genes are found adjacent to each other in the genome, implying that they may have been generated by a tandem duplication, and that they may be transient (tandem arrays are prone to deletion). Other lineage-specific duplications, including those of many genes encoding hypothetical and conserved hypothetical proteins, may not simply be transient mutations and may instead have been maintained because they confer an evolutionary advantage on the organism. The second category contains redundant genes that do not appear to be recently duplicated, and are evolutionarily divergent, suggesting ancient duplications or exogenous acquisition. The divergent phylogeny of these genes is inconsistent with ancient duplication and subsequent vertical transmission, but we cannot determine the origin, direction, and exact path of a possible lateral transfer. Past exchange of genetic material between a methanogen and a methanotroph ancestral to *M. capsulatus,* whether direct or indirect, is certainly plausible, given their biochemical dependency. The presence of both categories of redundancy for a given enzyme or pathway makes it more plausible that the enzyme or pathway is functionally important and that its redundancy is advantageous to the organism.
*M. capsulatus,* like some other bacteria ([@pbio-0020303-Karunakaran1]), contains multiple copies of the chaperonins GroES and GroEL (see [Table 2](#pbio-0020303-t002){ref-type="table"}) that appear to be recent duplications. The two GroEL genes found in an operon structure with GroES share more sequence similarity with each other than either does to the third distal GroEL. MCA1202 is part of the *mmo* operon and was previously identified as a GroEL ([@pbio-0020303-Csaki2]).
The genome also contains two sets of ATP synthase genes, as has been found in four other completed genomes (*Chlorobium tepidum, Pirellula* \[1\], and two *Listeria* spp.), one of which is located at the putative origin of replication. Only one of these genes, that encoding the ATP synthase F~1~ epsilon subunit, appears to be recently duplicated (see [Table 2](#pbio-0020303-t002){ref-type="table"}), and has not been reported to be present in more than one copy in other genomes. This subunit is thought to regulate the H^+^/ATP ratio ([@pbio-0020303-Jones1]); it is possible that M. capsulatus alters the H^+^/ATP ratio by two different ATP synthases depending on its growth substrate (methane or glycogen/sugars). Phylogenetic analysis suggests that the other ATP synthase genes are not recently duplicated. Genes of the operon located at the origin of replication (MCA0006--0013) are of a type found only in Gammaproteobacteria or Betaproteobacteria, whereas the nonorigin genes (MCA2699--2708 and MCA1556) are divergent and related to the methanogenic Archaea and C. tepidum. The cooccurrence of the divergent genes in another organism able to fix nitrogen *(C. tepidum)* suggests that they may be involved in generation of extra ATP required to fix nitrogen.
Other redundant genes with divergent phylogenies include those that encode the MetK S-adenosylmethionine synthetase (MCA0450 and MCA0139), which is involved in methionine and selenoamino acid metabolism and has a role in activation of formate dehydrogenase; the GlpG glycogen phosphorylase (MCA0067 and MCA2540), which has a role in starch and sucrose metabolism; and the cell division protein FtsH (MCA0851 and MCA1848), which is a proteolytic regulator of cell division under stress. One of each duplicated pair is most closely related to genes from other Gammaproteobacteria, whereas its partner is either most closely related to genes from cyanobacteria, or occupies a deep-branching position.
The genome encodes formylmethanofuran dehydrogenase (MCA2860), an enzyme central to methanogenesis in Archaea. The fact that methanogenesis has not been previously reported in M. capsulatus suggests that this enzyme (along with methenyl-THMPT cyclohydrolase and formylmethanofuran THMPT formyltransferase) is instead functioning in reverse, in THMPT-linked formaldehyde oxidation ([@pbio-0020303-Pomper1]) ([Figure 2](#pbio-0020303-g002){ref-type="fig"}), as seen in some methylotrophs. Genes encoding subunits A, B, and C are found in an operon structure (MCA2857--2860), and there is a second distal subunit A gene (MCA2319) upstream of *pmoCAB,* together with *ftr,* which encodes the previous step in the TMPT pathway ([Figure 2](#pbio-0020303-g002){ref-type="fig"}), which appears to be a recent duplication (see [Table 2](#pbio-0020303-t002){ref-type="table"}). Subunits A and C were previously known in M. capsulatus ([@pbio-0020303-Vorholt2]). Other genes similar to those of Archaea include those containing archaeal inteins (described above), His A/His F (involved in histidine biosynthesis in Archaea) (MCA2867), a putative arsenite transporter (MCA0791), and four conserved hypothetical proteins (MCA0196, MCA0197, MCA2834, and MCA2732).
### Non-homology-based functional prediction. {#s2d2}
Phylogenetic profiling ([@pbio-0020303-Pellegrini1]; [@pbio-0020303-Eisen5]) and comparative analysis of M. capsulatus (Bath) with the incomplete genome data from the methylotroph M. extorquens were used to identify additional novel genes. Phylogenetic profiling identified four genes not previously known to have a role in methane oxidation pathways in *M. capsulatus.* Two of them (MCA0180 and MCA3022) clustered with the gene that ecodes methylene THF dehydrogenase (transfer of C1 compounds) together with a gene from *Pirellula,* and the others (MCA0346 and MCA2963) grouped with *pmoC3* (oxidation of methane to methanol) and a gene from *Nitrosomonas*.
Specific comparisons with *M. extorquens,* which possesses a much larger genome (7.6 Mb) than that of M. capsulatus (Bath) ([@pbio-0020303-Chistoserdova2]), revealed shared genetic elements for methylotrophy. Determination of putative orthologous genes shared between M. capsulatus (Bath) and M. extorquens (best hits) yielded a total of 572 genes in 88 role categories. The majority of these shared genes are of unknown function. Putative orthologs detected included 24 conserved hypothetical genes. Phylogenetic profiling showed that ten of the 24 occur in a species distribution similar to proteins of the methane oxidation pathway, suggesting that they may also have a role in methane oxidation. Three of the ten (MCA1278, MCA1279, and MCA2862) were found within methanotrophy gene "islands" (see below), and three had the highest levels of similarity to M. extorquens (MCA1497, MCA1647, and MCA2862) supporting a putative role in the methane oxidation pathway.
Of the 89 genes putatively involved in methylotrophy in *M. extorquens,* we found orthologs of 69, mostly in the categories of energy and carbon metabolism; the remaining 20 genes found in M. extorquens but not M. capsulatus (Bath) are involved in the metabolism of other C1 compounds not used by *M. capsulatus.* Many (41 of 69) of these shared methylotrophy genes are clustered on the chromosome into 13 groups, seven of which contain more than three genes, and the largest of which contains nine. Three hypothetical proteins were identified in these clusters, suggesting a role in C1 metabolism.
Conclusions {#s2e}
-----------
Our analysis of the M. capsulatus (Bath) genome has illuminated the genomic basis for the highly specialized methanotrophic lifestyle, including redundant pathways involved in methanotrophy and duplicated genes for essential enzymes such as the MMOs. We used phylogenomic analysis, gene order information, and comparative analysis with a partially sequenced methylotroph to detect genes of unknown function likely to be involved in methanotrophy and methylotrophy. Many methylotrophy genes were found to be clustered in gene islands in both organisms. We found genomic evidence for the organism\'s ability to acquire copper (including a previously unknown NRPS) and to use copper in regulation of methanotrophy, but the exact regulatory mechanisms remain unclear.
The genome sequence suggests previously unexpected metabolic flexibility, including the ability to oxidize chemolithotrophic hydrogen and sulfur and to live under reduced oxygen tension, both of which have implications for methanotroph ecology. There is a clear need for experimental validation of these genome-based hypotheses.
The availability of the complete genome of M. capsulatus (Bath) deepens our understanding of methanotroph biology, its relationship to global carbon cycles, and its potential for biotechnological applications, and it provides a set of hypotheses of gene function that can now be experimentally tested. In addition, the annotated genome provides a source of gene probes for detection and differentiation of methanotrophs in environmental samples.
Materials and Methods {#s3}
=====================
{#s3a}
### Genome sequencing {#s3a1}
M. capsulatus (Bath) was purchased from National Collection of Industrial and Marine Bacteria (Aberdeen, United Kingdom) as strain NCIMB 11132, and its DNA was isolated as previously described ([@pbio-0020303-Johnson1]). The complete genome sequence was determined using the whole-genome shotgun method ([@pbio-0020303-Venter1]). Clone libraries with insert sizes of 1.8--2.8 kb (small) and 6.5--11 kb (medium) were used for the random shotgun-sequencing phase. Physical and sequencing gaps were closed using a combination of primer walking, generation and sequencing of transposon-tagged libraries of large-insert clones, and multiplex PCR ([@pbio-0020303-Tettelin1]). Sequence assembly was performed using The Institute for Genome Research (TIGR) Assembler ([@pbio-0020303-Sutton1]). Repeats were identified using RepeatFinder ([@pbio-0020303-Volfovsky1]), and sequence and assembly of the repeats were confirmed using medium-insert clones that spanned the repeat.
### Sequence annotation {#s3a2}
Identification of putative protein-encoding genes and annotation of the genome were performed as previously described ([@pbio-0020303-Eisen5]). An initial set of open reading frames predicted to encode proteins (also termed CDSs here) was initially identified using GLIMMER ([@pbio-0020303-Salzberg1]). Open reading frames consisting of fewer than 30 codons and those containing overlaps were eliminated. Frame shifts and point mutations were corrected or designated "authentic." Functional assignment, identification of membrane-spanning domains, determination of paralogous gene families, and identification of regions of unusual nucleotide composition were performed as previously described ([@pbio-0020303-Tettelin2]). Phylogenomic analysis ([@pbio-0020303-Eisen1], [@pbio-0020303-Eisen2]; [@pbio-0020303-Eisen3]) was used to assist with functional predictions. Initially, all putative M. capsulatus (Bath) proteins were analyzed using the Automated Phylogenetic Inference System (J. H. Badger, personal communication, 2003). This system automates the process of sequence similarity, alignment, and phylogenetic inference for each protein in a genome. Sequence alignments and phylogenetic trees were refined using the methods described previously ([@pbio-0020303-Salzberg3]; [@pbio-0020303-Wu1]).
### Comparative genomics {#s3a3}
Proteins were searched by BLASTP ([@pbio-0020303-Altschul1]) against the predicted proteomes of published complete organismal genomes and a set of complete plastid, mitochondrial, plasmid, and viral genomes. The results of these searches were used (a) for phylogenetic profile analysis ([@pbio-0020303-Pellegrini1]; [@pbio-0020303-Eisen4]), (b) to identify putative lineage-specific duplications (proteins showing the highest E-value scores in pairwise comparison to another protein from M. capsulatus \[Bath\]), and (c) to determine the presence of homologs in different species. Orthologs between the M. capsulatus (Bath) genome and that of M. extorquens were identified by requiring mutual best-hit relationships (E-values less than 10^--15^) among all possible pairwise BLASTP comparisons, with some manual corrections. A total of 89 genes involved in methylotrophy in M. extorquens ([@pbio-0020303-Chistoserdova2]) were obtained from GenBank and used in a BLASTP search against M. capsulatus (Bath) and M. extorquens. Comparative genome analyses were also performed using the Comprehensive Microbial Resource ([@pbio-0020303-Peterson1]).
### Identification of prophage regions {#s3a4}
Putative prophage regions were defined as containing genes that encode proteins bearing sequence similarity to known phage or prophage proteins. We are using "prophage" to refer to sequences with similarity to lysogenic bacteriophages that have not been experimentally demonstrated to form infectious particles. Additional supporting information included the presence of direct repeats representing the att~core~ of the putative prophage (identified using MUMmer \[[@pbio-0020303-Kurtz1]\]), the conserved late-gene operon responsible for packaging and head morphogenesis of tailed dsDNA bacteriophages ([@pbio-0020303-Duda1]), and, in the case of bacteriophage Mu-like phages, conserved gene order (putative phage repressor, transposase A and B subunits, and a Mu-like *mom* DNA methyltransferase) demarking the 5′ and 3′ boundaries of the region ([@pbio-0020303-Morgan1]). Best matches were determined by searching a custom database containing 14,585 total amino acid sequences from 185 published completed bacteriophage genomes, one TIGR unpublished completed bacteriophage genome, five published incomplete bacteriophage genomes, 54 published prophage genomes, and 18 TIGR unpublished putative prophage genomes, for a total of 258 unique phage or prophage entries. WU-BLASTP version 2.0 ([@pbio-0020303-Altschul1]) was implemented through an in-house modification of the Condor parallel search tool ([@pbio-0020303-Litzkow1]), reporting only those hits having E-values less than or equal to 10^--6^. In-house Perl and Linux shell scripts were used to identify the best hit (lowest E-value) per protein sequence query.
Supporting Information {#s4}
======================
Accession Number {#s4a1}
----------------
The GenBank (<http://www.ncbi.nlm.nih.gov/Genbank/>) accession number for the Methylococcus capsulatus genome discussed in this paper is AE017282.
We thank the TIGR sequencing facility, informatics group, and IT group, as well as sponsored projects, legal, and other administrative staff, for their support. Ivar Lossius is thanked for his invaluable support throughout this project. Tanja Davidsen is thanked for her help with the Comprehensive Microbial Resource. This project was funded by the U.S. Department of Energy, Office of Biological Energy Research, Co-operative Agreement DE-FC02--95ER61962; the Norwegian Research Council (grant 140785/420); the University of Bergen Research Foundation; and the Meltzer Foundation.
**Conflicts of interest.** The authors have declared that no conflicts of interest exist.
**Author contributions.** NW, CMF, JRL, and JAE conceived and designed the experiments. ØL, LB, HK, GD, LJ, DS, KK, ML, SV, TU, and TVF performed the experiments. NW, ØL, JS, LB, HK, ASD, GD, LJ, DS, KK, ML, KEN, BM, MW, JFH, ITP, DF, JR, HT, QR, TR, RD, RS, SLS, HBJ, NKB, WN, RJD, SV, TU, TVF, JRL, and JAE analyzed the data. SHG, IH, IE, and IJ contributed reagents/materials/analysis tools. NW, ØL, JS, LB, BM, JFH, ITP, DF, JR, TR, RD, RS, HBJ, NKB, CMF, JRL, and JAE wrote the paper.
Academic Editor: Nancy A. Moran, University of Arizona
Citation: Ward N, Larsen Ø, Sakwa J, Bruseth L, Khouri H, et al. (2004) Genomic insights into methanotrophy: The complete genome sequence of Methylococcus capsulatus (Bath). PLoS Biol 2(10): e303.
ABC
: ATP-binding cassette
ACP
: acyl carrier protein
CDS
: coding sequence
G+C percent
: DNA base composition (mol% guanine + cytosine)
MMO
: methane monooxygenase
NRPS
: nonribosomal peptide synthase
PKS
: polyketide synthase
pMMO
: particulate form of MMO
RuMP
: ribulose monophosphate
sMMO
: soluble form of MMO
SQR
: sulfide-quinone reductase
TCA
: tricarboxylic acid
THF
: tetrahydrofolate
THMPT
: tetrahydromethanopterin
TIGR
: The Institute for Genome Research
|
PubMed Central
|
2024-06-05T03:55:47.789483
|
2004-9-21
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517821/",
"journal": "PLoS Biol. 2004 Oct 21; 2(10):e303",
"authors": [
{
"first": "Naomi",
"last": "Ward"
},
{
"first": "Øivind",
"last": "Larsen"
},
{
"first": "James",
"last": "Sakwa"
},
{
"first": "Live",
"last": "Bruseth"
},
{
"first": "Hoda",
"last": "Khouri"
},
{
"first": "A. Scott",
"last": "Durkin"
},
{
"first": "George",
"last": "Dimitrov"
},
{
"first": "Lingxia",
"last": "Jiang"
},
{
"first": "David",
"last": "Scanlan"
},
{
"first": "Katherine H",
"last": "Kang"
},
{
"first": "Matt",
"last": "Lewis"
},
{
"first": "Karen E",
"last": "Nelson"
},
{
"first": "Barbara",
"last": "Methé"
},
{
"first": "Martin",
"last": "Wu"
},
{
"first": "John F",
"last": "Heidelberg"
},
{
"first": "Ian T",
"last": "Paulsen"
},
{
"first": "Derrick",
"last": "Fouts"
},
{
"first": "Jacques",
"last": "Ravel"
},
{
"first": "Hervé",
"last": "Tettelin"
},
{
"first": "Qinghu",
"last": "Ren"
},
{
"first": "Tim",
"last": "Read"
},
{
"first": "Robert T",
"last": "DeBoy"
},
{
"first": "Rekha",
"last": "Seshadri"
},
{
"first": "Steven L",
"last": "Salzberg"
},
{
"first": "Harald B",
"last": "Jensen"
},
{
"first": "Nils Kåre",
"last": "Birkeland"
},
{
"first": "William C",
"last": "Nelson"
},
{
"first": "Robert J",
"last": "Dodson"
},
{
"first": "Svenn H",
"last": "Grindhaug"
},
{
"first": "Ingeborg",
"last": "Holt"
},
{
"first": "Ingvar",
"last": "Eidhammer"
},
{
"first": "Inge",
"last": "Jonasen"
},
{
"first": "Susan",
"last": "Vanaken"
},
{
"first": "Terry",
"last": "Utterback"
},
{
"first": "Tamara V",
"last": "Feldblyum"
},
{
"first": "Claire M",
"last": "Fraser"
},
{
"first": "Johan R",
"last": "Lillehaug"
},
{
"first": "Jonathan A",
"last": "Eisen"
}
]
}
|
PMC517822
|
Introduction {#s1}
============
Text-mining tools have become indispensable for the biomedical sciences. The increasing wealth of literature in biology and medicine makes it difficult for the researcher to keep up to date with ongoing research. This problem is worsened by the fact that researchers in the biomedical sciences are turning their attention from small-scale projects involving only a few genes or proteins to large-scale projects including genome-wide analyses, making it necessary to capture extended biological networks from literature. Most information of biological discovery is stored in descriptive, full text. Distilling this information from scientific papers manually is expensive and slow, if the full text is available to the researcher at all. We therefore wanted to develop a useful text-mining tool for full-text articles that allows an individual biologist to locate efficiently information of interest.
The natural language processing field distinguishes information retrieval from information extraction. Information retrieval recovers a pertinent subset of documents. Most such retrieval systems use searches for keywords. Many Internet search engines are of this type, such as PubMed (<http://www.ncbi.nlm.nih.gov/entrez/query.fcgi>). Information extraction is the process of obtaining pertinent information (facts) from documents. The facts can concern any type of biological object (entity), events, or relationships among entities. Useful measures of the performance of retrieval and extraction systems are recall and precision. In the case of retrieval, recall is the number of pertinent documents returned compared to all pertinent documents in the corpus of text. Precision is the number of pertinent documents compared to the total number of documents returned. A fully attentive reader would have complete recall, but low precision, because he has to read the whole body of text to find information. The emphasis for most applications is on recall, and we thus sought a system with high recall and as high precision as possible.
Attempts to annotate gene function automatically include statistical approaches, such as cooccurrence of biological entities with a keyword or Medical Subject Heading term ([@pbio-0020309-Stapley1]; [@pbio-0020309-Jenssen1]). These methods have high recall and low precision, as no effort is being made to identify the kind of relationship as it occurs in the literature. Another approach has involved semantic and/or syntactic text-pattern recognition methods with a keyword representing an interaction ([@pbio-0020309-Sekimizu1]; [@pbio-0020309-Thomas1]; [@pbio-0020309-Friedman1]; [@pbio-0020309-Ono1]). They have high precision but low recall, because recognition patterns are usually too specific. Other machine learning approaches have classified abstracts and sentences for relevant interactions, but have not extracted information ([@pbio-0020309-Marcotte1]; [@pbio-0020309-Donaldson1]). For a more detailed report of these and related projects, see reviews by [@pbio-0020309-Andrade1], [@pbio-0020309-de1], and [@pbio-0020309-Staab1].
The precision of a keyword search can be increased by searching for combinations of keywords. For example, a researcher might construct a search for "anchor cell" and the gene name "lin-12" because he is interested in learning whether *lin-12* plays a role in the anchor cell. However, there are many potential ways to describe the same concept or biological entity. Also, one often wants to search for a category of terms such as any gene or any body part. In this case, the intended search might be of a more general nature: If the researcher asks which genes are of interest in the anchor cell at all, he might have a hard time typing in all the known gene names (either one by one or concatenated with the Boolean operator "or") in combination with the cell name. We therefore sought to develop a system that uses categories of terms such as "gene," "cell," or "biological process." We established these categories of terms and organized them as an ontology, a catalog of types of objects and concepts and their relationships. The categories impart a semantic quality to searches, because the categories are based on the meaning of the entries.
In many cases literature databases only contain bibliographic information and abstracts. The latter suffer from the constraint of information compression and convolution imposed by a word limit. Access to the full text of articles is critical for sufficient coverage of facts and knowledge in the literature and for their retrieval ([@pbio-0020309-Blaschke1]); our results confirm these findings. We wanted to use the Caenorhabditis elegans literature as a test case for developing a useful information extraction system. C. elegans has a relatively small literature, so in principle we could use it to test a complete, well-defined corpus.
We also wanted to support a new database curation effort involving manual literature curation ([@pbio-0020309-Stein1]). Literature curation consists of identifying scientific data in literature and depositing them in an appropriate manner in a database. One extreme curation method is to read through the whole corpus of literature, identifying and extracting all significant information. This approach has the advantage that quality control of the data is done to the highest degree, based on human expertise. However, the volume and growth of biological literature makes it hard to keep the biological database up to date. In addition, data in literature may be missed by oversight, an inevitable flaw of purely human curation. The other extreme curation method is to extract data automatically. We therefore wanted a system that uses the computer to assist the curators.
Our system is defined by two key components: the introduction of an ontology and the searchability of full text. The ontology is organized into categories that facilitate broader searches of biological entities as illustrated above. To be useful, it should also contain other categories that are not composed of biological entities, but describe relationships between entities. We sought to offer the user an opportunity to query the literature in the framework of the ontology such that it returns sentences for inspection by the user. We hypothesized that searching the corpus of text with a combination of categories of an ontology could facilitate a query that contains the meaning of a question in a much better way than with keywords alone. For example, if there is a "gene" category containing all gene names and a "regulation" category that includes all terms (nouns, verbs, adjectives, etc.) describing regulation, searching for (at least) two instances of the category gene and one instance of the category regulation in a sentence increases the chance that the search engine will return a sentence describing a gene-gene regulation. The search could then be limited by using a particular gene name as a keyword to get a list of genes that regulate or are regulated by that particular gene.
Results {#s2}
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We have developed a text processing system, Textpresso, that splits papers into sentences, and sentences into words or phrases. Each word or phrase is then labeled using the etensible arkup anguage (XML) according to the lexicon of our ontology (described below). We then index all sentences with respect to labels and words to allow a rapid search for sentences that have a desired label and/or keyword. The labels fall into 33 categories that comprise the Textpresso ontology. We built a database of 3,800 C. elegans papers, bibliographic information from WormBase, abstracts of C. elegans meetings and the Worm Breeder\'s Gazette, and some additional links and WormBase entities. See [Materials and Methods](#s4){ref-type="sec"} for details on the database preparation.
Textpresso Ontology {#s2a}
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Abstracts, titles, and full texts in the Textpresso system are processed for the purpose of marking them up semantically by the ontology we constructed. An ontology is a catalog of types of objects and (abstract) concepts devised for the purpose of discussing a domain of interest. An ontology helps to clarify a domain\'s semantics for everyday use, as is nicely demonstrated by Gene Ontology (GO; [@pbio-0020309-The1]). Although GO terms are not intended as a representation of natural language prose, they are a rich source of biologically meaningful terms and synonyms. They are the foundations for three corresponding categories in Textpresso, which are added to its 30 other categories. GO terms comprise approximately 80% of the lexicon.
The first group of categories in the Textpresso ontology consists of biological entities: It contains the categories gene, transgene, allele, cell and cell group, cellular component, nucleic acid, organism, entity feature, life stage, phenotype, strain, sex, drugs and small molecules, molecular function, mutant, and clone. We have incorporated the GO molecular function category and proteins in the Textpresso molecular function category. A more detailed list with definitions can be found on the Textpresso Web site, and the most important ones are provided in [Table 1](#pbio-0020309-t001){ref-type="table"}. Many of these categories have subcategories. For example, the molecular function category has the subcategories "source = (Go\|Textpresso)" and "protein = (yes\|no)." As we have imported all terms from GO, the first subcategory makes it possible to search specifically for GO terms. Terms added by us have the attribute "Textpresso." Similarly, not all molecular function terms are classified as protein. The word "co-transporter," for example, conveys more of a function and would be used more in this context in the literature, even though its physical realization may in fact be a protein. A list of all subcategories can be found in [Table 2](#pbio-0020309-t002){ref-type="table"}.
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Table 1
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###### The 18 Biologically Most Relevant of the 33 Categories of the Textpresso Ontology
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^a^ HSN, hermaphrodite-specific neuron
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Table 2
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###### The Subcategories of the Ontology
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Categories without any subcategories are omitted
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The second group of categories comprises terms that characterize a biological entity or establish a relation between two of them. It includes physical association (in the sense of binding) and consort (abstract association), effect, purpose, pathway, regulation, comparison, spatial and time relation, localization in time and space, involvement, characterization (terms that express the characterization of something), method, biological process, action, and descriptor (words that describe the state or condition of an entity). These categories, while well defined, have somewhat delicate boundaries, and the common-sense aspects of our ontology apply more to this group. It is likely that its categories are going to be changed as we continue to develop the system. In some instances terms are attributed to one category, even though they might as well fit into another. As an example, the term "coexpress" is put in the "consort" category to emphasize the concurrent aspect of the process, while it could as well be classified as a biological process. However, we believe that in most cases the first sense of the word is used in the literature.
The last group (auxiliary) contains categories that can be used for more involved semantic analysis of sentences. These categories are auxiliary (forms of the verbs "be" and "have"), bracket, determiner, conjunction (and, or, because, since, although, etc.), conjecture (could, might, should, suggests), negation, pronoun, preposition, and punctuation. Some of them overlap with the syntactic categories that the part-of-speech tagger (used in the preprocessing steps; see [Materials and Methods](#s4){ref-type="sec"}) assigns to terms, but are repeated here as they also contain some semantic component. The category "conjecture" is introduced to distinguish statements that convey hypotheses, speculations, or theoretical considerations from sentences that are expressed with confidence, thus representing more of a fact. The words of this category indicate the certainty of a statement.
The Textpresso ontology is organized into a shallow hierarchy with 33 parent categories. The parent categories may have one or more subcategories, which are specializations of the parent category. For example, all of the terms in the parent category "biological process" will belong to one of its subcategories, "transcription," "translation," "expression," "replication," "other," or "no biosynthesis." This is user friendly and certainly serves the current implementation of the user interface well, which is oriented more towards information retrieval.
The ontology is populated with 14,500 Practical Extraction and Report Language (PERL) regular expressions, each of which covers terms with a length from one to eight words. These expressions are contained in a lexicon. [Table 3](#pbio-0020309-t003){ref-type="table"} shows examples of regular expressions for each category and examples of text strings matching them. Each regular expression can match multiple variable patterns. The multiple forms of regular verbs, for example, can be conveniently expressed as "\[Ii\]nteract(s\|ed\|ing)?" which stands for the eight cases "interact," "interacts," "interacted," "interacting," "Interact," "Interacts," "Interacted," and "Interacting." All regularly named C. elegans genes are matched with the expression "\[A--Za--z\]\[a--z\]\[a--z\]--\\d+" matching three letters (\[A--Za--z\]\[a--z\]\[a--z\]), a dash (--), and a sequence of digits (\\d+). As this example illustrates, the expressions can be made case sensitive. This is important as biological nomenclature becomes more elaborate, and the ability to distinguish subtle differences is pivotal for separating terms into the correct categories. Many of the regular expressions are generated automatically via scripts, taking a list of plain words as input and transforming them as shown in this example, to account for regular forms of verbs and nouns. The text-to-XML converter (see [Materials and Methods](#s4){ref-type="sec"}) marks up the whole corpus of abstracts, full texts, and titles and produces XML documents. [Figure 1](#pbio-0020309-g001){ref-type="fig"} illustrates this process with an example. The computer identifies terms by matching them against regular expressions (such as the one shown above) and encloses them with XML tags. The tag \<text\> serves as a containment of terms not semantically marked up. These tags will be used for a repeated reevaluation of the lexicon, as these terms can be easily pulled out and analyzed. A list of the most frequently missed terms is then produced and included in the lexicon for the next markup.
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Figure 1
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###### The Process of Marking up a Sentence
The process of marking up the sentence "In par-1, par-4 and par-3 mutant four-cell embryos, MEX-3 is present at high levels in all cells, indicating that activity of these par genes is required to restrict MEX-3 to the anterior." This sentence is taken from [@pbio-0020309-Huang1].
\(A) The computer identifies terms that are stored in a lexicon according to categories of the ontology. A text-to-XML converter marks up the terms by enclosing them in XML brackets.
\(B) The fully marked-up sentence. Some categories have subcategories (for example, the category "regulation" is subdivided into "positive," "negative," and "unknown"). Grammar attributes have been omitted here for the sake of clarity, because they are not used in the current version of the system. Some white spaces have been inserted in the graphics for clarity enhancement.
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Table 3
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###### Categories of the Ontology with Examples of Regular Expressions and Matching Text Strings
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This table also contains the distribution of 24,542,376 tags in the 1,035,402 sentences of the corpus
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Applications of Textpresso {#s2b}
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The marked-up text is stored in a database and can be queried. We built a user interface for general queries and another one for a specific type of query for WormBase curators (gene-gene interactions; see below). Textpresso is used in several related ways. Individual biologists use it to find specific information. Database curators, whose job is to extract information from papers or abstracts and to add this to a database, use it repeatedly to find all information of a particular type, in addition to using it for individual queries.
The current Textpresso user interface (<http://www.textpresso.org/>) includes a query interface, a side menu with links to informative pages about the ontology, a document type definition, a user guide, and example searches, as well as the two retrieval and customization interfaces. The Web site offers two different types of retrieval, simple and advanced. Options for the retrieval queries are offered: searching a combination of categories, subcategories, and keywords in a Boolean fashion, specifying the frequency of occurrences of particular items, and choosing where in the article to search (title, abstract, body). The user can also determine whether a query is to be met in the whole publication or in a sentence. These options make the search engine powerful; for example, if a query is met in the whole article, the search has the function of text categorization, while meeting it in a sentence aims at extracting facts, which can be viewed in the context of a paragraph. The specification of cooccurrence determines the character of a search. If a combination of keywords and categories is found in a sentence, the likelihood that a sentence contains a fact involving the chosen categories and keywords is quite high. If the user chooses cooccurrence within a document, he is more interested in finding a relevant document. The scope of a search can be confined to full text, abstract, title, author, year, or any combination thereof, for document searches as well as sentence searches. A typical result page shows a list of documents with all bibliographical information and the abstract as displayed in [Figure 2](#pbio-0020309-g002){ref-type="fig"}. A simplified version of the Textpresso interface is incorporated within WormBase (<http://www.wormbase.org>).
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Figure 2
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###### A Typical Result Page Returned from a Simple Retrieval Query (Keyword)
A simple retrieval was performed with "let-23" as keyword and "regulation," "cell or cell group," and "molecular function" as categories. A total of 245 matches were found in 113 publications.
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The result list retrieved by a query can be customized in such a way that the user can choose how to display the information. This list is sorted according to the number of occurrences of matches in the document, so the most relevant document will be on the top of the list. A series of buttons for the whole list as well as for each document is available, allowing the user to view matching sentences or prepare search results in various formats. The individual result entries have up to six links: One can view matches for each paper only, go to the Web site of the journal to read the online text of the article (this only works if the user is subscribed to the journal), view a list of related articles that is provided by PubMed, export the bibliographical information into Endnote (two different links), or, if the user is accessing Textpresso internally (currently at Caltech), one can download the PDF of the paper.
The power of Textpresso\'s search engine unfolds when category searches are used. By searching for a category, the researcher is targeting all keywords that populate that category. For example, the researcher might be interested in facts about genetic regulation of cells. Assuming that many facts are expressed in one sentence, he would search for the categories "gene," "regulation," and "cell or cell group" in a sentence. He can then view the matches (and surrounding sentences) of the search return and decide which facts are relevant. If one is not interested in all genetic regulation instances mentioned in the literature, it might be more useful to combine keywords with categories. For example, the question "What entities interact with 'daf-16\' (a C. elegans gerontogene)?" can be answered by typing in the keyword "daf-16" and choosing the category "association."
Advanced Retrieval and Subcategories {#s2c}
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An extension (the advanced retrieval interface) allows the use of the subcategories of the ontology and the specification of Boolean operators, thereby concatenating categories and keywords with "or" or "not" to permit alternatives or exclude certain items. One special subdivision of terms is the distinction between named and unnamed entities: Categories can include both general terms and specific names of entities. For example, the word "gene" would be an unnamed term of the gene category, while "lin-11" is a named entity. The general terms will likely be used for fact extraction across several neighboring sentences, but they might also be useful for retrieval purposes, even though the rate of false positives might be much higher in the latter case. Lastly, the user can determine how a keyword or category term has to be matched numerically. The options "greater than," "less than," and "equal to" are available together with a drop-down menu for the number of occurrences.
With these additional tools, document categorization can be made more effective. A detailed profile of which categories and keywords should occur a minimum, maximum, or exact number of times for triggering a match can be established. Similarly, searches on the sentence level acquire a semantic quality, i.e., they at least partially encompass a meaning. In many cases, the answers to questions, phrased in the form of a sophisticated query, can immediately be read off the result screen. If, for example, one were to ask in which cells *lin-11* is expressed, one would search sentences for a combination of the category "biological process" (subcategory "biosynthesis: expression"), the category "cell or cell group" (subcategory "type: name") and the exact keyword "lin-11." The subcategory "expression" filters out all words that relate to expression, the subcategory "name" limits the search to specific cells which have a name, such as "anchor cell," "HO neurons," "IL sensillum," etc. Other subcategory options would be "group" (for example, "head," "vulva," "tail") and "lineage" ("AB lineage," "EMS lineage," etc.). To better understand the following results, note that the term "cell(s)" has the type "name," to gain the correct meaning of phrases such as "AB lineage cells." The first two words of this phrase are marked as lineage, but the last word makes the whole phrase named cells.
The system returns sentences of different quality. Some of them answer the question posed immediately (returned sentences are taken from [@pbio-0020309-Gupta1]; that paper produced the most hits). The underlined words mark the matched items: "An analysis of the pattern of in *vulva and uterine lineage* earlier suggested that cellular defects arise due to a failure in the differentiation process"; "Our analysis of the expression of in VPC granddaughters (Pn.pxx stage) has revealed the following pattern in *P5.p and P7.p lineage* (from anterior to posterior; L, low; H, high), LLHH and HHLL , respectively." Other sentences meet the truth more by accident, as the terms are matched within a sentence, but the statement does not really express the fact sought. The cells where *lin-11* is expressed might be inferred by the knowledgeable reader, and not stated explicitly: "Our results demonstrate that the tissue-specific of is controlled by two distinct regulatory elements that function as independent modules and together specify a wild-type -laying system"; "Using a temporally controlled system, we show that is initially required in vulval for establishing the correct invagination pattern." Finally, some sentences just do not give any clue about the posed question: " cDNA- vectors under the control of lin-11- (pYK452F7-3) and lin-11-C (pYK452F7-2) elements were designed as follows." Here, "AB" is marked up as a named cell, but this is not the semantically correct tag in this context. This false positive might have been prevented if specific sections of a paper could be searched, as this statement comes from the method section.
Evaluation of the Textpresso System {#s2d}
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An automatic method for retrieving or extracting information from text is only useful if it is as accurate and reliable as human curation. We devised two tests based on two common tasks performed by human experts who extract biological data from journal articles. The first task was the automatic categorization of papers according to the types of biological data they contain. Our study used a large test set of papers scanned by a curator to examine the effectiveness of automatically searching for information in the full text of a journal article compared to its abstract. The second task focused on retrieving sentences containing a specific type of biological data from text. Sentences from eight journal articles were manually inspected on a sentence-by-sentence basis and compared to the return from a Textpresso query on the same articles. From this study we present a detailed error analysis outlining the strengths and weaknesses of the current Textpresso system as an automatic method for information retrieval.
We evaluated the performance of Textpresso using the information extraction performance metrics of precision, which is a measure of the amount of true returned data compared to the amount of false returned data, and recall, which is a measure of the true data returned compared to the total amount of true data in the corpus. These values are formulated as *recall* = *number of true returns* / *total number of true data items* and *precision* = *number of true returns* / *total number of returns.*
Classification of Journal Articles: Full Text Versus Abstract {#s2e}
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We examined the effectiveness of automatically identifying journal articles that contain particular types of data. A test set of 965 journal articles pertaining to C. elegans biology was assessed by a human expert and categorized into groups according to six different types of data (antibody data, ablation data, expression data, mapping data, RNAi data, and transgenes). Note that there can be more than one data type per article.
We first measured the value of searching for keywords in the full text of an article as opposed to searching its abstracts ([Table 4](#pbio-0020309-t004){ref-type="table"}). The overall information recall when searching abstracts is low (∼44.6%) compared to the information recall when searching full text (∼94.7%). Furthermore, keywords for some specific types of data (e.g., antibody data, mapping data, transgene data) are very unlikely to appear in abstracts (∼10% recall) but can be found in full text (∼70% recall). However, precision of the keyword search is reduced by almost 40% when searching full text compared to abstracts (30.4% and 52.3%, respectively). Single keyword searches of full text return a large number of irrelevant documents for most searches. This higher false positive rate might reflect the writing style found in full text, where facts can be expressed within complex sentence structures (as compared to abstracts, where authors are forced to compress information), combined with the inability of a keyword search to capture context.
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Table 4
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###### Comparison of a Keyword Search on Abstracts versus Full Text
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Automatic classification of journal articles based on the biological information they contain (i) searching abstracts with keywords and (ii) searching full text with keywords. The keywords used as search terms are indicated by *k*(*keyword*). A, the number of true articles returned; B, the total number of articles returned
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Small-Scale Information Retrieval Study {#s2f}
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We tested the accuracy of a search combining word categories and keywords to retrieve sentences containing genetic interaction data. For this experiment we broadly defined genetic interaction as the effect of one or more genes on the function of another gene or genes (and thus it includes genetic interaction, regulation, and interaction of gene products). To directly assess how Textpresso performs, a human expert manually evaluated the text sentence by sentence ([Figure 3](#pbio-0020309-g003){ref-type="fig"}).
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Figure 3
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###### Schema of Small-Scale Information Retrieval Study
Sentences from eight journal articles were both queried by Textpresso and evaluated by a human expert for sentences that described genetic interaction (information retrieval task). In the information extraction task, a human expert inspected the sentences returned by each method to determine the amount of distinct gene-gene interactions that could be extracted in order to analyze the output of the first task.
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We formulated a Textpresso query that searched for the presence of at least two genes mentioned by name and at least one term belonging to the "regulation" or "association" word categories (see [Materials and Methods](#s4){ref-type="sec"}). A total of 178 sentences were matched for this query in the eight journal articles, and the results are shown in [Table 5](#pbio-0020309-t005){ref-type="table"}. A human expert assessed the returned sentences and determined that 63 sentences contained gene-gene interaction data according to our criterion. The same set of journal articles had been independently manually evaluated for their description of genetic interactions, and 73 true sentences were identified. In both cases, information from the article title, abstract, contents of tables, and reference section was excluded. Sentences that described genetic interaction using the gene product name rather than the gene were also excluded from this study. To measure recall, we first determined the total number of sentences that contained genetic interaction data.
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Table 5
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###### Retrieval of Sentences Containing Gene-Gene Interaction Data from a Set of Journal Articles
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Retrieval was performed manually or automatically using Textpresso
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For this analysis we took the union of true sentences manually identified in the journal articles and the true sentences returned by Textpresso. The total number of true sentences identified by the two methods was 102. The recall of sentences containing genetic interaction was ∼62% using Textpresso compared to ∼71% for those sentences manually identified in journal articles. One-third of the sentences returned by Textpresso were true positives (35%).
Although the numbers of true sentences retrieved by the automatic and manual methods were similar (63 and 73, respectively), only 34 of these sentences overlapped. To investigate this discrepancy, we manually extracted the genetic interactions described in both sets of sentences and determined the number of distinct genetic interactions found by each method ([Table 6](#pbio-0020309-t006){ref-type="table"}). The sentences manually identified from the journal articles yielded 23 more distinct genetic interactions than those which were extracted from true sentences retrieved by Textpresso. However, 43 interactions derived from the Textpresso output overlapped with the manually identified set, and Textpresso located sentences describing seven genetic interactions that the human expert missed. The average redundancy (how many times the same gene-gene interaction occurred) of a distinct genetic interaction extracted from both the manual and automatic methods was 3-fold.
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Table 6
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###### Distinct Gene-Gene Interactions Retrieved from Journal Articles
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Interaction data were either manually retrieved from journal articles or manually retrieved from sentences retrieved by Textpresso
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We analyzed the gene-gene interaction sentences missed by Textpresso. In many cases (65%) the word or phrase used to describe the genetic interaction belonged to neither the "association" nor the "regulation" word category and so the sentence was not returned. In some cases, the term or phrase that determined "genetic interaction" belonged to some other Textpresso word category (e.g., some terms that implied genetic interaction and were not matched by the query were "epistatic," which belongs to the "consort" word category, and "alters," which belongs to the "effect" word category). This type of analysis is useful for revising and updating the ontology. In other cases, due to the intricacies of natural language prose, it was difficult to isolate an interaction term in the sentence (e.g., "Thus *ref-2* alone is insufficient to keep P(3--6).p unfused when *lin-39* is absent."). Approximately 8% of true sentences were missed because the genetic interaction information was discussed over a number of sentences. This is a limitation of the current Textpresso system, as search queries are matched per sentence (or per entire article).
Our analysis of the false positive sentences returned by Textpresso revealed that approximately 10% discussed gene-gene interactions that did not occur (e.g., "Neither *pdk-1(gf)* nor *akt-1(gf)* suppressed the Hyp phenotype of *age-1(mg44)*."). While we do have a "negation" category in our Textpresso ontology, we chose not to exclude negation terms from the posed query, to avoid missing true positives (in case the negation does not apply to the interaction term in a sentence, but to some other portion of it). Twenty-one percent of the false positive sentences were determined by inspection to suggest genetic interaction, but were too weakly phrased to extract the information in confidence without the context of the sentence. However, the majority of false positives (70%) were due to the lack of context of the search terms in the sentence, where they matched the query terms (underlined) but in a context that did not mention genetic interaction: " and , two genes that a C. elegans pathway, encode proteins similar to Rb and its binding protein RbAp48." This example strongly supports the idea that an information extraction method that considers semantic context of a search query would dramatically increase the precision of the return.
Large-Scale Information Retrieval to Expedite Information Extraction {#s2g}
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We performed extraction of genetic interaction information from a corpus of 3,307 journal articles. A Textpresso query searched for the presence of at least two uniquely named genes and at least one term belonging to the "regulation" or "association" word categories (see [Materials and Methods](#s4){ref-type="sec"} for more details). A total of 17,851 sentences were returned by this query. Due to the lack of context of some sentences, true sentences were determined by a more stringent definition of genetic interaction, i.e., where one or more named genes were described as modifying the phenotype of another named gene or genes by suppression, enhancement, epistasis, or some other genetic method. To determine the frequency of true sentences, a random sample of 200 of the sentences returned by Textpresso was evaluated by a human expert according to this more stringent criterion ([Table 7](#pbio-0020309-t007){ref-type="table"}, column C). This sample was compared to 200 sentences chosen from the whole corpus at random ([Table 7](#pbio-0020309-t007){ref-type="table"}, column A) and 200 sentences randomly chosen from the whole corpus that contained two or more named genes ([Table 7](#pbio-0020309-t007){ref-type="table"}, column B).
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Table 7
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###### The Frequency of Genetic Interaction Data Contained in Full Text
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A, 200 random sentences; B, 200 sentences containing at least two genes; C, 200 sentences returned from a Textpresso query for at least two uniquely named genes and at least one "regulation" or "association" word. See [Materials and Methods](#s4){ref-type="sec"} for details
:::
A typical sentence that was determined to be true for genetic interaction data is "Interestingly, at lower temperatures, the *akt-2(+)* transgene can supply sufficient Akt/PKB activity to weakly suppress the dauer arrest caused by *age-1(mg44)*." Some of the sentences strongly suggested genetic interaction but did not quite meet the genetic interaction criterion. These were grouped as "possible genetic interaction," for example, if a phenotype was not mentioned: "For example, *lin-15(lf)* animals display a 54% penetrance of P11 to P12 fate transformation, while all *egl-5(lf)*;*lin-15(lf)* double mutants show a P12 to P11 fate transformation." Sometimes it is unclear exactly which genes are participating in the genetic interaction: "Evidently the effect of the sir-2.1 transgene alone is too subtle to trigger dauer formation without the sensitizing *daf-1* or *daf-4* mutations." Another group was highlighted as discussing interaction, but fell outside the criterion set for genetic interaction. These were classified "non-genetic interaction." Some examples of this are sentences that specify gene regulation: "These studies have shown that *smg-3(Upf2)* and *smg-4(Upf3)* are required for SMG-2 to become phosphorylated." Finally, sentences that describe physical interaction were also put into the category "possible genetic interaction": "For example, GLD-1 represses translation of *tra-2*, one of the sex-determination genes, by binding to the 3′-UTR or the *tra-2* mRNA (Jan et al. 1999)."
This analysis shows that there is a 1 in 200 chance of a sentence discussing genetic interaction (as defined above) randomly occurring in the full text of the journal articles analyzed. The odds increase to 7 in 100 if one looks at sentences containing at least two named genes. The returned matches from the Textpresso search are enriched 39-fold for genetic interaction compared to random chance, and there is a significant 3-fold enrichment when compared to sentences containing at least two named genes. There is a 1 in 5 chance that a returned Textpresso match is true. To date, 2,015 of the 17,851 returned sentences have been evaluated. Of these, 370 discuss genetic interaction, yielding 160 distinct gene-gene interactions mined from the literature. There are 213 sentences that mention nongenetic interactions, and 419 sentences are classified as possible genetic interactions.
Large-Scale Simple Fact Extraction {#s2h}
----------------------------------
We have extracted gene-allele reference associations from the corpus of papers to populate the WormBase database by searching for the pattern \<gene\>\<bracket\>\<allele\> \<bracket\>. Of the 10,286 gene-allele associations extracted, 9,230 were already known by WormBase, while 1,056 associations were new and could be added to the database. In addition, 1,464 references could be added to the 2,504 allele reference associations in WormBase. Ninety-eight percent of the data extracted went into the database without any manual correction, and the last 2% were compromised because of typographical errors in the original paper or the inherent character of the data (i.e., gene name synonyms and changes).
Discussion {#s3}
==========
Accomplishments {#s3a}
---------------
We have developed a system to retrieve information from the full text of biological papers and applied it to the C. elegans literature. As of March 2004, the database contains full texts of 60% of all papers listed by the *Caenorhabditis* Genetics Center (CGC; <http://www.cbs.umn.edu/CGC/CGChomepage.htm>) and almost all abstracts that are information rich for C. elegans research. The introduction of semantic categories and subsequent marking up of the corpus of texts introduce powerful new ways of querying the literature, leading towards the formulation of meaningful questions that can be answered by the computer. We have demonstrated such queries with one example and have successfully tried many others. A more thorough evaluation of the system revealed that the availability of full text is crucial for building a retrieval system that covers many biological data types with a satisfying recall rate, and thus is truly useful for curators and researchers. For biologists, an automated system with high recall and even moderate precision (like the current Textpresso) confers a great advantage over skimming text by eye. Textpresso is already a useful system, and thus serves not only as proof of principle for ontology-based, full-text information retrieval, but also as motivation for further development of this and related systems to achieve higher precision and hence even greater time savings.
It is apparent that the number of articles available in the C. elegans literature (currently about 6,000) can be curated with the assistance of Textpresso, as it is much more efficient than when done by human readers alone. The larger the corpus of papers, the more useful Textpresso will become. We have shown this by calculating the frequencies of genetic interaction data in sentences in three different cases: random sentences, sentences that contain at least two genes, and sentences returned from a Textpresso advanced query. The efficiency was shown to increase dramatically (39-fold in the best case). We have outlined the first steps of how Textpresso helps the curation effort by extracting gene-gene interactions. Overall, we have shown that Textpresso has several uses for researchers and curators: It helps to identify relevant papers and facts and focuses information retrieval efforts. Indeed, Textpresso is used daily by C. elegans researchers and WormBase curators: The server sends 530 files to requests daily via the Web, a quarter of which are to WormBase curators.
Areas for Improvement {#s3b}
---------------------
Textpresso is limited in two ways: the lack of complete coverage of the C. elegans literature and the fact that the ontology and its corresponding lexicon are still in their infancy. The preparation of full texts has to be better and more efficient. The conversion of PDF to plain texts was problematic because of the different layouts of each journal. Even with the software we developed, a layout template for each journal needs to be written to specify where different components of text can be found. Prior to the use of this software, we had to forgo the use of figure and table captions. Acquisition of processable text is a general problem for biologists. A new release of XPDF (a PDF viewer for X; <http://www.foolabs.com/xpdf/>) eases this problem considerably (see [Materials and Methods](#s4){ref-type="sec"}).
One of our studies on the effectiveness of the extraction of a specific type of biological fact, in this case gene-gene interaction, showed that the machine still cannot replace the human expert, although it increases efficiency greatly. We anticipate that the computer does better with a larger number of articles because of redundancy. While roughly 9% of distinct gene-gene interactions from a corpus of eight journal articles were missed by the human but revealed by Textpresso, 29% of the interactions were missed by Textpresso, primarily due to flaws in the ontology.
Advancing the Textpresso ontology will help to increase the specificity of the retrieval system. A deeper, meaningful structure is likely to make extraction easier and more stable. Possible improvements are to include other biological ontologies and language systems, such as UMLS (<http://www.nlm.nih.gov/research/umls/>) and SNOMED (<http://www.snomed.org/>, and to establish a more sophisticated tree structure. Our core lexicon recognizes 5.5 tags per sentence (out of an average of 23.7 tags per sentence) that are of scientific interest. This density results in a term coverage of 23.2%, while the maximum that could theoretically be added is 36.5%, assuming that all terms currently not marked up belong to relevant categories. An average of 9.5 tags per sentence are apparently of no interest for information retrieval; however, this is due to the nature of human language (and will be nonetheless useful for information extraction purposes). Reevaluation of the corpus of text for terms and their meanings that have been missed is necessary. This process will result in an expansion of our ontology, thus continually expanding the resulting lexicon, or revising the structure of the ontology. Ontology and lexicon revision is most efficiently done by a human, and a feasible automated approach seems out of reach. However, we have illustrated semiautomatic methods to help make this task easier in the future: The containment of words that are not covered in our lexicon with \<text\> tags serves several purposes. First, we are able to extract all words (or n-grams, which are represented as a consecutive sequence of words embedded in \<text\> tags), assemble a histogram of the most frequent terms, and add important ones to our lexicon. Second, having identified frequently occurring semantic patterns in the corpus, we are able to infer likely candidates of words for specific categories. For example, one popular pattern that indicates a gene-allele association is \<gene\>\<bracket\>\<allele\>\<bracket\>. If one now searches for patterns such as \<gene\>\<bracket\> \<text\>\<bracket\> and extracts the word enveloped by the \<text\> tags, then a frequency-sorted list of words that are likely to be alleles can be assembled, presented to a curator for approval, and deposited into the lexicon. The alternative, \<text\>\<bracket\>\<allele\>\<bracket\>, would give a list of possible gene names. Many other patterns, identified by statistical means and similarity measures, could be obtained and used in such a fashion. These two methods will help us to systematically and significantly reduce the number of terms not marked up in the corpus, making it more complete. The procedure can be repeated with every build of the Textpresso database and has the advantage that the list of words added to the lexicon is tailored to the literature for which it is used. In addition, shortcomings in the general structure of the ontology can be detected and corrected, if those issues have not been caught in the research and development of the information extraction aspects of the system. If the strategy outlined above is applied continually, we will be able to close this gap and reach saturation, even with the addition of new papers and abstracts.
About 89% of current users take advantage primarily of the full text and multiple keywords. Some (11%) proceed to keyword plus category. Only 0.3% of users use the advanced retrieval search. It is clear that the implementation of a user test interface improvement/education cycle will greatly help the development of Textpresso and subsequently help users take full advantage of this system. More generally, biologists will become increasingly familiar with ontology-based search engines.
Prospects {#s3c}
---------
Future development of Textpresso can be undertaken at many different levels. A synonym search could be enabled for keyword searches: After having compiled lists of them, an option could be given to automatically include synonyms for a given term (e.g., genes, cells, cellular component) in a search. Similarly, GO annotations could be used to search for and display sentences involving genes associated with gene ontology terms, after the latter ones have been queried first. As already mentioned, search targeting could be made more flexible: Papers could be subdivided into more sections (such as introduction, methods, results, conclusion, etc.), and a query could then be applied only to the specified sections. In addition, the limitation of searching criteria to just one sentence can be relaxed to a set number of neighboring sentences. Finally, one could improve on links to other databases of relevance besides WormBase and PubMed and increase the wealth of links to the latter ones.
An important issue is the portability of the system to other model organism databases. This undertaking is part of the Generic Model Organism Database (GMOD) project (<http://www.gmod.org>, and a downloadable package with software will be made available on their Web site. For a different model organism, parts of the lexicon, and maybe also parts of the ontology, need to be modified. Language and jargon in each community differ, and terms need to be systematically collected to accommodate their specific usage in the respective communities. However, this is not too laborious, as we have been able to generate a yeast version in a few weeks (E. E. Kenny, Q. Dong, R. S. Nash, and J. M. Cherry, unpublished data).
We believe that Textpresso can be extended to achieve information extraction. The wealth of information buried in semantic tag sequences of 1 million sentences asks to be massively exploited by pattern-matching, statistical, and machine learning algorithms. Having the whole corpus semantically marked up provides bioinformaticians with the opportunity to develop fact extraction algorithms that might be quite similar to sequence alignment and gene-finding methods, or, more generally, algorithms that have similarity measures at their core, because sentences can now be represented as sequences of semantic tags. Furthermore, semantic sequences of related sentences show similar properties as related genomic sequences, such as recurring motifs, insertions, and deletions. The relatively rigid structure of the English language (subject-verb-object) and the comparatively low degree of inflections and transformations certainly help. In addition, some scientific information is stored in a structured manner. We have already started to run simple pattern-matching scripts to populate gene-allele associations from the literature for WormBase, as many of them are written in the form "gene name(allele name)," such as "lin-3(n1058)."
Materials and Methods {#s4}
=====================
{#s4a}
### Sources. {#s4a1}
Textpresso builds its C. elegans database from four sources. A collection of articles in PDF format is compiled according to the canonical C. elegans bibliography maintained at the CGC (<http://www.cbs.umn.edu/CGC/CGChomepage.htm> ). As of March 2004 we had around 3,800 (60%) CGC papers in our database. Software developed by us (see below) converts the PDFs to plain text. We import additional bibliographical information from WormBase: titles of documents and author and citation information. WormBase data comprise additional *C. elegans-*related documents such as C. elegans meeting abstracts and Worm Breeder\'s Gazette articles. We also curate certain types of data ourselves. Some *C. elegans-*related papers are not found in the CGC bibliography or WormBase. We compile lists of URLs of journal Web sites and their articles, and links to related articles (provided by PubMed). Citations are prepared in Endnote format for download. Finally, as Textpresso returns scientific text to the user, we construct links to report pages of WormBase that display detailed information about biological entities, such as genes, cells, phenotypes, clones, and proteins. All data and links produced by us are referred as "Textpresso" data in [Figure 4](#pbio-0020309-g004){ref-type="fig"}.
::: {#pbio-0020309-g004 .fig}
Figure 4
::: {.caption}
###### Schema of Textpresso Database Preparation
The regular hexagons indicate the sources from which Textpresso is built. The rounded rectangles are either intermediate or final processed parts of the corpus. The dashed-dotted rectangles signify automatic processing units or actions.
:::
:::
### Ontology. {#s4a2}
The objective of an ontology is to make the concepts of a domain and the relationships and constraints between these concepts computable. For an ontology to be utilized in a search engine for biological literature, it has to include the language of everyday use and common sense. We have therefore assigned the most commonly used meaning to a word even though it has several meanings in different contexts. We have consequently adopted a strategy of devising an ontology drawing from our own knowledge. Our ontology includes all terms of the three major ontologies of GO, namely "cellular component," "biological process," and "molecular function." The current ontology is unstructured for the sake of straightforward usability, our first priority.
A variety of approaches were utilized to construct and populate the 33 categories of the Textpresso ontology. We first designed individual categories for well-defined biological units or concepts such as strain, phenotype, clone, or gene. The terms in some of these categories (such as clone, allele, and gene) were represented by a PERL regular expression designed to match any text that looked like that particular biological unit. This was possible where a conserved and unique nomenclature for that biological concept had been established in the literature. Any exceptions to the established nomenclature recorded in WormBase were also added to these categories.
For other biological concepts (e.g., "method," "phenotype," "cellular component," and "drugs and small molecules"), we extracted information from publicly accessible biological databases, such as WormBase, GO, and PubMed/NCBI to construct lists of terms. We supplemented these lists through primary literature and textbook surveys.
Next, we conceived categories of terms that would describe the relationship between the biological categories. To structure these "relationship" categories, we listed words of the text of 400 C. elegans journal articles for analysis. From this list we flagged natural prose words that we felt had at least some defined meaning within the context of biological literature (for example, "expressed," "lineage," "bound," "required for"). From this list we constructed 14 new categories designed to encapsulate the natural language used by biologists to describe biological events and the relationship between them (action, characterization, comparison, consort, descriptor, effect, involvement, localization in time and space, pathway, purpose, physical association, regulation, spatial relation, and time relation). We made a second pass through the subset of flagged words from the list and assigned them to one of these categories according to what the sense of the word was in the biological literature for the majority of the time.
Finally, a number of categories were designed to account for syntax and grammatical construction of text, such as "preposition," "conjunction," and "bracket."
### Names. {#s4a3}
We have manually curated a lexicon of names because it has proved difficult in the past to automatically recognize names of biologically relevant entities ([@pbio-0020309-Fukuda1]; [@pbio-0020309-Proux1]; [@pbio-0020309-Rindflesch1]; [@pbio-0020309-Blaschke2]; [@pbio-0020309-Hanisch1]). We therefore chose to curate and maintain a lexicon with names of interest by hand. In this *C. elegans-*specific implementation of Textpresso, the effort was helped by the fact that the C. elegans community is somewhat disciplined in choosing names and WormBase includes names of interest. Of course, there is the danger that entities not listed in WormBase (and therefore in our lexicon) will be missed in our system, and those cases are of special interest to curators (of WormBase) and researchers, such as newly defined genes or newly isolated alleles. Dictionaries tend to be incomplete and turn stale rapidly, because of the issues of synonyms, lack of naming conventions, and the rapid pace of scientific discovery. Thus, we do not rely only on WormBase, but maintain an independent, Textpresso-specific part of the lexicon.
### Technical aspects of the system. {#s4a4}
[Figure 4](#pbio-0020309-g004){ref-type="fig"} shows the details of database preparation. The regular hexagons indicate the sources from which Textpresso is built. The PDF collection was converted to plain text by a software package written by Robert Li at Caltech. The development of such a software tool had become necessary, as current PDF-to-text converters do not comply with the typesetting of each journal, i.e., footnotes, headers, figure captions, and two-column texts in general are dispersed and mixed up senselessly in the converted text. The application works with templates that specify the structure and fonts used in a particular journal and uses this information to convert the articles correctly. A high-fidelity conversion is crucial for any information retrieval and extraction application. The software will be made available at the GMOD Web site (<http://www.gmod.org>). While this manuscript was being written, a new version (2.0.2) of XPDF (<http://www.foolabs.com/xpdf/>) was released. This version, unlike its predecessors, does a superb job in converting PDF into a congruent stream of plain text.
Additional bibliographic data of references for which PDFs are not available are imported from WormBase (symbolized as "WormBase data" in [Figure 4](#pbio-0020309-g004){ref-type="fig"}). These are mainly abstracts from various meetings. The data collected from our primary sources are treated in two different ways. Author, year, and citation information are deposited "as is" into the database, while abstracts, titles, and full texts are further processed. First, the texts are tokenized. Our tokenizer script reads the ASCII text derived from the conversion from PDF and splits the text into individual sentences based on the end-of-sentence period, where words hyphenated at the end of a line are concatenated and instances of periods within sentences (which are used mainly in technical terms and entity names) are ignored. The script also adds an extra space preceding any instance of punctuation within a sentence, which is a requirement for the Brill tagger ([@pbio-0020309-Brill1]), a publicly available part-of-speech tagger, to attach 36 different grammatical tags to each tokenized word. The tagger has been trained specifically to handle the C. elegans literature, and additional tagging rules are applied. For example, gene names are forced to be tagged as nouns. The grammatical tags are not further used in the current Textpresso system. After this preprocessing step, the corpus of titles, abstracts, and full texts is marked up using the lexicon of the ontology (PERL expressions), as explained in Results and exemplified in [Figure 1](#pbio-0020309-g001){ref-type="fig"}. The tags contain the name of the category as well as all attributes that apply to a matched term. Terms that are not matched by any of the 14,500 PERL expressions are given the tag \<text\>, one token at a time.
The corpus of searchable full texts, abstracts, and titles has 1,035,000 sentences. A total of 351,000 keywords have been indexed, covering 19,180,000 words in the texts. The semantic mark-up yields a total of 24,542,000 tags. [Table 3](#pbio-0020309-t003){ref-type="table"} shows the distribution of tags. The number of meaningful tags (the ones that are not just \<text\>) is only 15,577,368, or 15.04 tags per sentence. An average of 5.5 tags per sentence are of scientific interest, i.e., are either biological entities or words that describe a relationship or characterize an entity.
When displaying sentences and paragraphs, Textpresso provides links to report pages of several biological entities, such as proteins, transgenes, alleles, cells, phenotypes, strains, clones, and loci. There are a total of 165,000 different entities in WormBase to which Textpresso links, including links to journal articles and PubMed. All these links are produced statically and again deposited on disk for fast retrieval, and these data are referred to as "Textpresso data" in [Figure 4](#pbio-0020309-g004){ref-type="fig"}. In this way the actual link is not made on the fly from generic URLs, and the response time for queries remains short.
We generated an exhaustive keyword and category index for the whole corpus. This index makes the search extremely fast, using rapid file access algorithms. All keywords and tags in the corpus are indexed. Also, all terms in the corpus that have a report page in WormBase are indexed. For 2,700 full-text articles and 16,300 abstracts, the index takes up 1.7 Gb.
The interfaces for submitting queries and customizing display options are written as CGI scripts. They are supported by simple HTML pages that contain documentation. The Web site runs with a RedHat Linux operating system and an Apache http server. No special changes to the standard configuration are required. The Web interface accesses the custom-made Textpresso database; no commercial-grade database systems have been used. It takes 2--3 d to build the complete 6.9-Gb database.
### Methodology of evaluation. {#s4a5}
For the preliminary study, a query was formulated using three category rows of the Textpresso "advanced retrieval" interface to identify sentences containing gene-gene interaction data from a test set of eight full-text journal articles (see [Table 5](#pbio-0020309-t005){ref-type="table"}): the PMID:11994313 ([@pbio-0020309-Norman1]), PMID:12091304 ([@pbio-0020309-Alper1]), PMID:12051826 ([@pbio-0020309-Maduzia1]), PMID:12110170 ([@pbio-0020309-Francis1]), PMID:12110172 ([@pbio-0020309-Bei1]), PMID:12065745 ([@pbio-0020309-Scott1]), PMID:12006612 ([@pbio-0020309-Piekny1]), and PMID:12062054 ([@pbio-0020309-Boxem1]). In the top row of the advanced retrieval tool the "association" ontology was selected in the "category or keyword" column. No other changes in the first row were made, which implies that no subcategory or specification was selected, and the occurrences of association terms in one sentence were "greater than 0." In the second row, the Boolean operator "or" and the category "regulation" were selected, with no further specification, again asking the machine to return sentences with at least one regulation term. Finally, in the third row, the category "gene" was chosen, with a specification of "named" and an occurrence of "greater than 1." The Boolean operator to connect this row with the former ones is "and." All other values remained as default, resulting in no further query specification. As the "advanced retrieval" search engine processes queries sequentially from the top row to the bottom row, this query asks to return sentences with at least one association or regulation term in conjunction with at least two genes mentioned by name.
For the semiautomatic information extraction from text, the same query was utilized as above. In addition, sentences that did not mention at least two uniquely named genes were eliminated.
This work was supported in part by a grant (\# P41 HG02223) from the National Human Genome Research Institute at the United States National Institutes of Health. HMM was a participant in the Initiative in Computational Molecular Biology, which was funded by the Burroughs Wellcome Fund Interfaces program, and was a Howard Hughes Medical Institute Associate, with which Paul W. Sternberg is an Investigator. We thank Juancarlos Chan for programming help, Andrei Petcherski for his help with evaluating the Textpresso system, Robert Li for developing the PDF-to-text conversion software package, and Daniel Wang for the continued acquisition of papers. We thank Igor Antoshechkin, Kimberly Van Auken, Carol Bastiani, Ranjana Kishore, Raymond Lee, Alok Saldanha, Erich Schwarz, Weiwei Zhong, and the anonymous referees for helpful comments on the manuscript.
**Conflicts of interest.** The authors have declared that no conflicts of interest exist.
**Author contributions.** HMM, EEK, and PWS conceived and designed the experiments. HMM, EEK, and PWS performed the experiments. HMM, EEK, and PWS analyzed the data. HMM, EEK, PWS contributed reagents/materials/analysis tools. HMM, EEK, and PWS wrote the paper.
Academic Editor: Michael Ashburner, University of Cambridge
Citation: Müller HM, Kenny EE, Sternberg PW (2004) Textpresso: An ontology-based information retrieval and extraction system for biological literature. PLoS Biol 2(11): e309.
CGC
: *Caenorhabditis* Genetics Center
GMOD
: Generic Model Organism Database
GO
: Gene Ontology
PERL
: Practical Extraction and Report Language
PMID
: PubMed unique identifier
SNOMED
: Systemized Nomenclature of Medicine
UMLS
: Unified Medical Language System
XML
: eXtensible Markup Language
XPDF
: a PDF viewer for X
|
PubMed Central
|
2024-06-05T03:55:47.794352
|
2004-9-21
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517822/",
"journal": "PLoS Biol. 2004 Nov 21; 2(11):e309",
"authors": [
{
"first": "Hans-Michael",
"last": "Müller"
},
{
"first": "Eimear E",
"last": "Kenny"
},
{
"first": "Paul W",
"last": "Sternberg"
}
]
}
|
PMC517823
|
Introduction {#s1}
============
GTPases comprise a superfamily of proteins that provide molecular switches to regulate many cellular processes, including translation, signal transduction, cytoskeletal organization, vesicle transport, nuclear transport, and spindle assembly ([@pbio-0020320-Gilman1]; [@pbio-0020320-Bourne1]). In many cases, the GTPases exert their regulatory function through a "GTPase switch" mechanism ([@pbio-0020320-Bourne1]) in which the GTPase assumes two alternative conformational states: an active, GTP-bound state and an inactive, GDP-bound state. Each state is kinetically stable, and interconversion between these states is facilitated by external regulatory factors, such as GTPase-activating proteins (GAPs) and guanine nucleotide exchange factors (GEFs).
Two homologous GTPases, one in the signal recognition particle (SRP) and one in the SRP receptor (SR; called Ffh and FtsY in bacteria, respectively), mediate the cotranslational targeting of membrane and secretory proteins to the eukaryotic endoplasmic reticulum (ER) membrane or the bacterial plasma membrane. During the targeting reaction, SRP and SR switch between different functional states ([@pbio-0020320-Walter1]; [@pbio-0020320-Keenan1]). SRP first binds to a nascent polypeptide that contains a signal sequence as it emerges from the ribosome ([@pbio-0020320-Walter2]; [@pbio-0020320-Pool1]). The ribosome•nascent chain complex (RNC) is then delivered to the membrane via an interaction between the GTP-bound forms of SRP and SR. Upon arrival at the membrane, SRP releases its "cargo," the RNC, to the translocation apparatus or the translocon ([@pbio-0020320-Walter2]; [@pbio-0020320-Gilmore1], [@pbio-0020320-Gilmore2]). Once the RNC is released, both SRP and SR hydrolyze their bound GTPs to drive dissociation of the SRP•SR complex, allowing the SRP and SR components to be recycled ([@pbio-0020320-Connolly1]; [@pbio-0020320-Connolly2]). Analogous to other GTPases, the switch in the functional states of SRP and SR is coordinated by their GTPase cycles.
However, the regulatory mechanism of the SRP family GTPases provides a notable exception to the "GTPase switch" paradigm. Unlike many other GTPases, no external GEFs or GAPs are known for the SRP and SR GTPases. Instead, Ffh and FtsY bind nucleotides weakly, and nucleotide dissociation and exchange are very fast ([@pbio-0020320-Moser1]; [@pbio-0020320-Jagath1]; [@pbio-0020320-Peluso2]); thus, there is no requirement for external GEFs to facilitate their conversion from the GDP- to GTP-bound forms. In addition, Ffh and FtsY reciprocally activate each other\'s GTPase activity upon formation of the Ffh•FtsY complex ([@pbio-0020320-Powers1]; [@pbio-0020320-Peluso2]); thus, there is no requirement for external GAPs to facilitate their conversion from the GTP- to GDP-bound forms.
The structure of Ffh and FtsY also defines them as a unique subgroup in the GTPase superfamily ([@pbio-0020320-Freymann1]; [@pbio-0020320-Montoya1]). Both proteins contain a central GTPase "G" domain that shares homology with the classical *Ras* GTPase fold. In addition, all SRP family GTPases contain a unique "N" domain, which together with the G domain forms a structural and functional unit called the NG domain. The crystal structures of the individual Ffh and FtsY NG domains show that both proteins have a wide-open GTP-binding pocket, and the apoforms of these proteins are stabilized by a network of side-chain interactions in the empty active site ([@pbio-0020320-Freymann1]; [@pbio-0020320-Montoya1]); the need to reposition the active-site residues for binding nucleotides may contribute to the low nucleotide affinities of these GTPases. Recently, the crystal structure of the GTP analog-bound Ffh•FtsY complex was determined ([@pbio-0020320-Egea1]; [@pbio-0020320-Focia1]). The two proteins form a pseudosymmetrical heterodimer via an extensive interaction surface that includes both the G and N domains. A composite active site is formed at the interface in which the two nucleotides are "twinned" in a head-to-tail manner, forming reciprocal hydrogen bonds between the ribose 3′-OH of one GTP and the γ-phosphate of the other. Hydrolysis of the nucleotide at each active site is also facilitated by multiple catalytic groups from its own protein, brought into the active site by conformational rearrangements that occur upon complex formation. These substrate-substrate interactions in *trans* and active site-substrate interactions in *cis* thus provide a novel mechanism for the GTP-dependent association and reciprocal activation between the two GTPases.
The unique structural and functional properties of the SRP and SR GTPases raise intriguing questions: (i) How do these GTPases act as reciprocal activating proteins for one another, and (ii) how does the SRP family of GTPases switch between the "on" and "off" states, as the GTPases are predominantly in the GTP-bound state as they enter the targeting cycle and no stable, GDP-bound state exists under cellular conditions?
In a previous paper, we described a scanning mutagenesis study of the conserved surface residues of Escherichia coli FtsY and showed that mutations that have deleterious effects on the Ffh-FtsY interaction define a large surface patch on FtsY that lies on its interaction surface with Ffh identified in the crystal structure ([@pbio-0020320-Egea1]). Here we show that these mutants can be categorized into distinct classes, each defective at a different step during the Ffh-FtsY interaction, suggesting that the Ffh-FtsY interaction is a dynamic process that involves multiple experimentally separable conformational changes. Thus, the mutants allow us to glean mechanistic insights into the alternative molecular switch that allows the SRP and SR to change their functional states.
Results {#s2}
=======
In light of the recently published structures of the Ffh•FtsY complex, kinetic analyses become increasingly valuable in unraveling the dynamic nature of the Ffh-FtsY interaction. To this end, we generated 45 site-directed mutants that were made in surface residues of FtsY. As previously described ([@pbio-0020320-Egea1]), all but one mutation that functionally compromise the Ffh-FtsY interaction map to the extensive interaction surface between the two proteins ([Figure 1](#pbio-0020320-g001){ref-type="fig"}). As we show below, dissection of the mutational effect on individual steps allows us to divide the deleterious mutants into distinct classes: Class I mutants primarily affect complex formation, Class II mutants primarily affect the reciprocal GTPase activation, Class III mutants are defective in both steps, and Class IV or half-site mutants block the activation of only one GTPase site in the complex ([Table 1](#pbio-0020320-t001){ref-type="table"}).
::: {#pbio-0020320-g001 .fig}
Figure 1
::: {.caption}
###### The Mutational Effects in E. coli FtsY Mapped onto the Crystal Structure of the Ffh•FtsY Complex
The bound nucleotides are shown as black sticks, and the dotted white lines in the interface view outline the contact surface of Ffh with FtsY. The colors denote different classes of mutational effects: blue, Class I mutants defective in complex formation; red, Class II mutants defective in the reciprocal GTPase activation; magenta, Class III mutants defective in both steps; green, Class IV mutants exhibiting half-site reactivity; yellow, Class V or neutral mutants.
:::
:::
::: {#pbio-0020320-t001 .table-wrap}
Table 1
::: {.caption}
###### Summary of Different Classes of Mutational Effects
:::
To facilitate comparison with the crystal structures solved using the Thermus aquaticus proteins, for each residue mutated in E. coli FtsY, the corresponding residue number in the T. aquaticus Ffh sequence is indicated in parentheses
The *k~cat~/K~m~* values for each mutant were previously reported as supplementary material in [@pbio-0020320-Egea1]. The compromised activity of these mutants is not due to defects in the folding of the mutant protein, as the basal GTP-binding and hydrolysis activities of all the mutants are either unaffected or only moderately (2- to 8-fold) reduced ([@pbio-0020320-Egea1])
:::
All of the Class I--III mutants have deleterious effects on the reciprocally stimulated GTPase reaction between Ffh and FtsY ([Figure 2](#pbio-0020320-g002){ref-type="fig"}). The protein concentration dependence of this reaction further indicates that the defects in these mutants can be functionally distinguished, allowing us to group them into different classes. For Class I mutants (see [Figure 1](#pbio-0020320-g001){ref-type="fig"}, blue), the maximal rate of GTP hydrolysis is within 3-fold of that of wild-type FtsY, although a significantly higher concentration of mutant than wild-type FtsY is required to reach saturation (data for a representative mutant are shown in [Figure 2](#pbio-0020320-g002){ref-type="fig"}A). Thus, these mutants are primarily defective in the Ffh-FtsY complex formation step, but the reciprocal activation of GTP hydrolysis is not significantly affected once the complex is forced to form at the higher FtsY concentrations.
::: {#pbio-0020320-g002 .fig}
Figure 2
::: {.caption}
###### The Effect of FtsY Mutations on the Reciprocally Stimulated GTPase Reaction between Ffh and FtsY
The stimulated GTPase reactions of (A) mutant FtsYE475(274)K (•), (B) FtsY T307(112)A (•), (C) FtsYA335(140)W (•), (D) FtsYR333(138)A (•), and wild-type FtsY (○) were determined as described in [Materials and Methods](#s4){ref-type="sec"}. The insets show the reaction curve of the mutant FtsYs on an expanded scale.
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In contrast, for Class II and III mutants, the rate of GTPase reaction remains slow even at saturating concentrations of FtsY (data for representative mutants are shown in [Figure 2](#pbio-0020320-g002){ref-type="fig"}B--[2](#pbio-0020320-g002){ref-type="fig"}D). There are two possible explanations for the defects of these mutants: (i) The reciprocal GTPase activation in the Ffh•FtsY complex is compromised, or (ii) both complex formation and reciprocal GTPase activation are affected. The concentration dependence of the stimulated GTPase reaction, however, does not provide an unambiguous way to distinguish between these possibilities, because different steps become rate limiting at different concentration regimes. For wild-type FtsY, the reaction is limited by complex formation with subsaturating FtsY, but becomes limited by GTP hydrolysis with saturating FtsY ([@pbio-0020320-Peluso2]). Thus, for wild-type FtsY the *K~m~* of the reaction (1 μM) does not equal the *K~d~* (16 nM) of the Ffh•FtsY complex. Likewise, the *K~m~* of the reaction with mutant FtsY does not necessarily equal the *K~d~* of the mutant Ffh•FtsY complex, and thus cannot meaningfully distinguish between mutational effects on complex formation and GTPase activation.
To circumvent these problems, we devised an assay to determine the ability of each FtsY mutant to inhibit the interaction of wild-type FtsY with Ffh. This assay allowed us to monitor selectively complex formation between Ffh and the FtsY mutants. The conditions of the assay were designed so that in the absence of any mutant FtsY as an inhibitor, a robust GTPase reaction mediated by Ffh and wild-type FtsY was observed ([Figure 3](#pbio-0020320-g003){ref-type="fig"}A, *k~0~*). Addition of mutant FtsY \[FtsY(mt)\], which can form a complex with Ffh, will sequester the Ffh molecules into a less active Ffh•FtsY(mt) complex (*k~1~* ≪ *k~0~;* see [Figure 2](#pbio-0020320-g002){ref-type="fig"}B--[](#pbio-0020320-g002){ref-type="fig"}D), thus inhibiting the observed GTPase reaction. The reaction was carried out with subsaturating concentrations of wild-type FtsY to ensure that Ffh molecules were predominantly in the free form and able to bind FtsY(mt); under these conditions, the inhibition constant *K~i~* equals *K~d~,* the dissociation constant of the Ffh•FtsY(mt) complex.
::: {#pbio-0020320-g003 .fig}
Figure 3
::: {.caption}
###### Determination of Complex Formation between Ffh and FtsY Mutants
\(A) Inhibition assay for determining the affinity of mutant FtsY proteins for Ffh, as described in the text and in [Materials and Methods](#s4){ref-type="sec"}.
(B and C) Representative inhibition curves are shown for FtsY mutants (B) T307(112)A and (C) A335(140)W. The data were fit to [equation 3](#pbio-0020320-e003){ref-type="disp-formula"} in [Materials and Methods](#s4){ref-type="sec"}.
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:::
Most of the mutants inhibit the reaction only weakly, with inhibition constants about 10^2^-fold weaker than the affinity of wild-type FtsY for Ffh (data for a representative mutant are shown in [Figure 3](#pbio-0020320-g003){ref-type="fig"}B; a complete list of *K~i~* values is given in [Table 2](#pbio-0020320-t002){ref-type="table"}). These mutants are therefore defective in both complex formation and GTPase activation (defined as Class III mutants; see [Figure 1](#pbio-0020320-g001){ref-type="fig"}, magenta). These mutations involve residues throughout the entire G domain, including the interface between the N and G domains (see [Figure 1](#pbio-0020320-g001){ref-type="fig"}). Thus, complex formation and GTPase activation are highly coupled. This is presumably due to the fact that the two GTPs are bound at a composite active site formed at the interface, so that many residues that contribute to GTP hydrolysis are also crucial for formation of the interface.
::: {#pbio-0020320-t002 .table-wrap}
Table 2
::: {.caption}
###### Affinity of FtsY Mutants for Ffh Determined from the Inhibition Assay
:::
:::
In contrast, six mutants (involving mutation of five residues) stood out as strong inhibitors. These mutants (here defined as Class II mutants; see [Figure 1](#pbio-0020320-g001){ref-type="fig"}, red) can therefore form tight complexes with Ffh and are primarily compromised in the reciprocal activation of GTP hydrolysis. One of these, FtsY A335(140)W, showed an inhibition constant of 16 nM ([Figure 3](#pbio-0020320-g003){ref-type="fig"}C), indistinguishable from the *K~d~* of the wild-type Ffh•FtsY complex ([@pbio-0020320-Peluso1]). Moreover, the association and dissociation rate constants ([Figure 4](#pbio-0020320-g004){ref-type="fig"}B and [4](#pbio-0020320-g004){ref-type="fig"}C, respectively) for complex formation are also indistinguishable between mutant FtsY A335(140)W and wild-type FtsY, as measured using tryptophan fluorescence changes upon complex formation ([Figure 4](#pbio-0020320-g004){ref-type="fig"}A) as previously described ([@pbio-0020320-Jagath2]; [@pbio-0020320-Peluso1]). Like the wild-type FtsY, this fluorescence change upon complex formation requires the presence of GTP or the nonhydrolyzable GTP analog GMPPNP (5′-guanylylimidodiphosphate; unpublished data), indicating that the interaction of the Class II mutants with Ffh remains nucleotide dependent. The remaining Class II mutants also have inhibition constants well in the submicromolar range, albeit 10-fold higher than that of FtsY A335(140)W ([Table 2](#pbio-0020320-t002){ref-type="table"}).
::: {#pbio-0020320-g004 .fig}
Figure 4
::: {.caption}
###### Fluorescence Characterization of Complex Formation between Ffh and Mutant FtsYA335(140)W
\(A) The tryptophan fluorescence of mutant FtsYA335(140)W changes upon complex formation with Ffh. Complex formation was initiated by the addition of Mg^2+^, as described previously ([@pbio-0020320-Shan1]). Other Class II mutants do not exhibit as significant a fluorescence change (unpublished data). Thus, the conformational change that alters the environment surrounding the fluorescent W343(148) does not occur even though these mutants can form stable complexes with Ffh.
\(B) Association rate constants for complex formation with mutant FtsYA335(140)W (○) and wild-type FtsY(•). Linear fits to the data gave association rate constants of 6.36 × 10^4^ and 6.34 × 104 M^−1^ s^−1^ for wild-type and mutant FtsY, respectively.
\(C) Dissociation rate constants of the Ffh•FtsY complexes formed by mutant FtsYA335(140)W (upper curve) and wild-type FtsY (lower curve). First-order fits to the data gave dissociation rate constants of 3.6 × 10^−3^ and 4.2 × 10^−3^ s^−1^ for wild-type and mutant FtsY, respectively.
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:::
The mutants described above were identified by analyzing the sum of the two GTP hydrolysis reactions from both Ffh and FtsY. All of the Class II and III mutants must be defective in *both* GTP hydrolysis events; inhibition of only one GTPase site would be predicted to give at most a 2-fold effect because both sites hydrolyze GTP at about the same rate. Half-site mutants defective in GTP hydrolysis in only one active site, however, could be hidden among the Class I and the neutral mutants. To explore this possibility, we monitored the two hydrolysis events individually. To this end, we took advantage of a xanthosine-5′-triphosphate (XTP)-specific Ffh mutant, Ffh D251(248)N. Asp251(248), located in the GTP-binding consensus motif, is conserved throughout the GTPase superfamily and forms a hydrogen bonding network with the N2 and N3 amino protons on the guanine ring ([@pbio-0020320-Hwang1]; [@pbio-0020320-Weijland1]). The Asp → Asn mutation weakens the affinity of Ffh for GTP by 200-fold and increases its affinity for XTP by 10^2^-fold, resulting in a 10^4^-fold switch in nucleotide specificity (SS and PW, unpublished data). In the presence of XTP, Ffh D251(248)N stimulates the GTPase reaction of FtsY and, reciprocally, its XTPase reaction is stimulated by FtsY in the presence of GTP. We therefore used Ffh D251(248)N to monitor the individual hydrolysis events---XTP hydrolysis from Ffh D251(248)N and GTP hydrolysis from the mutant FtsY constructs---in the Ffh D251(248)N•FtsY complex.
As expected, all of the Class II and Class III mutants were defective in both hydrolysis reactions and, similarly, all but one Class I mutant and most of the neutral mutants showed no significant defect in either of the two reactions (unpublished data). Five half-site mutants, however, stood out from the pool of originally categorized Class I and neutral mutants (see [Table 1](#pbio-0020320-t001){ref-type="table"}, Class IV mutants, and [Figure 1](#pbio-0020320-g001){ref-type="fig"}, green). As expected, the sum of the two GTP hydrolysis reactions was impaired by less than 2-fold in the Class IV mutants (data for a representative mutant are shown in [Figure 5](#pbio-0020320-g005){ref-type="fig"}A; data for all the Class IV mutants are summarized in [Table 3](#pbio-0020320-t003){ref-type="table"}, first column). In contrast, the rates of GTP hydrolysis of all Class IV mutants are reduced by 20- to more than 100-fold ([Figure 5](#pbio-0020320-g005){ref-type="fig"}B and [Table 3](#pbio-0020320-t003){ref-type="table"}, second column). The reciprocal reaction reveals the striking asymmetry of the inhibition: XTP hydrolysis from Ffh D251(248)N is reduced by only 2- to 5-fold ([Figure 5](#pbio-0020320-g005){ref-type="fig"}C and [Table 3](#pbio-0020320-t003){ref-type="table"}, third column).
::: {#pbio-0020320-g005 .fig}
Figure 5
::: {.caption}
###### Half-Site Mutants Are Compromised in the Hydrolysis Reaction from the FtsY but Not Ffh Active Site
\(A) The reciprocally stimulated GTPase reaction with wild-type Ffh for wild-type FtsY (○) and mutant FtsYG455(254)W (•).
\(B) The FfhD251N-stimulated GTPase reaction from wild-type FtsY (○) and mutant FtsYG455(254)W (•), determined as described in [Materials and Methods](#s4){ref-type="sec"}.
\(C) The XTP hydrolysis reaction from FfhD251N stimulated by wild-type FtsY (○) and mutant FtsYG455(254)W (•), determined as described in [Materials and Methods](#s4){ref-type="sec"}.
:::
:::
::: {#pbio-0020320-t003 .table-wrap}
Table 3
::: {.caption}
###### Summary of the Relative Reactivity of Class IV(Half-Site) Mutants in the Individual Nucleotide Hydrolysis Reactions from the Two Active Sites: Reaction of FtsY Mutants with XTP-Specific FfhD251N
:::
The reaction rates were determined as described in [Materials and Methods](#s4){ref-type="sec"}, and are listed as relative to that of wild-type FtsY
^a^It is interesting to note that the G454(253)A mutant has the same rate constant as wild-type FtsY for GTP hydrolysis from the ^\*GTP•^Ffh•FtsY^•GTP\*^ complex, even though only one of the two GTPase sites, that from Ffh, is active in the complex formed by the mutant. It is possible that the G454(253) mutation, situated at the interface between the two GTPases, might have slightly altered the conformation of the Ffh GTPase site to allow a faster reaction from this site. Nevertheless, the small magnitude of this effect (\<2-fold) does not warrant a more specific molecular interpretation
:::
To provide additional evidence for half-site reactivity, we introduced three of the Class IV mutations into an XTP-specific FtsY, FtsY D449(248)N, thereby reversing the nucleotide specificity of the two binding partners. Upon complex formation, FtsY D449(248)N becomes XTP specific and reciprocally activates GTP hydrolysis in Ffh. Consistent with the results observed with Ffh D251(248)N, all Class IV mutations thus analyzed reduce the rate of XTP hydrolysis from mutant FtsYs by more than 10^2^-fold, whereas the reciprocal reaction, GTP hydrolysis by Ffh, is reduced only 2- to 4-fold ([Table 4](#pbio-0020320-t004){ref-type="table"}). Thus taken together, Class IV mutations break the symmetry and the remarkable coupling between the two GTPase sites in the Ffh•FtsY complex, such that the nucleotide bound at one active site is hydrolyzed much faster than the nucleotide at the other site.
::: {#pbio-0020320-t004 .table-wrap}
Table 4
::: {.caption}
###### Summary of the Relative Reactivity of Class IV(Half-Site) Mutants in the Individual Nucleotide Hydrolysis Reactions from the Two Active Sites (Continued from [Table 3](#pbio-0020320-t003){ref-type="table"}): Reaction of Ffh with Mutant FtsYs that also Bear the XTP-Specific D449(248)N Mutation
:::
The reaction rates were determined as described in [Materials and Methods](#s4){ref-type="sec"}, and are listed as relative to that of FtsY D449(248)N
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Discussion {#s3}
==========
The mutational analyses described here define four distinct classes of mutants that map to the Ffh-FtsY interface. Each mutant class blocks the reaction in a different way and at a distinct stage, demonstrating that (i) multiple conformational rearrangements are required to form an activated Ffh•FtsY complex and (ii) some rearrangements can be blocked without preventing other rearrangements from taking place. The different classes of mutant interrupt the reaction in different ways, as represented by the states depicted in [Figure 6](#pbio-0020320-g006){ref-type="fig"}A, in the pathway of Ffh•FtsY complex formation and reciprocal GTPase activation. The most plausible interpretation of our analysis and the crystallographic analysis of the Ffh•FtsY complex suggest that each of the states blocked by the mutants represents a step on the pathway for the wild-type protein. However, we cannot rule out that some of the rearrangements could occur independently of one another, in which case their depicted order represents only one of the possibilities. Our analysis leads to the conclusion that perturbations, such as those introduced here by site-specific mutations, can modulate specific conformational changes during the Ffh-FtsY interaction. Each of these states provides a potential regulatory point during the protein-targeting reaction, at which analogous effects could be exerted by the cargoes of SRP and SR---the ribosome, signal sequence, and translocon.
::: {#pbio-0020320-g006 .fig}
Figure 6
::: {.caption}
###### Model for Conformational Changes during Ffh-FtsY Reciprocal GTPase Activation and Implications for the Protein-Targeting Reaction
\(A) Model for conformational changes during formation of an activated Ffh-FtsY complex. Step a is the rearrangement of both proteins from the open to the closed state during complex formation. Step b is the coordinate docking of the IBD loops into the active sites, and step c is the docking of the Arg191s. Step d is the additional rearrangement of residues that completes one or the other GTPase site. Step e is the rearrangement that completes the other active site. GTP can be hydrolyzed from either the hemiactivated complexes (step f) or the activated complex (step g) to drive complex dissociation.
(B--D) Catalytic interactions made by residues exhibiting the Class II phenotype. FtsY is in surface representation, the catalytic residues from FtsY are depicted as red sticks, the nucleotides bound to FtsY and Ffh are in dark green and dark blue, respectively, and the dotted lines depict hydrogen bonds or van der Waals contacts.
\(B) Interaction of IBD loop with GTP in the FtsY active site. The blue ball represents the attacking water molecule (A.W.); the violet red ball represents the active site Mg^2+^.
\(C) Interactions of Asn111(107) at the Ffh-FtsY interface. The residue homologous to Asn111, Gln107 in Ffh, is in violet red.
\(D) Arg195(191) is in a "pending" position. The residue homologous to Arg191 in *Ras,* Gln61, is in violet red.
\(E) Conformational changes in the GTPase domains of SRP and SR provide potential regulatory points during the protein-targeting reaction. Step 1, SR undergoes an open → closed conformational change upon association with the membrane translocon. Step 2, SRP undergoes an open → closed conformational change upon association with the ribosome and nascent polypeptide. Step 3, complex formation between SRP and SR delivers the cargo to the membrane. Step 4, cargo release from SRP allows the SRP•SR complex to undergo additional conformational changes to activate GTP hydrolysis. Step 5, SRP dissociates from SR after GTP is hydrolyzed. Note that steps 1--3 correspond to Ffh-FtsY binding (step a) in the model shown in (A), step 4 corresponds to Ffh•FtsY activation (steps b--e) in the model shown in (A), and step 5 corresponds to Ffh•FtsY complex dissociation (step g) in the model shown in (A).
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Step A: An "Open"-to-"Closed" Conformational Change upon Complex Formation {#s3a}
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We previously showed that FtsY exhibits little discrimination between different nucleotides in its free, uncomplexed form, but gains substantial specificity for GTP only in the Ffh•FtsY complex ([@pbio-0020320-Shan1]). We therefore proposed that upon complex formation, FtsY changes from a floppy, nonspecific "open" state to a more specific, "closed" state in which the nucleotide is better positioned at the active site and contacts between the guanine ring and Asp449(248), the nucleotide specificity determinant, are established ([Figure 6](#pbio-0020320-g006){ref-type="fig"}A, step a). The recently determined crystal structures of the Ffh•FtsY complex support this notion ([@pbio-0020320-Egea1]; [@pbio-0020320-Focia1]). Upon complex formation, a major rearrangement occurs at the N-G domain interface, allowing Asp449(248) to move closer to the guanine ring and form hydrogen bonds, thus explaining the enhanced nucleotide specificity of FtsY upon complex formation. We therefore propose that the N-G domain rearrangement during complex formation is central to the open → closed conformational change.
The crystal structure of the Ffh•FtsY complex also shows that Ffh undergoes similar N-G domain rearrangements upon complex formation, although the effects of this rearrangement on nucleotide specificity are less apparent, as free Ffh already displays significant discrimination between nucleotides (SS and PW, unpublished data). Indeed, mutations at the N-G domain interface in either Ffh or FtsY impair complex formation, supporting the functional importance of this rearrangement in both binding partners ([@pbio-0020320-Lu1]). We propose that both free GTPases oscillate between the open and closed states, and that complex formation drives the equilibrium to the closed state ([Figure 6](#pbio-0020320-g006){ref-type="fig"}A, step a).
Steps B and C: Docking of Active-Site Residues at the Interface {#s3b}
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The Class II mutants allow stable complexes to form but are specifically defective in reciprocal GTPase activation, thus suggesting that the reaction occurs in two steps that can be uncoupled. Further, all of the Class II mutants exhibit significant nucleotide specificity in their interaction with Ffh (unpublished data), suggesting that the mutant proteins have assumed the closed conformation in the complex. Because single mutations in FtsY can disrupt GTPase activation in *both* active sites, the defect in these mutants is not a consequence of simply removing a catalytic residue. Rather, this suggests that even after a stable, closed complex is formed, activation requires additional conformational changes (the "docking" process) that align active-site residues with respect to the bound nucleotides in *both* GTPase sites ([Figure 6](#pbio-0020320-g006){ref-type="fig"}A, closed →→ docked). Furthermore, as both sites are affected, these rearrangements are highly cooperative and bridge the interface between the two GTPases.
The model in [Figure 6](#pbio-0020320-g006){ref-type="fig"} portrays the docking event as two sequential steps: Step b represents the concerted rearrangements of the IBD loops that lead to the predocked state ([@pbio-0020320-Egea1]; [@pbio-0020320-Focia1]). Step c represents the additional rearrangements of the Arg191s in both Ffh and FtsY to form the docked complex. The observation that the crystal structure is "trapped" in a state with the IBD loop docked but with the Arg191s undocked suggests that docking of the IBD loop either precedes that of the Arg191s, as depicted in [Figure 6](#pbio-0020320-g006){ref-type="fig"}A, or that these two rearrangements can occur independently of one another.
Evidence for the importance of a concerted rearrangement of the IBD loops (step b) comes from three of the Class II mutants, \[R333(138)A, A335(140)W, and A336(141)W\], which all map to the conserved IBD loop (D^135^TFRAAA). As concluded from the structure, this loop can move relatively independently from the rest of the protein ([@pbio-0020320-Egea1]; [@pbio-0020320-Focia1]). As a result, additional interface contacts are formed between the two loops, and multiple catalytic residues are brought into the active site and positioned close to the nucleotides. [Figure 6](#pbio-0020320-g006){ref-type="fig"}B highlights the catalytic interactions contributed by these residues: Asp139(135) coordinates the attacking water (A.W.), Arg142(138) coordinates the γ-phosphate oxygen, and Gln148(144) coordinates the β-phosphate oxygen and the active site Mg^2+^. Most importantly, disruption of any of these contacts also destroys activation of the other GTPase site. Therefore, coordinate docking of the IBD loops from *both* interacting partners into their respective active sites is crucial for reciprocal GTPase activation ([Figure 6](#pbio-0020320-g006){ref-type="fig"}A, step b).
Mutation of Asn302(107) to either Ala or Trp also results in a Class II phenotype. This residue in FtsY hydrogen bonds across the interface to the ribose 3′-OH of the nucleotide bound to Ffh. The ribose 3′-OH reciprocally donates a hydrogen bond back to the γ-phosphate of the twinned substrate in FtsY \[[Figure 6](#pbio-0020320-g006){ref-type="fig"}C, N111(107)\]. This interaction is matched by a contact between Q107 of Ffh and the ribose of the nucleotide bound to FtsY ([Figure 6](#pbio-0020320-g006){ref-type="fig"}C, Q107). These side chains are the only ones that interact with the opposing substrate, and, in addition to the IBD loops, form a second network of catalytically important interactions that bridges the two active sites. Because both of these networks are observed in the crystal structures, we cannot distinguish at this time whether the two networks are assembled coordinately, sequentially, or independently. Potentially, therefore, step b in [Figure 6](#pbio-0020320-g006){ref-type="fig"}A could be further subdivided.
In contrast to the other Class II mutants, the side chains of the Arg191s point away from the γ-phosphate group in the crystal structure. By analogy to the homologous residue Gln61 in the *Ras*•*Ras*GAP structure, which contacts the γ-phosphate, [@pbio-0020320-Focia1] proposed that Arg191s are in a "pending" position, forming a "latch" structure that requires additional rearrangements to activate the GTPases, as depicted in [Figure 6](#pbio-0020320-g006){ref-type="fig"}A (step c) and [6](#pbio-0020320-g006){ref-type="fig"}D. The deleterious effect on catalysis displayed by the Arg386(191) mutant strongly supports this notion. Because *both* active sites are affected by the Arg386(191) mutation, the consequences of this additional contact must be transmitted across the interface, perhaps resulting in a slight rearrangement of the twinned GTP molecule to optimize active site-substrate interactions in the other GTPase.
Step D: Conformational Changes to Activate Individual GTPases {#s3c}
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Remarkably, the Class IV, or half-site, mutants demonstrate that activation of the individual GTPase sites can be further uncoupled from one another. This suggests that after all the molecular rearrangements required to activate the interacting GTPase have been accomplished, additional rearrangements are required to complete each active site. Further, these rearrangements either occur late in the docking process ([Figure 6](#pbio-0020320-g006){ref-type="fig"}A) or they occur independently of the various docking steps. In contrast to the docking steps that are tightly coupled between the two active sites, these additional rearrangements can occur independently in one GTPase but not the other, leading to the formation of "hemiactivated" intermediates ([Figure 6](#pbio-0020320-g006){ref-type="fig"}A, step d).
Four of the five Class IV half-site mutants (see [Figure 1](#pbio-0020320-g001){ref-type="fig"}, green) are positioned away from the γ-phosphate group: G454(253) and G455(254) map to the conserved DARGG motif at the NG domain interface, L480(279) maps to the "closing loop" that packs against the guanine base, and Q430(229) is situated away from any residue for which a function can be assigned intuitively. The mechanistic interpretation of these mutants will have to await structural information from crystallization of the mutant proteins and additional characterization of the dynamics during Ffh-FtsY association and activation.
Importantly, all of the half-site mutants are less than 2-fold reduced in the rate of multiple-turnover GTPase reactions, indicating that multiple cycles of Ffh•FtsY complex formation and dissociation can still occur efficiently. Thus, only one of the two bound GTPs needs to be hydrolyzed in order for the Ffh•FtsY complex to dissociate ([Figure 6](#pbio-0020320-g006){ref-type="fig"}A, step f). In the wild-type Ffh•FtsY complex, it is well established that both nucleotides are hydrolyzed during each turnover. Thus, after a hemiactivated state is formed, rearrangement of the other GTPase site must follow on a time scale faster than the rate of GTP hydrolysis or complex dissociation ([Figure 6](#pbio-0020320-g006){ref-type="fig"}A, step e), so that a fully activated complex is formed and both GTP molecules are hydrolyzed ([Figure 6](#pbio-0020320-g006){ref-type="fig"}A, step g).
Implications for the Protein-Targeting Reaction {#s3d}
-----------------------------------------------
During protein targeting, SRP and SR are thought to interact with their respective cargoes, the RNC and the translocon. Thus, targeting involves a series of ordered steps in which cargo binding and release must occur at the proper stages. Each of the conformational changes in the GTPase domains of SRP and SR described above provides a potential point at which such control can be exerted, thereby coordinating the loading and unloading of cargoes ([Figure 6](#pbio-0020320-g006){ref-type="fig"}E).
One possible view is that the switch from open to closed conformation provides the regulatory point that distinguishes free from cargo-loaded SRP and SR. Under cellular conditions, both SRP and SR are likely to be GTP bound before entering the targeting reaction. Thus, GTP binding per se cannot be the switch that sets these GTPases to the "on" state, as happens with classical signaling GTPases. Free SRP receptor is predominantly in the open conformation; interaction with phospholipid membranes and the translocon could shift its conformational equilibrium towards the closed state ([Figure 6](#pbio-0020320-g006){ref-type="fig"}E, step 1), thereby facilitating its interaction with SRP. Reciprocally, the SRP could undergo a similar open-to-closed conformational change, facilitated by association with the RNC ([Figure 6](#pbio-0020320-g006){ref-type="fig"}E, step 2). In this view, the SRP and receptor molecules that are prebound to their respective cargoes are "primed" to interact with each other, ensuring efficient delivery of cargo proteins to the membrane and avoiding futile cycles of SRP-receptor interactions ([Figure 6](#pbio-0020320-g006){ref-type="fig"}E, step 3).
Once at the membrane, it is crucial that SRP releases its cargo to the translocon before it dissociates from the SRP receptor. Because both GTPases reciprocally activate each other, regulation of GTP hydrolysis must involve mechanisms different from regulation by external GAPs, as happens with classical signaling GTPases. The conformational changes required for GTPase activation ([Figure 6](#pbio-0020320-g006){ref-type="fig"}A, steps b--d) provide the potential to control the relative timing of the cargo release versus GTP hydrolysis steps. In solution, the SRP•SR complex exists only transiently, with a half-life of less than 1 s, because rapid GTP hydrolysis drives complex dissociation. However, RNC, SRP, and SR can be cross-linked to each other in the absence of the translocon ([@pbio-0020320-Song1]). Although this does not provide conclusive evidence, it is an attractive possibility that RNC could delay GTP hydrolysis, possibly by inhibiting one of the docking steps described here ([Figure 6](#pbio-0020320-g006){ref-type="fig"}A, steps b--d), thereby ensuring that the cargo is released from SRP before GTP is hydrolyzed ([Figure 6](#pbio-0020320-g006){ref-type="fig"}E, step 4). Release of the cargo then allows the SRP•SR complex to undergo the additional rearrangements to activate GTP hydrolysis, leading to complex dissociation ([Figure 6](#pbio-0020320-g006){ref-type="fig"}E, step 5).
The demonstration that hemiactivated complexes can exist and that hydrolysis of a single GTP is sufficient for complex dissociation ([Figure 6](#pbio-0020320-g006){ref-type="fig"}A, steps d and f) raises intriguing questions as to the precise role of the individual GTP hydrolysis events during each cycle of the targeting reaction. Potentially, asymmetric, half-site hydrolysis could be used to introduce branches into the pathway, leading to abortive targeting reactions. In this way, the GTP hydrolysis events could have proofreading roles similar to those proposed for translation elongation factors to help ensure the fidelity of protein targeting. The analysis described here therefore not only dissects the reciprocal GTPase activation events into a set of conformational rearrangements, but also provides invaluable tools to assess the role of these states as potential control points in the targeting reaction.
Materials and Methods {#s4}
=====================
{#s4a}
### Cloning and purification of mutant proteins. {#s4a1}
Expression plasmids for mutant FtsYs were constructed from that for wild-type FtsY(47--497) using the QuickChange Mutagenesis protocol (Stratagene, La Jolla, California, United States). Mutant FtsY proteins were expressed and purified using the same procedure as that for wild-type FtsY ([@pbio-0020320-Powers2]; [@pbio-0020320-Peluso2]).
### Kinetics. {#s4a2}
GTP hydrolysis reactions were followed and analyzed as described in [@pbio-0020320-Peluso2]. The reciprocally stimulated GTPase reactions between Ffh and FtsY were measured in multiple-turnover experiments (\[GTP\] \> \[E\]) with a small fixed amount of Ffh and varying amounts of wild-type or mutant FtsY, and the FtsY concentration dependences were analyzed as described in [@pbio-0020320-Peluso2].
The Ffh(D251N)-stimulated GTPase reaction of FtsY was determined in single-turnover experiments in the presence of 10 μM FtsY and varying amounts of Ffh(D251N), with 50 μM XTP present to selectively occupy the Ffh(D251N) active site \[ = 0.37 and 460 μM for Ffh(D251N) and FtsY, respectively; SS and PW, unpublished data; [@pbio-0020320-Shan1]\]. The concentration dependence of the observed GTPase rate constant is fit to [equation 1](#pbio-0020320-e001){ref-type="disp-formula"}, in which *k~max~* is the maximal rate constant with saturating Ffh(D251N), and *K~1/2~* is the concentration of Ffh(D251N) required to reach half saturation.
The reciprocal reaction, the FtsY-stimulated XTPase reaction of Ffh(D251N), was determined in single-turnover experiments with 1 μM Ffh(D251N) and varying amounts of FtsY. 50 μM GTP was present to ensure that FtsY was selectively bound with GTP \[ = 15 μM and 101 μM for FtsY and Ffh(D251N), respectively; SS and PW, unpublished data; [@pbio-0020320-Shan1]\]. The FtsY concentration dependence is fit to [equation 2](#pbio-0020320-e002){ref-type="disp-formula"}, in which *k~max~* is the maximal rate constant with saturating FtsY, and *K~1/2~* is the concentration of FtsY required to reach half saturation.
The affinity of mutant FtsY proteins for Ffh was determined using an inhibition assay that measures the ability of mutant FtsYs \[FtsY(mt)\] to inhibit the interaction between Ffh and wild-type FtsY, as described in detail in the text (see [Figure 3](#pbio-0020320-g003){ref-type="fig"}A). The data are fit to [equation 3](#pbio-0020320-e003){ref-type="disp-formula"}, derived from [Figure 3](#pbio-0020320-g003){ref-type="fig"}A.
### Fluorescence measurements. {#s4a3}
Fluorescence emission spectra were acquired as described in [@pbio-0020320-Peluso1] in the presence of 1 μM mutant or wild-type FtsY, 2 μM SRP, and 100 μM GppNHp, and complex formation was initiated by addition of Mg^2+^ as described in [@pbio-0020320-Shan1]. The rate constants for association and dissociation of the Ffh•FtsY complex were determined by following the time course of the fluorescence change at 335 nm as described in [@pbio-0020320-Peluso1], [@pbio-0020320-Peluso2]).
We thank Geeta J. Narlikar, Wallace Marshall, Pascal F. Egea, and Niels R. Bradshaw for helpful comments on the manuscript. This work was supported by National Institutes of Health grants to PW and RMS. PW is an investigator of the Howard Hughes Medical Institute. SS was a cancer research fund fellow of the Damon Runyon-Walter Winchell Foundation when this work began and is currently a Burroughs Wellcome Fund fellow.
**Conflicts of interest.** The authors have declared that no conflicts of interest exist.
**Author contributions.** SS and PW conceived and designed the experiments. SS performed the experiments. SS analyzed the data. SS contributed reagents/materials/analysis tools. SS, RMS, and PW wrote the paper.
Academic Editor: Fred Hughson, Princeton University
Citation: Shan S, Stroud RM, Walter P (2004) Mechanism of association and reciprocal activation of two GTPases. PLoS Biol 2(10): e320.
ER
: endoplasmic reticulum
GAP
: GTPase-activating protein
GEF
: guanine nucleotide exchange factor
GMPPNP
: 5′-guanylylimidodiphosphate
RNC
: ribosome•nascent chain complex
SR
: SRP receptor
SRP
: signal recognition particle
XTP
: xanthosine-5′-triphosphate
|
PubMed Central
|
2024-06-05T03:55:47.800386
|
2004-9-21
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517823/",
"journal": "PLoS Biol. 2004 Oct 21; 2(10):e320",
"authors": [
{
"first": "Shu-ou",
"last": "Shan"
},
{
"first": "Robert M",
"last": "Stroud"
},
{
"first": "Peter",
"last": "Walter"
}
]
}
|
PMC517824
|
Introduction {#s1}
============
Many proteins of diverse sequences, structures, and functions form morphologically similar β-sheet--rich fibrillar aggregates commonly referred to as amyloid ([@pbio-0020321-Kelly1]; [@pbio-0020321-Dobson1]). Amyloid formation is associated with a range of disorders, including neurodegenerative diseases such as Alzheimer\'s and Parkinson\'s, and the self-propagating nature of amyloids is thought to underlie prion inheritance. Despite the importance of this process, many questions remain about how amyloid fibers form and grow ([@pbio-0020321-Goldberg1]; [@pbio-0020321-Zerovnik1]; [@pbio-0020321-Ross1]; [@pbio-0020321-Thirumalai1]). While reminiscent of other protein polymerization processes, such as those of actin and tubulin, amyloid formation in most cases does not seem to be well described by simple nucleated polymerization models ([@pbio-0020321-DePace2]; [@pbio-0020321-Serio1]; [@pbio-0020321-Padrick1]; [@pbio-0020321-Zerovnik1]; [@pbio-0020321-Ross1]; [@pbio-0020321-Thirumalai1]). Efforts to decipher the underlying mechanism of amyloid conversion have been greatly complicated by the near ubiquitous presence of smaller, oligomeric aggregates during fiber formation and growth ([@pbio-0020321-Serio1]; [@pbio-0020321-Bitan1]; [@pbio-0020321-Caughey1]; [@pbio-0020321-Souillac1]). These oligomers vary widely in morphology, and include spherical, protofibrillar, and annular structures. A growing body of evidence suggests that certain oligomers may be the toxic species that gives rise to amyloid disease ([@pbio-0020321-Caughey1]). Furthermore, it remains an open question whether the fibers themselves are toxic, neutral, or even protective in some cases. However, despite great interest in these oligomers, it is unknown whether they are critical intermediates for amyloid formation or if fibers can form in their absence ([@pbio-0020321-Goldberg1]; [@pbio-0020321-Ross1]; [@pbio-0020321-Scheibel1]).
The yeast prion state \[*PSI^+^*\], which results from self-propagating aggregation of the translation termination factor Sup35 and leads to a nonsense suppression phenotype, provides an excellent system for studying amyloid fiber formation and prion propagation ([@pbio-0020321-Tuite1]). Prion inheritance in vivo is mediated by a glutamine/asparagine-rich N-terminal domain (N) and, to a lesser extent, a charged middle domain (M) ([@pbio-0020321-Bradley1]). In vitro the NM domain forms self-replicating amyloid fibers ([@pbio-0020321-Glover1]; [@pbio-0020321-King2]), and when introduced into yeast these fibers initiate the \[*PSI^+^*\] prion state ([@pbio-0020321-Sparrer1]; [@pbio-0020321-King1]; [@pbio-0020321-Tanaka1]), establishing that the amyloids are in fact the infectious prion element underlying \[*PSI^+^*\]. De novo NM polymerization is characterized by a long lag phase followed by a cooperative conversion into amyloid. The lag phase can be eliminated by addition of preformed NM fibers. Oligomers similar to those seen during polymerization of other amyloidogenic proteins have been observed during NM fiber formation and even have been seen localized proximal to fiber ends ([@pbio-0020321-Serio1]). The kinetic role of these oligomers, however, remains poorly understood ([@pbio-0020321-Scheibel1]); for example, does amyloid growth occur by capture of oligomeric intermediates at fiber ends, as suggested in earlier studies ([@pbio-0020321-Serio1])? Here we use a combination of kinetic studies designed to report on specific, well-defined steps in the polymerization reaction together with direct single-molecule fluorescence measurements to explore the mechanism of formation and growth of the infectious NM amyloids.
Results {#s2}
=======
We first examined the distribution of oligomeric species present during NM amyloid formation using analytical ultracentrifugation (AUC). Equilibrium AUC indicated the material was predominantly monomeric, giving fitted average molecular masses of 28.5 ± 1.7 kDa (calculated monomer mass is 29.6 kDa), with no appreciable concentration dependence from 1.5 to 5.8 μM ([Figure 1](#pbio-0020321-g001){ref-type="fig"}A and [1](#pbio-0020321-g001){ref-type="fig"}B). By velocity AUC, which is better suited to resolve a small population of a larger oligomer ([@pbio-0020321-Schuck2]), the vast majority of the material fit well to a single peak in a sedimentation coefficient distribution obtained by direct boundary modeling \[c(s)\] ([@pbio-0020321-Schuck2]) with a sedimentation coefficient of 1.9 S ([Figure 1](#pbio-0020321-g001){ref-type="fig"}C). The lack of other detectable peaks is significant, as we were readily able to detect the presence of small amounts of a larger protein complex (10% GroEL) added to an NM sample ([Figure 1](#pbio-0020321-g001){ref-type="fig"}D). Thus, on the time scale of the 5--20 h needed for the AUC analysis, which exceeds the polymerization reaction times in our present studies, the large majority of NM is monomeric. This has allowed us to examine fiber formation in the absence of significant off-pathway aggregation, which was seen to obscure the underlying kinetics of other amyloid systems ([@pbio-0020321-Rhoades1]; [@pbio-0020321-Padrick1]; [@pbio-0020321-Souillac1]). However, our AUC data did not address whether a rare oligomeric species serves as a critical on-pathway intermediate for fiber growth.
::: {#pbio-0020321-g001 .fig}
Figure 1
::: {.caption}
###### NM Is Predominantly Monomeric
\(A) Oligomeric state of NM prior to assembly was assessed by equilibrium AUC. Above, raw plot of absorbance versus radial position for 5.8 μM NM at equilibrium, with best-fit line for a single species. Below, residuals from the fit shown above.
\(B) Equilibrium AUC data from 1.5, 3.8, 5.2, 5.5, and 5.8 μM samples of NM were fit to a single-species model. Shown is fitted molecular mass versus concentration. For reference, dashed lines are shown at the calculated monomer mass (29.6 kDa) and dimer mass (59.2 kDa).
\(C) Distribution of absorbance versus sedimentation coefficient at the indicated concentrations was obtained from velocity sedimentation data using Sedfit ([@pbio-0020321-Schuck2]). Inset is a magnification of the main peaks.
\(D) A small amount of a larger complex could be resolved by velocity sedimentation. Distribution of absorbance versus sedimentation coefficient for each of 3 μM NM and 2.7 μM NM plus GroEL (with absorbance equivalent to that of 0.3 μM NM) is shown. Inset is a magnification for sedimentation coefficients between 15.6 S and 28.4 S.
:::
:::
To explore this possibility, we looked at the concentration dependence of the initial rate of growth of soluble NM onto the ends of a well-defined amount of preformed fibers. If a rare oligomer is critical for fiber growth, then mass action dictates that the quantity and rate of formation of such oligomers will be highly concentration dependent. As a consequence, the initial rate of polymerization should depend strongly on the concentration of soluble NM. Using a thioflavin T binding assay that allows continuous measurement of amyloid formation, we measured the rate of amyloid growth after mixing a quantity of soluble NM with a known amount of preformed nuclei. We found that the initial rate of fiber growth was directly proportional to the concentration of soluble NM over a range of 0--1 μM ([Figure 2](#pbio-0020321-g002){ref-type="fig"}A). This linear dependence of fiber growth on NM concentration was not dependent on the method used to monitor growth ([Figure 2](#pbio-0020321-g002){ref-type="fig"}B and [2](#pbio-0020321-g002){ref-type="fig"}C). We also looked at the dependence of the polymerization rate on seed concentration. As expected, this rate was directly proportional to concentration of fiber ends ([Figure 2](#pbio-0020321-g002){ref-type="fig"}D--[2](#pbio-0020321-g002){ref-type="fig"}F), and importantly, the rate was still linear up to a concentration of seed at which half of the soluble material was polymerized in less than 3 min. Therefore, NM in solution is in rapid equilibrium with conformations competent to add to fibers.
::: {#pbio-0020321-g002 .fig}
Figure 2
::: {.caption}
###### Kinetics of NM Fiber Growth Support a Monomer Addition Model
\(A) Initial rate of polymerization versus concentration of NM. Soluble NM at the indicated final concentrations was mixed with sonicated fibers (2.5 μM fibers at 5% of final volume) and polymerization was followed by a continuous thioflavin T assay. Rates shown were determined by the initial slopes of polymerization curves.
\(B) Initial rate of polymerization versus concentration of soluble NM in the presence of sonicated seed (1% of final volume) measured by a discrete thioflavin T binding assay. Error bars throughout represent the standard deviation of at least three measurements.
\(C) Polymerization of NM labeled with Alexa-647 at a C-terminal cysteine was monitored by the quenching of Alexa-647 fluorescence. The indicated concentrations of soluble NM were mixed with sonicated fibers (4% of final volume), and the initial rate of polymerization was measured.
\(D) Initial rate of polymerization versus concentration of seed. Soluble NM (2.5 μM final concentration) was mixed with the indicated quantity of sonicated seed. Highly fragmented fibers were used to maximize the absolute rate. Rates were measured as in (A).
\(E) Initial rate of polymerization versus concentration of seed as measured by discrete thioflavin T binding assay. Initial soluble NM concentration was 2.5 μM.
\(F) Initial rate of polymerization versus concentration of seed as measured by Alexa-647 fluorescence quenching. Initial soluble NM concentration was 200 nM.
:::
:::
Interestingly, at higher NM concentrations (\>10 μM), the rate of fiber elongation shows a weaker-than-linear dependence on NM concentration. Accumulation of off-pathway aggregates, which we can observe at high \[NM\], could contribute to such an effect. However, in the presence of moderate levels of denaturant (100 mM guanidine hydrochloride \[GuHCl\] and 100 mM urea), NM remained monomeric up to at least 20 μM ([Figure 3](#pbio-0020321-g003){ref-type="fig"}A), and under these conditions we still observed that the rate of polymerization becomes largely independent of the concentration of NM ([Figure 3](#pbio-0020321-g003){ref-type="fig"}B). This suggests that a conformational rearrangement of NM after binding to fiber ends becomes rate limiting at high NM concentrations (see [Figure 5](#pbio-0020321-g005){ref-type="fig"}C). As would be expected if unconverted NM is occupying fiber ends, even at the highest NM levels the rate of polymerization remains linearly dependent on the amount of seed added ([Figure 3](#pbio-0020321-g003){ref-type="fig"}B, inset). This conformational rearrangement may be analogous to the locking step observed in Aβ polymerization ([@pbio-0020321-Esler1]; [@pbio-0020321-Cannon1]), although here it occurs on a faster time scale. Estimates from growth rates measured by atomic force microscopy (AFM) indicate that the rearrangement occurs within ∼1 s (see [Materials and Methods](#s4){ref-type="sec"}), a time similar to that seen for the folding of comparably sized β-sheet--rich proteins ([@pbio-0020321-Reid1]).
::: {#pbio-0020321-g003 .fig}
Figure 3
::: {.caption}
###### Evidence that a Conformational Conversion following NM Monomer Binding to Fiber Ends Becomes Rate Limiting at High \[NM\]
\(A) NM is predominantly monomeric at concentrations up to 20 μM in the presence of a moderate level of denaturant (100 mM urea and 100 mM GuHCl). Oligomeric state was assessed by velocity AUC as in [Figure 1](#pbio-0020321-g001){ref-type="fig"}C for NM at 10, 15, and 20 μM.
\(B) Soluble NM was mixed with sonicated fibers in the presence of 100 mM urea and 100 mM GuHCl to minimize off-pathway aggregation at higher \[NM\], and the initial rate of polymerization was measured as in [Figure 2](#pbio-0020321-g002){ref-type="fig"}A. Inset, rate of polymerization of 20 μM soluble NM versus seed percentage (v/v). The continued linear dependence of rate on fiber ends indicates that at high \[NM\], fiber ends remain limiting.
:::
:::
::: {#pbio-0020321-g005 .fig}
Figure 5
::: {.caption}
###### Effect of Fiber Fragmentation on Polymerization Kinetics
\(A) De novo NM polymerization (1.0--12 μM) followed by a continuous thioflavin T binding assay.
\(B) Lag time (measured as time to 5% completion of polymerization) versus NM concentration for the polymerizations shown in (A).
\(C) Schematic of nucleated polymerization with fragmentation. At low concentrations fiber growth is limited by monomer binding, whereas at high concentrations conformational conversion after binding becomes limiting.
\(D) The de novo polymerization data shown in (A) were fit with a linearized model ([@pbio-0020321-Ferrone1]) that includes nucleation, fiber growth by monomer addition, and fragmentation, assuming the indicated sizes for the smallest stable amyloid species (nucleus size). Plotted are the residuals (best-fit value minus observed data). Each block (labeled at the left by the nucleus size used) represents the residuals from simultaneously fitting all of the data. Each line within the block displays the individual residuals from a single concentration (1 μM \[top\] to 12 μM \[bottom\]). Residuals are color coded according to the color key at the right, with red and green indicating large errors and yellow indicating a good fit. Time varies from time zero (farthest left) to the time of 3% completion of polymerization. Below (NP) are residuals from fitting the same data using a simple nucleated polymerization model. Note the systematic deviations from the model for large nucleus sizes and for NP.
:::
:::
A model in which growth of NM fibers is largely limited by the encounter rate of monomer and fiber end still has two puzzling features of the polymerization process to explain. First, like many other amyloid formation reactions, NM polymerization is dramatically accelerated by agitation ([@pbio-0020321-DePace2]; [@pbio-0020321-Serio1]) ([Figure 4](#pbio-0020321-g004){ref-type="fig"}A), which has been hypothesized to increase the fiber growth rate by breaking up off-pathway aggregates or speeding up diffusion of large on-pathway oligomers ([@pbio-0020321-Serio1]). Neither of these explanations applies to a predominantly monomeric solution where fibers grow by monomer addition. Previous attempts to understand agitation were complicated by the multistep nature of the polymerization process, which includes nucleation, growth, and other steps. We specifically looked at the effect of agitation on the fiber growth step using two identical seeded reactions, one agitated and one undisturbed. Remarkably, we found that seeded polymerizations initially proceeded at exactly the same rate with or without agitation ([Figure 4](#pbio-0020321-g004){ref-type="fig"}B). However, after extensive growth of the added seeds (∼20 min) the rate of the agitated reaction began to accelerate markedly ([Figure 4](#pbio-0020321-g004){ref-type="fig"}B, inset), whereas unagitated reactions slow down as the pool of monomeric NM becomes depleted.
::: {#pbio-0020321-g004 .fig}
Figure 4
::: {.caption}
###### Agitation Causes Fiber Fragmentation
\(A) Dependence of de novo polymerization reactions on degree of agitation. Polymerization in a microplate with shaking every minute (line only) was followed by thioflavin T fluorescence. Polymerization in a test tube disturbed only by pipetting to take samples for measurement (diamonds) was measured by Congo Red binding. Polymerization in a microplate with absolutely no agitation (multiple samples were started in parallel and no sample was measured more than once) (squares) was measured by Congo Red binding.
\(B) Effect of agitation on elongation rate. Identical reactions with 5 μM soluble NM and 2% (v/v) seeds were grown with (triangles) or without (circles) agitation. The seeds were made fresh and sheared by passing through a 25-gauge needle ten times. Polymerization was assayed by discrete thioflavin T measurements. Inset, identical reactions followed for 100 min.
\(C) Effect of agitation on fiber lengths. Long fibers were grown from sonicated seeds in the absence of agitation and then subjected to agitation (end-over-end rotation in a 2-ml tube). AFM images were taken after 0, 1, and 15 h of rotation. Each image is 5 μm by 5 μm.
\(D) Effect of agitation on seeding efficacy. Fibers from the samples imaged in (C) were used to seed polymerization of 10 μM soluble NM, and the initial rate of polymerization was measured as in [Figure 2](#pbio-0020321-g002){ref-type="fig"}A.
\(E) De novo NM polymerization was measured by continuous thioflavin T fluorescence, and relative fiber number was computed as a function of time (see [Materials and Methods](#s4){ref-type="sec"}). Inset, fiber number versus time was fit to an exponential curve for time = 0 to time = 100 min.
:::
:::
At a given NM concentration the rate of polymerization is proportional to seed concentration, and therefore the acceleration seen in the agitated reaction implies that the number of fiber ends is increasing with time, perhaps due to the ability of agitation to fragment long fibers. To test this possibility, we prepared long fibers by allowing prolonged growth of NM onto preformed seeds in the absence of agitation, and then subjected the fibers to end-over-end rotation. Prior to rotation, the fibers were very long and had a weak ability to seed polymerization of monomeric NM. After 1 h of rotation, we saw many more fibers of much shorter length, and the seeding activity had increased 10-fold. Further rotation (14 h) produced still shorter fibers and higher seeding activity ([Figure 4](#pbio-0020321-g004){ref-type="fig"}C and [4](#pbio-0020321-g004){ref-type="fig"}D). Interestingly, a reanalysis of the kinetics of de novo NM polymerization, based on the fact that the rate of polymerization is linearly dependent on the amount of seed present and the amount of monomer remaining (see [Figure 2](#pbio-0020321-g002){ref-type="fig"}), indicates that the number of seeds increases exponentially during NM polymerization ([Figure 4](#pbio-0020321-g004){ref-type="fig"}E). Thus, while agitation does not affect the rate of NM addition to fiber ends, it accelerates polymerization by increasing the number of ends through amyloid fragmentation.
The second unusual feature of NM polymerization that must be reconciled with a model of monomer addition is the weak dependence (less than first order) of the length of the lag time on the concentration of NM in unseeded polymerizations ([@pbio-0020321-DePace2]; [@pbio-0020321-Serio1]). This finding, together with the sigmoidal curve shape involving a pronounced lag phase followed by an abrupt increase in the rate of polymerization, provided key evidence against a simple nucleation-polymerization model ([@pbio-0020321-DePace2]; [@pbio-0020321-Serio1]; [@pbio-0020321-Padrick1]), which is characterized by an initially parabolic (t^2^) time course ([@pbio-0020321-Ferrone1]). We similarly observed a lag phase that depends on approximately the 0.4 power of initial concentration ([Figure 5](#pbio-0020321-g005){ref-type="fig"}A and [5](#pbio-0020321-g005){ref-type="fig"}B). In other systems, this weak concentration dependence has been attributed to an accumulation of large off-pathway species whose formation is competitive with on-pathway processes ([@pbio-0020321-Rhoades1]; [@pbio-0020321-Serio1]; [@pbio-0020321-Padrick1]; [@pbio-0020321-Souillac1]). However, in our experiments NM is predominantly monomeric, so the observed weak concentration dependence is not a simple consequence of the accumulation of off-pathway aggregates.
Previous work from [@pbio-0020321-Ferrone1] using a linearized model demonstrated that addition of fragmentation to a nucleation-polymerization process could lead to sigmoidal polymerization curves. We explored whether fragmentation could also explain the weak concentration dependence using both numerical integration and direct fitting of the data to a linearized model. We modeled a simple polymerization process involving nucleation, growth, and fragmentation ([Figure 5](#pbio-0020321-g005){ref-type="fig"}C). Numerical integration confirmed the expected strongly sigmoidal curve shape, but we also found that fragmentation greatly reduced the concentration dependence. For example, a nucleus size (the number of monomers in the smallest stable amyloid species) of six gives a third-order concentration dependence in nucleated polymerization but only approximately a first-order dependence with fragmentation, and the apparent concentration dependence decreases further for smaller nucleus sizes. We additionally tried fitting data to the linearized analytical solution which is valid for early parts of the polymerization ([@pbio-0020321-Ferrone1]; we restrict ourselves to the first 3%) and only requires fitting two parameters. Fixing nucleus size and fitting polymerization curves at seven concentrations, we obtained residuals of fits at a series of potential nucleus sizes ([Figure 5](#pbio-0020321-g005){ref-type="fig"}D). Although more direct measurements are needed to define the exact size of the minimal stable seed, both approaches suggest a small nucleus size (three monomers or smaller), consistent with recent observations on polyglutamine polymerization ([@pbio-0020321-Chen1]).
The advent of single-molecule fluorescence technology enabled an independent and more direct way to test whether fibers grow by monomer addition. Previous work ([@pbio-0020321-Inoue1]) established that fluorescent NM fibers attached to a microscope slide could be grown and visualized using epifluorescence. Here we examined fiber growth using total internal reflection fluorescence microscopy (TIRF), which allows single-molecule detection. We attached Cy5-labeled NM fibers to a slide through a biotin-streptavidin linkage and added a solution of Cy3-labeled soluble NM ([Figure 6](#pbio-0020321-g006){ref-type="fig"}A). Working at a label concentration of 133 nM (200 nM or more total soluble NM) to minimize background fluorescence, we could readily detect addition of individual Cy3 fluorophores at the ends of Cy5-labeled fibers. Two observations indicate that we were monitoring growth events mediated by fiber ends. First, after extended time (∼1 h) at our working concentration, bright Cy3 fluorescence (consisting of many labeled NM molecules) accumulated specifically at fiber ends ([Figure 6](#pbio-0020321-g006){ref-type="fig"}B). Second, Cy3 addition events at fiber ends were long lived (55% of spots at fiber ends remained visible in the second frame measured 15 s later, whereas in the absence of fiber ends fewer than 20% of spots remained).
::: {#pbio-0020321-g006 .fig}
Figure 6
::: {.caption}
###### Fundamental Unit of Addition for NM Fiber Growth Determined by TIRF
\(A) Schematic of experimental setup. Cy5-labeled fibers (red) were attached to the microscope slide via biotin-streptavidin linkage. Cy3-labeled NM (green) was added in solution.
\(B) TIRF image of fibers (red) grown by addition of 200 nM NM (67% labeled with Cy3 \[green\]) for approximately 1 h. Cy3 fluorescence at fiber ends in this image represents multiple addition events.
\(C) Schematic of expected results if oligomers (top, trimer model shown for example) or monomers (bottom) are added to fiber ends. Graphs at the right show simulated data of fraction of additions versus fluorescence intensity of addition. Note that for the monomer model, the simulated intensities are the same whether 9% or 67% of the soluble NM is labeled.
\(D) Observed data: fraction of observed events versus fluorescence intensity of events. Intensities of Cy3 spots appearing at fiber ends were measured.
\(E) Intensities of Cy3 spots appearing at fiber ends (circles) and intensities of Cy3 spots that bleached in a single step (squares).
:::
:::
By following the intensities of single fluorescent addition events, we could directly determine the size of the unit of addition. Oligomer addition (unlike monomer addition) predicts that the fluorescence intensity of a single addition event should depend strongly on the fraction of NM that is fluorescently labeled ([Figure 6](#pbio-0020321-g006){ref-type="fig"}C). We prepared NM at both 67% (133 nM label, 200 nM total soluble NM) and 9% (89 nM label, 966 nM total soluble NM) labeling efficiency. Intensities of Cy3 spots that appeared at fiber ends were then measured, and for each degree of labeling, a histogram of intensities was created. Strikingly, we observed that the distribution of intensities was independent of the degree of labeling ([Figure 6](#pbio-0020321-g006){ref-type="fig"}D). Furthermore, the intensity distribution of the fiber addition events was comparable to that of NM-Cy3, which was confirmed to be monomeric by single-step photobleaching experiments ([Figure 6](#pbio-0020321-g006){ref-type="fig"}E). Together these data establish that amyloid growth is occurring by the addition of NM monomers onto fiber ends.
Discussion {#s3}
==========
Amyloid formation is a ubiquitous feature of polypeptides. However, compared to protein folding reactions, for which a wide range of biophysical, structural, and analytical approaches have provided detailed information on the pathways by which native states are obtained, very little is known about the underlying steps by which amyloid fibers assemble and grow. In large part this is due to the complexity of the amyloid formation reaction, which can involve a wide spectrum of on- and off-pathway intermediates. In the present study, we have used a combination of kinetic analysis designed to look at specific mechanistic steps and single-molecule fluorescence to determine how amyloid fibers of Sup35, the prion determinant of the yeast state \[*PSI^+^*\], form and grow.
A key finding is that Sup35 NM amyloids grow efficiently by the addition of monomers to fiber ends. We also establish that monomer addition, in combination with fiber fragmentation, accurately predicts the otherwise puzzling features of de novo polymerization kinetics. While it is still possible that oligomers could add to the ends of fibers if allowed to accumulate, we find that monomer addition is rapid and efficient. This monomer addition mechanism can account for the generation of the \[*PSI^+^*\] translation read-through phenotype in vivo. While division of Sup35 prion particles appears to depend on cellular chaperones including Hsp104 ([@pbio-0020321-Ness1]; [@pbio-0020321-Osherovich1]), both genetic and biochemical evidence suggests their growth is an Hsp104-independent process ([@pbio-0020321-Ness1]; [@pbio-0020321-Shorter1]). Additionally, with approximately 200 seeds in a cell ([@pbio-0020321-Cox1]) and the second-order rate constant we observe (approximately 2 × 10^5^ M^−1^ s^−1^), soluble Sup35 would have a half-life of about 3 min, which is comparable to the time scale of Sup35 translation and much faster than the doubling time of yeast (90 min). Thus, the monomer growth mechanism would lead to the depletion of Sup35 characteristic of the \[*PSI^+^*\] state (see [Materials and Methods](#s4){ref-type="sec"}). Moreover, the properties of Sup35 polymerization we observe seem particularly well suited to explain the prion phenotype in yeast. De novo nucleation of new fibers is extremely slow, but existing fibers grow rapidly and their fragility may allow them to be divided easily. These features are appropriate for a protein-based switch that is bistable (\[*PSI^+^*\] and \[*psi* ^−^\] are both stable states) and whose aggregated state must be amplified exponentially to keep pace with cell division.
Many kinetic features seen for NM polymerization are shared by other amyloidogenic proteins ([@pbio-0020321-Uversky1]; [@pbio-0020321-Chen1]; [@pbio-0020321-Padrick1]), suggesting that monomer addition may represent a mechanism of amyloid growth common to other fibers. Whether other amyloids do in fact grow by monomer addition and how the role of oligomeric species in the polymerization process correlates with toxicity remain important open questions. Many of the analytical approaches and experimental techniques used in this work should be directly applicable for exploring these issues in other systems. A broader understanding of the role of oligomeric species in the formation and growth of amyloids will be critical for determining the physiological effects of amyloidogenesis as well as guiding efforts to counteract amyloid toxicity. For example, the conclusion that amyloid growth and oligomer formation can occur in distinct, competitive reactions may help explain the poor correlation between formation of visible aggregates and toxicity in neurodegenerative diseases of protein misfolding ([@pbio-0020321-Saudou1]; [@pbio-0020321-Cummings1]; [@pbio-0020321-Goldberg1]; [@pbio-0020321-Wittmann1]). More speculatively, the finding that fiber growth does not require oligomeric intermediates raises the possibility that agents designed to promote direct fiber formation, by disfavoring oligomer formation, may help prevent the accumulation of potentially toxic oligomeric intermediates.
Materials and Methods {#s4}
=====================
{#s4a}
### Reagents {#s4a1}
Cy3 mono maleimide Gold and Cy5 mono maleimide Gold were purchased from Amersham (Little Chalfont, United Kingdom). Alexa Fluor 647 C~2~ maleimide was purchased from Molecular Probes (Eugene, Oregon, United States). Streptavidin was purchased from Molecular Probes. Biotinylated BSA and thioflavin T were purchased from Sigma (St. Louis, Missouri, United States). Biotin-PEAC~5~-maleimide (6-{N′-\[2-(N-Maleimido)ethyl\]-N-piperazinylamido}hexyl [D]{.smallcaps}-biotinamide, hydrochloride) was purchased from Dojindo (Gaithersburg, Maryland, United States). Alkali-soluble casein (5%) was purchased from Novagen (Madison, Wisconsin, United States).
### Protein expression {#s4a2}
Sup35 residues 1 to 254 (NM) C-terminally tagged with 7×-histidine were purified as reported previously ([@pbio-0020321-DePace2]; [@pbio-0020321-Tanaka1]).
### Fluorescence labeling {#s4a3}
NM with a single cysteine inserted after the polyhistidine tag was labeled by Cy3 mono maleimide Gold, Cy5 mono maleimide Gold, or Alexa Fluor 647 C~2~ maleimide (10 equivalents) in 25 mM sodium phosphate buffer containing 6 M GuHCl and 0.1 mM TCEP (pH 8.0) at 4 °C overnight with 67% efficiency. Efficiency of labeling was determined from absorbance at 275 nm and at the excitation maximum of the dyes, correcting for absorbance of the dye at 275 nm. Biotinylated NM was made analogously using biotin-PEAC~5~-maleimide (2.5 equivalents) with 1 mM TCEP, obtaining about 20% efficiency.
### AUC {#s4a4}
Both velocity and equilibrium AUC were performed in a Beckman Optima XL-A analytical ultracentrifuge using an An60Ti-Rotor at 20 °C. Protein was in buffer C (5 mM potassium phosphate and 150 mM sodium chloride \[pH 7.4\]). Velocity sedimentation was analyzed at a speed of 40,000 rpm at NM concentrations of 3.7, 6.2, and 12.9 μM (determined by absorbance at 275 nm). Data were collected with three replicates at radial steps of 0.003 cm and scans every 9 min. Data were analyzed with Sedfit using the c(s) method ([@pbio-0020321-Schuck2]). Equilibrium sedimentation was analyzed at a speed of 23,300 rpm for concentrations of 1.5, 3.8, 5.0, 5.5, and 5.8 μM. Data were analyzed with Sedphat ([@pbio-0020321-Schuck1]) by fitting each curve individually to a single species model. Sedfit and Sedphat are available at <http://www.analyticalultracentrifugation.com>.
### Polymerizations {#s4a5}
For continuous thioflavin T assay measurements (see [Figures 2](#pbio-0020321-g002){ref-type="fig"}A, [2](#pbio-0020321-g002){ref-type="fig"}D, [3](#pbio-0020321-g003){ref-type="fig"}B, [4](#pbio-0020321-g004){ref-type="fig"}A, [4](#pbio-0020321-g004){ref-type="fig"}D, [4](#pbio-0020321-g004){ref-type="fig"}E, [5](#pbio-0020321-g005){ref-type="fig"}A, [5](#pbio-0020321-g005){ref-type="fig"}B, and [5](#pbio-0020321-g005){ref-type="fig"}D), concentrated stocks of NM stored in either 6 M GuHCl (fluorescently labeled NM and NM used for [Figures 2](#pbio-0020321-g002){ref-type="fig"}C, [2](#pbio-0020321-g002){ref-type="fig"}F, and [6](#pbio-0020321-g006){ref-type="fig"}) or 4 M GuHCl and 4 M urea (NM used for all other experiments) were diluted at least 200-fold into buffer C. In order to compare polymerizations done at different concentrations of NM, residual denaturant concentrations were equalized for all samples in each experiment. Reactions consisted of 100 μl of protein in buffer C plus 100 μl of 25 μM thioflavin T in 50 mM glycine (pH 8.5). Seed was added immediately before observation. Fluorescence was monitored in a 96-well fluorescence plate reader (Molecular Devices, Sunnyvale, California, United States; 442 nm excitation and 483 nm emission). Reactions were carried out at 25 °C either without (for seeded reactions) or with (for unseeded reactions) 3 s of shaking between each measurement. Unseeded polymerizations were done in the presence of a small amount of soluble casein (0.02%), as empirically that condition gave flatter plateaus at the end of the reaction.
Discrete thioflavin T assay measurements (see [Figures 2](#pbio-0020321-g002){ref-type="fig"}B, [2](#pbio-0020321-g002){ref-type="fig"}E, and [4](#pbio-0020321-g004){ref-type="fig"}B) were performed as continuous measurements, except that polymerization proceeded in buffer C in the absence of thioflavin T. At indicated time points, a 100-μl aliquot of polymerization reaction was mixed with 100 μl of thioflavin T for measurement. Reactions were either undisturbed or rotated end-over-end in a 2-ml tube as indicated.
For polymerizations followed by Alexa Fluor 647 fluorescence (see [Figures 2](#pbio-0020321-g002){ref-type="fig"}C and [2](#pbio-0020321-g002){ref-type="fig"}F), the fluorescence of a 200-μl volume containing the indicated concentration of labeled NM and the indicated quantity of sonicated fibers was measured over time in a 96-well fluorescence plate reader (Molecular Devices; 650 nm excitation and 670 nm emission). Fluorescence was partially quenched (approximately 56% of fluorescence lost) upon polymerization. Rates of polymerization were determined by taking the initial slope of the polymerization curve divided by the total change in fluorescence multiplied by the concentration of the sample. Wells in the microplate were blocked with 5% casein and washed with water prior to polymerization experiments to minimize adsorption of NM to the sides of the wells.
Seeds used were produced by polymerization of 2.5 μM NM followed by sonication with a Fisher Scientific Sonic Dismembrator (Model 500) fitted with a microtip for 60 s (for all experiments except that shown in [Figure 4](#pbio-0020321-g004){ref-type="fig"}B) or sheared by passing through a 25-gauge needle ten times (for [Figure 4](#pbio-0020321-g004){ref-type="fig"}B). Sheared rather than sonicated fibers were used for examining the effect of agitation on fiber growth because longer fibers were seen to break more easily than shorter fibers.
### AFM {#s4a6}
AFM samples were prepared and analyzed essentially as previously described ([@pbio-0020321-DePace1]). All images were taken using tapping mode on a Digital Instruments Multimode AFM, Nanoscope IIIa controller, and Micromasch NSC15 tips. For fiber images (see [Figure 4](#pbio-0020321-g004){ref-type="fig"}C), 20 μl of fibers (either 2.5 or 5.0 μM total NM) was deposited on mica disk for 20 s. The disk was then washed twice with 160 μl of distilled deionized water and aspirated until dry.
For estimating fiber growth rates (see below), new growth of unlabeled NM off of preformed fibers made from NM tagged with an HA epitope was measured as previously described ([@pbio-0020321-DePace1]). The HA epitope allows the initial seeds, but not new growth, to be labeled with antibody after the fibers are deposited on the mica.
### Computer simulation, curve fitting, and computation {#s4a7}
Numerical integration was performed using Euler\'s method implemented in a C program (code available upon request). The following is a general description of the strategy used for numerical modeling. A set of differential equations was written to account for the following steps: formation of a new stable nucleus from a defined number (n) of monomers, growth of fibers by monomer addition (limited by the rate of encounter of monomer and fiber end), and production of new fibers by fragmentation of existing fibers. Fiber growth was modeled to be irreversible (i.e., fibers do not depolymerize) ([@pbio-0020321-DePace1]), because experimentally the critical concentration for growth appeared to be very small (less than 50 nM), if one exists. Fragmentation was modeled as a length-dependent process (long fibers break more easily than short fibers), and to simplify calculations, it was assumed that no fiber breaks to yield a fragment as small or smaller than the size of the smallest stable nucleus. This is likely to be true for the large majority of fragmentation events because of the tendency of fibers to break closer to their center rather than their ends and because of the low propensity of short fibers to break ([@pbio-0020321-Hill1]). Concentrations of monomers and fibers of each length from n to 3,016 monomers were modeled as a function of time. An upper bound for fiber length was necessary to make the calculations possible, and the total of 3,016 was chosen because increasing this bound had no measurable impact on results.
Variables and parameters used for modeling were the following: *t* = time; *x* = concentration of monomers; *y* ~i~ = concentration of fibers containing i monomers; *y* = concentration of all fibers of length n or greater; n = the number of monomers in the smallest stable species; BreakDep = the power to which the rate of fragmentation of a fiber depends on its length. For all simulations this value was set to 3, based on theoretical estimates for polymers ([@pbio-0020321-Hill1]), although the results were robust to changes in this parameter. The BreakDep parameter was included to model the length dependence of fragmentation:
Here, j represents fiber length (the number of monomers in a fiber) and the sum is taken over all values of j greater than or equal to (i + n + 1). The *z* ~above(i)~ term accounts for fragmentation of all fibers long enough to break and give a resulting fiber of length i. The sum begins at j = (i + n + 1) because no smaller fiber could break to give a fragment of size i, leaving another fragment of at least size (n + 1).
Differential equations for modeling contain the following terms: k~nuc~ = effective fiber nucleation rate constant; k~growth~ = fiber elongation rate constant; k~break~ = fiber fragmentation rate constant. The equations are as follows.
For monomer concentration:
The k~nuc~\*n\**x* ^n^ term accounts for the loss of n monomers during the formation of each stable nucleus. Stable nuclei are modeled to form at a rate of k~nuc~\**x* ^n^. The k~growth~\**x*\**y* term accounts for the loss of one monomer for each fiber elongation event; each fiber grows at a rate of k~growth~\**x* and there are *y* total fibers.
For the smallest stable species:
The k~nuc~\**x* ^n^ term accounts for the spontaneous formation of new nuclei. The k~growth~\**x*\**y* ~n~ term accounts for the disappearance of fibers of length n as they grow into longer fibers.
For short fibers (of length less than or equal to twice the size of the nucleus plus one monomer):
Fibers of length i are created by elongation of shorter fibers at a rate of k~growth~\**x*\**y* ~i−1~ and lost by growth into longer fibers at a rate of k~growth~\**x*\**y* ~i~, accounting for the first term. The second term accounts for formation of fibers of length i by fragmentation of longer fibers (see description of *z* ~above(i)~ above). There is no loss of fibers of these lengths from fragmentation because they are assumed to be too short to break.
For fibers longer than twice the size of the nucleus plus one monomer:
The first two terms are the same as for the short fibers. The additional term accounts for fragmentation of fibers of length i into shorter fibers. This term is arrived at in the following way: k~break~ is a rate constant for the fragmentation process, *y* ~i~ is the number of fibers of this length, (i − 2\*n − 1) is the number of points along the length of the fiber where it could break, and i^BreakDep^ accounts for the tendency of longer fibers to break more easily than shorter fibers (see the description of BreakDep above). There are (i − 2\*n − 1) places the fiber could break because there are (i − 1) monomer-monomer interfaces in a fiber of length i and breaking at any of the n interfaces closest to either end of the fiber would give one fiber of size n or smaller.
Curve fitting of experimental data to the linearized model of [@pbio-0020321-Ferrone1] was performed using a Levenberg-Marquardt least squares fitting method implemented in MATLAB (The Mathworks, Natick, Massachusetts, United States). Data was fit to the equation *y* = A(cosh (B*t*) − 1), where *t* is time and A and B are parameters to be fit with the restriction that AB^2^ scales as \[NM\]^n+1^ (where n is the number of monomers in the smallest stable species).
Relative fiber number (see [Figure 4](#pbio-0020321-g004){ref-type="fig"}E) was computed in the following way: If *z* = total amount of NM in amyloid, and z~final~ = total amount of NM in amyloid at the end of the reaction, then relative fiber number = (d*z*/d*t*)/(z~final~ − *z*). Values for *z* were measured by thioflavin T fluorescence (continuous thioflavin T assay). The equation used for relative fiber number comes from the observation (see [Figure 2](#pbio-0020321-g002){ref-type="fig"}) that the bulk growth rate (d*z*/d*t*) is proportional to both fiber concentration (relative fiber number) and soluble NM concentration (z~final~ − *z*). The relative fiber number versus time was fit to an exponential (*y* = Ae^b*t*^) by nonlinear least squares regression as described above (see [Figure 4](#pbio-0020321-g004){ref-type="fig"}E).
### TIRF {#s4a8}
Single-molecule imaging was performed using objective-type TIRF illumination configured on a Zeiss Axiovert 200M (Carl Zeiss, Inc., Zurich, Switzerland), and controlled by the QED in vivo software package (Media Cybernetics, Silver Spring, Maryland, United States). Images were acquired digitally with a Mega-10 intensified CCD camera (Stanford Photonics, Stanford, California, United States) and analyzed using ImageJ (National Institutes of Health, Bethesda, Maryland, United States) and MATLAB software. Samples were analyzed in glass-bottom microwell dishes (MatTek, Ashland, Massachusetts, United States; catalog \#P35G-1.5-14-C) which were prepared by application of 60 μl of biotinylated BSA (1 mg/ml) for 20 min followed by washing with buffer, application of 60 μl of streptavidin (0.2 mg/ml) for 20 min, washing, application of 100 μl of casein (5%) for 30 min to 2 h, washing, application of 40 μl of Cy5-labeled fibers for 10 min, and finally washing with buffer. The fibers were prepared in a 300-μl reaction with 1% (v/v) seed (sonicated from a 2.5 μM NM reaction). The sonicated seed was grown for 15 min with NM at 2.5 μM (5% biotinylated NM, 20% Cy5-labeled, and 75% unlabeled). The seed was diluted 2-fold and sheared with a 200-μl pipet tip before application to the slides. The slides were kept in buffer until use. Buffer was removed and Cy3-labeled NM (200 nM, 67% labeled; or 955 nM, 9% labeled) was added to the slide immediately before viewing. For addition studies, a Cy5 image was taken to locate the fiber ends and then images were taken every 15 s in the Cy3 channel to look for events at fiber ends.
### Estimate of maximum fiber growth rate {#s4a9}
AFM analysis established that NM fibers grow at an average rate of 100 nm/min at a soluble NM concentration of 2.5 μM and can grow at least a factor of two faster at higher concentrations. Estimating one monomer per 3 nm of length in a fiber (from the approximate monomer volume and a fiber diameter of 4.5 nm from AFM) gives a rate of at least one per second. This is a conservative estimate (the real rate may be faster) because larger fiber diameters have been measured by electron microscopy ([@pbio-0020321-Kishimoto1]), indicating that fibers may have more than one monomer per 3 nm of length.
### Estimating a half-life for Sup35 in a cell {#s4a10}
We observe a second-order rate constant for fiber elongation of approximately 2 × 10^5^ M^−1^ s^−1^, and estimating 200 seeds ([@pbio-0020321-Cox1]), giving an approximate seed concentration of 20 nM in a yeast cell, would result in a half-time of approximately 3 min. We observe Sup35 to be relatively stable against proteolysis within cells, so it would need to be replenished with a half-time of 90 min dictated by the doubling time of yeast. Excluded volume effects from the high concentration of proteins in cytoplasm may further increase the polymerization rate, as we found that 25% ficoll 70 increases polymerization rates by a factor of two or three. Also, 2 × 10^5^ M^−1^ s^−1^ may be an underestimate of the second-order rate constant if we underestimated the number of monomers per unit length in a fiber. We also note that fiber growth in the cell is not likely to be limited by conformational rearrangement after binding of monomer to fiber end because the concentration of Sup35 in a cell is in the neighborhood of 1 μM ([@pbio-0020321-Sparrer1]).
Supporting Information {#s5}
======================
Protocol S1
::: {.caption}
###### Overview of Approach and Techniques Used
(590 KB DOC).
:::
::: {.caption}
######
Click here for additional data file.
:::
Accession Numbers {#s5a2}
-----------------
The GenBank accession number for Sup35p is NP\_010457.
We would like to thank Peter Chien, Angela DePace, Joanna Masel, Kim Tipton, Motomasa Tanaka, and members of the Lim and Weissman labs for helpful discussions and advice on the manuscript, and Gigi Knudsen for assistance with the analytical ultracentrifuge. This work was supported by the National Institutes of Health, the Howard Hughes Medical Institute, the David and Lucile Packard Foundation, and two predoctoral fellowships from the National Science Foundation (SRC and AD).
**Conflicts of interest.** The authors have declared that no conflicts of interest exist.
**Author contributions.** SRC, AD, RDV, and JSW conceived and designed the experiments. SRC and AD performed the experiments. SRC, AD, and JSW analyzed the data. RDV and JSW contributed reagents/materials/analysis tools. SRC and JSW wrote the paper.
Academic Editor: David Eisenberg, University of California, Los Angeles
Citation: Collins SR, Douglass A, Vale RD, Weissman JS (2004) Mechanism of prion propagation: Amyloid growth occurs by monomer addition. PLoS Biol 2(10): e321.
AFM
: atomic force microscopy
AUC
: analytical ultracentrifugation
GuHCl
: guanidine hydrochloride
NM
: a fragment of the Sup35 protein containing the glutamine/asparagine-rich N-terminal (N) and highly charged middle (M) domains
TIRF
: total internal reflection fluorescence microscopy
|
PubMed Central
|
2024-06-05T03:55:47.804428
|
2004-9-21
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517824/",
"journal": "PLoS Biol. 2004 Oct 21; 2(10):e321",
"authors": [
{
"first": "Sean R",
"last": "Collins"
},
{
"first": "Adam",
"last": "Douglass"
},
{
"first": "Ronald D",
"last": "Vale"
},
{
"first": "Jonathan S",
"last": "Weissman"
}
]
}
|
PMC517825
|
Introduction {#s1}
============
A fundamental challenge in the field of development is to understand the entire program of gene expression for a single differentiating cell type in terms of an underlying regulatory circuit. This challenge can be met in part through recent advances in transcriptional profiling, which have made it possible to catalog changes in gene expression on a genome-wide basis ([@pbio-0020328-Brown1]). However, most systems of development involve multiple differentiating cell types, complicating the challenge of deciphering the program of gene expression for individual cell types. Also, many developmental systems are insufficiently accessible to genetic manipulation to allow genome-wide changes in gene expression to be understood in detail in terms of an underlying regulatory program. An understanding of how a cell differentiates from one type into another requires both a comprehensive description of changes in gene expression and an elucidation of the underlying regulatory circuit that drives the program of gene expression. Here we report our efforts to comprehensively catalog the program of gene expression in a primitive system of cellular differentiation, spore formation in the bacterium *Bacillus subtilis,* and to understand the logic of this program in terms of a simple regulatory circuit involving the ordered appearance of two RNA polymerase sigma factors and three positively and/or negatively acting DNA-binding proteins.
Spore formation in B. subtilis involves the formation of an asymmetrically positioned septum that divides the developing cell (sporangium) into unequal-sized progeny that have dissimilar programs of gene expression and distinct fates ([@pbio-0020328-Piggot1]; [@pbio-0020328-Stragier2]; [@pbio-0020328-Piggot2]; [@pbio-0020328-Errington1]). The two progeny cells are called the forespore (the smaller cell) and the mother cell. Initially, the forespore and the mother cell lie side by side, but later in development the forespore is wholly engulfed by the mother cell, pinching it off as a cell within a cell. The forespore is a germ cell in that it ultimately becomes the spore and, upon germination, gives rise to vegetatively growing cells. The mother cell, on the other hand, is a terminally differentiating cell type that nurtures the developing spore but eventually undergoes lysis to liberate the fully ripened spore when morphogenesis is complete. The entire process of spore formation takes 7--8 h to complete with approximately 5 h of development taking place after the sporangium has been divided into forespore and mother-cell compartments.
Much is known about the transcription factors that drive the process of spore formation, and in several cases transcriptional profiling has been carried out to catalog genes switched on or switched off by individual sporulation regulatory proteins ([@pbio-0020328-Fawcett1]; [@pbio-0020328-Britton1]; [@pbio-0020328-Eichenberger2]; [@pbio-0020328-Feucht1]; [@pbio-0020328-Molle1]). Here we have attempted to go a step further by comprehensively elucidating the program of gene expression for a single cell type in the developing sporangium. For this purpose we focused on the mother cell and its 5-h program of gene expression. Gene expression in the mother cell is governed by five positively and/or negatively acting transcription factors. These are the sigma factors σ^E^ and σ^K^ and the DNA-binding proteins GerE, GerR (newly characterized in the present study), and SpoIIID.
The appearance of these regulatory proteins is governed by a hierarchical regulatory cascade of the form: σ^E^→SpoIIID/GerR→σ^K^→GerE ([Figure 1](#pbio-0020328-g001){ref-type="fig"}A) in which σ^E^ is the earliest-acting factor specific to the mother-cell line of gene expression ([@pbio-0020328-Zheng2]; results presented herein). The σ^E^ factor is derived from an inactive proprotein, pro-σ^E^ ([@pbio-0020328-LaBell1]), whose synthesis commences before asymmetric division ([@pbio-0020328-Satola1]; [@pbio-0020328-Baldus1]), but whose continued synthesis becomes strongly biased to the mother cell after asymmetric division ([@pbio-0020328-Fujita1] [@pbio-0020328-Fujita2]). Proteolytic conversion to mature σ^E^ takes place just after asymmetric division ([@pbio-0020328-Stragier3]) and is triggered by an intercellular signal transduction pathway involving a secreted signaling protein that is produced in the forespore under the control of the forespore-specific transcription factor σ^F^ ([@pbio-0020328-Hofmeister1]; [@pbio-0020328-Karow1]; [@pbio-0020328-Londono-Vallejo1]). Transcriptional profiling has established that σ^E^ turns on an unusually large regulon consisting of 262 genes, which are organized in 163 transcription units ([@pbio-0020328-Eichenberger2]; results presented herein). Among the targets of σ^E^ are the genes for the DNA-binding proteins SpoIIID and GerR ([@pbio-0020328-Kunkel1]; [@pbio-0020328-Stevens1]; [@pbio-0020328-Tatti1]; [@pbio-0020328-Wu1]; results presented herein). SpoIIID is both a negatively acting protein that switches off the transcription of certain genes that have been activated by σ^E^ and a positively acting protein that acts in conjunction with σ^E^-containing RNA polymerase to switch on additional genes, including genes involved in the appearance of σ^K^ ([@pbio-0020328-Kroos1]).
::: {#pbio-0020328-g001 .fig}
Figure 1
::: {.caption}
###### The Mother-Cell Line of Gene Transcription
\(A) Gene transcription is governed by a hierarchical regulatory cascade that involves gene activation and gene repression. The σ^E^ factor turns on a large regulon that includes the genes for GerR and SpoIIID. These DNA-binding proteins, in turn, block further transcription of many of the genes that had been activated by σ^E^. SpoIIID is also an activator, and it turns on genes required for the appearance of pro-σ^K^. The conversion of pro-σ^K^ to mature σ^K^ is governed by a signal emanating from the forespore as represented by the squiggle. Next, σ^K^ activates the subsequent regulon in the cascade, which includes the gene for the DNA-binding protein GerE. Finally, GerE, which, like SpoIIID, is both an activator and a repressor, turns on the final regulon in the cascade while also repressing many of the genes that had been activated by σ^K^. The thickness of lines represents the relative abundance of genes activated (arrows) or repressed (lines ending in bars) by the indicated regulatory proteins.
\(B) The regulatory circuit is composed of two coherent FFLs linked in series and three incoherent FFLs. In the first coherent FFL, σ^E^ turns on the synthesis of SpoIIID, and both factors act together to switch on target genes, including genes involved in the appearance of σ^K^. Likewise, in the second coherent FFL, σ^K^ directs the synthesis of GerE, and the two factors then act together to switch on target genes (X~4~). The σ^E^ factor and SpoIIID also constitute an incoherent FFL in which SpoIIID acts as a repressor to downregulate the transcription of a subset of the genes (X~2~) that had been turned on by σ^E^. Similar incoherent FFLs are created by the actions of σ^E^ and GerR (X~1~) and by σ^K^ and GerE (X~3~), with GerR and GerE repressing genes that had been switched on by σ^E^ and σ^K^, respectively. The AND symbols indicate that the FFLs operate by the logic of an AND gate in that the output (either gene activation or a pulse of gene expression) requires the action of both transcription factors in the FFL (see [@pbio-0020328-Mangan1]). For example, σ^K^ and GerE are both required for the activation of X~4~ genes, whose induction is delayed compared to genes that are turned on by σ^K^ alone. Similarly, both σ^E^ and the delayed appearance of GerR are anticipated to create a pulse of transcription of X~1~ genes.
:::
:::
The appearance of σ^K^ is a critical control point that involves multiple levels of regulation: transcription, DNA recombination, and proprotein processing. SpoIIID both activates the transcription of the 5′ coding region for σ^K^ *(spoIVCB)* and that for a site-specific DNA recombinase *(spoIVCA)* ([@pbio-0020328-Kunkel2]; [@pbio-0020328-Halberg1]) that joins the 5′ coding sequence to the 3′ coding region by the excision of an intervening sequence of 48 kb called *skin* ([@pbio-0020328-Stragier4]). Finally, the product of the intact coding sequence is an inactive proprotein, pro-σ^K^ ([@pbio-0020328-Kroos1]), whose conversion to mature σ^K^ (as in the case of pro-σ^E^) is governed by a complex, intercellular signal transduction pathway involving a secreted signaling protein that is produced in the forespore under the control of the forespore-specific transcription factor σ^G^ ([@pbio-0020328-Cutting3], [@pbio-0020328-Cutting4]; [@pbio-0020328-Lu2]). The signal transduction pathway helps to coordinate the appearance of σ^K^ in the mother cell with the timing of events taking place in the forespore. The σ^K^ factor turns on an additional gene set that includes the gene for GerE ([@pbio-0020328-Cutting2]), a DNA-binding protein that is responsible for activating the final temporal class of genes in the mother-cell line of gene expression ([@pbio-0020328-Zheng1]).
Other than the case of σ^E^, little was previously known about the full set of genes, whose transcription is governed by the five regulators in the mother-cell line of gene expression---indeed, nothing at all in the case of GerR, whose function had previously been uncharacterized. Here we present evidence indicating that the program of mother-cell-specific gene transcription involves the activation of at least 383 genes (242 transcription units), representing 9% of the genes in the B. subtilis genome. We explain the pattern of transcription of each of these genes in terms of the action of the five regulatory proteins that govern the mother-cell program of gene transcription. Our results reveal that the program chiefly consists of a series of pulses in which large numbers of genes are turned on and are then turned off shortly thereafter by the action of the next regulatory protein in the hierarchy. Evidence is also presented that this repression is critical for proper morphogenesis. Finally, we show that the mother-cell program of gene transcription can be understood in terms of a simple regulatory circuit involving a linked series of feed-forward loops (FFLs) that are responsible for generating pulses of gene transcription. We propose that this regulatory circuit will serve as a model for understanding other programs of cellular differentiation.
Results {#s2}
=======
Transcriptional Profiling {#s2a}
-------------------------
Our strategy for elucidating the mother-cell program of gene transcription was to carry out transcriptional profiling at hourly intervals during sporulation at 37 °C, starting just after asymmetric division and ending before the time at which lysis of the mother cell had commenced. At each time point, RNA from cells mutant for the transcriptional regulator that was maximally active at that time interval was compared against RNA from cells mutant for the next transcription factor in the hierarchy or, in the case of the last regulatory protein in the hierarchy, GerE, against RNA from wild-type cells. Thus, at hour 2.5, RNA from cells mutant for σ^E^ (strain PE437) was compared against RNA from cells (strain PE436) that were wild type for σ^E^ but mutant for the next regulatory protein in the sequence, SpoIIID. Likewise, at hour 3.5, RNA from cells that were mutant for SpoIIID (strain PE456) was compared against RNA from cells that were mutant for σ^K^ (strain PE452). (Strains PE456 and PE452 were additionally mutant for σ^G^ to eliminate indirect effects of the presence or absence of SpoIIID on the activity of the forespore-specific transcription factor. Although SpoIIID has no direct effect on σ^G^, the absence of negative feedback on several σ^E^-controlled genes \[see below\] in the strain mutated for *spoIIID* could have had indirect consequences on σ^G^ activity.) Likewise, at hour 4.5, RNA from cells that were mutant for σ^K^ (strain PE455) was compared against RNA from cells mutant for GerE (strain PE454). Finally, at hours 5.5 and 6.5, RNA from cells mutant for GerE was compared against RNA from wild-type cells (PY79). Three transcriptional-profiling analyses were carried out for each of these time points, using three independent preparations of RNA from each of the two cultures of cells that were being compared against each other. The complete dataset for these experiments is presented in [Table S1](#st001){ref-type="supplementary-material"}, and transcriptional profiles for representative genes are displayed in [Table 1](#pbio-0020328-t001){ref-type="table"}.
::: {#pbio-0020328-t001 .table-wrap}
Table 1
::: {.caption}
###### Transcriptional Profile of Representative Genes
:::
^a^ Ratios of relative RNA levels in *sigE* ^+^ versus *sigE* mutant
^b^ Ratios of relative RNA levels in *spoIIID* ^+^ versus *spoIIID* mutant
^c^ Ratios of relative RNA levels in *gerR* ^+^ versus *gerR* mutant
^d^ Ratios of relative RNA levels in *sigK* ^+^ versus *sigK* mutant
^e^ Ratios of relative RNA levels in wild type versus *gerE* mutant
:::
In addition to the four previously known members of the hierarchical regulatory cascade, one of the genes in the σ^E^ regulon is inferred to encode a previously uncharacterized DNA-binding protein YlbO ([@pbio-0020328-Wu1]; [@pbio-0020328-Eichenberger2]). Additional transcriptional-profiling experiments were carried out to assess the function of this putative regulatory protein.
Updating the σ^E^ Regulon {#s2b}
-------------------------
We previously reported that the σ^E^ regulon is composed of 253 genes, organized in 157 transcription units. Since then two additional σ^E^-controlled genes, *yjcA* ([@pbio-0020328-Kuwana2]) and *ctpB (yvjB)* ([@pbio-0020328-Pan1]), have been identified. These genes were found to be transcribed in a σ^E^-dependent manner during sporulation in our previous analysis, but they were not significantly induced in cells engineered to produce σ^E^ during growth and hence had not been included in our original list of σ^E^-controlled genes. In addition, results presented here (see below) show that one gene, *ypqA,* and two operons, *yhcOP* and *yitCD,* that are chiefly under the control of σ^K^, are also transcribed, albeit at a low level, in a σ^E^-dependent manner. These and other considerations (see below) bring the current total number of genes in the σ^E^ regulon to 262 and the total number of transcription units to 163 ([Table 2](#pbio-0020328-t002){ref-type="table"}).
::: {#pbio-0020328-t002 .table-wrap}
Table 2
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###### Genes Activated in the Mother-Cell Line of Gene Expression
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^a^ Includes four genes (two transcription units) that were also repressed by SpoIIID and one gene (one transcription unit) that was also activated by SpoIIID
^b^ Only includes genes that were strongly dependent upon SpoIIID for expression. Fifteen genes (11 transcription units) that were partially dependent on SpoIIID are in the "activated by σ^E^" category
^c^ Only includes genes that were strongly dependent upon GerE for expression. Twenty-eight genes (12 transcription units) that were partially dependent on GerE for expression are in the "activated by σ^K^" category
^d^ Numbers include genes and transcription units that were transcribed under the control of σ^E^ as well as σ^K^
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This updated description of the σ^E^ regulon does not include genes and transcription units that are additionally strongly dependent upon SpoIIID for their transcription because our previous transcriptional-profiling experiments were performed with a strain that was mutant for SpoIIID. SpoIIID is a DNA-binding protein that acts in conjunction with σ^E^-containing RNA polymerase ([@pbio-0020328-Kroos1]; [@pbio-0020328-Kunkel1]; [@pbio-0020328-Halberg1]). Therefore, as a starting point for the present study, we investigated the influence of SpoIIID on the global pattern of σ^E^-directed transcription. As we shall see, this analysis revealed ten genes (representing eight transcription units) that were strongly dependent upon SpoIIID for expression and were not expressed under the control of σ^E^ alone**,** bringing the present total number of genes in the σ^E^ regulon to 272 and the total number of transcription units to 171 ([Table 2](#pbio-0020328-t002){ref-type="table"}).
SpoIIID Is Both a Repressor and an Activator of Genes Whose Transcription Is Dependent Upon σ^E^ {#s2c}
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Transcriptional profiling revealed that SpoIIID had profound effects on the global pattern of σ^E^-directed gene transcription. As many as 181 genes were found to be downregulated in the presence of SpoIIID. Of these, 148 had previously been identified as being activated in a σ^E^-dependent manner, at least 112 of which (representing 62 transcription units) were bona fide members of the σ^E^ regulon (that is, they met multiple criteria for being under the direct control of σ^E^) (see [Table S2](#st002){ref-type="supplementary-material"}). Therefore, a principal function of SpoIIID is to inhibit the transcription of a substantial proportion (greater than 40%) of the genes whose transcription had been activated by σ^E^ prior to the appearance of SpoIIID. Members of the σ^E^ regulon that are downregulated by SpoIIID are colored green in [Figure 2](#pbio-0020328-g002){ref-type="fig"}A.
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Figure 2
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###### Location of Genes in the σ^E^ and σ^K^ Regulons and Their Regulation by DNA-Binding Proteins
\(A) The σ^E^ regulon and its modulation by SpoIIID and GerR. The first gene of each σ^E^-controlled transcription unit identified by transcriptional profiling is indicated. In the inner circle, genes repressed by SpoIIID are green, and genes repressed by GerR are blue. In the outer circle, genes partially dependent on SpoIIID for expression are orange, and genes strongly dependent on SpoIIID are red. Underlined are SpoIIID-controlled genes for which SpoIIID binding to their upstream sequences has been demonstrated biochemically. Genes unaffected by SpoIIID or GerR are indicated in black.
\(B) The σ^K^ regulon and its modulation by GerE. The first gene of each σ^K^-controlled transcription unit identified by transcriptional profiling is indicated. In the inner circle, genes repressed by GerE are green. In the outer circle, genes partially dependent on GerE for expression are orange, and genes strongly dependent on GerE are red. Genes unaffected by GerE are indicated in black.
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SpoIIID not only repressed many genes in the σ^E^ regulon but also stimulated or activated the transcription of many others. At least 70 genes were identified whose transcription was upregulated by SpoIIID ([Table S2](#st002){ref-type="supplementary-material"}), but in many cases these genes were not members of the σ^E^ regulon, and the effect of SpoIIID could have been indirect. Examples are seven genes *(cysK , cysH, cysP, sat, cysC, yoaD,* and *yoaB)* from the S-box regulon ([@pbio-0020328-Grundy1]) and two genes *(argC* and *argJ)* from the arginine biosynthesis operon ([@pbio-0020328-Smith3]). In other cases, however, SpoIIID stimulated or activated the transcription of genes that had been reported to be under the control of σ^E^. Thus, 13 *(asnO, cwlJ, proH, proJ, spoIVCA, spoIVCB, spoVK , yhbB, yheC, yheD, yknT, yknU,* and *yknV)* of the genes whose transcription was upregulated by SpoIIID had previously been assigned to the σ^E^ regulon, and four others *(mpr, ycgM, ycgN,* and *yqfT)* were known to be under σ^E^ control but had not met all of the criteria for assignment to the σ^E^ regulon ([@pbio-0020328-Eichenberger2]). In two of these 17 cases *(spoIVCA* and *spoVK),* the dependence on SpoIIID was almost complete, whereas in the other 15 the dependence was partial.
Our analysis revealed eight additional genes *(cotF, cotT, cotV, cotW, lip, ydcI, yheI,* and *yheH)* that were almost completely dependent on SpoIIID for their transcription and that are likely to be under the dual control of σ^E^ and SpoIIID. Thus, in addition to repressing at least 112 members of the σ^E^ regulon, SpoIIID activates the transcription of 25 other members of the regulon, representing 19 transcription units. The 15 σ^E^-transcribed genes (11 transcription units) whose expression was partially dependent upon SpoIIID are indicated in orange in [Figure 2](#pbio-0020328-g002){ref-type="fig"}B, and those whose expression was completely dependent on the DNA-binding protein are indicated in red (ten genes; eight transcription units).
Evidently, then, SpoIIID plays a pivotal role in the mother-cell line of gene expression, negatively or positively affecting the transcription of many members of the σ^E^ regulon. It was therefore important to determine whether the genes so affected were direct targets of the DNA-binding protein. For this purpose, we used three complementary approaches to identifying binding sites for SpoIIID: biochemical analysis by gel electrophoretic mobility-shift assays (EMSAs) and DNAase I footprinting, in vivo analysis by chromatin-immunoprecipitation in combination with gene microarrays (ChIP-on-chip), and the identification of SpoIIID-binding sequences by computational analysis.
Biochemical Identification of SpoIIID-Binding Sites {#s2d}
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We selected 18 of the newly identified SpoIIID-regulated genes for EMSA analysis, mostly on the basis of the importance of their role in sporulation. As positive controls, we subjected two previously known targets of SpoIIID, *bofA* and *spoIVCA* ([@pbio-0020328-Halberg1]), to EMSA analysis, and as negative controls three Spo0A-regulated genes ([@pbio-0020328-Molle1]), *abrB, racA,* and *spoIIGA* ([Figure 3](#pbio-0020328-g003){ref-type="fig"}A). SpoIIID exhibited binding to the upstream sequence of all 18 of the selected genes ([Figure 3](#pbio-0020328-g003){ref-type="fig"}B). In some cases (those of *asnO, gerM, spoIVA, spoIVFA, ybaN, ycgF, yitE, ykvU,* and *ylbJ*) additional shifted bands were detected at high concentrations of SpoIIID, which may indicate the presence of two or more SpoIIID-binding sites with distinct binding affinities.
::: {#pbio-0020328-g003 .fig}
Figure 3
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###### Gel Electrophoretic Mobility-Shift Analysis of SpoIIID Binding
DNA fragments of interest were amplified by PCR, gel-purified, and end-labeled using \[γ-^32^P\]-ATP and polynucleotide kinase. Purified SpoIIID was added at increasing concentrations (0 nM for lanes 1 and 5, 50 nM for lane 2, 100 nM for lane 3, and 200 nM for lane 4) and incubated at room temperature for 30 min before loading on to a nondenaturing gel containing 6% polyacrylamide. With the exception of (D), the DNA fragments corresponded to the upstream regions of the indicated genes. See [Materials and Methods](#s4){ref-type="sec"} for the identity (coordinates) of the specific DNA sequences used in the analyses.
\(A) Gel shifts for known targets of SpoIIID (*bofA* and *spoIVCA*), representing positive controls, and genes (*abrB, spoIIGA,* and *racA*) under the control of another DNA-binding protein (Spo0A), representing negative controls.
\(B) Gel shifts for genes identified as possible targets of SpoIIID by transcriptional profiling.
\(C) Gel shift for *cotE*. Expression of *cotE* from its P2 promoter is strongly dependent on SpoIIID. No binding of SpoIIID to the upstream sequence for *cotE* is observed, suggesting that the effect of SpoIIID on transcription from the P2 promoter is indirect.
\(D) Gel shifts for chromosomal regions strongly enriched for SpoIIID binding as judged by ChIP-on-chip analysis. For each region, four consecutive DNA fragments of approximately 400 nucleotides in length were analyzed.
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In addition, we also subjected the upstream region of *cotE* to EMSA analysis ([Figure 3](#pbio-0020328-g003){ref-type="fig"}C). The *cotE* gene is transcribed from two promoters: a σ^E^-controlled promoter called P1 and a second promoter called P2 that strongly depends on SpoIIID ([@pbio-0020328-Zheng2]). It had been assumed that transcription from P2 is under the dual control of σ^E^ and SpoIIID, but EMSA analysis failed to reveal a binding site for SpoIIID, and other work presented below indicates that transcription from *cotE* P2 is governed by σ^K^ rather than by σ^E^. We conclude that the SpoIIID dependence of *cotE* P2 is an indirect consequence of the dependence of σ^K^ synthesis on SpoIIID.
To obtain further evidence for direct interaction by SpoIIID and to investigate the mechanism by which SpoIIID inhibits transcription, we subjected the promoter regions of three genes *(spoIID, spoIIIAA,* and *spoVE)* identified as being under the negative control of SpoIIID to DNAase I footprinting analysis. SpoIIID protected two regions in the upstream sequence of *spoIID* from DNAase I digestion ([Figure S1](#sg001){ref-type="supplementary-material"}). One region (extending from positions −10 to −28 on the top strand and from −18 to −35 on the bottom strand) overlapped with the −10 element of the σ^E^ promoter, and the other (extending from −33 to −52 on the top strand) overlapped with the −35 element. The binding site for SpoIIID also overlapped with the promoter in the case of *spoIIIAA,* in this case protecting a single sequence that included the −35 element (extending from −21 to −45 on the top strand and from −30 to −48 on the bottom strand). Finally, the regulatory sequence of *spoVE* exhibited two binding sites, one (extending from +16 to −1 on the bottom strand) that was located in the vicinity of the predominant σ^E^-controlled promoter (P2) for this gene and another further upstream, overlapping with a secondary promoter (P1) (extending from +13 to −7 on the top strand). Thus, repression of the promoters of *spoIID, spoIIIAA,* and *spoVE* by SpoIIID is likely to be a direct consequence of the binding of the sporulation regulatory protein to the promoter in such a way as to compete with binding by σ^E^--RNA polymerase.
SpoIIID Binds to Some Sites that Do Not Correspond to Genes under Its Control {#s2e}
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ChIP-on-chip analysis was carried out as described in [Materials and Methods](#s4){ref-type="sec"} and previously ([@pbio-0020328-Molle1], [@pbio-0020328-Molle2]), using DNA--protein complexes from formaldehyde-treated cells at hour 3 of sporulation. After sonication, SpoIIID--DNA complexes were precipitated with antibodies against SpoIIID. Next, after reversal of the cross-links, the precipitated DNAs were amplified by PCR in the presence of cyanine 5-dUTP. In parallel, total sonicated DNA from the formaldehyde-treated cells (i.e., DNA that had not been subjected to immunoprecipitation) was similarly amplified, but in the presence of cyanine 3-dUTP. The two differentially labeled DNAs were combined and hybridized to the same batch of DNA microarrays that were used for the transcriptional-profiling experiments. Transcriptional profiling was carried out with three independent preparations of formaldehyde-treated cells, twice with two of the preparations and once with the third, for a total of five analyses. An enrichment factor was calculated for each gene, representing the enrichment of that gene by immunoprecipitation relative to DNA that had not been subjected to immunoprecipitation, and the entire dataset is displayed in [Table S3](#st003){ref-type="supplementary-material"}.
Thirty-one genes, corresponding to 26 regions of the chromosome, were found to be enriched by immunoprecipitation by a factor of two or greater. Only seven of the regions *(cotF, lip, spoIIIAF, spoVD, ycgF, yhbH,* and *ykvI)* identified by the ChIP-on-chip analysis were in close proximity to a gene that was differentially expressed in the SpoIIID transcriptional-profiling experiments. Thus, in only a small number of cases did ChIP-on-chip analysis support the idea that a gene under SpoIIID control was a direct target of the DNA-binding protein. Our interpretation of these findings is that ChIP-on-chip is less sensitive for detecting SpoIIID-binding sites than it is for the B. subtilis DNA-binding proteins CodY ([@pbio-0020328-Molle2]), Spo0A ([@pbio-0020328-Molle1]), and RacA ([@pbio-0020328-Ben-Yehuda1]). Likely contributing to this decreased sensitivity is the fact that SpoIIID is present in only one of the two chromosome-containing compartments (the mother cell) of the sporangium and that its concentration is low (∼1 μM; [@pbio-0020328-Zhang1]).
While providing support for only a small proportion of the herein identified targets of SpoIIID regulation, ChIP-on-chip analysis, nonetheless, proved to be revealing. Specifically, we found that SpoIIID bound to many regions of the chromosome that did not correspond to genes under its negative or positive control. Were these regions bona fide SpoIIID-binding sites? To address this question, we subjected five regions that were most enriched for SpoIIID-binding *(albE*--*albF, dctR*--*dctP, tenI*--*goxB*--*thiS, treA*--*treR--yfkO,* and *yfmC--yfmD)* to EMSA analysis ([Figure 3](#pbio-0020328-g003){ref-type="fig"}D). Given that SpoIIID was not exerting a transcriptional effect in these regions, we reasoned that the sites to which SpoIIID was binding might not reside in upstream regulatory regions and could instead be located in coding sequences. We therefore scanned across each of the five chromosomal regions by EMSA using successive DNA fragments of about 400 bp in length. The results showed that each of the five regions contained more than one binding site for SpoIIID and that some of these binding sites were indeed located within protein-coding sequences. (The presence of more than one binding site in each region may have facilitated their detection by the ChIP-on-chip analysis.) We conclude that SpoIIID binds to some sites on the chromosome at which it does not function as a transcriptional regulator. Conceivably, it plays an architectural role in the folding of the chromosome in the mother cell in addition to its role as a transcriptional regulator. [@pbio-0020328-Moqtaderi1] have similarly found that in Saccharomyces cerevisiae the RNA polymerase III transcription factor TFIIIC binds to sites where binding of other components of the RNA polymerase III machinery is not detected and where the transcription factor does not activate transcription.
Identification of Putative SpoIIID-Binding Sites by Bioinformatics {#s2f}
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As a final, computational approach to identifying direct targets of SpoIIID, we used the Gibbs sampling algorithm BioProspector to identify conserved motifs in sequences upstream of genes under the control of SpoIIID ([@pbio-0020328-Liu1]). Initially, we limited our search to 40 regions where SpoIIID binding had been confirmed by biochemical analysis. BioProspector was used to find the best 35 motifs across several different widths (6--12 bp) under the restriction that every sequence had to contain at least one site. Each of these motifs was separately used as a starting point for BioOptimizer ([@pbio-0020328-Jensen1]) and applied to an expanded dataset that included the 89 upstream sequences for all SpoIIID-controlled genes (not just those analyzed by EMSA or footprinting). BioOptimizer optimized both the set of predicted sites and the motif width, as detailed in the [Materials and Methods](#s4){ref-type="sec"} section. BioOptimizer was required to identify at least one binding site in the sequences that had been confirmed by EMSA but was unrestricted for the sequences for which a binding site had not been confirmed biochemically. The optimized motif was 8 bp in length and identified at least one putative SpoIIID-binding site in 60 of the 89 upstream sequences that were analyzed (see [Table S2](#st002){ref-type="supplementary-material"}). [Figure 4](#pbio-0020328-g004){ref-type="fig"} shows that the logo for the optimized motif (B) was similar to a consensus sequence (A) that was derived independently using 12 previously reported binding sites (for the genes *bofA, cotD, spoVD, spoIVCA,* and *spoIVCB;* [@pbio-0020328-Halberg1]; [@pbio-0020328-Zhang1]) and five sites herein identified by DNAase I footprinting.
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Figure 4
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###### Consensus Sequences for SpoIIID, σ^K^, and σ^E^
Consensus sequences are displayed as sequence logos ([@pbio-0020328-Schneider1]). The height of the letters in bits represents the information content at each position (the maximum value is two bits).
\(A) Consensus binding sequence for SpoIIID as derived from 17 SpoIIID-binding sites mapped by DNAase I footprinting ([@pbio-0020328-Halberg1]; [@pbio-0020328-Zhang1]; results presented herein).
\(B) Consensus binding sequence for SpoIIID obtained by compilation of 68 putative SpoIIID-binding sites identified as common motifs by BioProspector and BioOptimizer analysis in sequences upstream of genes identified by transcriptional profiling or within regions identified by ChIP-on-chip analysis.
\(C) Consensus binding sequence for SpoIIID obtained by MDscan analysis of the sequences of 26 SpoIIID-binding regions identified by ChIP-on-chip analysis.
\(D) Consensus promoter sequence for σ^K^-containing RNA polymerase obtained from the compilation of 58 sequences identified as common motifs in regions upstream of σ^K^-regulated genes by a BioProspector/BioOptimizer computational approach ([@pbio-0020328-Jensen1]). Positions 1--5 on the horizontal axis correspond to the −35 element and positions 21--30 to the −10 element. The optimal spacing between the two regions is 15 bp (± 1 bp).
\(E) Consensus promoter sequence for σ^K^-containing RNA polymerase obtained from the compilation of 23 previously mapped (<http://dbtbs.hgc.jp/>; [@pbio-0020328-Helmann1]) and 18 newly identified σ^K^-controlled promoters identified by transcription start site mapping.
\(F) Consensus promoter sequence for σ^E^-containing RNA polymerase obtained from the compilation of 62 σ^E^-controlled promoters identified by transcription start site mapping ([@pbio-0020328-Eichenberger2]). Positions 1--8 on the horizontal axis correspond to the −35 element, and positions 21--30 to the −10 element. The optimal spacing between the two regions is 12 bp (± 1 bp).
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In an independent computational approach, we sought to identify a conserved motif in the 26 regions that had been identified by ChIP-on-chip analysis, which likely represent the strongest binding sites for SpoIIID. We used Motif Discovery scan(MDscan) ([@pbio-0020328-Liu2]) for this analysis, which is designed to identify conserved motifs in sequences that have been ranked according to their enrichment factor in ChIP-on-chip experiments. The resulting sequence logo is displayed in [Figure 4](#pbio-0020328-g004){ref-type="fig"}C. Whereas it is largely similar to that obtained from the BioProspector/BioOptimizer analysis ([Figure 4](#pbio-0020328-g004){ref-type="fig"}B), there is one notable difference: The first position of the binding motif corresponds almost exclusively to a guanine in the sites identified by ChIP-on-chip analysis. The presence of a guanine at this position could be characteristic of high-affinity sites for SpoIIID binding.
In conclusion, SpoIIID negatively or positively influences the transcription of over half of the members of the σ^E^ regulon, and a combination of complementary approaches leads us to believe that it does so for many of the genes so identified by direct interaction with their promoter regions. In the case of genes under the negative control of SpoIIID, the mechanism of this repression probably involves steric interference as the inferred binding sites for SpoIIID were generally found to overlap with the expected binding sites for RNA polymerase. No such overlap was generally observed in the case of genes under the positive control of SpoIIID.
GerR *(ylbO),* a Second Negative Regulator of the σ^E^ Regulon {#s2g}
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The *spoIIID* gene is not the only member of the σ^E^ regulon that appears to encode a DNA-binding protein. The inferred product of *ylbO* exhibits significant similarity to members of the basic leucine zipper family of transcription factors and is, in particular, 52% similar to RsfA ([@pbio-0020328-Wu1]), a regulator of σ^F^-controlled genes in the forespore line of gene expression. To study a possible role for *ylbO* we investigated the effect of a null mutation of the gene on sporulation and on σ^E^-directed gene expression. As noted previously, the mutation has no effect on the production of heat-resistant spores, but we have now discovered that the mutation causes a conspicuous defect in the capacity of the spores to germinate, as judged by their impaired ability to reduce 2,3,5-triphenyltetrazolium chloride (see [Materials and Methods](#s4){ref-type="sec"}). We therefore rename *ylbO* as *gerR* (in keeping with the nomenclature for germination genes in B. subtilis \[[@pbio-0020328-Setlow1]\]). We also carried out transcriptional profiling using RNA collected at hour 3.5 of sporulation from cells of a strain (PE454) that was wild type for GerR and from cells of a newly constructed strain (SW282) that was mutant for GerR. Both strains were also mutant for the next transcription factor in the hierarchical cascade, σ^K^. No genes were identified whose transcription was dependent on GerR, but 139 genes were found that were downregulated in a GerR-dependent manner by a factor of two or greater (see [Table S1](#st001){ref-type="supplementary-material"}). Among the downregulated genes were 14 members of the σ^E^ regulon. Nine of these members (colored blue in [Figure 2](#pbio-0020328-g002){ref-type="fig"}A) were known not to be under SpoIIID control *(cypA, kapD, spoIIM, spoIIP, ybaS , yfnE , yfnD, yhjL,* and *yqhV),* whereas the remaining five *(phoB, spoIIIAA, spoIIIAB, spoIVCA,* and *ydhF)* were also under the control of SpoIIID.
We selected three of the putative targets of GerR for further analysis. The promoter sequences of *spoIIM* and *yqhV* were fused to the coding sequence of β-galactosidase and introduced into the chromosome at the *amyE* locus and a previously constructed fusion of *lacZ* to *spoIIP (amyE*::*spoIIP*-*lacZ)* was obtained from P. Stragier (Institut de Biologie Physico-Chimique, Paris). The results, shown in [Figure 5](#pbio-0020328-g005){ref-type="fig"}, confirmed that GerR had a pronounced negative effect on the level of expression of all three fusions.
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Figure 5
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###### Repression of σ^E^ -Controlled Genes by GerR
Culture samples from strains PE551 (solid triangles, *amyE*::P*~spoIIM~--lacZ*), SW312 (open triangles, *amyE*::P*~spoIIM~--lacZ,* Δ*gerR*), PE511 (solid squares, *amyE*::*spoIIP--lacZ*), PE568 (open squares, *amyE*::*spoIIP--lacZ,*Δ*gerR*), PE553 (solid diamonds, *amyE*::P*~yqhV~--lacZ*), and PE558 (open diamonds, *amyE*::P*~yqhV~--lacZ,* Δ*gerR*) were collected at indicated intervals after the start of sporulation in Sterlini--Mandelstam medium and analyzed for β-galactosidase activity.
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An example of σ^E^-controlled genes that are under the dual negative control of GerR and SpoIIID is the eight-cistron *spoIIIA* operon ([@pbio-0020328-Illing1]). As we have demonstrated, GerR is responsible for repressing *yqhV,* which is located just upstream of the *spoIIIA* operon. Given the absence of an apparent transcriptional terminator at the end of the gene, σ^E^-directed transcription from *yqhV* is likely to read into *spoIIIA,* which is also transcribed from its own σ^E^-controlled promoter located in the intergenic region between *yqhV* and the operon. Thus, by repressing *yqhV,* GerR would inhibit read-through transcription into *spoIIIA*. Indeed, our transcriptional-profiling analysis revealed a small negative effect of GerR on *spoIIIA* transcription. Meanwhile, SpoIIID acts at the promoter for the *spoIIIA* operon to inhibit it from being used by σ^E^-RNA polymerase. Thus, maximum repression of *spoIIIA* is evidently achieved by the combined action of GerR and SpoIIID, each acting to block different promoters.
Finally, we note that GerR inhibited the expression of a large number of genes that do not belong to the σ^E^ regulon. Interestingly, many of these genes are organized in large clusters, such as *azlB--azlC--azlD--bnrQ--yrdK--gltR, albA--albB--albC--albD, yefA--yefB--yefC--yeeA--yeeB--yeeC, yjcM--yjcN--yjcO,* and *yydB--yydC--yydD--yydG--yydH--yyd --yydJ*. The genes found in these clusters rarely belong to a single transcription unit and are sometimes transcribed in opposite directions (either convergently or divergently).
In summary, transcription of genes in the σ^E^ regulon is in part self-limiting. The σ^E^ factor induces the synthesis of two proteins, GerR and SpoIIID, that act to switch off other genes in the regulon, thereby preventing their continued transcription during the next stage of the mother-cell line of gene expression.
The σ^K^ Regulon {#s2h}
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Next, we used two complementary transcriptional-profiling approaches to identify genes under the control of σ^K^, an RNA polymerase sigma factor that follows SpoIIID in the hierarchical regulatory cascade. In one approach, we sought to identify genes that were upregulated during sporulation in a σ^K^-dependent (but not a GerE-dependent) manner. In the other approach, we sought to identify genes whose transcription was artificially activated in cells engineered to produce σ^K^ during growth. For this approach we used a strain in which the coding sequence for the mature form of the transcription factor (σ^K^ is normally derived by proteolytic processing from an inactive proprotein \[[@pbio-0020328-Kroos1]\]) was under the control of an inducible promoter (see [Materials and Methods](#s4){ref-type="sec"}). Ninety-five genes were identified that were induced both during growth and sporulation in a σ^K^-dependent manner. Eight additional genes *(cotA, cotE, cotM*, *gerE, gerPA, yfhP, yjcZ*, and *ykuD)* that had previously been assigned to the regulon on the basis of gene-specific analysis were added to the tally, bringing the total to 103 (and representing 63 transcription units). These eight genes were cases in which we did not obtain a statistically significant score in one or the other of the two transcriptional-profiling approaches or for which a signal was not obtained for technical reasons (e.g., the strain used was mutant for *gerE* and *yjcZ* had not been annotated when the arrays were built). The list of 103 did not include σ^K^-controlled genes whose transcription additionally and strongly required the DNA-binding protein GerE. Some (28) of these 103 genes were also transcribed under the control of σ^E^ (see [Table 2](#pbio-0020328-t002){ref-type="table"}), leaving a total of 75 genes that were newly activated during sporulation under the control of σ^K^. As we shall see, when genes that were strongly dependent on GerE are included (41 genes, five of which were also expressed under the control of σ^E^), the size of the regulon increases to 144 genes (103 + 41) organized in 94 transcription units ([Table 2](#pbio-0020328-t002){ref-type="table"}). A map of the σ^K^ regulon is displayed in [Figure 2](#pbio-0020328-g002){ref-type="fig"}B and a detailed list of the genes in the regulon is presented in [Table S4](#st004){ref-type="supplementary-material"}.
Identification of Promoters Controlled by σ^K^ Using Bioinformatics and Transcriptional Start Site Mapping {#s2i}
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As a further approach to assessing our assignments to the σ^K^ regulon, we used BioProspector and BioOptimizer to obtain a consensus sequence for promoters under the control of the sporulation transcription factor. The computational approach was complicated by the fact that the program had to find a two-block motif, with the first block corresponding to the −35 element and the second block to the −10 element separated by a gap of fixed length (+/− one nucleotide). The dataset consisted of 76 upstream sequences (the upstream sequences of transcription units that were strongly dependent on GerE were not included). The optimized motif with the best score identified 58 promoters and was composed of a five-nucleotide-long −35 element and a ten-nucleotide long −10 element, separated by a gap of 14--16 nucleotides ([Figure 4](#pbio-0020328-g004){ref-type="fig"}D; [@pbio-0020328-Jensen1]) To assess the validity of the predicted consensus sequence for σ^K^ promoters, we mapped the transcription start sites of 18 of the newly identified targets of σ^K^ by 5′ rapid amplification of complementary DNA ends--PCR (RACE--PCR). The results of the mapping experiments are displayed in [Figure S2](#sg002){ref-type="supplementary-material"}. The newly identified σ^K^ promoters were combined with the promoter sequences of 23 previously mapped σ^K^ promoters to obtain an updated consensus sequence corresponding to a total of 41 promoters ([Figure 4](#pbio-0020328-g004){ref-type="fig"}E). The logo for σ^K^ promoters whose start sites had been mapped was very similar to the logo obtained by the BioProspector/BioOptimizer procedure (see [Figure 4](#pbio-0020328-g004){ref-type="fig"}D). Moreover, out of the 41 confirmed σ^K^ promoters, the correct promoter was identified in 24 cases, with no prediction being made in 15 cases and an incorrect prediction in just two cases. All of the predicted sites are listed in [Table S4](#st004){ref-type="supplementary-material"}.
The σ^E^ and σ^K^ factors are highly similar to each other, and the promoters they recognize are also very similar. The availability of updated logos for both categories of promoters based on the nearly complete regulons for both regulatory proteins provided an opportunity to revisit the issue of how the two regulatory proteins discriminate between their two classes of cognate promoters. A comparison of the motif recognized by σ^K^ to that recognized by σ^E^ ([Figure 4](#pbio-0020328-g004){ref-type="fig"}F) reveals that both classes of promoters share identical −10 sequences and that the −35 elements differ by a single base pair: a cytosine in the fourth position of σ^K^-controlled promoters versus a thymine at the corresponding position in σ^E^-controlled promoters. These results reinforce the findings of [@pbio-0020328-Tatti2] who identified glutamine 217 of σ^E^ as the contact residue for the base pair at position 4. The two proteins are identical to each other in the region inferred to interact with the −35 element except for the presence of arginine instead of glutamine at the corresponding position in σ^K^. Moreover, replacing glutamine 217 with arginine was found to confer on σ^E^ the capacity to recognize σ^K^-controlled promoters ([@pbio-0020328-Tatti2]). The high similarity between the two classes of promoters also helps to explain why some σ^K^-controlled promoters are also recognized by σ^E^, but our bioinformatics analysis does not allow us to explain why some promoters are recognized exclusively by one or the other sigma factor and others are not.
GerE Is Both a Repressor and an Activator of Genes Whose Transcription Is Dependent upon σ^K^ {#s2j}
---------------------------------------------------------------------------------------------
The last regulator in the mother-cell line of gene expression is the DNA-binding protein GerE ([@pbio-0020328-Cutting2]). Genes under GerE control were identified by transcriptional-profiling experiments carried out at two times (5.5 h and 6.5 h) late in sporulation. Strikingly, as many as 209 genes were downregulated in the presence of GerE at one or both time points, with many more genes being downregulated at the later time point (201 versus 61; see [Table S1](#st001){ref-type="supplementary-material"}). Some of these downregulated genes (55) were members of the σ^K^ regulon, with 29 being downregulated at the earlier time point and an additional 26 at the later time point. Thus, GerE is responsible for inhibiting the expression of 53% of the genes in the σ^K^ regulon, but its repressive effects are not limited to genes under σ^K^. We note that the gene coding for σ^K^ is itself repressed by GerE, which would be expected to curtail further synthesis of the mother-cell sigma factor late in sporulation. Thus, GerE has a wide impact in inhibiting gene transcription late in the process of spore maturation, including many genes in the preceding regulon of σ^K^-activated genes.
At the same time, GerE is also an activator that stimulated or switched on the transcription of as many as 65 genes by hour 5.5 and 71 genes by hour 6.5. Of these, 41 were strongly dependent upon GerE for their expression and hence were not identified as members of the σ^K^ regulon. Leaving aside genes that were members of both the σ^E^ and σ^K^ regulons (five), we see that GerE is responsible for turning on an additional 36 genes (27 transcription units) in the final phase of the mother-cell line of gene expression ([Table 2](#pbio-0020328-t002){ref-type="table"}).
Evidence that SpoIIID-Mediated Repression Is Required for Sporulation {#s2k}
---------------------------------------------------------------------
As we have seen, a striking feature of the mother-cell line of gene expression is that many of the genes activated by one transcription factor are turned off by the next-appearing regulatory protein in the cascade. Thus, most of the genes that are turned on by σ^E^ are subsequently repressed by GerR or SpoIIID. Likewise, many of the genes activated by σ^K^ are, in turn, downregulated by GerE. In the case of GerR, a mutant lacking the regulatory protein produced spores that were defective in germination. Hence, proper morphogenesis depends on the capacity of GerR, which appears to act exclusively as a repressor, to turn off genes under its control.
The case of SpoIIID is more complex because in addition to its role as a repressor this DNA-binding protein is also an activator of two genes, *spoIVCA* and *spoIVCB,* that are essential for sporulation because of their role in the synthesis of σ^K^ ([@pbio-0020328-Halberg1]). To investigate the role of SpoIIID-mediated repression in spore formation, we created a construct in which a copy of the intact pro-σ^K^ coding sequence, *sigK,* was introduced into the *amyE* locus, thereby bypassing the requirement for the *spoIVCA*-encoded recombinase, which is normally needed for creating *sigK* by a chromosomal rearrangement ([@pbio-0020328-Stragier4]), and for *spoIVCB,* the 5′ portion of the coding sequence that participates in the rearrangement. In our construct, the insertion of *sigK* at *amyE* was under the direction of a σ^E^-controlled promoter that is not dependent upon SpoIIID for its activation (the promoter for *spoIVF;* [@pbio-0020328-Cutting5]). The *amyE*::P*~spoIVF~--sigK* construct was introduced into *spoIVCB* mutant cells to create strain BDR1663. Even though pro-σ^K^ was expected to be synthesized somewhat prematurely in BDR1663, the appearance of mature σ^K^ remained subject to the pathway governing the proteolytic processing of pro-σ^K^ and hence would have occurred at the normal time ([@pbio-0020328-Cutting4]). Indeed, cells harboring the *amyE*::P*~spoIVF~--sigK* construct sporulated as efficiently as the wild type and did so in a manner that did not depend on the presence of *spoIVCB* ([Table 3](#pbio-0020328-t003){ref-type="table"}). We conclude that bypassing the requirement for SpoIIID in σ^K^ synthesis does not measurably affect sporulation efficiency.
::: {#pbio-0020328-t003 .table-wrap}
Table 3
::: {.caption}
###### Systematic Inactivation of SpoIIID-Activated Genes
:::
^a^ Sporulation efficiency is defined as the number of heat-resistant spores in a sporulating culture of the mutant strain divided by the number of heat-resistant spores present in a sporulating culture of the wild-type (PY79) strain grown in parallel
:::
However, when the *amyE*::P*~spoIVF~--sigK* construct was introduced into cells harboring a *spoIIID* mutation (generating strain BDR1666), sporulation efficiency was still reduced by about a 100,000-fold compared to the wild type ([Table 3](#pbio-0020328-t003){ref-type="table"}). This result reinforces the findings of [@pbio-0020328-Lu1], who showed that sporulation was impaired in *spoIIID* mutant cells even in the presence of a construct that allowed pro-σ^K^ to be produced in a SpoIIID-independent manner. A possible explanation for these results is that, in addition to its role in σ^K^ synthesis, SpoIIID is required for the synthesis of some other unidentified protein or proteins that are needed for sporulation. To investigate this possibility, we systematically inactivated all of the newly identified SpoIIID-activated transcription units ([Table 3](#pbio-0020328-t003){ref-type="table"}). With three exceptions, those of *spoVK, asnO,* and *ycgM,* the resulting mutants sporulated at levels comparable to that of the wild type. In the case of *spoVK, asnO,* and *ycgM,* evidence suggests that each is transcribed in both a SpoIIID-dependent and a SpoIIID-independent mode. Thus, *spoVK* is transcribed from both a σ^E^-controlled (P1) and a σ^K^-controlled (P2) promoter, and it is known that P1 is dispensable for sporulation ([@pbio-0020328-Foulger1]). Experiments based on the use of cells engineered to produce σ^K^ during growth indicate that *asnO* is capable of being transcribed under the direction of σ^K^. Finally, it has been shown that *ycgM* is induced during the early stages of sporulation under the control of Spo0A ([@pbio-0020328-Molle1]), and so at least some YcgM protein should be present in a *spoIIID* mutant. Besides, complete inactivation of *ycgM* resulted in a sporulation defect that is less severe than that observed for strain BDR1666.
These results do not rule out the possibility that SpoIIID activates the transcription of one or more genes in addition to *spoIVCA* and *spoIVCB* that are needed for sporulation. Nevertheless, the simplest interpretation of our findings is that the strong sporulation defect of strain BDR1666 is due to a failure in gene turn off rather than gene activation.
Discussion {#s3}
==========
The Mother-Cell Line of Gene Transcription Is a Hierarchical Regulatory Cascade That Is Subject to Successive Negative Regulatory Loops {#s3a}
---------------------------------------------------------------------------------------------------------------------------------------
Our results reveal the almost complete program of gene transcription for a single differentiating cell type, the mother-cell compartment of the B. subtilis sporangium. The mother cell is a terminally differentiating cell that ultimately undergoes lysis (programmed cell death) when its contribution to the maturation of the spore is complete. Its program of transcription is played out over the course of about 5 h and, as we have shown, involves the activation in a cell-type-specific manner of 383 genes, which are grouped together in 242 transcription units. This corresponds to 9% of the 4,106 annotated protein-coding genes in the B. subtilis genome. The transcription of these 383 genes is orchestrated by five developmental regulatory proteins: two RNA polymerase sigma factors, σ^E^ and σ^K^, and three DNA-binding proteins, SpoIIID, GerE, and a previously uncharacterized regulatory protein, GerR. The five regulatory proteins are organized in a hierarchical regulatory cascade of the form: σ^E^→SpoIIID/GerR→σ^K^ →GerE. The earliest-acting regulatory protein in the cascade, σ^E^, turns on the transcription of 262 genes (163 transcription units), including the genes for GerR and SpoIIID. GerR and SpoIIID, in turn, acting as repressors, downregulate further transcription of almost half of the genes in the σ^E^ regulon. In addition, however, SpoIIID, acting in conjunction with σ^E^-containing RNA polymerase, turns on the transcription of ten genes (eight transcription units), including genes involved in the appearance of σ^K^. Next, σ^K^ activates 75 additional genes (44 transcription units). Among the members of the σ^K^ regulon is the gene for the final regulatory protein in the cascade GerE. Strikingly, GerE represses the transcription of over half of the genes that have been activated by σ^K^ while switching on 36 additional genes (27 transcription units), the final temporal class in the mother-cell line of gene transcription. Thus, the program of gene expression is driven forward by its hierarchical organization as well as by the successive, repressive effects of the DNA-binding proteins, which inhibit continued transcription of many genes that had been activated earlier in the cascade. Indeed, evidence presented herein is consistent with the idea that repression by GerR and SpoIIID contributes to proper sporulation, modestly in the case of GerR, and perhaps more significantly in the case of SpoIIID.
The Mother-Cell Line of Gene Transcription Is Governed by a Linked Series of Coherent and Incoherent FFLs {#s3b}
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Transcription networks are based on recurring circuit modules, one of the most common of which is the FFL ([@pbio-0020328-Milo1]; [@pbio-0020328-Shen-Orr1]; [@pbio-0020328-Mangan1]). FFLs are simple circuits involving two regulatory proteins in which one (the primary regulatory protein) governs the synthesis of the other and both then control the expression of a set of target genes. Certain types of FFLs known as type 1 are particularly prevalent because of their favorable biological properties ([@pbio-0020328-Shen-Orr1]). In type-1 FFLs, the primary regulatory protein acts positively on the synthesis of the second. The mother-cell line of gene transcription is based on two kinds of type-1 FFLs known as a "coherent" and "incoherent." In coherent type-1 FFLs, both regulatory proteins act positively on target genes, whereas in incoherent type-1 FFLs, the primary regulatory protein acts positively and the second acts negatively.
Using this nomenclature, we see that the hierarchical regulatory cascade that governs the mother-cell line of gene transcription is a circuit composed of two coherent type-1 FFLs linked in series ([Figure 1](#pbio-0020328-g001){ref-type="fig"}B). Thus, σ^E^ turns on the synthesis of SpoIIID, and both transcription factors then act jointly to turn on target genes, including genes involved in the appearance of σ^K^. The FFL is acting by the logic of an AND gate in that both σ^E^ and SpoIIID are required for the expression of target genes. This first FFL is linked in series to a second coherent type-1 FFL in which σ^K^ turns on the synthesis of GerE, and the two transcription factors then collaborate to activate the transcription of target genes (the terminal temporal class of gene transcription in the mother cell). Once again this is an AND gate in that both σ^K^ and GerE are required for the activation of target genes. Simulation studies show that coherent type-1 FFLs have the property of being persistence detectors in which the activation of target genes depends on the persistence of the primary regulatory protein (σ^E^ and σ^K^) and "rejects" situations in which the primary regulatory protein is present only transiently in its active form ([@pbio-0020328-Mangan1]).
The mother-cell line of gene transcription is also governed by three incoherent type-1 FFLs, involving SpoIIID, GerR, and GerE, each acting in this context as repressors. Thus, σ^E^ turns on the synthesis of SpoIIID, which in turn represses a subset of the genes that have been turned on by the primary regulatory protein. The σ^E^ factor similarly turns on the synthesis of GerR, which then represses a largely nonoverlapping subset of the genes that have been activated by σ^E^. Finally, the σ^K^ factor turns on the synthesis of GerE, which then acts to downregulate the transcription of many of the genes that have been switched on by σ^K^. Simulations have shown that incoherent type-1 FFLs have the property of producing a pulse of gene transcription ([@pbio-0020328-Mangan1]). Incoherent type-1 FFLs also operate by the logic of an AND gate in that pulses of gene transcription require the action of both the activator and the delayed appearance of the repressor.
Viewing the mother-cell line of gene transcription in terms of an interconnected series of FFLs reveals an underlying logic to the mother-cell program of gene expression. The use of coherent type-1 FFLs to drive the activation of successive sets of genes and the ordered appearance of regulatory proteins may help to minimize noise and to ensure that each temporal class of gene activation is tightly tied to the persistence of the previously acting regulatory proteins in the sequence ([@pbio-0020328-Mangan2]). Meanwhile, the use of incoherent type-1 FFLs to switch off the transcription of genes in previously activated gene sets helps to generate pulses of gene transcription in which certain genes, whose products may only be required transiently during differentiation, are transcribed over a limited period of time. Indeed, as we now consider, genes with related functions are often transcribed coordinately in a pulse, the timing of which corresponds to the function of their products.
Coordinated Expression of Functionally Related Genes {#s3c}
----------------------------------------------------
The mother-cell program of gene expression is characterized, as we have seen, by pulses of gene expression in which different sets of genes are successively switched on and then switched off. In some cases, these pulses correspond to the expression of genes with related functions ([Table 4](#pbio-0020328-t004){ref-type="table"}). This can be most clearly seen with the gene set that is activated by σ^E^ and repressed by SpoIIID or GerR, which includes genes involved in engulfment, cortex formation, and the appearance of σ^G^ and σ^K^. Thus, three genes that are responsible for driving engulfment, *spoIID* ([@pbio-0020328-Lopez-Diaz1]), *spoIIM* ([@pbio-0020328-Smith1]; [@pbio-0020328-Smith2]), and *spoIIP* ([@pbio-0020328-Frandsen1]), are coordinately activated by σ^E^ and then repressed by SpoIIID (in the case of *spoIID*) or by GerR (in the case of the other two). Likewise, all of the σ^E^-controlled genes that are known to be required for spore cortex formation (*cwlD, dacB--spmAB, spoIVA, spoVB, spoVD, spoVE, yabPQ, ykvUV, ylbJ,* and *yqfCD;* [@pbio-0020328-Piggot2]; [@pbio-0020328-Eichenberger2]) are repressed by SpoIIID. Yet another example is the eight-gene *spoIIIA* operon, which is involved in the activation of σ^G^ in the forespore ([@pbio-0020328-Stragier2]). The operon is transcribed from two σ^E^-controlled promoters, one located immediately upstream of the operon and one preceding the next upstream gene, *yqhV*. As we have shown, both promoters are turned off shortly after their activation; one by SpoIIID and the other by GerR.
::: {#pbio-0020328-t004 .table-wrap}
Table 4
::: {.caption}
###### Functional Categories
:::
^a^ In cases where the transcription start site has been mapped by primer extension, the corresponding σ factor is indicated in bold characters
^b^ In cases where binding of the transcription factor has been confirmed by DNAase I footprinting or EMSA analysis, the corresponding regulator is indicated in bold characters
:::
Particularly illuminating is the case of the five σ^E^-controlled genes involved in the appearance of σ^K^: *bofA, spoIVCA, spoIVCB, spoIVFA,* and *spoIVFB*. Two of these genes *(spoIVCA* and *spoIVCB)* are involved in the synthesis of the proprotein precursor, pro-σ^K^, whereas the remaining three *(bofA*, *spoIVFA,* and *spoIVFB)* are involved in the conversion of the proprotein to mature σ^K^ ([@pbio-0020328-Cutting5]; [@pbio-0020328-Ricca1]). Interestingly, *bofA*, *spoIVFA,* and *spoIVFB* are repressed by SpoIIID, whereas *spoIVCA* and *spoIVCB* are switched on by SpoIIID, in this context acting as an activator. Hence, and ironically, genes involved in the processing of pro-σ^K^ are expressed in a pulse that precedes the time of activation of the genes involved in the synthesis of the substrate for processing.
How can we explain these seemingly anomalous observations? BofA, SpoIVFA, and SpoIVFB are integral membrane proteins that form a complex in the mother-cell membrane that surrounds the forespore ([@pbio-0020328-Resnekov1]; [@pbio-0020328-Rudner1]). Evidence indicates that they initially localize to the cytoplasmic membrane that surrounds the mother cell and then reach their final destination by diffusion to, and capture at, the outer forespore membrane ([@pbio-0020328-Rudner2]). Such a diffusion-and-capture mechanism requires that the synthesis of BofA, SpoIVFA, and SpoIVFB takes place prior to the completion of engulfment since the outer membrane surrounding the forespore has become topologically isolated from the cytoplasmic membrane once engulfment is complete. Conversely, no such restriction applies to pro-σ^K^ (a peripheral membrane protein) whose synthesis is delayed (by virtue of being under the positive control of SpoIIID) relative to that of the integral membrane proteins. Strikingly, and in extension of these observations, a high proportion of σ^E^-controlled genes that encode proteins with predicted transmembrane segments are negatively regulated by SpoIIID and GerR. We speculate that many of these genes encode proteins that localize to the outer forespore membrane and do so by a diffusion-and-capture mechanism. Hence their synthesis is restricted to the time prior to the completion of engulfment. By contrast, σ^E^-controlled genes that are unaffected by SpoIIID and GerR, or are activated by SpoIIID, rarely encode proteins with predicted transmembrane segments (see [Table S2](#st002){ref-type="supplementary-material"}).
As a final example of the coordinate expression of genes with related function we consider the case of *cwlC* and *cwlH,* which are switched on in the terminal phase of differentiation under the positive control of GerE ([@pbio-0020328-Kuroda1]; [@pbio-0020328-Smith4]; [@pbio-0020328-Nugroho1]). The *cwlC* and *cwlH* genes encode cell-wall hydrolases that are responsible for the lysis of the mother cell when morphogenesis is complete so that the mature spore can be liberated from the sporangium. It is of crucial importance that mother-cell lysis not take place prematurely, and thus it makes sense that genes involved in this process are among the last genes to be turned on in the mother-cell line of gene expression.
Some Functionally Related Gene Classes Exhibit Heterogeneous Patterns of Gene Expression {#s3d}
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Many of the genes in the mother-cell line of gene expression are known or inferred to be involved in metabolism, assembly of the spore coat, or the synthesis of coat-associated polysaccharides (see [Table 4](#pbio-0020328-t004){ref-type="table"}). Interestingly, not all of the genes in these categories are coordinately expressed. Rather, genes in all three categories exhibit heterogeneous patterns of expression. Thus, among genes inferred to be involved in metabolism, some, such as members of the *yngJIHGFE* operon, which are expected to govern lipid catabolism, and members of the *yjmCD--uxuA--yjmF--exuTR* operon, which are expected to direct hexuronate synthesis ([@pbio-0020328-Mekjian1]), are expressed early in development, whereas other genes, such as the members of the *yitCD* and *yitBA*--*yisZ* operons, which are inferred to be involved in phosphosulfolactate synthesis ([@pbio-0020328-Graham1]), are expressed late in development. Sulfolactate is indeed known to be a major component of the dry weight (5%) of mature spores of B. subtilis but is not found in spores of B. megaterium and B. cereus ([@pbio-0020328-Bonsen1]). Consistent with these observations, the genome of B. cereus lacks an ortholog of the *yitCD* operon. Interestingly, the gene for *asnO,* which encodes an asparagine synthetase ([@pbio-0020328-Yoshida1]), is under the positive control of three of the five mother-cell-specific transcription factors (σ^E^, σ^K^, and SpoIIID) and the negative control of GerE, and hence its expression is maintained until very late in development.
Of special interest are genes involved in the assembly of the coat, the most conspicuous morphological feature of the mature spore. The coat is a complex, two-layered structure that creates a protective shield around the spore and is composed of at least 30 proteins ([@pbio-0020328-Driks1]; [@pbio-0020328-Kuwana1]; [@pbio-0020328-Takamatsu1]; [@pbio-0020328-Lai1]). The earliest-acting protein in the formation of the coat is SpoIVA, which creates a substratum around the outer forespore membrane upon which assembly of the coat takes place ([@pbio-0020328-Roels1]; [@pbio-0020328-Stevens2]; [@pbio-0020328-Driks2]; [@pbio-0020328-Price2]). In keeping with its early role in the assembly process, the gene for SpoIVA is switched on early in the mother-cell line of gene expression under the control of σ^E^ and is then turned off by the action of SpoIIID. The σ^E^ factor also turns on the genes for at least five other coat proteins that play important roles in coat assembly (*cotE, cotH, safA, spoVM,* and *spoVID;* [@pbio-0020328-Piggot2])*,* but expression of these genes persists longer than that for *spoIVA* as none of these is repressed by SpoIIID. In fact, *cotE* and *cotH* continue to be expressed at even higher levels later in development under the control of σ^K^, eventually being downregulated by GerE. In the case of *cotE,* [@pbio-0020328-Li1] have shown that transcription from its σ^E^-dependent promoter P1 ceases before the activation of σ^K^. Interestingly, certain temporal classes of mother-cell-specific genes are particularly enriched in coat protein genes. For instance, almost half of the σ^E^-controlled genes that are strongly or partially dependent on SpoIIID for expression (i.e., ten out of 25; C. F., P. E., and R. L., unpublished data) code for coat proteins. Similarly, our preliminary cytological data (C. F., P. E., and R. L., unpublished data) indicate that many of the newly identified σ^K^-controlled genes encode coat-associated proteins.
In addition to being composed of many different proteins, the coat is composed of polysaccharides. Playing an important role in the synthesis of these polysaccharides is the 11-gene *sps* operon, the longest of the 236 mother-cell-specific transcription units identified in this study. The *sps* operon is transcribed from a σ^K^-controlled promoter, which we have mapped to a site just upstream of the first gene in the operon, *spsA*. Transcription from this promoter is enhanced by the appearance of GerE but is not dependent upon it. Thus, expression of genes involved in the biosynthesis of spore-coat polysaccharides persists until the very late stages of sporulation, in keeping with the idea that these polysaccharides are a component of the outer surface of the spore. Nevertheless, some genes in the *sps* operon are switched on early in sporulation under the control of σ^E^, most likely from a second promoter located upstream of the seventh gene in the operon, *spsG*. Hence *spsG* and the genes downstream of it exhibit a protracted pattern of expression that persists throughout the entire process of differentiation.
The *sps* operon may not be the only set of genes involved in the synthesis of coat-associated polysaccharides. We have identified several paralogs of members of the operon that contribute to the mother-cell line of gene expression. These include genes in the *yfnED* operon, which is switched on by σ^E^, downregulated by GerR, and turned on again by σ^K^. Another example is the *yfnHGF* operon, which is under the positive control of σ^K^ and GerE. Yet another example is a paralog of *spsJ, yodU--ypqP,* which is activated under the dual control of σ^K^ and GerE. Interestingly, in the strain used in this study (PY79), *yodU* and *ypqP* actually correspond respectively to the 5′ end and the 3′ end of a single gene. However, in strain 168, the gene formed by *yodU* and *ypqP* is interrupted by the prophage of the large temperate phage SPβ, thereby greatly separating *ypqP* from the sporulation promoter that would otherwise direct its transcription. It would be interesting to investigate whether the interruption of the *yodU*--*ypqP* gene by SPβ influences the polysaccharide composition of the spore coat.
The Mother-Cell Line of Gene Transcription in Other Endospore-Forming Bacteria {#s3e}
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Endospore formation has been documented in many species of the low G+C group of gram-positive bacteria ([@pbio-0020328-Stragier1]). Two distantly related genera in that group, *Bacillus* and *Clostridium,* are able to sporulate, whereas several genera that are phylogenetically closer to *Bacillus,* such as *Listeria* and *Staphylococcus,* do not sporulate. Remarkably, in genome regions of otherwise high conservation (synteny) to corresponding regions in *B. subtilis,* sporulation genes are missing from *Listeria* ([@pbio-0020328-Eichenberger2]) and *Staphylococcus.* It is likely that the common ancestor of all of these genera was an endospore-forming bacterium and that sporulation genes were deleted over time from genera that had adapted alternative modes of survival in their ecological niche or host in a manner that did not involve the need for a robust resting state.
To investigate further the evolutionary relatedness of the mother-cell differentiation program among endospore-forming species, we searched for the presence of orthologs of B. subtilis genes in the mother-cell line of gene expression in the genome sequences of the following species: B. anthracis (Ames strain) ([@pbio-0020328-Read1]), B. cereus (ATCC14579) ([@pbio-0020328-Ivanova1]), B. halodurans ([@pbio-0020328-Takami2]), and Oceanobacillus iheyensis (HTE831) ([@pbio-0020328-Takami1]); Listeria monocytogenes and L. innocua ([@pbio-0020328-Glaser1]); and Clostridium acetobutylicum (ATCC 824) ([@pbio-0020328-Nolling1]) and C. perfringens (strain 13) ([@pbio-0020328-Shimizu1]) (Tables [S2](#st002){ref-type="supplementary-material"} and [S4](#st004){ref-type="supplementary-material"}).
First, we searched for orthologs of the mother-cell-specific transcription factors. Interestingly, whereas genes for σ^E^, σ^K^, and SpoIIID were present in the *Bacillus* and *Clostridium* species, GerE ([@pbio-0020328-Stragier1]) and GerR were absent from *Clostridium,* suggesting that significant differences exist in the mother-cell programs between the two genera, especially during the terminal (GerE-controlled) phase of gene expression. Nonetheless, in cases when a transcription factor was conserved between *Bacillus* and *Clostridium,* the protein domains involved in nucleotide-sequence recognition were also highly conserved, indicating that the consensus binding sequences that we described here are likely to be conserved among many, if not all, endospore-forming bacteria. For instance, the glutamine residue that recognizes the specificity determinant in the −35 element of σ^E^-controlled promoters is absolutely conserved in all of the available σ^E^ protein sequences, and the corresponding arginine is conserved in all of the available σ^K^ protein sequences.
In addition to differences in the presence of certain mother-cell regulatory proteins (e.g., GerR and GerE) among endospore-forming species, the gene composition of the individual regulons also varies in a species-specific manner. In general, genes in the σ^E^ regulon appear to be more highly conserved than genes in the σ^K^ regulon. For instance, approximately 75% of the B. subtilis σ^E^-controlled transcription units have orthologs in B. anthracis and *B. cereus,* whereas only 50% of the σ^K^-controlled transcription units do. Similarly, close to 40% of the B. subtilis σ^E^-controlled transcription units are present in *Clostridium,* but only about 20% of the σ^K^-controlled transcription units are present. An appealing explanation for the lower level of conservation among σ^K^ regulons is that genes switched on late in the mother-cell line of gene expression are enriched for genes encoding components of the outer surface of the spore---proteins that are likely to undergo the greatest evolutionary adaptation to the ecological niche in which a particular species is found. Indeed, experiments involving the use of atomic force microscopy reveal that the surfaces of the spores of the closely related species *B. subtilis, B. anthracis,* and B. cereus exhibit quite distinctive landscapes ([@pbio-0020328-Chada1]).
Conclusions {#s3f}
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We have provided a comprehensive description of the program of gene transcription for a single differentiating cell type and have shown that this program is governed by a regulatory circuit involving the action of five transcriptional control proteins acting as activators or repressors or both. The underlying logic of the circuit is that of a linked series of coherent and incoherent type-1 FFLs involving two-way combinations of the five regulatory proteins. The circuit is expected to create pulses of gene transcription in which large numbers of genes are switched on and subsequently switched off. We anticipate that type-1 FFLs linked in series are likely to be a common feature of programs of cellular differentiation in a wide variety of developing systems.
Materials and Methods {#s4}
=====================
{#s4a}
### Strains {#s4a1}
All strains used here are derivatives of the wild-type strain PY79, with the exception of the σ^K^ overproducing strain, which is a derivative of strain 168. Strains PE436 and PE437 ([@pbio-0020328-Eichenberger2]), PE452, PE454, PE455, PE456, and SW282 were used for transcriptional profiling under conditions of sporulation. PE452 was obtained by transformation of strain RL560 to MLS resistance with chromosomal DNA from strain MO1027 (*spoIVCB*::*erm,* a gift from P. Stragier, Institut de Biologie Physico-Chimique, Paris) (*sigG*::*cat;* a derivative in the PY79 background of strain MO479.2 \[[@pbio-0020328-Karmazyn-Campelli1]\]). PE454 was generated by transformation of PY79 to chloramphenicol resistance with chromosomal DNA from strain RL16 (*gerE*::*cat;* [@pbio-0020328-Cutting1]). PE455 is the result of the transformation of strain PE454 with chromosomal DNA from strain MO1027. PE456 was obtained by transformation of PE452 to spectinomycin resistance with chromosomal DNA from strain PE239 (*spoIIIDΔ*::*spc;* [@pbio-0020328-Eichenberger1]). SW282 was generated by transformation of PE454 to spectinomycin resistance with chromosomal DNA from strain PE316 (*ylbOΔ*::*spc;* [@pbio-0020328-Eichenberger2]). Strain SI01, which was used for overproduction of σ^K^, was created by double cross-over recombination at the *amyE* locus, following transformation with XhoI-digested plasmid pMFNsigK. Strains PE511, PE551, PE553, PE558, PE568, and SW312 were used for β-galactosidase activity assays. PE511 is a derivative in the PY79 background of strain MO1533 (*amyE*::*spoIIP--lacZ cat;* [@pbio-0020328-Frandsen1]). PE551 and PE553 were obtained by double cross-over recombination of XhoI-digested plasmids pPE72 and pPE74, respectively, into PY79 and selection for chloramphenicol resistance and spectinomycin sensitivity. SW312, PE568, and PE558 were generated by transformation with chromosomal DNA from strain PE316 to spectinomycin resistance of strains PE551, PE511, and PE553, respectively. Strains PE529 *(yheDΔ*::*erm),* PE534 *(mprΔ*::*tet),* PE538 *(yqfTΔ*::*kan),* PE548 *(lipΔ*::*erm),* PE549 *(cotTΔ*::*spc),* RL3231 *(ycgMΔ*::*tet),* PE566 *(cotVWΔ*::*erm),* PE569 *(ydcIΔ*::*tet),* and PE570 *(yheIΔ*::*spc)* were generated with the technique of long-flanking homology PCR ([@pbio-0020328-Wach1]). The sequence of the primers used for gene inactivation is available upon request. Strain PE563 *(cotFΔ*::*cat)* was obtained by transformation of PY79 to chloramphenicol resistance with chromosomal DNA from RL654 ([@pbio-0020328-Cutting6]). PE564 is the equivalent of strain MO1057 (*spoIVCA*::*erm;* a gift from P. Stragier) in the PY79 background. Strains RL2391, RL2396, and RL2519 are from [@pbio-0020328-Eichenberger1] and RL2393, RL2559, RL2570, RL2571, and RL2581 are from [@pbio-0020328-Eichenberger2]. Strain BDR107 is a derivative of PY79 harboring *spoIVCB*::*erm* from strain MO1027. BDR362 corresponds to RL75 (*spoIIID*::*erm;* [@pbio-0020328-Kunkel1]). P*~spoIVF~pro*--*sigK spc* from pDR191 was introduced into the *amyE* locus of BDR107 to generate BDR1663. Genomic DNA from BDR1663 was used to transform BDR362 to spectinomycin resistance to generate BDR1666.
### Plasmids {#s4a2}
Plasmid pMFN20 was constructed by cloning a PstI (blunted)-EcoRI (blunted) 1.3-kb Neo^r^ cassette from pBEST501 ([@pbio-0020328-Itaya1]) and a 7.2-kb DNA fragment from plasmid pMF20 (M. F., unpublished data), amplified with primers SI1 (5′-ATGGATGAGCGATGATGATATCCGT-3′) and SI2 (5′-AACTATTGCCGATGATAAGCTGTC-3′). The pro-less *sigK* gene was constructed using recombinant PCR ([@pbio-0020328-Wach1]). A DNA fragment containing the upstream region of the *sigK* gene was amplified from chromosomal DNA of strain 168 using primers SI3 (5′-CCCTTAGTATGCTGCTTACC-3′) and SI4 (5′-AAG*GCATTGTTTTTCACGTA*CATCGTCACCTCCACAAAAGTAT-3′) (restriction site is underlined; the sequence complementary to primer SI5 is italicized). The other primer set, primer SI5 (5′-TACGTGAAAAACAATGC-3′) and primer SI6 (5′-CGCTCTGCATTATTTCCCC-3′), was used for PCR amplification of chromosomal DNA of strain 168 isolated from cells 6 h after initiation of sporulation to generate the rearranged *sigK* gene. The two PCR products were fused by PCR to generate the pro-less *sigK* gene. Plasmid pMFNsigK was constructed by cloning the pro-less *sigK* fragment into pMFN20 between HindIII and BamHI.
Plasmids pPE72 *(amyE*::P*~spoIIM~--lacZ cat)* and pPE74 *(amyE*::P*~yqhV~--lacZ cat)* were obtained as follows. Primers PE857 (5′-CGTCTAGCCCAGCACACCATCTTTCAGCACACA-3′) and PE858 (5′-CGTATCCCGCGCCCGCTCTAGTGATTTGATTTA-3′) were used to amplify the promoter sequence of *spoIIM* from PY79 chromosomal DNA by PCR (restriction sites are underlined), whereas primers PE860 (5′-CGTCTAGCCGGCTTGTTGTAAACGTGCCGTTCT-3′) and PE861 (5′-CGTATCCCGCCCATTTTTTTATATGATATGCTCT-3′) were used for the PCR amplification of the promoter sequence of *yqhV.* The PCR products were gel-purified (QIAquick Gel extraction kit; Qiagen, Valencia, California, United States) and digested with EcoRI and BamHI. In parallel, vector pDG1661 ([@pbio-0020328-Guerout-Fleury1]) was similarly digested with EcoRI and BamHI and treated with shrimp alkaline phosphatase (USB). The digested vector and PCR fragments were purified (QIAquick PCR purification kit; Qiagen) and ligated using T4 DNA ligase. Ligations were transformed in DH5α cells to ampicillin resistance, and plasmids pPE72 and pPE74 were recovered by alkaline lysis.
Primers odr261 (5′-GGCAAGCTTGTGGAGGTGACGATGGTGACAG-3′) and odr262 (5′-GGCGGATCCTGCGGGAGGATTATAAGTCAAG-3′) were used to amplify *pro--sigK* from pSK6 ([@pbio-0020328-Kunkel2]). The PCR product was cloned into pdr77 ([@pbio-0020328-Rudner1]) between HindIII and BamHI to generate pdr191 *(amyE*::P*~spoIVF~*--*pro*--*sigK spc).*
### Growth and sporulation conditions {#s4a3}
Strains used for transcriptional profiling, β-galactosidase activity assays, and ChIP-on-chip experiments were grown in hydrolyzed casein medium at 37 °C to an A~600\ nm~ of 0.6. Pellets obtained by centrifugation were suspended in Sterlini--Mandelstam medium ([@pbio-0020328-Sterlini1]; [@pbio-0020328-Harwood1]) and placed in a shaking water bath at 37 °C. Samples were collected at the indicated times after resuspension.
A fresh colony of the σ^K^ overproducing strain SI01 was grown in 5 ml of Penassay broth (Difco Laboratories, Detroit, Michigan, United States) overnight at 30 °C. Next, 50 ml of LB broth with and without 10 mM of xylose was inoculated with 1 ml of the overnight culture. Cells were grown by incubation at 37 °C with shaking and harvested 2 h after induction (A~600\ nm~ of 0.8) for extraction of RNA.
### Transcriptional profiling {#s4a4}
DNA microarrays were generated as described by [@pbio-0020328-Britton1]. RNA preparation, sample labeling, and hybridization procedures were performed as described by [@pbio-0020328-Eichenberger2]. Expression data were obtained from three independent experiments for SpoIIID, GerR, σ^K^, and GerE. Our statistical analysis procedure, described in detail by [@pbio-0020328-Conlon1], was performed separately for each set of microarrays for SpoIIID, GerR, σ^K^, and GerE. Normalization of each slide was performed using an iterative rank-invariant method. A Bayesian hierarchical model incorporating experimental variation was used to combine normalized slides across replicated experiments. A Markov chain Monte Carlo implementation of the model with 4,000 iterations produced a posterior median estimate of the log-expression ratio for each gene, and the corresponding Bayesian confidence interval. Genes were scored for the posterior probability of a positive log-expression ratio. Genes with scores above or equal to a threshold of 0.95 were determined to be upregulated in an experimental condition, and genes with scores below or equal to a threshold of 0.05 to be downregulated. Finally, genes in the upregulated category with a nonlogarithmic expression ratio inferior to a threshold of 2.0 and, similarly, genes in the downregulated category with an expression ratio superior to a threshold of 0.5 were not included, unless indicated otherwise (Tables [S2](#st002){ref-type="supplementary-material"} and [S4](#st004){ref-type="supplementary-material"}) in the list of differentially expressed genes. The data are available online in MIAME-compliant format at <http://mcb.harvard.edu/losick> and were also deposited in the Gene Expression Omnibus database under the accession number GSE1620.
### Overexpression and purification of SpoIIID protein {#s4a5}
SpoIIID protein was overproduced by the T7 promoter overexpression system of *Escherichia coli.* The SpoIIID protein expression plasmid was constructed by amplifying the corresponding region from PY79 chromosomal DNA using primers 5′-TACATATGCACGATTACATCAAAGAG-3′ and 5′-CCCTCGAGCGATTGCTGAACAGGCTC-3′. The PCR fragment was digested by NdeI and AvaI and ligated into the NdeI/AvaI-digested vector pET22b (Novagen, Madison, Wisconsin, United States) to generate the SpoIIID protein expression plasmid (pETIIID). The plasmid was transformed into strain BL21 (DE3). Cells carrying pETIIID were grown at 37 °C in 2 l of LB containing 100 μg/ml of ampicillin to an A~600\ nm~ of 0.6, at which point T7 RNA polymerase synthesis was induced by the addition of IPTG to a final concentration of 1 mM. Cells were harvested 5 h later by centrifugation. The pellet was resuspended in 40 ml of binding buffer (50 mM Tris-HCl \[pH 8.0\], 500 mM NaCl, 5 mM imidazole) and disrupted by sonication. Cell debris was removed by centrifugation at 20,000*g* for 30 min and the supernatant was loaded on 1 ml of Ni^2+^--NTA agarose resin (Qiagen) equilibrated with binding buffer. SpoIIID was eluted with a 20-ml imidazole gradient from 5 to 500 mM in binding buffer. Peak fractions were pooled and dialyzed against TGED buffer. The amount of protein was determined with a Bio-Rad (Hercules, California, United States) protein determination kit with BSA as the standard. The purified SpoIIID protein was tested in an in vitro transcription system using reconstituted σ^E^--RNA polymerase and *spoIID* as template (data not shown).
### Gel EMSAs {#s4a6}
DNA fragments of interest were obtained by PCR amplification of PY79 chromosomal DNA (see Supporting Information for the description of primers used), gel-purified (QIAquick Gel extraction kit), and end-labeled with T4 polynucleotide kinase in the presence of \[γ--^32^P\]-ATP for 30 min at 37 °C. After labeling, the fragments were purified with the QIAquick PCR purification kit. Prior to loading on a 6% polyacrylamide--0.16% Bis-0.5X TBE gel that had been prerun at 200 V for 1 h, DNA fragments were preincubated in gel shift-binding buffer (10 mM Tris-HCl \[pH 7.5\], 50 mM NaCl, 1 mM EDTA, 5% glycerol, 1 mM DTT, and 50 μg/ml BSA) for 30 min at room temperature with various amounts of purified SpoIIID protein (0 nM, 50 nM, 100 nM, and 200 nM). The gel was run for 1 h at 200 V, dried, and exposed to Kodak X-OMAT film (Kodak, Rochester, New York, United States).
The following DNA fragments were used in the analysis: *abrB, spoIID, spoIIG,* and *racA* ([@pbio-0020328-Molle1]), *bofA* (from nucleotide 29439 to 30030), *spoIVCA* (from 2654348 to 2654008), *asnO* (from 1156248 to 1156617), *cotE* (from 1774088 to 1774414), *cotF* (from 4165851 to 4166189), *cotT* (from 1280431 to 1280108), *gerM* (from 2902355 to 2902020), *spoIVA* (from 2387164 to 2386826), *spoIVFA* (from 2856840 to 2856657), *spoVB* (from 2828500 to 2828872), *spoVK* (from 1873045 to 1873470), *yabP* (from 67986 to 68297), *ybaN* (from 160708 to 160468), *ycgF* (from 333921 to 334278), *yitE* (from 1174319 to 1174179), *ykvU* (from 1448417 to 1448728), *ylbJ* (from1571288 to 1570927), *ypjB* (from 2361797 to 2361463), *yqfC* (from 2616344 to 2616016), *yqfZ* (from 2587752 to 2588021), *albE--albF*1 (from 3838793 to 3839220), *albE--albF*2 (from 3839214 to 3839656), *albE--albF*3 (from 3839637 to 3840082), *albE--albF*4 (from 3840067 to 3840481), *dctR--dctP*1 (from 498913 to 499280), *dctR--dctP*2 (from 499263 to 499554), *dctR--dctP*3 (from 499531 to 499913), *dctR--dctP*4 (from 499912 to 500356), *tenI--goxB--thiS*1 (from 1242878 to 1243331), *tenI--goxB--thiS*2 (from 1243322 to 1243755), *tenI--goxB--thiS*3 (from 1243749 to 1244115), *tenI--goxB--thiS*4 (from 1244063 to 1244366), *treA--treR--yfkO*1 (from 852742 to 853109), *treA--treR--yfkO*2 (from 853071 to 853409), *treA--treR--yfkO*3 (from 853387 to 853810), *treA--treR--yfkO*4 (from 853797 to 854209), *yfmC--yfmD*1 (from 825948 to 825585), *yfmC--yfmD*2 (from 825607 to 825255), *yfmC--yfmD*3 (from 825266 to 824884), *yfmC--yfmD*4 (from 824903 to 824489).
### DNAase I footprinting {#s4a7}
DNAase I footprinting was carried out as described by [@pbio-0020328-Fujita3].
### Antibodies for SpoIIID {#s4a8}
The C-terminus of the SpoIIID protein was overproduced by the T7 promoter overexpression system of E. coli and used as an antigen for the production of anti-SpoIIID antibodies. The SpoIIID C-terminus protein expression plasmid was constructed by amplifying the region from PY79 chromosomal DNA using primers, 5′-GAAGCTAGCATGATTAACCCCGACTTGGCAAACG-3′ and 5′-GAACTCGAGCGATTGCTGAACAGGCTCTCCTT-3′. The PCR fragment was digested by NheI and XhoI and ligated into the NheI/XhoI-digested vector pET21b (Novagen) to generate the SpoIIID C-terminus protein expression plasmid pMF213. Overexpression and purification of the protein are described in a previous section. The anti-SpoIIID antibodies were prepared by Covance Research Products (Denver, Pennsylvania, United States) and were highly specific as judged by Western blot analysis, which revealed only a single cross-reacting species.
### Chromatin immunoprecipitation in combination with gene microarrays (ChIP-on-chip) {#s4a9}
Three hours after resuspension of PY79 cells in Sterlini-Mandelstam medium at 37 °C, cross-links were generated by treatment with formaldehyde (1% final concentration) for 30 min. The rest of the procedure was identical to the one described by ([@pbio-0020328-Molle1], [@pbio-0020328-Molle2]).
The data analysis for the ChIP-on-chip experiments was carried out using the Resolver statistical package (Rosetta, Seattle, Washington, United States). Experiments were normalized and combined for enrichment-factor determination (Rosetta Resolver). An enrichment factor for a given gene represents the ratio of immunoprecipitated DNA to total DNA. It was considered significant when higher than 2 and with an associated *p*-value lower than 0.001.
### BioProspector/BioOptimizer {#s4a10}
BioProspector ([@pbio-0020328-Liu1]) is a stochastic motif-discovery program used to find conserved subsequences of fixed width in a set of DNA sequences, based on a statistical motif-discovery model reviewed in [@pbio-0020328-Jensen2]. The program can also be used for motifs consisting of two conserved blocks connected with a variable-length gap of unconserved nucleotides, and BioProspector can also be forced to find sites in every input sequence. Since BioProspector is a stochastic algorithm, more than one possible motif can be found, and since the program requires the motif width to be fixed, several different fixed widths should be used in the usual case where the motif width is not known. Thus, we collected the top five Bioprospector motifs under a range (6--12 bps) of seven fixed widths, giving a total of 35 putative motifs.
BioOptimizer ([@pbio-0020328-Jensen1]) is an optimization program designed to improve the results of each discovered BioProspector motif and to score each motif so that the "best" putative motif can be selected out of the 35 we discovered. The scoring function used is the exact log-posterior density of the Bayesian motif-discovery model given in [@pbio-0020328-Jensen1]. Starting from the set of sites predicted by BioProspector, the scoring function is optimized by accepting the addition of new motif sites or removal of current motif sites only if these changes increase the score. BioOptimizer also has the flexibility to allow the motif width to vary, so that the "best" width can also be determined. As well, BioOptimizer can be restricted to force particular sequences in the dataset to contain at least one site while leaving other sequences unrestricted. This property was utilized in our SpoIIID motif search, where a subset of sequences has additional biochemical evidence that they contain at least one SpoIIID-binding site.
Having found an optimal motif with our combined BioProspector/BioOptimizer procedure, we implemented an additional scanning procedure to find more potential SpoIIID sites. Using the estimated proportion of nucleotide *k* in position *j* of the motif (θ\^~*j,k*~ ) and the estimated proportion of nucleotide *k* in the background (θ\^~*j,k*~ ) provided by our optimal motif, we scanned all upstream sequences to see if there were additional sites that matched our discovered motif closely but were not strong enough to be detected by the motif-discovery procedure. In each sequence, for each potential starting position *i,* we had a potential site *S* ~*i*~ = *r~i~*, *r* ~*i*+l~, ..., *r* ~*i*+*w*−l~) , for which we compute the following score:
We considered the site in each sequence with the largest Strength value to be the best candidate as an additional site. If a sequence already contained a site found by our motif-discovery procedure, we would expect that this same site would be the one with the largest Strength value. For any sequence that did not have an optimal site found by the motif-discovery procedure, this scanning procedure gave us new site predictions. However, for any new sites found by the scanning procedure, one must be cautious about the strength of these sites, since the procedure found sites in each sequence regardless of how well those sites matched our optimal motif. Therefore, we also calculated a *p*-value for each site by comparing the Strength value calculated for that site to the Strength value calculated for 10,000 random sequences. Only sites with low *p*-values were considered as potential sites. With the Bonferroni correction for multiple comparisons, we considered only sites with *p*-values less than 0.000183.
### MDscan analysis of the SpoIIID-binding motif {#s4a11}
We used the word-enumeration algorithm "MDscan" ([@pbio-0020328-Liu2]) to identify motifs in sequences most enriched by immunoprecipitation experiments. In this algorithm, it is assumed that the most enriched sequences have stronger motif signals than the remaining sequences. MDscan first identifies oligomers of width *w* (*w*-mers) in the top sequences, which are used as seed oligomers. Motif matrices are constructed for each seed oligomer using all similar segments from the top sequences. Segments are defined to be similar if they share at least *m* matched positions, with *m* determined so that the probability that a pair of randomly produced *w*-mers are *m*-matches is less than 0.15%. The resulting motif matrices are evaluated using the following semi-Bayesian scoring function:
where *x~m~* is the number of segments aligned in the motif, *p~ij~* is the frequency of base *j* at motif position *i,* and *p~o~(s)* is the probability of generating segment *s* from the background model. The top distinct highest scoring motifs are defined as candidate motifs. These motifs are refined using the remaining sequences, by adding new *w*-mers to the matrix if the score is increased. The motifs are further refined by reexamining all segments of the motif matrix and removing segments if the motif score is increased.
We first ranked by enrichment ratio the 26 regions of the chromosome that were enriched by immunoprecipitation by a factor of 2 or greater. We used the top 20 regions as the top sequences, with the remaining six sequences used for refinement. The 26 regions were used as the background sequences, and we reported 30 candidate motifs. We first searched for motifs of width *w* = 8. In using alternative widths (*w* = 7, 9, and 10), and alternative definitions of top regions (15--25), the top reported motif was similar to that for width 8. As reported in [@pbio-0020328-Liu2], MDscan is tolerant of different top sequence definitions (∼3--20), and of moderate ranking errors.
### Germination assays {#s4a12}
Tests for germination using 2,3,5-triphenyltetrazolium chloride overlay were carried out as described in [@pbio-0020328-Nicholson1]. Strains mutant for GerR (PE316) were compared to wild-type cells (PY79), and strains mutant for GerE (strain PE454) or CotE (strain RL322; [@pbio-0020328-Driks2]) were described as negative controls. All strains were sporulated in DSM. Heat activation was performed in a 65 °C oven for 3 h.
### Measuring β-galactosidase activity {#s4a13}
β-galactosidase activity assays were carried out as previously described ([@pbio-0020328-Miller1]; [@pbio-0020328-Harwood1]).
### Promoter mapping by 5′ RACE--PCR {#s4a14}
The 5′ end of several σ^K^-controlled mRNAs was determined by the RACE--PCR procedure ([@pbio-0020328-Frohman1]; [@pbio-0020328-Price1]). Total RNA was extracted from strains PE454 *(sigE* ^+^ *, sigK* ^+^ *)* and PE455 *(sigE* ^+^ *, sigK* ^−^ *)* and analyzed as described by [@pbio-0020328-Eichenberger2].
### Measuring sporulation efficiency {#s4a15}
Strains were grown to exhaustion in DSM for 30 h at 37 °C and assayed for heat resistance as previously described by [@pbio-0020328-van1].
Supporting Information {#s5}
======================
Figure S1
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###### DNAase I Footprinting of SpoIIID Binding to the Promoters of *spoIID, spoIIIA,* and *spoVE*
\(A) Radioactive DNA fragments were incubated with no protein (left lane) or with 400 nM of SpoIIID protein (right lane) and then subjected to DNAaseI footprinting. A chemical sequencing ladder was used as a marker (not shown). Protected regions are indicated by a bar.
\(B) Position of SpoIIID-binding sites. The nucleotide sequence upstream of the transcriptional start site (+1) is shown for *spoIID, spoIIIA, spoVE*-P1, and *spoVE*-P2. The boundaries of the region protected from DNAase I digestion by SpoIIID are indicated by bars. The bold letters identify the sequences within the protected regions that match with the SpoIIID consensus sequence.
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Figure S2
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###### Mapping of Transcription Start Sites by 5′ RACE--PCR
The underlined uppercase bold letters identify the 5′ ends of mRNAs from σ^K^-controlled genes as determined by RACE--PCR. Also indicated are the corresponding −35 and −10 regions (uppercase letters in bold), the ribosome-binding site (double underlining), and the translation start site (uppercase letters). RNA collected from strain PE454 *(sigE* ^+^ *sigK* ^+^ *)* and strain PE455 *(sigE* ^+^, *sigK* ^−^ *)* was used for the determination of transcription start sites. In four cases indicated with an asterisk *(yfnE, yhcO, yitC,* and *ypqA),* an identical transcription start site was identified for strains PE454 and PE455, which is interpreted as evidence that the promoters for these three transcription units are recognized both by σ^E^ and σ^K^. In all of the other cases, a transcription start site was obtained only with RNA collected from strain PE454.
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Table S1
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###### Mother-Cell Gene Expression
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Table S2
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###### Effect of SpoIIID and GerR on the expression of genes in the σ^E^ regulon
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Table S3
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###### ChIP-on-chip data for SpoIIID
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Table S4
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###### Effect of GerE on the expression of genes in the σ^K^ regulon
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Accession Numbers {#s5a7}
-----------------
The Swiss-Prot (<http://www.ebi.ac.uk/swissprot/>) accession numbers for the gene products discussed in this paper are σ^E^ (P06222), σ^G^ (P19940), σ^K^ (P12254), BofA (P24282), CodY (P39779), GerE (P11470), GerR (O34549), RacA (P45870), Spo0A (P06534), SpoIIID (P15281), SpoIVFA (P26936), and SpoIVFB (P26937).
The GenBank (<http://www.ncbi.nlm.nih.gov/Genbank>) accession numbers for the genes discussed in this paper are *abrB* (BSU00370), *albA* (BSU37370), *albB* (BSU37380), *albC* (BSU37390), *albD* (BSU37400), *albE* (BSU37410), *albF* (BSU37420), *argC* (BSU11190), *argJ* (BSU11200), *asnO* (BSU10790), *azlB* (BSU26720), *azlC* (BSU26710), *azlD* (BSU26700), *bnrQ* (BSU26690), *bofA* (BSU00230), *cotA* (BSU06300), *cotD* (BSU22200), *cotE* (BSU17030), *cotF* (BSU40530), *cotH* (BSU36060), *cotM* (BSU17970), *cotT* (BSU12090), *cotV* (BSU11780), *cotW* (BSU11770), *ctpB/yvjB* (BSU35240), *cwlC* (BSU17410), *cwlH* (BSU25710), *cwlJ* (BSU02600), *cypA* (BSU26740), *cysC* (BSU15600), *cysH* (BSU15570), *cysK* (BSU00730), *cysP* (BSU15580), *dctP* (BSU04470), *dctR* (BSU04460), *exuR* (BSU12370), *exuT* (BSU12360), *gerE* (BSU28410), *gerM* (BSU28380), *gerPA* (BSU10720), *gltR* (BSU26670), *goxB* (BSU11670), *kapD* (BSU31470), *lip* (BSU31470), *mpr* (BSU02240), *phoB* (BSU05740), *proH* (BSU18480), *proJ* (BSU18470), *racA/ywkC* (BSU37030), *safA* (BSU27840), *sat* (BSU15590), *spoIID* (BSU36750), *spoIIGA* (BSU15310), *spoIIIAA* (BSU24430), *spoIIIAB* (BSU24420), *spoIIIAF* (BSU24380), *spoIIM* (BSU23530), *spoIIP* (BSU25530), *spoIVA* (BSU22800), *spoIVCA* (BSU25770), *spoIVCB* (BSU25760), *spoIVFA* (BSU27980), *spoIVFB* (BSU27970), *spoVD* (BSU15170), *spoVE* (BSU15210), spoVID (BSU28110), *spoVK* (BSU17420), *spoVM* (BSU15810), *spsA* (BSU37910), *spsG* (BSU37850), *spsJ* (BSU37830), *tenI* (BSU11660), *thiS* (BSU11680), *treA* (BSU07810), *treR* (BSU07820), *uxuA* (BSU12340), *ybaN* (BSU01570), *ybaS* (BSU01590), *ycgF* (BSU03090), *ycgM* (BSU03200), *ycgN* (BSU03210), *ydcI* (BSU04780), *ydhF* (BSU05730), *yeeA* (BSU06760), *yeeB* (BSU06770), *yeeC* (BSU06780), *yefA* (BSU06730), *yefB* (BSU06740), *yefC* (BSU06750), *yfhP* (BSU08620), *yfkO* (BSU07830), *yfmC* (BSU07520), *yfmD* (BSU07510), *yfnD* (BSU07310), *yfnE* (BSU07300), *yfnF* (BSU07290), *yfnG* (BSU07280), *yfnH* (BSU07270), *yhbB* (BSU08920), *yhbH* (BSU08980), *yhcO* (BSU09160), *yhcP* (BSU09170), *yheC* (BSU09780), *yheD* (BSU09770), *yheH* (BSU09720), *yheI* (BSU09710), *yhjL* (BSU10550), *yisZ* (BSU10910), *yitA* (BSU10920), *yitB* (BSU10930), *yitC* (BSU10940), *yitD* (BSU10950), *yitE* (BSU10960), *yjcA* (BSU11790), *yjcM* (BSU11910), *yjcN* (BSU11920), *yjcO* (BSU11930), *yjmC* (BSU12320), *yjmD* (BSU12330), *yjmF* (BSU12350), *yknT* (BSU14250), *yknU* (BSU14320), *yknV* (BSU14330), *ykuD* (BSU14040), *ykvI* (BSU13710), *ykvU* (BSU13830), *ylbJ* (BSU15030), *ylbO/gerR* (BSU15090), *yngE* (BSU18210), *yngF* (BSU18220), *yngG* (BSU18230), *yngH* (BSU18240), *yngI* (BSU18250), *yngJ* (BSU18260), *yoaB* (BSU18540), *yoaD* (BSU18560), *yodU* (BSU19810), *ypqA* (BSU22240), *ypqP* (BSU21670), *yqfT* (BSU25120), *yqhV* (BSU24440), *yrdK* (BSU26680), *yydB* (BSU40220), *yydC* (BSU40210), *yydD* (BSU40200), *yydG* (BSU40170), *yydH* (BSU40160), *yydI* (BSU40150), and *yydJ* (BSU40140).
Microarray data were deposited in the Gene Expression Omnibus database under the accession number GSE1620, where they are accessible at <http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE1620>.
We are grateful to Uri Alon, Harley McAdams, Lee Kroos, Patrick Piggot, and Patrick Stragier for critical comments of the manuscript. We also thank Uri Alon for helpful discussions and Patrick Stragier for strains. We are indebted to Eduardo Gonzalez-Pastor for his contribution in setting up the tools for the generation and utilization of B. subtilis DNA microarrays in the laboratory. We thank Claire Bailey and Paul Grosu at the Bauer Center for Genomics Research for help in the production of the DNA microarrays and with the Rosetta Resolver analysis, respectively. We also thank the members of the Losick laboratory for advice.
This work was supported by National Institutes of Health grant GM18458 to RL and in part by a Grant-in-Aid for Scientific Research on Priority Areas (genome biology) from the Ministry of Education, Science, Sports, and Culture of Japan to TS. PE was supported by a Merck Core Educational Support Program and the Swiss National Science Foundation. STJ, EMC, and JSL were supported by National Science Foundation grants DMS-0204674 and DMS-0244638 to JSL.
**Conflicts of interest.** The authors have declared that no conflicts of interest exist.
**Author contributions.** PE, MF, STJ, EMC, DZR, TS, JSL, and RL conceived and designed the experiments. PE, MF, DZR, STW, CF, and KH performed the experiments. PE, MF, STJ, EMC, DZR, and JSL analyzed the data. PE, MF, STJ, EMC, DZR, and JSL contributed reagents/materials/analysis tools. PE, MF, STJ, EMC, JSL, and RL wrote the paper.
Academic Editor: Jonathan A. Eisen, The Institute for Genomic Research
¤1 Current address: Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts, United States of America
¤2 Current address: Department of Microbiology and Molecular Genetics, Harvard Medical School, Boston, Massachusetts, United States of America
Citation: Eichenberger P, Fujita M, Jensen ST, Conlon EM, Rudner DZ, et al. (2004) The program of gene transcription for a single differentiating cell type during sporulation in *Bacillus subtilis.* PLoS Biol 2(10): e328.
ChIP-on-chip
: chromatin-immunoprecipitation in combination with gene microarrays
EMSA
: electrophoretic mobility-shift assay
FFL
: feed-forward loop
MDscan
: Motif Discovery scan
RACE--PCR
: rapid amplification of complementary DNA ends--PCR
|
PubMed Central
|
2024-06-05T03:55:47.808676
|
2004-9-21
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517825/",
"journal": "PLoS Biol. 2004 Oct 21; 2(10):e328",
"authors": [
{
"first": "Patrick",
"last": "Eichenberger"
},
{
"first": "Masaya",
"last": "Fujita"
},
{
"first": "Shane T",
"last": "Jensen"
},
{
"first": "Erin M",
"last": "Conlon"
},
{
"first": "David Z",
"last": "Rudner"
},
{
"first": "Stephanie T",
"last": "Wang"
},
{
"first": "Caitlin",
"last": "Ferguson"
},
{
"first": "Koki",
"last": "Haga"
},
{
"first": "Tsutomu",
"last": "Sato"
},
{
"first": "Jun S",
"last": "Liu"
},
{
"first": "Richard",
"last": "Losick"
}
]
}
|
PMC517826
|
Introduction {#s1}
============
In real world situations we often have to choose between possible actions that lead to different outcomes. To provide a computational framework for such a decision process, the notion of a utility function is often used ([@pbio-0020330-Neumann1]). A utility function assigns to each possible action a number that specifies how desirable each outcome is. In the theory of rational choice, it is assumed that subjects will choose the action that leads to the most desirable outcome and thus the highest utility. The economics literature extensively discusses the problem of having a utility function that depends on two or more variables ([@pbio-0020330-Edgeworth1]; [@pbio-0020330-Pareto1]). For example, people may associate a utility with the number of apples and oranges they are offered. There will be combinations of apples and oranges which have equal utility. Having three apples and three oranges could be judged as being equally good as having ten apples and one orange. These two possibilities would form two points along an "indifference curve" in apple--orange space, representing outcomes with identical utility that are, therefore, equally desirable. Such indifference curves have been extensively studied by economists in terms of goods and services (c.f. [@pbio-0020330-Humphrey1]). The sensorimotor system also has to choose between different actions. The utility of actions will depend on two components---the cost associated with performing an action and the desirability of the outcome. Here we characterize the utility function used by the sensorimotor system by measuring the indifference curves for human subjects experiencing short pulses of force.
In sensorimotor control, utility functions that depend on several variables occur frequently. Consider, for example, unpacking a car after a snowboarding vacation. We could carry all the suitcases at the same time, reducing the time to unpack but maximizing the weight we have to lift concurrently. At the other extreme we could transport each item individually, which would minimize the magnitude of the force required at the expense of a long unpacking duration. The chosen solution is likely to lie somewhere between these two extremes and may reflect an optimal decision based on a utility function that depends on duration and magnitude of the forces. Once a utility function is specified, the decision problem becomes one of solving an optimal control problem, finding the actions that maximize the utility.
A number of studies in the field of optimal sensorimotor control have proposed loss functions (the negative of utility) and derived the optimal actions given these proposed loss functions. For example, the minimum jerk model ([@pbio-0020330-Hogan1]; [@pbio-0020330-Flash1]) suggests that people minimize the average squared jerk of the hand (third derivative of position) when making reaching movements. Alternative models have suggested that during reaching people try to minimize the variation of endpoint errors that arise from noise on the motor commands ([@pbio-0020330-Harris1]; [@pbio-0020330-Todorov1]). However, these and many other similar studies assume a loss function and compare the predicted behavior with observed behavior, rather than measure the loss function directly. In recent works we have used a statistical approach to infer the loss function, instead of assuming it. We defined the statistics of the errors observed by subjects and showed that they were sensitive to quadratic errors for small errors but that for larger errors they were robust to outliers ([@pbio-0020330-Kording1]). Here we use an alternative approach that is analogous to the approaches used in economics to infer a loss function.
Different movements may be associated with different costs or utility. For example, a utility function could assign a numerical value to each possible movement, characterizing how costly it is to the organism. Here, we have examined how the utility associated with producing a force depends on two parameters, the duration and the magnitude of a force profile (see [Materials and Methods](#s3){ref-type="sec"} for details). The force profiles were smoothed square waves that could be linearly scaled by the duration of the force, *T,* and the maximum value of the force, *F.* On each trial, subjects experienced two force profiles that differed in both *T* and *F.* They then had to choose which of the two force profiles they would experience again. They were told to choose the force that required the least effort. In this two-alternative forced-choice experiment subjects thus indicated their preference for one combination of *F* and *T* over another combination of *F* and *T.* This allowed us to infer indifference curves: Given the choice of two combinations of *F* and *T* that are on the same indifference curve, subjects will have no preference. The associated utility of these force profiles is thus identical. To obtain a full utility function from a set of utility curves we additionally needed to determine the utility of one indifference curve relative to another. This was achieved by finding "doubling points." A doubling point is a point on one indifference curve that subjects show no preference for when compared to experiencing a point on another indifference curve twice (that is, two smoothed square waves in quick succession---see [Materials and Methods](#s3){ref-type="sec"} for details). Thus we could determine the full utility function.
Results/Discussion {#s2}
==================
In a two-alternative forced-choice paradigm, subjects chose which of two experienced force profiles they preferred to experience a second time (see [Figure 1](#pbio-0020330-g001){ref-type="fig"}). This allowed us to find a set of force profiles to which subjects showed equal preference and were therefore indifferent. Although subjects experience these force profiles as being physically different, they show no preference in terms of which they wish to experience again.
::: {#pbio-0020330-g001 .fig}
Figure 1
::: {.caption}
###### The Experimental Setup
The subject\'s hand position (pink circle) was visible on the screen. The hand movement was restricted to stay within a small area (blue box). The direction of the force is represented by the blue arrow, and the temporal profile of the force is shown by the blue curve.
:::
:::
Various hypothesized utility functions predict different choices and thus different indifference lines. The first model we hypothesized was that subjects would minimize the integrated force they are using *(F × T).* This predicts hyperbolas as indifference lines ([Figure 2](#pbio-0020330-g002){ref-type="fig"}A). Alternatively, people could minimize the integrated squared force *(F^2^ × T)* ([Figure 2](#pbio-0020330-g002){ref-type="fig"}B). In this case they would prefer long-duration, weak forces to short-duration, strong forces of equal integrated force. Another possible model would be that people would just try to minimize the maximal force they had to produce, regardless of how long they had to hold it *(F)* ([Figure 2](#pbio-0020330-g002){ref-type="fig"}C).
::: {#pbio-0020330-g002 .fig}
Figure 2
::: {.caption}
###### Hypothesized and Measured Indifference Curves and Loss Function from a Single Subject
(A--C) The predicted indifference lines are shown that minimize (A) the integrated force *(F × T),* (B) the integrated squared force *(F^2^ × T),* and (C) the maximal force *(F)*.
\(D) Experimental data from a single subject. The open circles are the reference forces. The blue full circles connected by the black lines represent indifference points. Error bars denote the 95% confidence intervals. Force profiles are illustrated (blue curves for single forces, pink curve for doubling points).
\(E) Inferred color plot of the loss function (warmer colors represent greater cost).
:::
:::
A single subject\'s results are shown in [Figure 2](#pbio-0020330-g002){ref-type="fig"}D. The reference forces are shown as open circles, while the indifference points are shown as filled circles. The location of the indifference points had relatively small error bars (black 95% confidence intervals). Therefore, this subject showed a preference for points towards the origin compared to those further from the origin (along the blue lines). Joining up such points in force--time space allows us to obtain indifference curves (black lines). For short duration profiles (less than 150 ms), as the duration increased, the force needed to decrease to maintain constant utility. This makes intuitive sense: as the duration of experienced force increases, more effort is required to stabilize the arm. For longer durations (greater than 500 ms), as the duration increased, the force required to maintain equal utility also increased. This means people prefer to experience a 2-s force profile compared to experiencing a 1-s force profile. We explain this counterintuitive result---that increasing both the duration and force can keep the utility constant---in the following way. The shape of the force profiles for all conditions was kept self-similar. This means that force profiles with a longer duration have a slow onset and offset (each is 20% of the total duration). For long durations subjects can, therefore, progressively compensate for the imposed forces as they ramp up slowly, thereby producing less loss.
We furthermore measured how much smaller a force profile needed to be (scaled uniformly in duration and force) so that experiencing it twice had the same utility as experiencing the unscaled profile once. For the four open-circle reference points in [Figure 2](#pbio-0020330-g002){ref-type="fig"}D, the pink circles show the corresponding four points that have half the utility. We can thus infer how the loss function changes as the force profiles are scaled ([Figure 2](#pbio-0020330-g002){ref-type="fig"}E; see [Materials and Methods](#s3){ref-type="sec"}). Any order-preserving transformation of the utility function will have no effect on subjects\' preferences. That means that arbitrary scalings can be applied to the loss function while the optimal behavior remains unchanged. This property of utility function is well known in economics and has led to the idea of ordinal utility ([@pbio-0020330-Pareto1]), in which the ordering of preferences is the key feature of utility. The utility of the first reference point is thus arbitrarily set to be equal to one. The plotted relative utility is the utility function arising from this assumption. The double-hump experiment defines the derivative of the utility, which is interpolated and integrated to obtain the relative utility. To infer the relative utility function ([Figure 2](#pbio-0020330-g002){ref-type="fig"}B), we had to assume local linearity. The loss function shows nonlinear behavior.
[Figure 3](#pbio-0020330-g003){ref-type="fig"} shows the inferred utility function averaged over all the subjects. We can analyze how loss increases along the line connecting the reference points (*F/T* = 44.6). Fitting a model of the form Loss = (*FT*)^α^ to the data from the double-hump experiments leads to an α of 1.1 ± 0.15 (mean ± SEM over subjects). This α, when fit to the data from all the subjects for each of the four lines, is approximately constant (1.2, 1.0, 0.9, 0.9). The shape of the loss function is highly conserved over the set of subjects. In particular, the effect that indifference curves increase for both very short and long durations is found over the set of subjects.
::: {#pbio-0020330-g003 .fig}
Figure 3
::: {.caption}
###### Iso-Loss Contours and Loss Function for the Set of All Subjects
The black curves are the iso-loss curves. Error bars denote the standard error of the mean over the population. The color plot represents the inferred loss function (warmer colors represent greater loss) obtained by interpolating the data from the double-hump forces.
:::
:::
By applying the methodology developed by economists, we have shown that fundamental properties of the nervous system, such as loss functions, can be inferred by the choices humans make in a sensorimotor task. In general, these loss functions will depend on a large number of factors that were not measured in our experiment. For example, there are subjective emotional components to human decision making ([@pbio-0020330-Sanfey1]). However, parametric variations would allow such multi-dimensional loss functions to be determined. Interestingly, the inferred loss function we report cannot easily be modeled by any simple function of our experimental variables *F* and *T.* However, it is highly conserved across the subjects, suggesting a common underlying mechanism is at work. Moreover, our results suggest that the opposite approach---first hypothesizing a loss function and then predicting human decision making---is likely to miss interesting aspects of the behavior and underlying processes. We are therefore hopeful that the application of economic methods to the study of the nervous system, referred to as neuroeconomics ([@pbio-0020330-Glimcher1]), will continue to provide new insights into the functioning of the central nervous system.
Materials and Methods {#s3}
=====================
{#s3a}
### Subjects and the manipulandum {#s3a1}
After providing written informed consent, five right-handed subjects (aged 20--40 y) participated in this study. The experiments were carried out in accordance with institutional guidelines. A local ethics committee approved the experimental protocols.
While seated, subjects held the handle of robotic manipulandum with two degrees of planar freedom. This was a custom-built device (vBot) consisting of a parallelogram constructed mainly from carbon fiber tubes that were driven by rare earth motors via low-friction timing belts. High-resolution incremental encoders were attached to the drive motors to permit accurate computation of the robot\'s position. Care was taken with the design to ensure it was capable of exerting large end-point forces while still exhibiting high stiffness, low friction, and also low inertia.
The robot\'s motors were run from a pair of switching torque control amplifiers that were interfaced, along with the encoders, to a multifunctional I/O card on a PC using some simple logic to implement safety features. Software control of the robot was achieved by means of a control loop running at 1,000 Hz, in which position and force were measured and desired output force was set.
A virtual reality system was used that prevented subjects seeing their hand, and allowed us to present visual images into the plane of the movement (for full details of the setup see [@pbio-0020330-Goodbody1]) (see [Figure 1](#pbio-0020330-g001){ref-type="fig"}A). The force between the subject\'s hand and the manipulandum was continuously measured using a six-axis force transducer (Nano25; ATI Industrial Automation, Apex, North Carolina, United States) sampled at 1,000 Hz by the control loop.
The experiment consisted of trials in which the robot generated force profiles on the subjects\' hands. The force profiles experienced were parameterized by their duration *T* in ms and their maximal strength *F* in Newtons. The force profile *f* (*t*) approximated a square profile, but with smooth onset and offset:
On each trial the subjects experienced two different force profiles and then could choose which of the two profiles to experience for a second time. Using such a forced-choice procedure allowed us to determine the indifference curves.
### Inferring indifference pairs {#s3a2}
Subjects saw a starting sphere and two selection spheres (see [Figure 1](#pbio-0020330-g001){ref-type="fig"}A). Each trial started when the subject moved the cursor, representing their hand, into the starting sphere. The trial then had three phases. (1) One of the selection spheres turned green, and subjects were required to place the cursor into this sphere, where they experienced a force profile *F~1~*. The subjects then returned the cursor to the starting sphere. (2) The other selection sphere turned green, and subjects were required to place the cursor in that sphere, where they experienced a force profile *F~2~*. Subjects then returned the cursor to the starting sphere. (3) Both selection spheres turned green, and subjects were required to choose which of the two spheres to move to, where they would experience the same force associated with that sphere, either *F~1~* or *F~2~*. Therefore, subjects could decide which force profile, *F~1~* or *F~2~,* to experience a second time.
To obtain four indifference curves, we chose four reference profiles that had durations *T* of 200, 300, 400 and 500 ms. The maximal force *F* was chosen for each reference so that the ratio *T/F* had the value 44.6. This gave a maximal force that ranged from 4.5 N for the shortest duration reference to 11.2 N for the longest duration reference. These reference points lie along a straight line in time--force space (see [Figure 2](#pbio-0020330-g002){ref-type="fig"}A, open circles).
On each trial, one of the two force profiles, *F~1~* or *F~2~,* was set to be one of the reference forces and the other was a test force. The sphere associated with the reference force was randomized each trial between the left and right locations. To obtain indifference lines, we wished to find points along the radial lines shown in [Figure 2](#pbio-0020330-g002){ref-type="fig"}A to which subjects were indifferent to the four reference points. To obtain these we used a two-alternative forced-choice paradigm in which the test force produced was chosen from one of these lines, which correspond to *T/F* ratios of 2.0, 7.4, 20.0, 44.6 (double-hump, see below), 85.4, 142.1, and 203.0, with the aim of finding the point along the line at which subjects would choose between the reference and test force indifferently (that is, at probability level 0.5). We used an adaptive fitting protocol (QUEST; [@pbio-0020330-Watson1]) to find the *p* = 0.5 threshold of a logistic function. The reference points and *T/F* ratio lines were interleaved in a pseudorandom order. Forty trials were performed to obtain each indifference pair. Each reference point, together with the six *T/F* ratio line points that subjects preferred equally, defines an indifference curve.
### Inferring the loss function {#s3a3}
The above procedure allowed us to obtain indifference lines---where the utility has equal value. However, to obtain a full utility function we need to join up these lines and determine the relative utility of one indifference line to another. To achieve this we performed a two-alternative forced-choice paradigm in which the reference force was as before, but the test force was selected from the *T/F* = 44.6 line, with the force profile presented twice in succession (the "double hump" force). This condition was run interleaved with the other conditions. We assumed that the utility of experiencing the double hump was twice the utility of a single hump (a linearity assumption). This assumption allowed us to link the reference point to a point of half its utility, further allowing us to linearly interpolate log(utility) between these points to obtain estimates of the loss function between the lines.
We would like to thank Josh Tenenbaum, Peter Dayan, and Zoubin Ghahramani for helpful discussions. This work was supported by the Wellcome Trust, McDonnell Foundation, and Human Frontiers Science Programme.
**Conflicts of interest.** The authors have declared that no conflicts of interest exist.
**Author contributions.** KPK, IF, ISH, JNI, and DMW conceived and designed the experiments. KPK and IF performed the experiments. KPK and IF analyzed the data. ISH and JNI contributed reagents/materials/analysis tools. KPK and DMW wrote the paper.
Academic Editor: James Ashe, University of Minnesota
Citation: Körding KP, Fukunaga I, Howard IS, Ingram JN, Wolpert DM (2004) A neuroeconomics approach to inferring utility functions in sensorimotor control. PLoS Biol 2(10): e330.
|
PubMed Central
|
2024-06-05T03:55:47.817763
|
2004-9-21
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517826/",
"journal": "PLoS Biol. 2004 Oct 21; 2(10):e330",
"authors": [
{
"first": "Konrad P",
"last": "Körding"
},
{
"first": "Izumi",
"last": "Fukunaga"
},
{
"first": "Ian S",
"last": "Howard"
},
{
"first": "James N",
"last": "Ingram"
},
{
"first": "Daniel M",
"last": "Wolpert"
}
]
}
|
PMC517827
|
Anyone who has used a search engine quickly becomes familiar with both their power and limitations. A key-word search for "bush kerry butterfly county" turns up almost twenty-eight thousand documents, but a scant few of them are of any interest to the botanist studying the butterfly bush in County Kerry. The problem is more circumscribed but no less significant within specialized databases, such as the fourteen-plus million medical journal articles catalogued by PubMed.
It is not so much that the literature is too vast, but that the search strategies are too weak. A simple list of key words used to tag and retrieve a document cannot begin to capture the richness of the information within, especially when that wealth is expressed in syntactically complex sentences like "It has not escaped our notice that the specific pairing we have postulated immediately suggests a possible copying mechanism for the genetic material."
But there is another way. Rather than simply extracting a limited list of key words from an article\'s abstract, the entire text of the document can be categorized into classes: some words represent entities (e.g., gene, cellular component, molecular function) and others relationships (e.g., physical association, purpose, comparison, regulation). The entire set of entities and relationships can be linked to create a map of the information within the document, which, like a physical map, captures some of the complexity of the territory it describes.
Humans excel at this type of concept mapping, but their labors are slow and expensive. In this issue, Paul Sternberg and colleagues at the California Institute of Technology (Caltech) describe a computer-based system that performs the same task, and show that it is almost as good as humans at mapping out the scientific literature concerning the laboratory nematode, Caenorhabditis elegans.
Sternberg\'s system, called Textpresso, includes 33 categories of terms, both of entities and relationships, and a full list of all possible examples for each entity (for genes, for example, this would be specific gene names) and relationship (for physical association, this would include bind, adhere, link, etc.). This collection, called an ontology, is then applied to sentences within the text of a document to map out the relationships within---for instance, the mention of two genes within a sentence along with any form of the word stem "regulat-" indicates that one gene probably regulates the other, and the sentence is marked accordingly. With scores of tags applied, the full markup of a sentence is typically much longer than the sentence itself. Currently, Textpresso has marked up almost 4,000 full-text articles on C. elegans, representing 60% of the entire literature.
::: {#pbio-0020343-g001 .fig}
::: {.caption}
###### Identifying terms in scientific prose
:::
:::
The final result is a document that can be queried in subtle ways impossible with mere key words. For instance, to find entities (whether they be transcription factors, small molecules, or anything else described to date) that interact with the aging-related gene *daf-16*, one enters the terms "daf-16" and "association." Textpresso returns 125 publications, with citations and links to the articles. (Textpresso is available at [www.textpresso.org](www.textpresso.org).) The results can be further refined by adding other entities or relationships, as well as by specifying author, journal, or year of publication.
Textpresso\'s ability to find relevant documents, and ignore irrelevant ones, is still not as great as an expert human curator of the same literature. But the system can be constantly tweaked to get better and better. This process requires human intervention, and the Caltech team does not think this is likely to be automated anytime soon. On the other hand, the structure of Textpresso, and to some extent the ontological lists from C. elegans, can be used for literature analysis of other model organisms. Finally, the fully annotated literature within a field is not only a repository of scientific facts, but also a data mine of human communication, which can be queried for patterns having little to do with model organisms and much to do with how scientists communicate with each other.
|
PubMed Central
|
2024-06-05T03:55:47.819393
|
2004-9-21
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517827/",
"journal": "PLoS Biol. 2004 Nov 21; 2(11):e343",
"authors": []
}
|
PMC517828
|
Cholesterol has a bad rap for its association with human heart disease. But actually cholesterol and other sterols are essential for a wide variety of organisms. For most eukaryotes---organisms whose cells have nuclei---sterols reside in the cell membrane and play major structural roles. Sterols keep cell membranes flexible, for example. These chemicals also hinder leakage of ions across the membrane, which is crucial in order for muscles to contract and nerves to conduct signals.
For the tiny (eukaryote) nematode worm Caenorhabditis elegans, sterols are a dietary staple. Worms can\'t make these chemicals from scratch, just as humans can\'t make vitamin C or the essential amino acids, so they have to harvest these chemicals from their surroundings. If nematodes hit hard times---they can\'t find enough sterols, say, or are starved or overcrowded---they can delay developing into adults. Instead, they enter a stage called a dauer in which they don\'t eat and hardly move a muscle. In this state, they can persist several months---many times their normal lifespan---and then revive when conditions improve.[](#pbio-0020345-g001){ref-type="fig"}
::: {#pbio-0020345-g001 .fig}
:::
Though C. elegans is extensively studied, there\'s still controversy over the role of cholesterol in this organism. To develop into adults, the nematodes need only small amounts of cholesterol in their diet, suggesting cholesterol does not play a major role in their membranes. Instead, nematodes---like many other eukaryotes---might use cholesterol to make hormones, which are typically active at very low concentrations. Such hormones could play a key role in the worms\' development into either adults or dormant dauers. But no one had found any nematode hormones derived from cholesterol---until now.
In this issue of *PLoS Biology,* Teymuras Kurzchalia and colleagues show definitively that cholesterol does not play an essential structural role in C. elegans. Rather, cholesterol is the precursor for a hormone---or set of hormones---key in the worms\' development into adulthood and thus key for reproduction. The researchers have partially purified this cholesterol derivative and named it gamravali, from the Georgian word for reproduction, "gamravleba."
When on sterol-free diets, all larvae showed arrested development, becoming dormant dauers. But, surprisingly, the concentration of cholesterol they needed to develop into adults was miniscule, around 20 nanomoles. When given scant amounts of cholesterol, the worms converted some of it to a sterol called lophenol. The researchers found, however, that supplementing a sterol-free diet with lophenol was not enough to sustain development into adulthood. Apparently the worms need cholesterol, which is fed into two distinct pathways: one makes lophenol and another makes the hormone gamravali.
The researchers have only partially purified gamravali, so they don\'t yet know its molecular weight or composition or even whether it is a single molecule. But by working with mutant worms, they have begun to pin down where gamravali acts in the worms\' developmental pathway. One mutant C. elegans line, for instance, was unfazed by the cholesterol-free diet. These mutants were missing the *daf-12* gene, one of a set of genes crucial in nematode development and aging. On the cholesterol-free, lophenol-supplemented diet, these mutants developed into normal adults. Other mutant lines that each lacked one of several other *daf* genes, however, developed into dauers when deprived of cholesterol. In this way the researchers found where gamravali acts in the worms\' developmental pathway: the hormone gamravali likely comes into play before *daf-12,* but after the other *daf* genes. Kurzchalia and colleagues are currently working to further purify gamravali and identify exactly how it gives cholesterol such a crucial role in the worms\' lifecycle.
|
PubMed Central
|
2024-06-05T03:55:47.820376
|
2004-9-21
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517828/",
"journal": "PLoS Biol. 2004 Oct 21; 2(10):e345",
"authors": []
}
|
PMC517829
|
The global debate over access to primary research literature heated up this summer, fueled by a slew of congressional and parliamentary recommendations, claims of political victory by critics and proponents of open access, and redoubled lobbying efforts on every side of the issue. After months of often dizzying rhetoric from virtually all camps, one concrete development has indisputably emerged from the fray: governments around the world have begun to take an interest in the question of who can and can\'t read the results of the scientific research they fund. "We are convinced," concluded a recent report from the Science and Technology Committee of the United Kingdom\'s House of Commons, "that the amount of public money invested in scientific research and its outputs is sufficient to merit Government involvement in the publishing process" ([@pbio-0020353-HCSTC1]). United States National Institutes of Health (NIH) Director Elias Zerhouni echoed the British assessment, asserting that "the public needs to have access to what they\'ve paid for," in a July 28 meeting of stakeholders in scientific and medical publishing. "The status quo," he added, "just can\'t stand" ([@pbio-0020353-Park1]).
While such pronouncements may sow fear in the hearts of some scientists and publishers, concerns that governments are poised to tell researchers where or how to publish seem largely unfounded. Both the UK report and rumblings from the US government suggest that any legislative dictates on access to scientific literature are likely to be structured to minimize potentially deleterious implications for established, subscription-based journals, for-profit and not-for-profit alike. Mandates for open access to articles summarizing the results of publicly funded research would not be mandates for scientists to submit work only to the handful of journals, like *PLoS Biology* and *PLoS Medicine,* that currently make their content immediately free online in centralized repositories. A US House of Representatives Committee on Appropriations, for example, recently passed language that would allow many, though not all, publishers six months between the date of publication of NIH-funded research articles and the date of their deposition in a free-to-use archive. (At the time of this writing, the bill is awaiting further discussion in the House and Senate.)
In any case, it is a perfectly reasonable premise that governments should attach conditions to grants mandating public access to resulting peer-reviewed, published articles. Making funding for research contingent on the results of the work being disseminated as widely as possible is hardly a revolutionary proposition. All funders expect, of course, that scientists won\'t simply stash their findings in a desk drawer. Most, like NIH, include in their mission statements clauses about "fostering the communication of medical and health sciences information" ([@pbio-0020353-NIH1]). The US National Library of Medicine, a division of NIH, goes so far as to provide the infrastructure for hosting and storing the full texts of journal articles online, in the form of PubMed Central. Actually requiring that publicly funded works be *included* in publicly funded electronic archives like PubMed Central, as the US Congress might, would be less a paradigm shift or a radically interventionist mandate than a sensible extension of existing policy for most governments and their funding agencies.
Increasingly, it seems, this is the view being adopted by policy makers---that it is the status quo, rather than prospective policy revision, that is anomalous or hard to justify. "We would be very surprised," the Science and Technology Committee notes, "if Government did not itself feel the need to account for its investment \[in research\] in the publishing process. We... hope that this report will be a catalyst for change" ([@pbio-0020353-HCSTC1]).
As a matter of sheer principle, it strikes many people as odd that "anyone can download medical nonsense from the Web for free, but citizens must pay to see the results of carefully conducted biomedical research that was financed by their taxes," as Rick Weiss noted on the front page of the *Washington Post* last year ([@pbio-0020353-Weiss1]). While neither the US nor the UK has yet to legislate a remedy for this *prima facie* paradoxical state of affairs, both appear ready to address the issue systematically, and---more significantly---with the input of a wide range of affected constituents: scientists, publishers, librarians, patient advocates, text-miners, entrepreneurs, and more. The Science and Technology Committee (2004) report was the product of a seven-month investigation, featuring some 127 submissions of written evidence and four days of oral testimony from the likes of Nature Publishing Group, Reed Elsevier, and indeed, the Public Library of Science. NIH has promised a period of public comment on its plan for implementing the Appropriations Committee\'s requirement before moving forward, in addition to the information-gathering meeting of publishers in July and subsequent meetings hosted by Dr. Zerhouni. All told, the current spate of government attention to the issue of public access to research results seems methodical, inclusive, and likely to prove productive for scientific communities and the public.
Andy Gass is the policy analyst at the Public Library of Science. E-mail: <agass@plos.org>
|
PubMed Central
|
2024-06-05T03:55:47.820910
|
2004-9-21
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517829/",
"journal": "PLoS Biol. 2004 Oct 21; 2(10):e353",
"authors": [
{
"first": "Andy",
"last": "Gass"
}
]
}
|
PMC517830
|
Mention greenhouse gases to most people and they\'re apt to think of carbon dioxide, fossil fuels, and big cars. Though carbon dioxide emissions are the major source of greenhouse gases, methane is far more effective at trapping heat in the atmosphere. Like increasing carbon dioxide levels, rising levels of atmospheric methane have been attributed to human activity, mostly in the form of landfills, natural gas and oil processing (about 60%), domesticated livestock (cattle account for about 75% of livestock contributions), and rice fields (up to 29% of total emissions).[](#pbio-0020358-g001){ref-type="fig"}
::: {#pbio-0020358-g001 .fig}
::: {.caption}
###### Methylococcus capsulatus cultured in the presence of a high concentration of copper (Image: Anne Fjellbirkeland)
:::
:::
Ruminants---from cows and water buffalo to llamas and vicunas---emit methane gas as a natural by-product of their digestive process, which confers a unique ability to digest cellulose. Ruminants don\'t digest cellulose directly, but depend on a variety of microbes living in their rumen (main stomach) to do it for them. These microbes ferment cellulose, breaking it down into products the ruminant can digest. During this process, some microbes---bacteria called methanogens---produce methane, which ruminants expel by eructation (otherwise known as belching).
Luckily, there are microbes, called methanotrophs, that consume methane. A type of aerobic bacteria, methanotrophs oxidize methane as an energy and carbon source using the enzyme methane monooxygenase. They\'ve been found in soils, landfills, sediments, hotsprings, and peat bogs, among other environments. Methanotrophs have been the subject of increasing interest because they can use methane as a sole source of carbon and energy---which means they play a major role in global carbon cycles---and could dramatically reduce biologically generated methane emissions. They\'ve also been the focus of bioremediation efforts aimed at environmental decontamination. And now, with the publication of the first complete genome sequence of a methanotroph, such efforts will be all the easier. In this issue of *PLoS Biology,* a multidisciplinary team spanning the fields of genomics, bioinformatics, microbiology, evolutionary biology, and molecular biology report the complete genome sequence of Methylococcus capsulatus and shed light on the metabolism and biology of this ubiquitous microbe.
Contained in a single, circular molecule, the M. capsulatus genome comprises about 3.3 million base pairs---which is about average for a free-living bacterium---with an estimated 3,120 genes. The genome appears well-equipped to meet the specialized needs of this methanotroph, with what appear to be multiple pathways involved in the metabolism of methane and duplications of genes that code for methane monooxygenases, which are essential for the first step of methane oxidation.
Ward et al. also found evidence of "genomic redundancy" in methane oxidation pathways, suggesting that M. capsulatus employs different pathways depending on the availability of molecules needed to sustain cellular activities. Most surprising, the researchers note, was evidence that this methane specialist can turn into a sort of metabolic generalist---with a capacity to use sugars, hydrogen, and sulfur---and appears able to survive reduced oxygen levels. These genome-based hypotheses will require experimental validation, the authors note, but could have important implications for M. capsulatus ecology---including what environments might be amenable to methanotroph-mediated bioremediation.
The genomes of important microbial players in the carbon cycle---including microbes involved in photosynthesis and methanogenesis (methane production)---have already been sequenced. With the addition of a sequenced methanotroph genome, scientists can systematically investigate different genes and regulatory elements to better understand how these methane consumers fit into this global cycle. The M. capsulatus genome provides a platform for investigating the details of methanotroph biology and its potential as a biotech workhorse. It may also guide efforts to harness this bacterium\'s penchant for methane to reduce global greenhouse gas emissions, to degrade chlorinated hydrocarbons and other persistent pollutants, and to produce protein for animal feed.
|
PubMed Central
|
2024-06-05T03:55:47.821782
|
2004-9-21
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517830/",
"journal": "PLoS Biol. 2004 Oct 21; 2(10):e358",
"authors": []
}
|
PMC517831
|
Assembling a complex structure like an automobile requires the tight coordination of hundreds of independent entities---parts must be shipped and arrive on time, workers with the right skills must be in the right place on the assembly line, four (not three, not five) wheels must be bolted into place just so. Overseeing the entire operation is a cadre of managers, whose ability to monitor and respond to changing conditions keeps the entire process moving forward on time and in step.[](#pbio-0020359-g001){ref-type="fig"}
::: {#pbio-0020359-g001 .fig}
::: {.caption}
###### A pair of Bacillus subtilis sporangia, consisting of a large mother cell (green) and a forespore (red)
:::
:::
A living cell is orders of magnitude more complex, and yet has no omniscient manager at the helm. So how does a cell make anything happen on time, and equally important, keep everything from happening all at once? These central questions in developmental biology now have the outlines of an answer in one species, Bacillus subtilis. In this issue, Richard Losick and colleagues show that spore formation in this bacterium is ultimately governed by the temporal interactions of five genes, which together coordinate the activity of almost 400 others.
When conditions are right, B. subtilis divides to form two different cell types: one is a resistant spore, and the other is a mother cell, which engulfs the spore and surrounds it with a protective coat. Building on the large literature addressing the genetic events underlying mother-cell development, Losick et al. performed a variety of experiments to determine exactly which genes turned on and off when, and which genes controlled which others. Over the five-hour process of mother-cell development, they determined that 383 individual genes were activated, representing 9% of the bacterium\'s 4,106 genes.
The instigator of the entire process is a protein called sigmaE (σ^E^). Sigma factors, such as the sigma-E protein, bind to RNA polymerase, and in so doing, increase its affinity for, and therefore its ability to activate, other genes. Thus, sigma factors preferentially activate a specific set of genes. Sigma-E turns on 262 genes (which together compose its "regulon"), kick-starting a variety of processes in the early development of the mother cell.
Importantly, two of its targets, SpoIIID and GerR, are genes for DNA-binding proteins, which themselves modulate the expression of genes in the middle phase of development. Part of SpoIIID\'s portfolio is turning off transcription of a portion of the sigma-E regulon, and amplifying transcription of another portion. This type of control circuit, in which A leads to B, and then both A and B influence C, is called a feed-forward loop.
Among the joint targets for sigma-E and SpoIIID is another sigma factor, sigma-K (σ^K^). By generating the DNA-binding protein GerE, this factor begins a second feed-forward loop, and together, sigma-K and GerE activate the final set of genes needed for mother-cell development. In outline, the system looks like this: sigma-E → SpoIIID/GerR → sigma-K → GerE.
The consequence of all this activity is a series of transcriptional pulses, timed to supply proteins just as they are needed, and then turn off their production when the need passes. For instance, to form the multilayered coat around the spore, sigma-E turns on genes that form the bottom layer, or substratum; these are turned off by SpoIIID. Genes for outer layers, also turned on by sigma-E, are not turned off by SpoIIID, but instead by GerE. Sigma-K turns on genes which form the polysaccharide surface of the coat, which is needed later on.
The elucidation of this complex pattern of gene expression doesn\'t by any means answer every question about B. subtilis development, let alone development in more complex organisms. There is much still to be learned about how genes lower down in the hierarchy---the "middle managers"---do their jobs, and how the system is fine-tuned by environmental conditions. And while the general scheme of feed-forward loops and hierarchical control is likely to apply to multicellular, eukaryotic organisms, the details are certain to be different, and much more complex.
|
PubMed Central
|
2024-06-05T03:55:47.822374
|
2004-9-21
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517831/",
"journal": "PLoS Biol. 2004 Oct 21; 2(10):e359",
"authors": []
}
|
PMC517832
|
The key to any protein\'s function is its structure. Proteins first emerge as a linear strip of amino acids from the cellular protein-manufacturing machinery, and it is this primary sequence that determines a protein\'s ultimate conformation. Improperly folded proteins---which can gum up cells and, when secreted, tissues---are normally destroyed. But in a wide range of diseases, including prion (from proteinaceous and infectious) diseases and neurodegenerative diseases like Parkinson disease and Alzheimer disease, amyloid fibrils, or plaques---misshapen proteins that aggregate into characteristic rope-like configurations---accumulate in tissue.[](#pbio-0020360-g001){ref-type="fig"}
::: {#pbio-0020360-g001 .fig}
::: {.caption}
###### Schematic of single-molecule fluorescence experiment used to establish amyloids growth mechanism
:::
:::
When amyloid precursors and prions (pronounced PREE-ons) lose their normal conformation, they acquire the ability to infect their neighbors. Like molecular dominoes, the fall of one malformed protein precipitates the downfall of its neighbors, as one protein after another assumes the misshapen form of the first. Any chance of developing methods to contain the expansionist tendencies of these proteins depends on understanding the mechanism of propagation, an area of active research.
An abundance of small protein aggregates, called oligomers, is associated with amyloid fiber growth and formation. (Single proteins are called monomers; they "polymerize" into longer chains.) Mounting evidence suggests these so-called amyloid intermediates are the "toxic species" underlying amyloid diseases. The steps in amyloid formation, however, are unclear: Must amyloids follow a progression from monomer to oligomer to plaque? That is, are oligomers required for amyloid plaque formation? Using the yeast prion protein Sup35 to study how amyloids form, Jonathan Weissman and colleagues propose a model of amyloid plaque formation and show that it can indeed occur in the absence of the putative toxic oligomers.
In yeast, the Sup35 protein forms self-replicating aggregations reminiscent of amyloid formation and prion propagation. Though yeast aren\'t susceptible to prion diseases, they do assume what scientists call the yeast prion state. Two protein domains called NM together form self-propagating amyloid fibers that give rise to the yeast prion state. Oligomers, which are typically seen when other proteins form amyloids, have also been seen during this process, some of them near NM fiber ends. Weissman\'s team wanted to know what these oligomers were doing.
To investigate the role of oligomers in NM amyloid formation and growth, the researchers explored the relationship between monomer concentration and polymerization progress. Initially, fiber growth rate was tied to the concentration of NM monomers; but as concentrations increased, growth rate was moderated by NM conformational changes caused after binding to the fiber ends. Shaking the samples increased polymerization rate.
During polymerization reactions, the authors observed a pronounced pause, followed by an abrupt increase in polymerization rate. Since the length of the pause showed only a weak dependence on the concentration of monomers, Weissman and colleagues explain, this finding could not be explained by a simple model of nucleation polymerization, in which growth occurs monomer by monomer, emerging from a monomer "nucleus."
Instead, Weissman and colleagues\' findings support a model in which nucleated monomers initially support fiber growth, fibers undergo fragmentation, and monomers rapidly grow from the broken ends. Weissman and colleagues confirmed that the fibers were growing monomer by monomer by attaching to fragmented fiber ends with fluorescent microscopy, which can detect single molecules.
Though the authors do not rule out the possibility that oligomers could attach to the fiber ends as well, their results show that amyloid growth can occur independently of oligomers. Since many of the properties observed in Sup35 polymerization are evident in other amyloid-forming proteins, the model presented here may be shared as well. Future studies will have to explore this question, along with the issues of how oligomers figure into the process and how they cause disease. Weissman and colleagues raise the possibility that creating conditions that favor fiber growth while inhibiting oligomer formation might limit the toxic effects of amyloid plaques. The approaches outlined here should lay the foundation for exploring these questions in higher organisms.
|
PubMed Central
|
2024-06-05T03:55:47.822983
|
2004-9-21
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517832/",
"journal": "PLoS Biol. 2004 Oct 21; 2(10):e360",
"authors": []
}
|
PMC517833
|
To keep a cell healthy, proteins must go to the right places within a cell. To direct proteins to specific areas of the cell, they\'re marked with tags akin to zip codes on mail. These tags can direct one protein to the cell\'s nucleus, where it regulates gene expression, say, while another is sent to the hinterlands of the cell membrane, where it receives environmental signals. Protein targeting is crucial even as cells are building proteins---otherwise, for example, proteins won\'t fold into the proper shape.
There\'s a pair of proteins that, across all organisms, plays a key role in protein targeting. Called Ffh and FtsY in bacteria, these proteins each have an active and inactive state; only when they\'re in their active state can they bind each other and deliver other proteins to their proper location. Both these proteins are GTPases, a class of proteins that work as molecular switches. However, among GTPases, Ffh and FtsY are unique. Other GTPases switch between active and inactive states by binding different forms of a small, energy-carrying molecule---either GTP or GDP. Such GTPases often require the help of other proteins to switch states. Ffh and FtsY, on the other hand, almost always have GTP bound. And when they interact, they change each other\'s state---allowing each other to convert GTP to GDP---without the help of other proteins. But researchers didn\'t know exactly how these proteins interacted or how they switched between their active and inactive forms.
Now, as reported in this issue of *PLoS Biology,* Shu-ou Shan and colleagues have found that when Ffh and FtsY bind and then activate each other, they likely go through an unusual, multi-step process in which the proteins change shapes, flexing so that different parts of the proteins become active at each step.
The researchers mutated 45 different sites in the gene that encodes the FtsY protein to produce a bevy of mutant proteins with different properties. The researchers chose mutations that produced amino acid substitutions at sites in the FtsY protein that have been preserved through evolution, and so are presumably crucial for the protein\'s function. These sites, it turns out, are all on the protein\'s surface where it interacts with Ffh.
The mutant versions of FtsY varied in how well they bound to the normal version of Ffh and how quickly the two proteins activated each other. The researchers were able to sort the different mutations into four different classes based on the type of problem the proteins had: some bound Ffh very loosely, some bound Ffh well but only weakly turned on its GTPase activity, and so on. All of these mutations would presumably foul up the protein targeting system, so this explains why certain amino acids have been preserved through evolution.
Both Ffh and FtsY change shapes as they bind, activate each other\'s GTPase activity, then cleave GTP and release each other, the researchers infer. They don\'t have direct evidence for these shape changes, but the postulated bends and twists during interaction are consistent with the build of the proteins. These shape changes, they speculate, could switch different parts of each protein between active and inactive states. By showing how this unique type of GTPase switch likely works, Shan and colleagues have helped explain how cells target proteins to specific areas---and perhaps have paved the way for others to find similar switches elsewhere within cells.
|
PubMed Central
|
2024-06-05T03:55:47.823551
|
2004-9-21
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517833/",
"journal": "PLoS Biol. 2004 Oct 21; 2(10):e361",
"authors": []
}
|
PMC517834
|
A man in a suit and bowler hat walks awkwardly down the street, each convoluted step a labored movement. He lifts up one knee, then briefly stoops. Stepping forward, he swings the other leg out to the side then kicks high in the air. In this old Monty Python skit, the man works for the Ministry of Silly Walks. It\'s his job to walk this way. The rest of us, however, tend to stroll along---or throw baseballs, or lift coffee mugs---in a much more efficient manner.
There\'s a nearly infinite number of silly walks, throws, and lifts, but somehow people tend to settle on one best way of doing these things. However, scientists studying motor control have been hard pressed to figure out what exactly we\'re doing when we move. People may be striking a balance between sloth and speed: too slow and our throws lack oomph; too fast, and instead of dunking our donuts in our coffee, we dunk our whole fist. Or people might be minimizing some version of jerk---physicists\' and engineers\' term for changes in acceleration. (Roller coaster engineers, for example, balance jerk against speed and g\'s to keep the ride smooth and safe, but also fun.) But so far, such models that start by assuming people minimize error or jerk haven\'t allowed researchers to deduce what dictates how people move.
To help solve this recalcitrant problem, Konrad Körding and colleagues, as reported in PLoS Biology, took a page from economists, who have long used equations called utility functions that incorporate the costs and benefits of a situation. Say you like oranges better than apples, but oranges cost more. Given a certain budget for fruit, the utility function says how many of each you should buy. Similarly, Körding and colleagues observed people\'s preferred movements, then inferred an underlying utility function that presumably describes bias in the nervous system for different movements.
To see which movements people preferred, the researchers engaged people in a simple virtual reality system. The subjects moved a joystick that fought back: it was connected to a set of motors that produced varying forces---with a strong force for a short time, say, or a mild force for a longer time. Over and over, the subjects moved their cursors from one spot to another. After each pair of moves, the subjects then chose which of the two movements they found easier.
In this way, the researchers were able to rank a large set of different movements relative to each other by individuals\' preferences. They found a surprising amount of agreement among the subjects on which movements were preferable. They also got a counterintuitive result: as the duration of the resistance got longer, people actually preferred stronger resistance. The researchers speculate that subjects didn\'t mind larger resistance when it acted over a longer period because the force takes longer to ramp up to its maximum value. Subjects would have more time to adjust---just as when someone gradually pushes into you, you can stay standing by leaning into them, whereas if they shove you with the same force it can knock you off balance.
By showing that utility functions can be of use not only in explaining the marketplace but also motor control, Körding and colleagues have added a new tool to biologists\' repertoire. Though their approach hasn\'t closed the case on the mysteries of movement, it could help explain why we settle for a particular, non-silly walk.
|
PubMed Central
|
2024-06-05T03:55:47.824015
|
2004-9-21
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517834/",
"journal": "PLoS Biol. 2004 Oct 21; 2(10):e370",
"authors": []
}
|
PMC517923
|
Background
==========
As a group, the rheumatic diseases of childhood represent one of the most common chronic disease conditions in children \[[@B1]\]. These illnesses have global distribution \[[@B2]-[@B5]\], but little information exists regarding either prevalence or phenotypic expression of these diseases in children in any population other than North American and European whites \[[@B6]\]. Aggarwal and colleagues \[[@B7]\] have reported their experience with juvenile rheumatoid arthritis (JRA) on the Indian subcontinent, and their findings suggest that the patterns of disease reported in Europe and North America are not seen in that population. Most conspicuous in Aggarwal\'s study was the relative rarity of the pauciarticular form of JRA, in contrast to European and North American populations, where that subtype accounts for 50 to 75% of the cases \[[@B3],[@B8]-[@B11]\]. The relative rarity of pauciarticular JRA in non-European populations has been documented in children of Kuwait \[[@B5]\], Turkey \[[@B12]\], Thailand \[[@B13]\], Japan \[[@B14]\] and South Africa \[[@B15]\] as well as in African American children in Detroit \[[@B16]\]. Further evidence that examining prevalence rates of rheumatic diseases in specific populations may be informative comes from studies of systemic lupus erythematosus (SLE). Studies from Great Britain, for example, indicate that the prevalence rates for SLE in people of Afro-Caribbean descent may be 4--8 times higher than that in Caucasians \[[@B17],[@B18]\].
Prevalence rates of rheumatic disease in North American Indian/First Nations populations have been reported in small studies from single tribes. From these studies, significantly higher prevalence rates for rheumatoid arthritis (RA) have been reported in adults from tribes living in the Great Lakes region \[[@B19]\], the Pacific Northwest \[[@B20]\], the Southwest \[[@B21]\] and Canada \[[@B22]-[@B24]\].
To our knowledge, a comprehensive survey of rheumatic diseases affecting children, adolescents, and young adults has not been reported in any non-Caucasian population. Because both our clinical experience here in Oklahoma suggests that rheumatic diseases in children may also be more prevalent in the American Indian population compared with Caucasians, we undertook a search of the Oklahoma City Indian Health Service (IHS) user population databases in order to develop prevalence estimates of rheumatic diseases in American Indian children and adolescents. We performed the same queries from the database in the Billings Area IHS office as a basis of comparison.
Methods
=======
Populations in the billings and Oklahoma City areas
---------------------------------------------------
The Oklahoma City Area IHS serves a population of 291,288 individuals, most of whom reside in Oklahoma, with small numbers living in the neighboring states of Kansas and Texas \[[@B25]\]. IHS services are limited to members of federally recognized tribes, 39 of whom have tribal headquarters in Oklahoma. The 39 federally recognized tribes \[[@B26]\] represent people from multiple Native cultures including Eastern Woodlands tribes (e.g., Cherokee, Delaware, Seneca), Southeastern tribes (e.g., Creek, Choctaw, Chickasaw, Seminole), Southwestern tribes (e.g., Apache), as well as tribes who have long been resident on the southern Great Plains (e.g., Kiowa, Comanche, Southern Cheyenne). Tribal membership is determined by the tribes themselves and may or may not include specific blood quantum requirements for membership. Historical factors, the absence of reservations, and the proximity of European-descended people in Oklahoma has resulted in significant admixture between Native and Caucasian populations in many parts of the Oklahoma City Service Area.
The Billings Area IHS serves a population of 72,591 individuals. The tribes in this service area, a significant proportion of whom live on 8 reservations located in Montana and Wyoming, consist largely of northern plains tribes (e.g., Crow, Sioux, Blackfeet).
In both Areas, the population is younger than the population of the United States as a whole, with 40 percent of the population 19 years of age or younger \[[@B27]\].
Database search
---------------
International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9) codes were used to search the Oklahoma City and Billings Area IHS National Patient Information Reporting Systems and Patient Registration user databases \[[@B28]\] over a three-year period (1998--2000) to identify individuals with rheumatic diseases.
Outpatient data over this three-year period was gathered for the user population ≤ 19 years of age and included: patient chart number (with the chart number scrambled to protect patient identity), date of birth, sex, date of visit and diagnosis (the IHS database allows at least 9 diagnoses to be recorded on any given patient). The codes used and the diagnoses denoted by those codes are listed in Table [1](#T1){ref-type="table"}. Data were downloaded into a standard database (Microsoft Excel), which was then searched to eliminate duplicate records and to sort patients for each year on the basis of age, sex, and diagnosis.
A case was defined as any person who was 19 years of age or younger on January 1,1998, January 1, 1999 and January 1, 2000 and whose diagnoses included at least one of the entities listed in Table [1](#T1){ref-type="table"}.
The population at risk was defined as the number of individuals ≤19 years of age within the IHS user population (i.e., eligible individuals who have used the IHS facilities at least one time in three years) \[[@B29]\]. The user population (i.e., people who actually used IHS services) may differ from the IHS *service*population, which includes all individuals who are eligible to receive IHS services. Estimation of disease prevalence was based on three assumptions: (1) that the diagnoses recorded were, in fact, accurate; (2) that the population at risk did not change significantly over the three-year period; (3) that the three-year mortality rate for the diseases of interest was no greater in the IHS user population than for all races in the United States.
For the Oklahoma City Area, accuracy of the IHS database information was assessed by matching the IHS identification number of known JRA cases followed at the Children\'s Hospital of Oklahoma with the same number in the IHS patient databank to be sure that known patients were identified and coded accurately.
Results
=======
Rheumatoid arthritis/juvenile rheumatoid arthritis
--------------------------------------------------
Rheumatoid arthritis and juvenile rheumatoid arthritis (RA/JRA; \#ICD-9 \# 714.0, 714.30) were the most frequent rheumatic disease diagnoses recorded in individuals ≤ 19 years of age in both IHS areas. In the Oklahoma City Area, we identified 62 individuals (45 females and 17 males) with these diagnoses. Assuming a population at risk of 117,409 (i.e., individuals 19 years of age or younger; source: IHS Headquarters office, data processing services unit, Albuquerque, NM), this gives a crude prevalence rate of 53 cases per 100,000 at risk. The prevalence rate for Billings was considerably higher. The 714.0 and 714.3 codes identified 33 individuals in the Billings Area. Based on a population at risk of 28,724, the prevalence estimate for Billings was 115 per 100,000 at risk (see Table [2](#T2){ref-type="table"}). The age distribution of affected children, adolescents, and young adults in both areas differed from what has been reported in studies from predominantly European or European-descended populations (Figures [1A](#F1){ref-type="fig"} and [1B](#F1){ref-type="fig"}). There is a distinct biphasic distribution of JRA prevalence by age in Caucasians, with peaks in the late preschool years and in early adolescence \[[@B30],[@B31]\]. Data from both IHS databases show a distinct peak at age 5--12 years with proportionately smaller numbers of patients in the preschool and early adolescent age groups. In both Areas, peaks in late adolescence and early adulthood are observed, consistent with our observation that rheumatoid arthritis is a disease of young adults in this population (Mauldin *et al*, manuscript in preparation). The absence of a prevalence peak in the preschool years may reflect the almost complete absence of children with monoarticular or pauciarticular JRA in the IHS user population, consistent with previous studies in non-European populations \[[@B5],[@B7],[@B8],[@B13],[@B15],[@B32],[@B33]\]. We found no individuals in the database with the ICD-9 code commonly used to denote pauciarticular-onset JRA (\#ICD-9 \# 714.32). In the Oklahoma City Area we found a single child (a 12 year old female) diagnosed with monoarthritis (\#ICD-9 \# 714.33).
Included in the above analyses are individuals who may not fit established criteria for a diagnosis of JRA. Since we did not examine age at onset, it is impossible to know whether a 19 year old identified as having rheumatoid disease was age 7 or age 17 at disease onset. JRA diagnosis criteria stipulate that patients must have disease onset at 15 years of age or younger \[[@B34]\]. When data were analyzed to include only children 15 years of age or younger, we identified 35 patients (23 females, 12 males) in the Oklahoma City Area and 21 patients in the Billings Area (9 females, 12 males) with a diagnosis of JRA. Based on the populations at risk of 87,936 (Oklahoma City) and 21,777 (Billings) this yields an estimated prevalence rate of 40 per 100,000 in the Oklahoma City Area and 96 per 100,000 in the Billings Area. Both of these estimates are more than twice the prevalence derived from a recent European study (14.8 per 100,000) \[[@B35]\].
In order to test the integrity of the IHS database in the Oklahoma City Area, we matched known cases of JRA followed at the Children\' Hospital of Oklahoma (CHO; n = 15) by IHS identification number with patients in the database. All 15 of the children followed at CHO were identified within the database and correctly identified by subtype.
We did not have access to patient records in the Billings Area, but do have access to databases at other IHS facilities. At a large facility in the Aberdeen Area (comprising the states of North Dakota, South Dakota, Nebraska, and Iowa and serving a patient population very similar to that served in the Billings Area) we identified 20 children with JRA using the same search strategy as that used in for the Billings and Oklahoma City Areas. Subsequent chart review demonstrated that 17 of these children had strong clinical evidence to confirm the diagnosis of JRA, while diagnosis could not be supported or excluded in the other three. The estimated prevalence for JRA in the population served by this facility calculates to 236/100,000, within the same order of magnitude by considerably higher than the Billings Area estimate.
Spondyloarthropathy
-------------------
The second most common diagnoses identified in each Area database were the group of illnesses collectively denoted spondyloarthropathies (\#ICD-9 \# 720.0, 720.1, 720.2, 720.8, 720.89). Although these illnesses are sometimes viewed as distinct entities, they share sufficient common features that allow them to be grouped for purposes of this analysis. These common features include: (1) male sex preponderance; (2) arthritic involvement of the axial skeleton (e.g., sacroiliac joints); (3) extra-articular musculoskeletal involvement (e.g., bursitis, enthesitis); and (4) extra-articular (e.g., ocular, genito-urinary) inflammation. In both white \[[@B36]-[@B38]\] and American Indian patients \[[@B39]-[@B43]\], the human class I histocompatibility complex antigen HLA-B27 constitutes a strong risk factor \[[@B44]-[@B47]\].
We identified 20 patients (12 females, 8 males) with spondyloarthropathy in the Oklahoma City Area IHS database, giving an overall crude prevalence rate of 17 per 100,000 at risk. Included in this group are three patients (all female) with psoriatic arthritis (ICD-9 Code \# 696.0). In the Billings Area, we identified 12 individuals (7 females and 5 males) with ICD-9 codes used to identify patients with spondyloarthopathy, yielding a prevalence rate of 42 per 100,000 at risk. These included one patient (a 12 year old male) with ankylosing spondylitis (\#ICD-9 \# 720.0), one (a 5 year old male) with psoriatic arthritis (\#ICD-9 \#696.0), and 10 patients (6 females and 4 males) with nonspecific sacroiliitis (\#ICD-9 \# 720.2). The Oklahoma and Billings Area estimates were within the range previously reported for childhood spondyloarthropathies (e.g. ankylosing spondylitis) in the United States and United Kingdom (12 to 33 per 100,000) and Mexico (13 to 65 per 100,000) \[[@B48]\], but slightly lower than previously estimated prevalence rates of 29 per 100,000 (all spondyloarthropathies) for First Nations children in western Canada \[[@B22]\]. The female-to-male preponderance in both Areas was unusual and has not been, to our knowledge, reported with any previous population.
Discussion
==========
Although rare individually, the rheumatic diseases, taken together, are among the most common chronic health conditions affecting children \[[@B1]\]. Exact prevalence rates among children living in the United States are difficult to obtain, owing, in large part, to the de-centralized delivery of health care in this country. The IHS represents an exception to that decentralization and is, arguably, the closest representation to a nationalized health care delivery system currently functioning within the United States. Thus, records and data available through the IHS represent a unique opportunity to assess population-wide health needs not otherwise available to child health researchers in this country. This report provides a first-ever population-wide estimate of the prevalence of chronic arthritis in American Indian children living within the United States. While the prevalence rate for the Oklahoma City Area was within the same order of magnitude as the most recent reports from Europe \[[@B35]\], the prevalence rate in the Billings Area was nearly 10 times this recent European estimate. These findings are consistent with earlier studies of rheumatoid disease in American Indian adults, where prevalence rates 10 times higher than the general population were reported \[[@B49],[@B50]\]. It should be pointed out, however, that prevalence estimates of JRA vary widely, ranging between 16 to 113 per 100,000 \[[@B30],[@B31],[@B51]-[@B55]\].
The reasons for the discrepancy in prevalence estimates between the Oklahoma City and Billings Areas are not clear. One possibility is that the northern plains tribes are particularly susceptible to rheumatoid disease in ways that other groups (e.g., Eastern Woodlands or Southwestern tribes) are not. It is also possible that the difference in ethnic composition of the two populations accounts for this difference. While many Oklahoma tribes require at least a 25% blood quantum of tribal ancestry (e.g., the Kiowa tribe \[[@B56]\]), other tribes require only proof of descent from an individual on the original Dawes rolls of 1893 \[[@B57]\]. Thus, the Oklahoma City Area includes many individuals whose degree of American Indian ancestry is 1/4 or less and may include individuals with less than 1/64 American Indian ancestry. In contrast, there has been less intermingling between Caucasian and American Indian populations on the northern plains, and a larger percentage of the Billings Area population includes individuals with full-blooded American Indian ancestry.
Our study once again points out the rarity of the pauciarticular form of JRA in non-European populations. In studies of European and European-descended populations, pauciarticular JRA is the most common form of chronic childhood arthritis \[[@B3],[@B8]\].
The Oklahoma City Area database listed a single child with ICD-9 codes \#714.32 (pauciarticular JRA) or 714.33 (monoarticular arthritis), the codes used to identify such children. These findings are consistent with reports from the Indian subcontinent,\[[@B7]\] Kuwait \[[@B5]\], Turkey \[[@B12]\], Thailand \[[@B13]\], Japan \[[@B14]\], South Africa \[[@B15]\], and with our experience with African American children in Detroit \[[@B16]\].
The slight female-to-male preponderance for spondyloarthopathy is also worth noting. High prevalence rates for spondyloarthopathies have been noted in both Northwestern and Southwestern tribes \[[@B24],[@B41]-[@B44]\]. However, in these studies, a strong male preponderance was noted. Whether the findings from Oklahoma City and Billings represent a novel finding or inaccuracies in the ICD-9 coding await confirmatory studies, as we discuss below.
An important limitation to this study is the fact that we did not have the means to verify every individual case listed in Oklahoma City database and were unable to confirm any diagnosis in the Billings Area database. However, our limited test of the accuracy of the Oklahoma City data provided surprising confirmation of the accuracy of coding for known cases. While we could not confirm any of the Billings cases, our search of the database of a single IHS facility in the neighboring Aberdeen Area corroborated the prevalence statistics we derived from the Oklahoma City and Aberdeen databases. Indeed, our experience suggests that a search strategy like the one we used is likely to under-estimate rather than over-estimate the prevalence of rheumatic disease in the IHS user population.
We are aware that there are many factors that might overestimate disease prevalence using this type of database search. The first is the possibility that a given ICD-9 code might have been used to designate a \"working\" diagnosis that was never established by the patient\'s clinical course. The second opportunity for overestimation of prevalence would occur if children were systematically misdiagnosed. This could occur easily if physicians use serologic data as the sole criterion for diagnosis. For example, many physicians routinely screen children with musculoskeletal complaints using antinuclear antibody (ANA) tests. However, the prevalence of low-titer positive ANA tests is extraordinarily high in the pediatric population \[[@B58]\]. Thus, if ANA-positive children with musculoskeletal pain \[[@B59]\] are listed as having \"JRA,\" then there would be a gross overestimation of the actual prevalence.
Similarly, there are factors that might have led to underestimation of JRA prevalence by relying solely on a three-year database search. Children or adolescents with well-controlled JRA may not have seen an IHS physician during the relevant time period, and thus would have been excluded. Similarly, physicians who rely on rheumatoid factor tests as a diagnostic criterion for JRA might fail to diagnose the disease in a child, since only a small number of children with JRA have detectable IgM rheumatoid factor \[[@B60]\].
The ideal method for obtaining true disease prevalence rates would include rigorous, pro-active case finding in a known population at risk. This approach was taken by Manners and Diepeveen in a study of school children in Australia \[61\]. Using such an approach, these authors reported a prevalence rate of 4 per 1,000 for JRA, significantly higher than any previous estimates. We are now preparing a similar project involving American Indian communities on the northern plains.
Conclusion
==========
We conclude that the rheumatic diseases of childhood may represent a significant burden of morbidity in these two IHS user populations. More detailed studies with rigorous case ascertainment are required to follow up these preliminary data.
Competing Interests
===================
None declared.
Authors\' Contributions
=======================
Dan Cameron provided data from the IHS database in Oklahoma City, and Diane Jeannotte provided the Billings Area data. Joyce Mauldin and Glenn Solomon performed the database searches. Dr. Jarvis directed this study and assisted in data analysis and interpretation.
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1471-2474/5/30/prepub>
Acknowledgements
================
This work was supported by a generous grant from the Arthritis Foundation (to JNJ). The authors would like to extend special thanks to Dr.\'s Everett R. Rhoades and David Grossman for their review and thoughtful comments on this manuscript. The authors would also like to thank Julie McGhee for proofreading and suggestions for this manuscript.
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Bar graphs showing the age and sex distributions of children with JRA identified in the Oklahoma City Area (A) and Billings Area (B) IHS databases. In each Area, there was a conspicuous under-representation of both pre-school children and early adolescents diagnosed with JRA.
:::
:::
::: {#T1 .table-wrap}
Table 1
ICD-9 CODES Disease
----------------------- ---------------------------------------------------------------------
696.0 Psoriatic arthropathy
695.4 Lupus erythematosus (discoid)
710.0 Systemic lupus erythematosus
710.1 Systemic sclerosis
710.2 Sicca syndrome
710.3 Dermatomyositis
710.4 Polymyositis
710.8 Other specified diffuse diseases of connective tissue
710.9 Unspecified connective tissue disease
714.0 Rheumatoid arthritis
Other rheumatoid arthritis of visceral or systemic involvement
714.2 Juvenile chronic polyarthritis
714.30 Polyarticular juvenile rheumatoid arthritis, chronic or unspecified
714.33 Monoarticular juvenile rheumatoid arthritis
Spondyloarthropathies
720.0 Ankylosing spondylitis
720.1 Spinal enthesopathy
720.2 Sacroilitis, not elsewhere classified
720.8 Other inflammatory spondyloarthopathies
720.89 Other spondyloarthropathies
:::
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Rheumatic Diseases in Children and Adolescents Identified in the Oklahoma City and Billings Area Databases
:::
**[Area]{.underline}** **[Oklahoma City Area]{.underline}** **[Billings]{.underline}**
------------------------ -------------------------------------- ----------------------------- ---------- -----------------------------
**Disease Entity** **Number** *Prevalence***(Estimated)** *Number* *Prevalence***(Estimated)**
*RA/JRA* 62 53/100,000 33 115/100,000
*Spondyloarthopathy* 20 17/100,000 12 42/100,000
*SLE* 13 11/100,000 4 14/100,000
*PMS/DMS* 5 4/100,000 4 13/100,000
*Other* 8 2
:::
|
PubMed Central
|
2024-06-05T03:55:47.824657
|
2004-8-27
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517923/",
"journal": "BMC Musculoskelet Disord. 2004 Aug 27; 5:30",
"authors": [
{
"first": "Joyce",
"last": "Mauldin"
},
{
"first": "H Dan",
"last": "Cameron"
},
{
"first": "Diane",
"last": "Jeanotte"
},
{
"first": "Glenn",
"last": "Solomon"
},
{
"first": "James N",
"last": "Jarvis"
}
]
}
|
PMC517924
|
Background
==========
This article describes the situation in a suburban area in Sweden, and concerns the comprehensive medical care of patients with primary-care home nursing, i.e. patients who require regular assistance from nurses in their homes in order to maintain their health and manage their health problems. This does not include hospital-at-home care, where a multiprofessional team is responsible for the medical care.
The use of inpatient hospital care in Sweden as in many other Western countries has diminished in recent decades. In combination with an ageing population with greater needs for medical care, this has resulted in an increase in different forms of home care. The overall situation is similar in many countries, although local conditions may vary considerably \[[@B1]-[@B4]\].
The shift of care from the hospital to the home \"has had an enormous impact on care recipients, their families and friends, and in-home service providers.\" \[[@B3]\] and \"is changing the meanings, material conditions, spatio-temporal orderings and social relations of both domestic life and health-care work.\" \[[@B5]\]. One effect has been \"the fragmentation and dispersion of specialised health services from hospitals to alternative locations.\".. \"especially revealed for people with diminished mobility\" \[[@B4]\]. These changes make the care of patients with home nursing an important area for investigation from the perspectives both of patients and of health care workers.
Much is known about the medical care, especially inpatient and outpatient hospital care of older persons, and that factors like age, health problems and socio-economic conditions influence the utilisation of inpatient hospital care \[[@B6],[@B7]\]. Hospital-at-home care has also been the subject of several studies \[[@B8]-[@B10]\]. However, most investigations of home care and home nursing, concern care in the patient\'s home \[[@B11],[@B12]\]. Other studies have focused on home nursing and medical care of patients with specific diseases, and whether care at home influences the risk of rehospitalisation \[[@B13],[@B14]\]. But little is known about the total care of patients with home nursing, which not only includes what takes place in the home, but also the care received in hospitals, out-patient departments, and from doctors in general practice, etc. There is also a lack of knowledge about what factors influence the care of these patients, apart from medical necessities. In view of the expansion of this health care sector, such knowledge should be of value, particularly for planning purposes.
In a previous paper \[[@B15]\] we have presented a picture of the patients with home nursing, in a Swedish suburb, and the primary health care of those patients. The patients were old (median age 83 years, range 46--95), and many had functional problems (e.g. reduced mobility (50%), vision (46%), cognitive ability (33%), hearing (29%)), and symptoms (e.g. musculoskeletal pain (53%), fatigue (46%), anxiety (44%)). Cardiovascular disorders (42%), psychiatric disorders including dementia (27%), and musculoskeletal disorders (21%) were the most common diagnoses in family physician records. Most patients had several symptoms and more than one diagnosis. All had contact with district nurses or assistant nurses, usually once a week or every second week. Ninety-seven percent of the patients had had medical care initiated by their family physician during the study year, but much of the care was carried out without direct contact between family physician and patient, as a significant part of the medical care was performed through collaboration with district nurses. This meant that the patients with home nursing saw their family physicians less often than other patients of comparable age.
In view of the lack of knowledge in this expanding field, we considered it important to investigate and describe the comprehensive care of patients with home nursing as a starting point for further research and development.
The objectives of the present paper are as follows:
To identify the specialised medical care of patients who were receiving primary-care home nursing.
To give a comprehensive view of the care of these patients.
To investigate how personal, social and functional factors and help by relatives influenced the use of specialised medical care by these patients.
Methods
=======
The study was performed in a suburban area of Stockholm with 40 000 inhabitants, 18 percent of whom were 70 years of age or older. The care of patients, with primary-care home nursing, who lived in ordinary houses or flats was studied. Patients in the study area who received regular nursing care at home for a period of more than two weeks from the district nurses in primary health care were registered as primary-care home nursing patients (Table [1](#T1){ref-type="table"}).
In Stockholm, patients can choose to go to any of the hospitals (11 emergency hospitals and several smaller geriatric hospitals during the study year) or outpatient departments in the city. Two emergency hospitals, two geriatric hospitals and two wards for psychiatric inpatient care were located in or close to the study area.
During the registration week (21 to 27 October 1996), 486 patients in the study area had primary-care home nursing. Using a random table, we selected one-third of the patients of each district nurse for the study.
The study was designed as a retrospective study of the comprehensive medical care of patients with primary-care home nursing, including the medical care they received both in their homes and in other places. It was also designed to study whether non medical factors that are common among patients with home nursing may have influenced the care. The data were not obtained from the patients, but from records and from the family physicians and district nurses responsible for the patients\' primary health care, i.e. professionals dealing with the patients\' medical problems. Data were also obtained from the official statistics of the Swedish County Councils, a source that is generally considered by researchers to be of high quality and well suited for scientific purposes. A description of the patients and the care performed by family physicians, district nurses and assistant nurses was given in a previous article \[[@B15]\].
The hypotheses were
\- that care outside the home comprises a substantial part of the total care of patients with home nursing.
\- that personal, social and functional factors may influence the use of medical care outside the home
Information concerning the situation during the registration week was obtained from questionnaires distributed the week following the registration week. Retrospective data from the study year (28 October 1995 to 27 October 1996) were obtained from the official statistics, and the family physician (21 family physicians) and nursing (20 district nurses) primary health care records.
The official statistics were used to identify and describe inpatient care and outpatient visits in specialised medical care, and the number of home and practice visits to/by the nurses in primary health care. Notes in the family physician records were used to describe the family physician care (reason for contact, who had been in contact and measures undertaken) as well as the diagnoses of the patients \[[@B16]\]. Notes in the nursing records were used by the district nurses to identify nursing procedures. The protocol for extraction of information from the nursing records comprised 18 questions with fixed-alternative answers and was designed for the study by the Stockholm Gerontology Research Centre in cooperation with a group of district nurses \[[@B17]\].
Personal, social and functional data concerning the situation during registration week, as well as patients\' symptoms, and help from relatives at that time, were obtained from the questionnaires. When possible, validated questions that had been tested in other studies were used, but some were modified to suit the situation in home nursing. These revisions were made by the Stockholm Gerontology Research Centre in cooperation with a group of district nurses \[[@B17]\]. Personal and social factors included age and sex, whether or not the patient lived alone, and whether there were one or more relatives who assumed responsibility for a substantial amount of the care. Functional problems concerned cognitive function (difficulty knowing the day of the week, finding the way home and/or recognising relatives/caregivers), mobility (being unable to move about in the immediate surroundings), and ADL capacity. For ADL capacity the different Katz index functions were used and the patients were grouped according to the degree of ADL dependency. Patients in *Group 1*were either without functional deficiencies or dependent only regarding cleaning, shopping and/or transport, patient in *Group 2*were, in additions, dependent with respect to cooking, bathing and/or dressing, but not eating, and patients in *Group 3*were in addition dependent concerning eating. The factor mobility was excluded from the ADL groups, as this was assessed separately using data from other questions. The factors toileting and continence were excluded, as the answers were not consistent when compared with answers to questions concerning the same functions in other parts of the questionnaire.
Symptoms were registered in a 23-item protocol originally used in studies of nursing homes, but modified to suit the situation in home nursing. The questionnaires also included questions about how long the patient had had home nursing, and whether the patient had had contact with any private doctor in specialised medical care.
The questions were thus chosen so that the district nurses responsible for the care could answer them without additional patients assessments, either because the information would be well known to them since they were responsible for the nursing care or because the answers were based on assessment tools used in the regular care, such as that used for ADL.
Questionnaires sent to the home-help providers focused on whether the patient had home help (Table [1](#T1){ref-type="table"}).
From the randomised one-third of selected patients (n = 158), we excluded 42, (16 declined to participate, and for ethical reasons we did not inquire why; ten had been discharged from home nursing, died or had been admitted to hospital; four could not participate for other reasons). Information about all patients from one district nurse was excluded (12 patients), since it was obvious that she had not understood the questions, leaving 116 patients (73%).
Information could not be obtained from all sources for all patients. Visits to private doctors in specialised medical care and to private physiotherapists are not included, as they were not included in the official statistics. According to questionnaire responses from the district nurses, 11 patients saw private doctors in specialised medical care on a regular basis. We have no information about private physiotherapists.
As the number of visits and care periods did not have a normal distribution, we used non-parametric statistical methods, i.e. medians and minimum -- maximum. The Mann-Whitney test and χ2 were used to compare differences between groups. Conditional logistic regression was used to study whether personal, social or functional factors influenced the chance (expressed as odds ratio) that study patients had made visits to or had had inpatient specialised medical care during the study year. We used a case control design where patients with specialised care were cases and patients without this care were controls. The different factors were first tested by univariate logistic regression. The factors that showed significant influences were included in a multiple logistic regression model. One of these factors (home help) showed no significant influence when included in the model, and it was therefore excluded from the main effect model \[[@B18]\]. The factors without significant influence were also tested and included in the model, but no significant influence was found. The SPSS data-analysing system, version 11.0, was used for the analyses.
The study was approved by the Research Ethics Committee at Huddinge University Hospital. This approval included the design of the study as well as the way informed consent was obtained from the individual patients.
Results
=======
Eighty-nine of the 116 study patients (77%) lived alone, 86 patients (74%) were women and 41 (35%) received substantial assistance from family members according to the district nurses. Sixty-eight patients (65%) had home help. Patients who lived alone were less likely to have assistance from family members than those who lived with a relative (31% compared to 58%, p \< 0.05), but on the other hand they were more likely to have home help (76% compared to 29%, p \< 0.001). Patients who got help from family members were less likely to have home help (51% compared to 75%, p \< 0.05).
Specialised inpatient care
--------------------------
More than half of the patients had been admitted to hospital during the study year (Table [2](#T2){ref-type="table"}). Among these, the majority were admitted twice or more and spent more than three weeks in hospital. In all, more than 15 specialities were represented. Geriatric care represented almost 2/3 of all days in inpatient care, but the care by specialists at the different emergency hospitals involved more patients and a greater number of care periods. The most common specialities were general internal medicine (32 study patients and 29% of the care periods), surgery (10 study patients and 6% of the care periods), neurology (nine study patients and 5% of the care periods) and orthopaedics (seven study patients and 4% of the care periods). Almost all inpatient care periods (93%) were spent at the two emergency hospitals, the two geriatric hospitals, and the two local psychiatric wards located in or close to the study area, but six other emergency hospitals and one other geriatric hospital also provided care for these patients.
The median values for all study patients were one care period and four days in care. The average number of care periods and days in inpatient care in Stockholm for the persons 75 to 84 years of age, and 85 years of age or older, were 0.6 of a care period and five days in inpatient care and 0.8 of a care period and seven days in inpatient care, respectively \[[@B19]\].
Specialised outpatient care
---------------------------
During the study year a majority of the patients made outpatient visits to hospitals and outpatient departments (Table [3](#T3){ref-type="table"}). In all, 22 different specialities were represented. Visits to departments of general internal medicine were most common (46% of the study patients, 22% of all visits), followed by visits to departments of surgery (26% of the study patients, 6% of the visits), orthopaedics (22% of the study patients, 6% of the visits) and ophthalmology (21% of the study patients, 9% of the visits). The visits in specialised care took place at eight different emergency hospitals, two geriatric hospitals, and two local psychiatric and one local ophthalmology department. However, 86% of the visits were to the two emergency hospitals located in or close to the study area. Of the 80 patients who made outpatient visits to hospitals 46 percent visited more than one speciality.
The median value for visits to doctors in specialised care for all study patients was one visit. The average numbers of outpatient visits to doctors outside primary health care (excluding doctors in private practice) in Stockholm for persons 75--84 years of age and 85 years of age or older were 1.7 and 0.8, respectively \[[@B20]\].
The comprehensive view
----------------------
In the 104 cases where a family physician record was found, a visit to either their family physician or a doctor in outpatient specialised care, or both, was found for 95 patients (91%) (median 3 visits). Approximately one third (32 %) of the patients saw doctors from two or more specialities, GP care not included. Thirty-eight study patients (33%) had visited a physiotherapist or an occupational therapist (290 visits in all). Of these, 141 visits (49%) took place in primary health care and comprised 23 (20%) of the study patients (Table [3](#T3){ref-type="table"}). Doctors and physiotherapists in private practice are not included.
More detailed examples of the care picture on an individual level are given in Table [4](#T4){ref-type="table"}, where the problems and the medical care provided for two patients are described. The objective is to give a picture of what the care may look like from the perspective of the individual patient, as well as to present a picture of what conditions may be like for the different caregivers with the task of cooperating and coordinating the care. We have chosen one patient with three visits to specialised care, which was the median number among those who had specialised care, and one patient with many visits to specialised care. In both cases, it was possible to obtain data from all sources of information.
Patients who did not see a family physician during the study year did not receive significantly more or less care from other caregivers (Table [5](#T5){ref-type="table"}). Patients with visits to doctors in specialised care made significantly more visits to family physicians, saw the district nurses and other caregivers in specialised care more often, and also had more inpatient care. Patients who had been admitted to the hospital had more contacts with both doctors and other caregivers in outpatient specialised care, but not with the family physicians or the nurses in primary health care.
The influence of personal, social and functional factors
--------------------------------------------------------
The influence of personal, social or functional factors on the chance of receiving specialised medical care was tested (Table [6](#T6){ref-type="table"}). When the groups with different degrees of ADL dependency were tested, we found no difference between groups 1 (30 patients) and 2 (62 patients), but found that both groups 1 and 2 differed from group 3 (23 patients). Therefore groups 1 and 2 were combined into one group (1--2) and compared with group 3 in the model. Patients with severe ADL dependence (group 3) were less likely, and patients who had help from family members were more likely to make outpatient visits in specialised medical care. The same factors were tested to see if they influenced the chance that a patient had had inpatient care, but here we found no significant association.
Discussion
==========
A majority of the patients with primary-care home nursing also received both inpatient and outpatient specialised medical care. Patients received care from home help, family members, family physicians, nurses in primary health care, and doctors and other caregivers in specialised medical care, thus providing a very complex picture. Many different hospitals and specialities were involved. Almost all patients had seen one or more doctors during the study year. Those who saw doctors in specialised care had more help from all categories of medical care. Patients with severely reduced ADL capacity were less likely, and patients with help from family members were more likely to have made outpatient visits in specialised medical care.
The limitations of this paper include that personal, social and functional factors as well as symptoms were recorded by the district nurses and not reported directly by the patients, which means that this is second hand information, sometimes including an assessment. However, all of the participating district nurses had four and a half years of university education as is required, as well as many years of professional experience, which should ensure a sound basis for their assessments. Most of the personal and social factors were of the kind that are readily available concerning any patient and do not need assessments. The exception is participation of family members in the care, where the district nurse with her often longstanding contact with the patient and family is a suitable source of information. The functional factors in the Katz ADL index, mobility and cognitive function, are functions the nurses were used to assessing and reporting in their cooperation with hospitals and home help services. The only inconsistencies found concerned toileting and continence, which were consequently excluded. Further, symptoms could have been underestimated, as the district nurses would only be aware of them if they were obvious, or if the patient reported them, but they have only been used to describe patients, and not for any analysis.
The study presents the medical care of patients with primary-care home nursing in one suburban area in one country. There are differences between the health-care systems and the informal and formal networks of care in different countries and sometimes also in different areas in the same country. This means that our conclusions are valid for patients with primary-care home nursing in this area; verifying whether they are valid in other areas would require further studies. However, as the study patients have the same type of problems described in other studies of patients with home nursing \[[@B21],[@B22]\], their care needs are probably not different from those of patients receiving home nursing elsewhere.
We have studied the situation in a city with easy access to near-by, specialised care, and with many different hospitals where patients are free to obtain medical services without a referral. This will have increased the number of hospitals and units involved in the care, as well as the number of outpatient visits \[[@B23],[@B24]\]. This part of our results might be representative for other areas with easily accessible specialised care, but to confirm this would require further studies.
The strengths of this paper include the following. A randomised third of a population is considered to provide a sufficient basis for conclusions about all patients receiving primary-care home nursing in a population, and a participation rate of 73 % is acceptable. The patients who were excluded were of the same age (median age 83, range 42--98 years) as the participants but might have had more severe conditions, as patients who had died or were admitted to hospital during the registration week were excluded. These patients probably did not receive less medical care than those who were included. Information about a few patients was missing from some sources. All practices had roughly the same proportion of drop-outs and missing data, and the reasons can be considered to be random. The results should then be valid for all patients with primary-care home nursing, in the study area. As the patients are similar to those with home nursing described in other studies, this study may serve as a reference for further investigation of the care of patients with home nursing.
These patients who had primary-care home nursing also had many instances of specialised inpatient and outpatient medical care. However, their care did not differ substantially from that of the average population of comparable age in Stockholm County during 1996 \[[@B19],[@B20]\]. This is somewhat surprising, as these patients with health problems could be expected to use more medical care. On the other hand, patients who regard a primary-care physician as their personal physician rather than a doctor in specialised care have lower total health-care expenditures \[[@B25]\], and patients who identify a doctor outside the hospital as their primary source of care are hospitalised less often \[[@B26]\]. Practice populations also have a major reduction in hospital care when a nurse is introduced into the primary-health-care team \[[@B27]\]. Since only patients with primary-care home nursing were included in the study and almost all (97%) received medical care from a family physician, this may explain why they did not use more specialised care than the average population.
There was one group with significantly more medical care than the others, i.e. those patients who made outpatient visits to doctors in specialised care. The probable reason is that they had more severe medical conditions, but this is not possible to confirm in the present study.
Inpatient care seemed to be strongly associated with more outpatient contacts in specialised care, but not with more contacts in primary health care. It is not possible to say whether this was the result of a greater need for specialised care, or the result of a tendency to keep the patients in specialised care \[[@B28]\].
Patients with no visits from a family physician received neither more nor less medical or nursing care elsewhere. The rest of the care was apparently not influenced by the low priority this was given by the family physicians.
The care of an individual patient often included several caregivers from different organisations. For the individual patient who meets many different persons and goes to many different places, this means a lack of continuity. For this group of elderly patients with complicated medical problems, reduced mobility, reduced cognitive ability and reduced ADL-capacity, the risk that the individual caregiver does not have the proper information when decisions are made must be extremely great, especially taking into account the problems involved in the exchange of information between primary care and specialised care \[[@B28]\]. On an organisational level, many different caregivers make demands on systems and time for co-operation and the exchange of information. From a health care perspective the risk of inefficiency, low quality and/or high costs is evident, as at one end the same procedures might be done by several caregivers, while at the other end vital measures might not be performed because no one has the total picture. Several Swedish studies describe serious quality problems related to the medication of persons in home nursing, and these may partially reflect this situation \[[@B29],[@B30]\], while other studies describe the lack of co-ordination and of an overall picture in the care of old persons with multiple problems \[[@B31],[@B32]\].
In Sweden, the share of health care expenditures allocated to primary health care is often low (12 -- 21 %) compared to other parts of Western Europe, where it is frequently 20 percent or more \[[@B33]\]. Further, this figure has not increased to any great extent since 1980, even though the inpatient hospital care has decreased dramatically \[[@B33]-[@B35]\]. The picture we report, where many patients remain in specialised care, is compatible with this economic situation.
We found that functional and social factors influenced the chance of a patient having made outpatient visits to specialised medical care. Severe ADL dependence reduced the chance and receiving help from family members increased the chance. The fact that patients with severe ADL dependence do not make many outpatient visits is not surprising as reduced function limits the possibility to get to locations outside the home. The findings that help from family members increased the chance of having made outpatient visits to specialised medical care is not surprising either, in view of the age and functional problems of the patients. Relatives might be more observant concerning new symptoms, might easier establish contact and assist in transportation of the patients, than professional caregivers. Is the care organised so that old patients with multiple diseases and reduced functions need the help of a relative in order to get outpatient specialised medical care? Or do patients who get help from family members have more severe medical problems, even though there are no differences in primary-health-care diagnoses? Further studies are needed in this area.
Conclusions
===========
The picture that evolves from our study is that the care of patients with home nursing is more complex than has previously been assumed. In parallel with their primary-care home nursing, all patients had contact with doctors, often from both primary and specialised medical care. The situation resembles that in a hospital ward, where many different caregivers and many different professions are involved in the care of the same patient, but without the ward\'s geographical and temporal unity. This renders it almost impossible for the individual patient to get continuity in all aspects of care, and the possibility of cost effective care of good quality is diminished.
Patients with home nursing have complicated medical problems and both nurses and doctors are involved in their care, contrary to the previous belief that some patients are cared for by nurses alone. Instead, there seems to be one group of patients with home nursing who also need both primary and specialised care, and who have greater care needs than other patients with home nursing.
That reduced function decreases and help from family members increases the chance of getting outpatient, specialised medical care raises questions concerning the medical care for patients with both medical and functional problems.
Our conclusions are based on a study in one suburban area, and further studies are needed in order to confirm them.
List of abbreviations used (if any)
===================================
ADL Activities of Daily Living
ENT Ear Nose and Throat
Competing interests
===================
None declared.
Authors\' contributions
=======================
SM designed and carried out the study, performed the statistical analysis, participated in the interpretation of results, wrote the initial draft of the manuscript and made subsequent revisions. AKF participated in the interpretation of results and made critical revisions of the manuscript. Both authors have read and approved the final manuscript.
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1472-6963/4/22/prepub>
Acknowledgements
================
We thank the personnel of the Stockholm Gerontology Research Centre who designed the questionnaires and carried out many of the practical arrangements as part of a study of their own. The financial support of Family Medicine Stockholm and The Swedish Foundation for Health Care Science and Allergy Research is gratefully acknowledged.
Figures and Tables
==================
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Definitions used in the article
:::
------------------------------- ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Home help Persons who deliver general care at home. They do not necessarily have medical training
Home-help organisation The organisation that delivers home help services
Home-help provider Decide whether a person can get subsidized home help, and if so how much.
Hospital-at-home Medical care in the home performed by a multi-professional team. Patients with this care were not included in this study, but some patients had had this form of care during the study year.
Nurses in primary health care District nurses and assistant nurses working in primary health care.
Primary-care home nursing Home nursing that is part of primary health care, and is performed by district nurses or by assistant nurses under the supervision of the district nurse. The family physician can be of support or actively involved in the care. Patients with this form of care were included in the study if they lived in ordinary houses or flats.
Specialised medical care Medical care outside of primary health care, often performed at hospitals or in outpatient clinics.
------------------------------- ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
:::
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Inpatient care and hospital-at-home care. Information from the official statistics of Stockholm County for the study year for the patients (n = 116) receiving primary-care home nursing (information missing for one patient).
:::
No. of patients No. of care episodes in patients with inpatient or hospital-at-home. No. of care days in patients with inpatient or hospital-at-home.
-------------------------------------------------------- ----------------- ---------------------------------------------------------------------- ------------------------------------------------------------------ -------- ------------ -------------- -------- ------------
Type of care n \% Total number Median Min -- max Total number Median Min -- max
All forms of inpatient care 64 56 190 2 1--10 1799 23 1--138
Inpatient care from emergency hospital specialities^1^ 51 44 107 1.5 1--10 599 7.5 1--49
Geriatric inpatient care 42 37 77 1 1--6 1063 19 1--109
Psychiatric inpatient care 2 2 3 \- 1--2 87 43.5 19--68
Hospital-at-home 3 3 3 \- 1--1 50 10 2--38
^1^E.g. internal medicine, surgery, neurology, orthopaedics
:::
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Outpatient medical care. Information from the official statistics of Stockholm County for the study year for the patients (n = 116) receiving primary-care home nursing (information missing for one patient).
:::
Patients No. of visits by those who made visits
------------------------------------ ------------------------------------------- ---------- ---------------------------------------- ----- -------- ------------
Type of care Type of caregiver N \% n Median Min -- max
All forms of specialised care All professions 83 72 957 5 1--173
Doctor 80 70 356 3 1--23
Physiotherapist or occupational therapist 18 16 147 5.5 1--33
Other^1^or unknown 60 52 454 2 1--166
Emergency hospital specialities^2^ All professions 78 68 785 5 1--173
Doctor 76 66 322 2.5 1--23
Physiotherapist or occupational therapist 7 6 52 4 1--23
Other^1^or unknown 52 45 411 2 1--166
Geriatric speciality All professions 18 16 168 5 1--45
Doctor 15 13 34 2 1--8
Physiotherapist or occupational therapist 13 11 95 4 1--33
Other^1^or unknown 12 10 39 2.5 1--9
Psychiatry All professions 2 2 4 \- 2--2
^1^E.g. nurse, welfare officer, speech therapist, dietician, ^2^E.g. internal medicine, surgery, orthopaedics, ophthalmology, dermatology All forms of care includes care at emergency hospital specialities, geriatric care, and psychiatric care. All professions includes doctors, physiotherapists and occupational therapists and other or unknown caregivers
:::
::: {#T4 .table-wrap}
Table 4
::: {.caption}
######
Examples of care situations during the study year involving patients receiving primary-care home nursing.
:::
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
[82-year-old woman who lives alone, has no home help, has help from family members.]{.underline} (Many visits in specialised care)
[Main medical problems:]{.underline} Asthma, facial skin disease, polyposis of the nose, needs a hearing aid, cataract operation, urinary problems, fever, mammary problems. [Functional problems]{.underline}: Reduced vision, reduced hearing. Primary-care home nursing for 5 months.
[Primary health care during the study year:]{.underline} 159 visits by nurses, who helped to prepare inhalations and made medical assessments.
The family physician record shows 2 notes concerning visits and 2 notes without a visit. Diagnoses in family physician record: Fever, skin disease, pathological urinary sample, examination including mammography.
[Medical care outside of primary health care:]{.underline} 18 visits (3 to audiology, 1 to ENT, 2 to dermatology, 8 to ophthalmology, 2 to surgery, 3 to pulmonary medicine). 14 of these visits were to doctors. One period of inpatient care: 2 days in the ENT clinic.
[88-year-old woman who lives alone, has home help.]{.underline} (Three visits in specialised care)
[Main medical problems:]{.underline} Heart failure, atrial fibrillation, depression, infections. [Functional problems:]{.underline} Reduced vision, reduced hearing, reduced mobility and reduced cognitive function. Primary-care home nursing for one year.
[Primary health care during the study year:]{.underline}52 home visits by nurses, who dispensed tablets and helped with general care, social rehabilitation, preparation before tests, blood and urinary sampling, measuring of blood pressure, and made medical assessments and did care planning.
The family physician record shows 3 notes concerning home visits, 3 concerning practice visits and 9 notes without a visit. Diagnoses in the family physician record: Depression, heart failure, atrial fibrillation, upper respiratory tract infection, pneumonia, cystitis.
[Medical care outside primary health care:]{.underline}2 visits to ophthalmology, 1 visit to general internal medicine. One visits was to a doctor. 3 periods of inpatient care in geriatric clinic, 18 days.
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
:::
::: {#T5 .table-wrap}
Table 5
::: {.caption}
######
Number of visits to principal caregivers. The number of visits are given in relation to the presence or absence of visits to family physicians and to doctors in specialised medical care, and to the presence or absence of inpatient care during the study year, for patients with primary-care home nursing (n = 116; information is missing concerning family physician visits for 12 patients, for specialised care for one patient). Number of patients (n), median (M), and p-value (Mann-Whitney test)
:::
No. of visits to family physicians No. of visits by district nurses No. of visits to doctors in specialised care No. of visits to caregivers other than doctors in specialised medical care No. of inpatient care periods
---------------------------- ----- ---- ------------------------------------ ---------------------------------- ---------------------------------------------- ---------------------------------------------------------------------------- ------------------------------- ---------- --- ---------- ---- ----------
n M p M p M p M p M p
Visits to family physician No 21 \- \- 29 n.s. 1 n.s. 1 n.s. 0 n.s.
Yes 83 \- 36 1 0 1
Visits to doctors in No 35 1 \< 0.01 25 \< 0.05 \- \- 0 \< 0.001 0 \< 0.001
specialised medical care Yes 80 2 37 \- 2 2
Inpatient care No 51 1 n.s. 34 n.s. 1 \< 0.001 0 \< 0.001 \- \-
Yes 64 2 36 2 1 \-
:::
::: {#T6 .table-wrap}
Table 6
::: {.caption}
######
The association of non-medical factors to outpatient visits in specialised care. Personal, social and functional factors concerning the patients receiving primary-care home nursing and how they are associated with the chance (odds ratio) of making outpatient visits in specialised medical care during the study year. (n = 115). Logistic regression.
:::
Univariate Main effect model
--------------------------- -------------------------------------- ---- ------------ -------------------- ------------ --------------------
Factors N Odds ratio 95% Conf. Interval Odds ratio 95% Conf. Interval
Age \> 83 years of age 53 0.68 0.30--1.53
≤ 83 years of age 62 1 (Reference)
Sex Male 30 1.37 0.52--3.60
Female 85 1 (Reference)
Living Living alone 88 0.68 0.25--1.88
Conditions Cohabiting 27 1 (Reference)
Care Family participates 41 3.11 1.15--8.44 3.17 1.12--9.00
Family does not participate 69 1 (Reference) 1 (Reference)
Home Help^1^ 68 0.31 0.11--0.89
No Home Help 35 1 (Reference)
Mobility Reduced ^2^ 58 0.51 0.22--1.17
Not reduced 57 1 (Reference)
Cognitive function Reduced ^3^ 38 0.52 0.23--1.22
Not reduced 77 1 (Reference)
ADL dependence Yes, severe (group 3)^4^ 23 0.20 0.08--0.53 0.21 0.08--0.59
None, or not severe (Groups 1--2)^5^ 92 1 (Reference) 1 (Reference)
Goodness of fit, Pearsson 0.58
^1^Not included, see explanation in the text, ^2^Is unable to move about in immediate surroundings, ^3^Difficulty in knowing day of week, finding the way home and/or recognising relatives/caregivers, ^4^Needs help to eat, ^5^Independent or needs help with cleaning, shopping, transport, bathing, cooking and/or dressing, but not eating.
:::
|
PubMed Central
|
2024-06-05T03:55:47.826992
|
2004-8-26
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517924/",
"journal": "BMC Health Serv Res. 2004 Aug 26; 4:22",
"authors": [
{
"first": "Sonja",
"last": "Modin"
},
{
"first": "Anna-Karin",
"last": "Furhoff"
}
]
}
|
PMC517925
|
Background
==========
The nematode *Caenorhabditis elegans*is among the most widely studied genetically-tractable experimental organisms. *C. elegans*is a soil-dwelling animal with a relatively simple and extremely well characterized anatomy; an adult hermaphrodite, for example, contains exactly 959 somatic cells, each with an identified position, morphology and cell lineage. Because of its short generation time, amenability to germline transformation, and completely sequence genome, it is ideally suited for classical and molecular genetic analysis. In particular, since the *C. elegans*nervous system is simple and well-characterized (the identity and connectivity of each neuron is known), it has become a facile model for studying the molecular basis for nervous system function. Robust behavioral phenotypes have been described for many *C. elegans*behaviors, including locomotion, egg-laying, mating and feeding, and these phenotypes have proven extremely useful for the genetic dissection of key aspects of neuronal function such as synaptic release, sensory transduction, and neuromuscular signalling \[[@B1]\].
Historically, a major limitation of such neurobiological studies in *C. elegans*has been the lack of quantitative methods for the evaluation of behavioral phenotypes. For example, the phenotypes of many behavioral mutants, even those defective in key aspects of neuronal signal transduction, appear subtle to a real-time human observer, and are difficult to assay without time and labor-intensive analysis of video recordings \[[@B2]-[@B4]\]. Even the phenotypes of mutants with grossly abnormal behavior are difficult to characterize precisely by manual observation. For example, mutants with striking defects in locomotion (uncoordinated, or Unc mutants) are typically classified using qualitative terms such as \"coiler\", \"kinker\", \"sluggish\", \"slow\" and \"loopy\" \[[@B5],[@B6]\]. Since these descriptions are imprecise and subjective, it is extremely difficult if not impossible to assess the phenotypic similarity between two mutants based solely on such characterizations. Another challenge occurs in the analysis of behaviors such as locomotion and egg-laying, which can fluctuate over long time scales or involve infrequently-occurring events that are difficult to evaluate through real-time observation \[[@B7]\]. Furthermore, the quantitative assays that have been used in *C. elegans*behavioral studies (e.g. \[[@B8]\]) generally differ from lab to lab, and this lack of standardization has made effective comparison of data collected by different researchers difficult.
To address these problems, we have developed an automated tracking and image analysis system for the quantification of *C. elegans*behavioral patterns. Using this system, it is possible to record the behavior of individual animals at high magnification over long time periods and to simultaneously quantify a large number of behaviorally-relevant features for subsequent analysis. This system has wide applications for the dissection of complex *C. elegans*behaviors, and will also make it possible to comprehensively classify the behavioral patterns of *C. elegans*mutants on a genome-wide scale. By making this system widely available to *C. elegans*neuroscientists, we intend to define a software architecture that can be continually optimized and upgraded to incorporate new parameters that are useful to worm researchers, as well as a hardware platform that can be expanded to provide additional mechanical capabilities for the research community.
Methods
=======
To effectively capture the locomotion behavior of a freely-moving worm, it is necessary to acquire a sequence of images from which the animal\'s position, speed and body posture at any given point in time can be derived. *C. elegans*are small (1 mm) animals which, in the laboratory, are normally cultured on agar plates covered with a lawn of the common laboratory bacterium *Escherichia coli.*Nematodes move using an approximately sinusoidal wave motion that is propagated along the anterior/posterior axis in the dorsal/ventral plane. On an agar plate, the animal will normally lie on either its left or right lateral surface, making the waveform associated with movement visible from above. When crawling at maximum speed, an adult nematode travels at a rate of approximately 500 μm/s; thus, under the relatively high magnification (40--50 X) required to measure detailed features of body posture the worm can quickly crawl outside the field of view. It is therefore necessary to incorporate into the imaging system a motorized stage that can automatically follow the animal\'s movements and keep it in the microscope\'s visual field.
The tracking system described here consists of (i) a Nikon SMZ-800 microscope with a stereoscopic zoom, for visualizing the animals; (ii) a Daedal motorized stage controlled by a National Instruments 4-axis controller, for maintaining the animal in the visual field; (iii) a Cohu monochrome analog CCD camera, for image acquisition; (iv) a Windows computer (PC) with a National Instruments video acquisition board, for tracking and image analysis (Figure [1](#F1){ref-type="fig"}). An optional VCR can also be included in the system for the purpose of cross verification of behavioral tracking. A complete parts list is in [Additional file 1](#S1){ref-type="supplementary-material"} (\"hardware\"). It should be noted that the software (see below) can, with very minor revisions, be adapted to other programmable motorized stages and frame grabbers that meet the industrial standards; questions about specific pieces of equipment can be addressed to the authors.
Software
========
Briefly, the software for the system consists of four basic modules. The first module, called the tracker, allows the system to follow the worm as it crawls around the plate by directing the movements of a motorized stage to maintain the animal in the center of the field of view. As the video acquisition board acquires digital images from the microscope field, the tracker program identifies the animal from each acquired image based on 1. size of the objective isolated from background and 2. the direction of the animal crawling in previous frame if more than two objectives are found Based on the coordinates of the animal\'s centroid within the field of view, the tracker directs the movements of the stage to recenter the animal in the visual field when animals approach the edge of the image frame. The program then saves an image (460 × 380) of the worm containing visual frame (i.e, the pixels composing the worm body plus the minimum enclosing rectangle), the position of the animal within the field of view, the position of the stage, the time the image was captured, and other information crucial for behavioral analysis. These data are saved into the widely used .avi multimedia format, with a MPEG-4 filter to significantly compress the size of data. Null images are not saved into the .avi format, and the user is notified of the null frame. The highest frame rate with which the tracker can perform these operations with our current hardware setting is 30 frame/sec.
Next, the system contains a module (called the converter) that processes the raw images to simplify parameter estimation. First, the grayscale image is thresholded and converted to a binary image representing the worm outline. The image is further simplified by generating a morphological skeleton along the midline of each binary image and then distributing 30 skeleton points along this skeleton. A third module (called Lineup) then orders the backbone points from head to tail. To distinguish head and tail, minor user input is required to achieve 100% accuracy. In wild type, this user input (which involves identifying the head with a mouse click) is only required on 1% of the frames. Otherwise, all image processing is completely automated.
Thus, for each raw acquired image, the system generates 4 representations of the animal (Figure [2](#F2){ref-type="fig"}) of increasing complexity: the centroid representing the animal\'s position, the set of ordered skeleton points representing the animal\'s body posture, the binary image, which provides information about the size and shape of the animal, and the grayscale image, which retains information about the translucency of the animal. Together the outputs of the first three modules then are used to extract quantitative image features that define the characteristic behavioral pattern of a particular mutant type. During image processing stage, aberrant frames (e.g. containing a \'worm\' with suddenly abnormal length) are marked and removed, and the user is notified of the defective image.
To obtain this information, the system has a fourth, parameter estimation module (called miner) that measures specific features based on grey/binary image, centroid, or skeleton point analysis that define important parameters related to locomotion or morphology. Broadly speaking, these include measurements of morphology, body posture, movement, and locomotion waveform. Morphological features include measurements of size, length, transparency, and elongation/eccentricity. Body posture features include measurements of body curvature as well as the occurrence of specific postures such as coils and omega turns. Movement features include centroid-based measurements of global speed and direction, skeleton point-based measures of local movement, and the occurrence of directional reversals and large turns. Waveform features include measurements of the frequency and amplitude of body bends, the flex of the animal\'s body during the locomotion wave, and the frequency and magnitude of foraging movements by the animal\'s nose. A total of 59 distinct features (Table [1](#T1){ref-type="table"}) are measured by the system. For most of these features, three statistics (top 5% as maximum, mean and lower 5% as minimum) are calculated for each recording, giving a total of 144 measured parameters. A list of all the features and the algorithms used to generate them are found in supplemental data \[see [Additional file 2](#S2){ref-type="supplementary-material"} \"algorithms\"\].
Implementation
==============
The software is available in a PC version (compiled and benchmarked on a PC with 1 G Hz Pentium-III running Windows 2000 or XP). Software is written with C/C++, Labview 7.0 and Matlab (release 13), and complied with NI LabWindow 7.0. Installation disk and dataset samples are available upon request for non-profit academic usage with a license fee (\$75, charged by National Instruments for the usage of their vision library; see [Additional file 3](#S3){ref-type="supplementary-material"} and [4](#S4){ref-type="supplementary-material"}, \"codes\" and \"filelist\" for details). Worm behavioral image data are in AVI format with a standard MPEG-4 filter (Microsoft MPEG-4 v2). Quantitative morphological and behavioral data are outputted into two widely distributed formats: Microsoft Excel and Microsoft Access. Using this hardware configuration, it is possible to process a 2 Hz 1 min real time data set in less than 5 minute (from image data to final data). Thus, it is feasible to envision using the system to screen for specific behavioral phenotypes among mutagenized *C. elegans.*
Applications
============
We describe here a prototype for a standard, open-source system for automated phenotypic analysis of *C. elegans*behavior. We anticipate that such a system will be extremely useful to *C. elegans*neurobiologists, as machine vision offers a number of clear advantages over real-time observation for the characterization of behavioral phenotypes. First, it provides a precise definition of a particular mutant phenotype, facilitating quantitative comparisons between different mutant strains. For example, the waveform parameters have provided detailed information about the effects of neuronal G-protein signalling pathway genes on locomotion behavior. Even phenotypes that are extremely difficult to distinguish by eye (e.g. those of the calcium channel mutants *unc-2*and *unc-36*) can be identified with relatively high reliability using the system \[[@B9]\]. In addition, it has been possible to use our system to reliably score behavioral events without labor-and time-intensive (and potentially biased) human scoring; for example, our system has been used to automatically detect directional reversals with high reliability in a touch avoidance assay \[[@B10]\]. Other specific postures such as coils can also be detected with high (\>90%) reliability (Z. Feng, unpublished data).
With appropriate controls, a standardized phenotyping system also makes it possible to compare behavioral data collected by different researchers in different labs with greater precision than is possible using qualitative observer-driven approaches. In particular, a computerized system makes it possible to comprehensively assay multiple aspects of behavior simultaneously, yielding a complex phenotypic signature that can be used for bioinformatic studies \[[@B11]\]. In the future, we hope to use the tools described here to generate a comprehensive *C. elegans*phenotypic database that could be used to explore the clustering and relative similarities of mutant phenotypes.
Supplementary Material
======================
::: {.caption}
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Hardware list
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###### Additional File 2
Algorithms for feature measurements
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###### Additional File 3
Codes
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###### Additional File 4
File list
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Click here for file
:::
Acknowledgments
===============
This work was supported by research grants from the National Institutes of Health (to W.R.S. and P.W.S.) and the Howard Hughes Medical Institute (P.W.S.). Zhaoyang Feng is a postdoctoral fellow of the Burroughs-Wellcome Fund/La Jolla Interfaces in Science interdisciplinary training program. The authors thank Anthony Kempf for critical discussion.
ZF and CJC jointly wrote the software and developed the system described here. JHW developed an early version of the system and designed the hardware configuration. PWS and WRS jointly conceived of this project, and participated in its design and coordination. WRS drafted the manuscript, CJC drafted the supplemental guide to the algorithms, and ZF drafted the supplemental hardware list. All authors read and approved the final version.
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Illustration of the hardware of tracking system. A Nikon SMZ-800 microscope with a stereoscopic zoom is used to visualize the animals. Image signal can be simultaneously captured by a VCR and digitalized by a NI PCI-1409 image capture board through a Cohu monochrome analog CCD camera. NI FlexMotion PCI-1744 stage controller controls the Deadal motorized stage to follow the animal, and receives the stage position information.
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Representations of the *C. elegans*animal. The image is recovered from avi file. The Red line shows the boundary of the binary image. The skeleton is shown in white line and the yellow dots represent the skeleton points.
:::
:::
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Features measured by the automated system. List of the behavioral and morphological features. Detail algorithms to output these features are found in supplemental data. 144 statistical results (mean, maximum and minimum where applicable) of these features are output into Microsoft Access, while the values of these feature at each time when an image is grabbed are saved in Microsoft Excel.
:::
Features Comments Catalog
--------------------- -------------------------------------------------------------- -----------------------------
Area Total area of worm Body morphology
BendingFrequency Frequency of body bends Wave form/speed
CmptFactor Compactness factor Body posture
ElgFactor Elongation factor Body posture
EllMAxis Best-fit ellipse, major axis Body posture
EllRatio Best-fit ellipse, major axis/minor axis Body posture
EqvlEllRatio Equivalent ellipse ratio Body posture
Fatness Area/Length Body morphology
Flex Maximum skeleton point angle difference Wave form
Foraging Frequency of sideways (foraging) head movements Specific behavior (feeding)
Foraging angle Angle of foraging movements Specific behavior (feeding)
Foraging distance Distance moved by head during foraging Specific behavior (feeding)
FRE Frequency of angle change between skeleton points Wave form/speed
GlbMvScope Maximum distance moved from starting point Global movement
GlbSpd Speed of the animal\'s centroid movement Global movement
HdTlRatio Ratio of head to tail movement speed Head movement
Heywood Heywood circularity factor Body morphology
Hydraulic Hydraulic radius Body morphology
IXX Inertia XX Body morphology
IXY Inertia YY Body morphology
IYY Inertia XY Body morphology
LclSpd Local movement speed Local speed
Length Distance from head to tail Body morphology/posture
LengthToPixel Length/number of pixels in skeleton Body posture
Loop Percentage of time worms coils their body Specific behavior (coil)
MaxIntercept Max intercept Body morphology
MeanIntcptPpdcl Mean perpendicular intercept Body morphology
MostPopularArea Mode of area Body morphology
MostPopularSpeed Mode of speed Global speed
PercentageMPArea Frequency of occurrence of modal area Body morphology
PercentageMPSpeed Frequency of occurrence of modal speed Global speed
Pushing Local body movement speed/centroid speed Locomotion wave efficiency
RectBigSide Minimum enclosing rectangle (MER) length Body posture
RectRatio Minimum enclosing rectangle length/width ratio Body posture
Reversal Percentage of time that a worm performs reversals Specific behavior (escape)
ReversalCount Number of reversal sessions that a worm performs Specific behavior (escape)
ReversalDisAve Average distance traveled backward in reversals Specific behavior (escape)
SktAglAve Mean value of skeleton point vector angle Body bending
SktCmptFactor Length of worm / oriented MER area Body posture
SktElgFactor Skeleton enlongation factor Body posture
SktHight Oriented MER height Body posture
SktIXX Sum of x coordinate times x coordinates of skeleton points Body posture
SktIXY Sum of x coordinate times y coordinates of skeleton points Body posture
SktIYY Sum of y coordinate times y coordinates of skeleton points Body posture
SktvAglAve Average angle between skeleton points and centroid Body bending
SktvAglMax Max angle between skeleton points and centroid Body bending
SktvDisAveToLength Average distance between skeleton points and centroid/length Body bending
SktvDisMaxToLength Max distance between skeleton points and centroid/length Body bending
SktvDisMinToLength Min distance between skeleton points and centroid/length Body bending
SktWidth Oriented MER width Body posture
Theta Direction of centroid movement Global movement
Thickness Thickness of worm Body morphology
TotalTravelDistance Total distance traveled by a worm Global movement
TrackAmplitude Amplitude of waves in worm\'s track Wave form
TrackWavlength Wavelength of waves in worm\'s track Wave form
Transparency Transparency of worm body Body morphology
Turn Percentage of time that a worm performs a sharp turn Specific behavior (search)
TypeFactor Type Factor Body morphology
Waddel Waddel disk diameter Body morphology
WaveLenth Largest spatial span of a sine wave Wave form
XSym Sum of X coordinates of all sktps Body bending
XYSym Sum f Y coordinates of all sktps Body bending
YSym Sum of X coordinate \* absolute value of Y coordinate Body bending
:::
|
PubMed Central
|
2024-06-05T03:55:47.832860
|
2004-8-26
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517925/",
"journal": "BMC Bioinformatics. 2004 Aug 26; 5:115",
"authors": [
{
"first": "Zhaoyang",
"last": "Feng"
},
{
"first": "Christopher J",
"last": "Cronin"
},
{
"first": "John H",
"last": "Wittig"
},
{
"first": "Paul W",
"last": "Sternberg"
},
{
"first": "William R",
"last": "Schafer"
}
]
}
|
PMC517926
|
Background
==========
Predicting ancestral protein sequences from a multiple sequence alignment is a useful tool in bioinformatics \[[@B1]\]. Many evolutionary sequence analyses require such predictions in order to map substitutions to a particular lineage (*e.g.*\[[@B2],[@B3]\]). In other situations, the predicted ancestral sequence alone may provide a more representative functional sequence than a simple consensus sequence constructed from an alignment.
Nevertheless, predicting ancestral sequences is not a simple procedure. It relies on a quality alignment plus an accurate -- and correctly rooted -- phylogenetic tree. Strict consensus methods are quick but can suffer from over-representation of larger clades of related sequences, which contribute more sequences to the consensus than more sparsely populated clades. Maximum Parsimony (MP) methods \[[@B4]\] overcome this problem by minimising mutational steps, rather than maximising agreement with the terminal sequences. MP, however, cannot distinguish between several equally parsimonious predictions. More sophisticated likelihood-based methods exist that can give probabilities for different ancestral sequences (*e.g.*\[[@B5]-[@B8]\]) and implementation such as CODEML \[[@B5]\] and FASTML \[[@B7]\] provide a good balance between speed and accuracy. However, many of these programs cannot predict ancestral sequences for columns of the alignment that have one or more gapped residues \[[@B9]\].
GASP (Gapped Ancestral Sequence Prediction) is an ancestral sequence prediction algorithm that is designed to handle gapped alignments of any size using a combination of MP and likelihood methods. Although probably not as accurate as some of the more sophisticated maximum likelihood approaches, it permits the estimation of ancestral states at residues that are gapped in any sequences of the alignment with comparable accuracy to that of ungapped residues.
Implementation
==============
The GASP algorithm
------------------
### Input
GASP uses input from three sources: a multiple sequence alignment (MSA); an accompanying phylogenetic tree in Newick format \[[@B10]\]; and a Point Altered Mutation (PAM) substitution probability matrix, such as that of Jones *et al.*1992 \[[@B11]\]. Sequences are read in from the alignment and node relationships established from the tree. The tree may be already rooted or rooted using GASP and must have branch lengths. Bootstrap values are not used by GASP but will be read if present. Sequences in the tree file can be represented by numbers (matching the order of the fasta alignment) or the first word of the sequence name. Details of the input formats can be found at: <http://bioinformatics.rcsi.ie/~redwards/gasp/>.
### Output
GASP outputs an alignment in fasta format with both input terminal sequences and predicted ancestral node sequences. Ancestral sequences can either be grouped together at the end of the file or interspersed throughout the terminal sequences to reflect the tree topology (Figure [1(a)](#F1){ref-type="fig"}). Three tree files are also output from GASP: (1) Newick format of the original input tree, rooted (Figure [1(b)](#F1){ref-type="fig"}); (2) A raw text version of the tree, with internal nodes numbered as for the output sequence file; (3) Newick format tree with node numbers instead of bootstrap values, which can be opened with K Tamura\'s TreeExplorer program \[[@B12]\] (Figure [1(c)](#F1){ref-type="fig"}). Branch lengths in this last file are replaced with the most likely PAM distance for a given branch, where PAM likelihoods for each branch are calculated as the product of each individual residue:
where *p*~*X*~is the likelihood for a PAM distance of *X*(see \'Ancestral sequences\' below), *i*is the ancestral amino acid at position *r*,*j*is the descendant amino acid at position *r*, *p*~*ijX*~is the substitution probability of *i*to *j*in a PAM*X*matrix, and *N*is the number of residues in the alignment. Substitutions involving gaps are ignored in this calculation.
This allows a visual comparison between the branch lengths of the input phylogeny and the predicted branch lengths given the ancestral sequence predictions.
### Gaps
If the MSA has gaps, GASP will first assign gap status to every residue at every node. Insertions and deletions are assumed to be equally likely, although a gap is assigned in the case of a tied probability (below). For each residue *r*, GASP starts at the tips and works deeper into the tree, assigning a probability of a gap at each node *n*, which is equal to the mean probability of a gap at the descendant nodes:
where *p*is the gap probability for residue *r*at node *n. p*~1~and *p*~2~are the gap probabilities for *r*at the two descendant nodes.
Terminal branches are given a probability of 1 if a gap is present or 0 if not. Once the root is reached, the gap status is fixed for the root. If the probability of a gap is greater than or equal to 0.5, residue *r*is fixed as a gap, otherwise *r*is fixed as a \'non-gap\'. GASP then works back up the tree from the root, this time using the new ancestral gap probability and both descendant gap probabilities to recalculate the gap probability:
where *p*~0~is the gap probability for *r*at the ancestral node.
As with the root, *r*is fixed as a gap if *p*≥ 0.5. This continues until all nodes are assigned as \'gap\' or \'non-gap\'.
### Ancestral sequences
Once gaps are assigned, ancestral sequences are predicted in a similar fashion. Each residue *r*is assigned a probability for each amino acid at each node *n*. At the tips, *r*has a probability of 1 for the amino acid that is present in the MSA. GASP then works down the tree assigning probabilities based on the descendant nodes, branch lengths and a substitution matrix. By default, the PAM matrix of Jones *et al.*1992 \[[@B11]\] is used. This is a PAM**1**matrix, which represents the probability that a given amino acid will be substituted by each other amino acid when the mean substitution rate is **1**/100 residues. To make a PAM*X*matrix, which represents a length of evolutionary time where a sequence will have undergone *X*substitutions per 100 residues, the PAM1 matrix is multiplied by itself *X*-1 times:
where *i*is the ancestral amino acid,*j*is the descendant amino acid, *k*is the 20 possible transitory amino acids, *p*~*ijX*~is the substitution probability of *i*to *j*in a PAM*X*matrix, *p*~*ik*(*X*-1)~is the substitution probability of *i*to *k*in a PAM(*X*-1) matrix and *p*~*kj*1~is the substitution probability of *j*to *k*in a PAM1 matrix.
Unless the ancestral node has a gap (as calculated above) at position *r*, the ancestral probabilities for each amino acid are calculated for the two descendant branches individually, using a PAM*X*matrix, where *X*is 100 times the branch length as substitutions per site, *i.e.*a branch of 0.1 substitutions per site would use a PAM10 matrix:
where *p*~*i*~is the probability of amino acid *i*at residue *r*of node *n*, *p*~*ijX*1~and *p*~*ijX*2~are the probabilities of substitution from amino acid *i*to each amino acid *j*in the appropriate PAM matrix for the two descendant branches, *p*~*dj*1~and *p*~*dj*2~are the probabilities of amino acid *j*being at position *r*at the two descendant nodes.
Once the root is reached, the most probable amino acid is fixed as the ancestral sequence. As with gaps, GASP then works back up the tree, using the fixed ancestral node amino acid and the descendant node probabilities to give new probabilities for each amino acid. The most probable amino acid is then fixed and the process continues until all residues and all nodes have a fixed sequence.
GASP is primarily designed for reasonably small trees (6--30 sequences), although there is no limit on input tree size. For larger trees, probabilities for each amino acid get very small near the root, which can lead to a heavy bias towards the fixed ancestral amino acid when GASP works back up the tree. To counter this GASP arbitrarily reduces any probabilities below a certain exclusion threshold (0.05 by default) to zero, thus reducing the slow accumulation of very unlikely amino acids.
### Variations
To optimise the PAM matrices used for probability calculations, GASP uses the variable branch lengths read from the input phylogeny. There is also an option to fix the PAM distance used for all branches, which would allow the use of trees without branch lengths.
Assignment of ancestral amino acids with the GASP algorithm is achieved by combining data from the descendants of a given node *n*and its direct ancestor *n*~0~. This ancestor itself is heavily influenced by the descendants of *n*but also by the \'outgroup\' to *n*, namely those sequences that are descendant to *n*~0~but not to *n*. The outgroup information contained by the ancestral node *n*~0~can be vital in determining the correct sequence for *n*when the descendants of *n*are variable. For this reason, the GASP algorithm will, by default, fix ancestral sequences as it moves back \'up\' the tree from the root, increasing the relative weighting of the outgroup to the two descendants. Because there is a chance of the wrong amino acid sweeping back up the tree (especially if rare amino acid probabilities are allowed to accumulate by reducing the exclusion threshold), there is an option to use amino acid probabilities from the ancestral node in the last stage of GASP rather than giving the fixed amino acid an ancestral probability of 1. This option should be used with caution.
Simulated datasets
------------------
### Basic trees
To test the GASP algorithm, a number of artificial phylogenies were simulated. Because there is a practically limitless number of possible tree sizes (in both numbers of sequences and branch lengths) and phylogenies, it was decided to test the algorithm on a set of simulated phylogenies based on real phylogenies that formed a subset of those for which the algorithm was originally written. This set comprised 94 neighbour-joining trees of protein families. Each tree contained at least two subfamilies of at least 3 members each, giving in total between 6 and 127 sequences. (The program used to generate these simulated phylogenies is also available from the author for testing the algorithm on a different set of trees.)
Simulations started by creating a random protein sequence 100 amino acids long. Each residue was assigned an amino acid randomly as determined by the amino acid frequencies in all the human sequences of SwissProt-TrEMBL (Release 42) \[[@B13]\]. Sequences then evolved according to the template phylogeny. For each branch, residues were randomly substituted as described below until the total number of observed changes (ignoring multiple hits) equalled or exceeded the branch length of the phylogeny, which was not corrected for multiple hits. At this point, a new node was created with the new sequence and the tree split into two descendants. This proceeded until the whole phylogeny had been reconstructed. Each template tree seeded ten randomly simulated datasets. Algorithms were then given as input the simulated alignment and the parent phylogeny with \'real\' branch lengths as calculated during simulation. (Note that PAML does not use these branch lengths.)
### Substitution methods
Three substitution methods were used. In the first \'PAM Equal Rates\' model, the PAM1 matrix of Jones *et al.*1992 \[[@B11]\] was used, giving variable rates of evolution for different amino acids and different substitution likelihoods. For comparison, a purely random substitution matrix was used where every amino acid had an equal probability of evolving into every other amino acid (the \'Random Equal Rates\' method). Under these methods, different residues have similar rates of evolution. A further model was used based on the PAM1 method where residues had different probabilities of evolving, before amino acid-dependent PAM effects are considered. Under this \'PAM Variable Rates\' model, 40% sites evolved at the \'normal\' rate, 20% half-rate, 20% double rate, and 20% almost fixed (1/50 rate). Note that the observed branch lengths remain the same as the normal \'PAM Equal Rates\' method but highly variable sites will be more likely to have multiple substitutions under the \'PAM Variable Rates\' method.
### Gapped data
Because one of the main advantages of GASP is its ability to deal with gaps, a second test dataset was generated from the \'PAM Equal Rates\' set of trees, this time with gaps added. The addition of gaps was kept simple so that the exact same trees could be used for the gap analysis, allowing direct comparison of the results with gaps and without. (See Testing the GASP Algorithm, below.) To do this, gaps were limited to single insertion/deletion (\'indel\') events per column of the MSA, allowing them to overlay onto the existing simulated \'PAM Equal Rates\' data. In addition, no indels occurring next to root were allowed as it is impossible to judge without an outgroup whether such an event would be an insertion or deletion.
To make the gaps, each residue *r*of the simulated sequences was considered in turn and had a probability of 50% of containing an indel. Gaps were all of length 1 (although two gaps may fall side by side, by chance). Although unrealistic for testing multiple alignment or phylogeny reconstruction programs, such a simplification is not a problem for ancestral sequence prediction as each residue is treated independently. The short gaps meant that, for the same total number of gapped residues, there is a higher diversity in the phylogenetic positioning of the indels.
Indels were placed randomly with respect to evolutionary time. Each node in the simulated data has an \'age\', which is the number of rounds of potential substitution it took to complete the simulation after that node was formed. Each indel occurs at a random age *T*between the tip (age 0) and the oldest direct descendant node from the root. A random branch (not leading to root) is then selected for which the ancestral node is older than *T*and the descendant node is no older. This is the branch on which the indel occurred. The indel is randomly assigned as an insertion or deletion event with equal probability. If it is an insertion then the ancestral node plus all nodes outside the descendant clade have residue *r*replaced with a gap. If it is a deletion then the descendant node and all its descendants have residue *r*replaced with a gap.
Results and discussion
======================
Testing the GASP algorithm
--------------------------
The simulated trees and alignments were run through the GASP algorithm. Because the \'real\' sequence of each simulated node was known, it was then possible to determine the accuracy of GASP predictions. To test the different parts of the GASP algorithm, predictions were also made using modified GASP algorithms with parts of the model excluded.
Because prediction for invariant sites is trivial for all methods, the expectation is that accuracy is inversely related to the number of variable sites. Therefore, comparisons of methods are presented as a percentage of the variable sites. In this context \'variable sites\' are defined independently for each node as those sites for which not all descendant nodes (including termini) have the same sequence as the ancestral node.
The simulated phylogenies are of different sizes. Considering all nodes of all trees would bias results towards the larger trees. To avoid this, each tree was arbitrarily reduced to four representative nodes:
1\. \'Root\' = The root of the tree.
2\. \'Near Root\' = A direct descendant node of the root.
3\. \'Mid Tree\' = A random node approx. midway in the tree.
4\. \'Near Tip\' = A direct ancestral node of a terminal sequence.
To determine whether the GASP algorithm was useful its performance was compared to a crude consensus sequence at each node. Where two amino acids were present at equal frequencies in a column of the MSA, the most frequent amino acid in the total MSA was selected for the ancestral sequence. GASP may be considered crude compared to some existing Maximum Likelihood approaches and so its performance was also compared to that of both ML algorithms implemented by the CODEML program from the PAML package \[[@B5]\], namely the marginal reconstruction algorithm of Yang *et al.*1995 \[[@B6]\] and the joint reconstruction algorithm of Pupko *et al.*2000 \[[@B7]\]. In addition, the MP method implemented in the PAMP program of PAML \[[@B9]\] was also tested for comparison.
The GASP model marginally out-performs all methods tested for constructing the ancestral sequence at the root of the tree (Figure [2](#F2){ref-type="fig"}). For all other representative node groups of the tree, GASP is comparable to the MP algorithm of PAMP but slightly inferior to both ML algorithms implemented in CODEML. PAMP is inferior to the ML methods at all levels of the tree. (In our hands, CODEML crashed in nearly 8% of cases. The problem was consistent and the troublesome input files crashed CODEML every time. However, there was no obvious difference between input files that presented CODEML with troubles and those that did not (Data not shown). To make a fair comparison of algorithms, data is only shown for datasets that did not cause CODEML to crash.)
Although the ML algorithms of Yang *et al*. 1995 and Pupko *et al*. 2000 performed better overall for internal nodes, this difference was not seen for every node of every tree. At each level, GASP is sometimes better and sometimes worse than all three other algorithms (Figure [3](#F3){ref-type="fig"}). This is also true when comparing the three other algorithms with each other (Data not shown).
GASP variants
-------------
Four individual elements of the GASP algorithm were explicitly tested by disabling each in turn and comparing the results to those generated by the complete algorithm. The four variants run were:
\(a) using fixed PAM matrices rather than matrices derived from observed tree branch lengths.
\(b) fixing ancestral sequences on initial pass towards root without a second pass back up the tree.
\(c) no filtering of rare amino acid probabilities.
\(d) using ancestral probabilities when working back up the tree rather than fixed ancestral amino acids.
Elements (a) and (b) were chosen for testing because they increase computational time, while (c) and (d) may not intuitively give the best results.
For the phylogenies used in these simulations, all four variants performed worse than the standard GASP algorithm (data not shown). Using a fixed PAM distance for all branches rather than approximating the PAM distance using tree branch lengths (a) gives an unfair weighting to long branches and thus increases the probability of substitutions that are, in reality, unlikely. Fixing ancestral sequences on the way \'down\' the tree to the root (b) does not use any outgroup information and is therefore significantly worse at distinguishing between two or more amino acids with similar ancestral probabilities. Less intuitive is the effect of reducing low amino acid probabilities to zero (c) and using fixed ancestral sequences when recalculating amino acid probabilities using all three connected nodes (d). Indeed, excluding these two elements have a much smaller effect but still reduce the overall accuracy of the algorithm (data not shown).
Using fixed amino acids when working back up the tree increases the influence of the outgroup sequence. As was seen by the difference in accuracy between predictions at the root and nodes near the root (Figure [2](#F2){ref-type="fig"}), outgroup information is very important in predicting the correct sequence. (Predictions at the root are considerably weaker because there is no outgroup to help discriminate between alternative ancestral states.) Filtering out rare amino acids has a small effect in these trees but would be expected to have a larger effect in deeper trees. If rare probabilities are not removed then the most likely amino acid in each position will have an ever-diminishing likelihood, while highly unlikely ancestral sequences will find their probabilities ever-increasing. In very deep trees, this could result in probabilities being homogenised in the deep nodes. When fixed ancestral sequences are used to make predictions back up the tree, the fixed ancestral amino acid would potentially swamp the reduced probabilities in descendant nodes near the root, and sweep the root amino acid up the tree incorrectly. If this filtering is turned off when using larger trees, it is recommended that ancestral node probabilities be used instead of fixed ancestral sequences (*i.e.*combining (c) and (d)).
A final test was performed to compare the use of \'real\' versus \'observed\' branch lengths. (This was possible because the simulations kept track of not only what changes really occurred but also how many were \'visible\', *i.e.*not correcting for multiple substitutions.) This is not testing the GASP algorithm *per se*but does provide information on the importance of using an accurate phylogeny construction algorithm. (The PAML package does not require pre-defined branch lengths and is therefore only affected by errors in supplied topology and not in branch lengths.) In many cases there was no difference. However, nearer to the root, using observed branch lengths rather than the real ones decreased prediction accuracy slightly. This decrease was correlated with total tree age (data not shown). This would imply that branch lengths corrected for multiple substitutions should be used for trees fed into the GASP algorithm, particularly with deep trees containing long branches.
Gapped data
-----------
A central part of the GASP algorithm is its ability to handle gapped alignments. As expected, GASP correctly placed 100% of simple gaps used in this test. (Each column of the alignment has a maximum of one indel, which is descendant of the root branches.) To analyse the effect of gaps on prediction accuracy, pairwise comparisons were made between the gapped datasets and the corresponding ungapped simulations (Figure [4](#F4){ref-type="fig"}). As would be expected, some of the gapped data shows reduced prediction accuracy because, as with the root of the tree, there is no \'outgroup\' information directly following an insertion event. In many situations, however, accuracy is increased. This is because a gap is easier to predict accurately (having only two states, present or absent) than an amino acid (which could be one of twenty). The Consensus method shows a similar pattern but with a smaller fraction of trees showing an increase in accuracy (Data not shown).
DNA data
--------
Although explicitly designed for use with protein sequence alignments and trees, it is relatively simple to convert GASP for use with nucleotide datasets. To do this, a new \'PAM matrix\' should be created with substitutions probabilities for A, C, G and T only. This structure would allow the user to fit fairly complex substitution models, with different substitution probabilities for each pair of nucleotides. If the aligned sequence is coding DNA, however, it is highly recommended to use the protein sequences or a different algorithm such as those in the PAML package \[[@B5]\], as the adjusted PAM matrix would not take any consideration of codon positions.
Conclusions
===========
We have presented an algorithm for predicting ancestral sequences in gapped datasets. At the root of the tree, GASP marginally outperforms three existing algorithms implemented in the PAML package. For other nodes of the tree, however, the ML algorithms of CODEML \[[@B5]-[@B7]\] generally perform better than GASP, while PAMP \[[@B9]\] gives a similar performance. The main advantage of GASP is its ability to use gapped datasets. Simple indel patterns are accurately predicted by GASP and do not greatly decrease ancestral sequence prediction accuracy. The GASP algorithm can be reliably run on either Windows or UNIX platforms with no discernable instability.
For real life datasets, as for all evolutionary studies, predictions are dependent on the quality of input alignments. Gapped residues are, by their nature, often located in regions of evolutionary instability and therefore the interpretations of predictions at such sites require extra care. In many scenarios, however, gaps are introduced into alignments by the missing termini of fragment sequences. In these situations, the complete sequences that form the rest of the alignment may be very well aligned and so it is highly desirable to have an algorithm that can process the gaps introduced by the truncated sequences.
Availability and requirements
=============================
**Project name:**GASP (Gapped Ancestral Sequence Prediction)
**Project home page:**<http://bioinformatics.rcsi.ie/~redwards/gasp/>
**Operating system(s):**Platform Independent. (Tested on PC (Windows 98/XP) and UNIX (Red Hat Linux 7.3))
**Programming language:**Perl.
**Other requirements:**None.
**License:**None.
**Any restrictions to use by non-academics:**Author\'s permission required.
List of abbreviations
=====================
**GASP.**Gapped Ancestral Sequence Prediction.
**Indel.**Insertion or deletion event.
**ML.**Maximum Likelihood.
**MP.**Maximum Parsimony.
**MSA.**Multiple Sequence Alignment.
**PAM.**Point Accepted Mutation.
Authors\' contributions
=======================
RE conceived the algorithm, coded the Perl script, designed and performed the accuracy tests and statistical analyses, designed the phylogeny simulation method, generated the simulated datasets and drafted the manuscript. DS helped in the design of test simulations and in drafting the manuscript.
Acknowledgements
================
The authors would like to thank K Johnston and S Park for helpful comments during the drafting of the manuscript.
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
**Sample output from GASP.(a)**The first 100 columns of a typical GASP ancestral sequence prediction output. Sequence order matches the default vertical ordering in the tree files produced by GASP. **(b)**A rooted version of the input tree. Lengths of branches are those defined in the input file. **(c)**A new version of the input tree with nodes labelled and branch lengths recalculated based on ancestral sequence prediction. **Note.**Data is output in (a) fasta format and (b & c) Newick format but for visual clarity the file has been shown using (a) BioEdit \[14\] and (b & c) TreeExporer \[12\].
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
**Mean accuracies of methods using the \'PAM Variable Rates\' Model.**Error Bars are Standard Errors. Percentage Accuracies are calculated for variable sites only (see text for details). The Percentage Accuracy for all sites is higher in all cases (Data not shown). The \'PAM Equal Rates\' and \'Random Equal Rates\' Models gave very similar results (Data Not Shown). Data shown includes only those phylogenies that did not crash CODEML (see text).
:::
:::
::: {#F3 .fig}
Figure 3
::: {.caption}
######
**Difference in prediction accuracies between GASP and three alternative algorithms.(a)**Yang *et al.*1995 ML \[6\], **(b)**Pupko *et al.*2000 \[7\] and **(c)**PAMP \[9\]. Percentage Accuracies are calculated for variable sites only and only those phylogenies that did not crash CODEML are shown (see text for details). Positive values indicate GASP is better than the other algorithm and negative values the reverse. Results for each tree depth are calculated separately. Values shown are for \'PAM Variable Rates\' simulations only but the other evolutionary models give very similar results (Data not shown).
:::
:::
::: {#F4 .fig}
Figure 4
::: {.caption}
######
**Difference in GASP prediction accuracies of methods using gapped and ungapped \'PAM Equal Rates\' simulations.**Percentage Accuracies are calculated for variable sites only (see text for details). Positive figures indicate that accuracies for the gapped dataset are higher than for the corresponding ungapped dataset. Results for each tree depth are calculated separately.
:::
:::
|
PubMed Central
|
2024-06-05T03:55:47.835721
|
2004-9-6
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517926/",
"journal": "BMC Bioinformatics. 2004 Sep 6; 5:123",
"authors": [
{
"first": "Richard J",
"last": "Edwards"
},
{
"first": "Denis C",
"last": "Shields"
}
]
}
|
PMC517927
|
Background
==========
Most proteins can be grouped, on the basis of similarities in their amino acid sequences, into a limited number of protein families. Proteins or protein domains that belong to a particular family usually share functional attributes and are derived from a common ancestor. Highly conserved sequences in protein families are generally important for the function of a protein and/or for the maintenance of its 3-dimensional structure. Within the last decade, the sensitivity of sequence searching techniques has been improved by profile or motif-based analysis, which uses information derived from multiple sequence alignments to construct and search for sequence patterns \[[@B1]-[@B4]\]. By studying constant and variable properties of such groups, a signature for a protein family or domain can be derived which distinguishes its members from all other unrelated proteins. The problem of fast exact and approximate searching for a pattern that contains classes of characters and bounded size gaps (CBG) in a text has a wide range of applications, among which a very important one is protein pattern matching \[[@B5]\]. Unlike single-sequence similarity, a profile or motif can exploit additional information, such as the position and identity of residues that are conserved throughout the family, as well as variable insertion and deletion probabilities \[[@B6]\]. These signatures can be used to assign a newly sequenced protein to a specific family to formulate hypotheses about its function.
By doing a keyword search, the protein sequences mined out from different databases is highly varied owing to different levels of redundancy. This could be due to the different strengths and weaknesses underlying the analysis algorithms used in different databases. The usage of the broad range signatures existing in databases, for the retrieval of blue copper proteins like the type 1 copper blue, multiple copper oxidase, cyt b/b6, photosystem 1 psaA&B, psaG&K, and reiske iron sulphur protein brings out different kinds of copper proteins and a lot more of unrelated proteins. A search once again becomes necessary for sorting out the required blue copper proteins. The usage of pattern database would be more selective as it can identify family members based on the conserved functional region patterns. Keeping these broad spectrum signatures in mind, more specific and targeted protein signatures for each of the blue copper proteins was designed. The diagnostic success of these specified signatures over the wide range signatures mentioned lies in the number of true positives picked over the minimal or nil false positives picked from the non redundant databases.
Blue copper proteins, which are also known as cupredoxins, are small, soluble proteins (10 -- 14 kDa) whose active site contains a type 1-copper \[[@B7]\]. All these type 1 blue copper proteins possess an eight stranded Greek key beta barrel or beta sandwich fold and have a highly conserved active site architecture. The type 1 blue copper proteins exert their function by shuttling electrons from a protein acting as an electron donor, to another acting as an electron acceptor in various biological systems such as bacterial and plant photosynthesis \[[@B8],[@B9]\]. During the electron transfer process, the copper ion changes from a diamagnetic Cu(I) to a paramagnetic Cu(II), oxidation state \[[@B10]\]. The coordination of the copper is determined by the conformation of its three closest ligands, two histidine nitrogens and a cysteine sulfur and of a fourth more distant ligand a methionine sulphur \[[@B11]\]. The coordination sphere of copper ions in blue copper protein rusticyanin is shown for example in Figure [1](#F1){ref-type="fig"}. Type 1 copper sites are characterized by an intense blue color due to copper bound to thiolate \[[@B12]\]. An absorption is seen at 600 nm and gives rise to an unusual EPR signal, arising from asymmetrical copper site. Most of the cupredoxins have similar redox potentials ranging from 260 to 375 mV and function at pH values ranging from 6 to 8 \[[@B9]\]. Rusticyanin is an exception in having a very high redox potential of 680 mV \[[@B13]\].
The use of active site patterns or signatures is very rapidly becoming one of the essential tools of sequence analysis \[[@B14],[@B15]\]. Although there is an appreciable amount of divergence in the sequences of the different blue copper proteins, the copper ligand sites are conserved. Direct application of the functionally specified signatures in databases, would help in quick retrieval of protein sequences related to that signature. The protein sequences thus retrieved were found to be highly specific to a particular blue copper protein. These signatures being highly specific allow the efficient mining out of uncharacterized proteins from the vast sequences deposited in different databases.
Results
=======
Differentiation of blue copper proteins based on source of origin and active site tabulation
--------------------------------------------------------------------------------------------
The eukaryotic blue copper proteins chosen for the study were plantacyanin, plastocyanin, cucumber basic protein, stellacyanin, umecyanin, uclacyanin, and cusacyanin. The prokaryotic blue copper proteins were rusticyanin, sulfocyanin, halocyanin, azurin, pseudoazurin, auracyanin, amicyanin and blue nitrite reductase. Plastocyanins are found both in eukaryotes and prokaryotes. Table [1](#T1){ref-type="table"} and [2](#T2){ref-type="table"} describe the active site functional region for each of the blue copper proteins mentioned above. The active site functional region indicates the aminoacids in the respective blue copper proteins bound to the copper atom. For example in plantacyanin with the protein data bank id 1F56, histidine at the 34^th^position, cysteine at the 74^th^position, histidine at 79^th^position and methionine at the 74^th^position are bound to the copper atom involved in electron transport chain.
Keyword search for the specified blue copper proteins in different databases
----------------------------------------------------------------------------
The number of sequences retrieved for a protein from different databases by keyword search are tabulated in Table [3](#T3){ref-type="table"}. As seen from Table [3](#T3){ref-type="table"}, a keyword search is no longer effective and precise in retrieving sequences of a particular kind. If still used, it is only a time consuming process, as the particular protein of interest has to be filtered from the retrieved sequences once again. For example, a varied response of data output is seen on a keyword search for plastocyanin. The sequences retrieved from each of the database in terms of number of protein sequences is 901 sequences in NCBI, 41 sequences in SwissProt, 10 sequences in TrEMBL, 350 sequences in Protein Information Resource, 375 sequences in EMBL, and 41 sequences in PDB.
A search for the existing signatures for the blue copper proteins
-----------------------------------------------------------------
The signatures already available for each of the blue copper proteins retrieved from the Prosite motif database are listed in Table [4](#T4){ref-type="table"}. The number of protein sequences retrieved in response to the input of the already existing signatures for blue copper proteins in the PIR nREF database is shown in Table [5](#T5){ref-type="table"}. An overview of the results in Table [4](#T4){ref-type="table"} indicates that most of the blue copper proteins have a type 1 blue copper signature with an id PS00196. The multiple copper oxidase signature present in rusticyanin as shown in Table [4](#T4){ref-type="table"} with id PS00079 and PS00080 retrieves out 799 and 366 sequences respectively as shown in Table [5](#T5){ref-type="table"}. The existing rusticyanin sequences are very few in actual number and hence a secondary search becomes necessary. Even if the signature has annotated an unknown protein such as rusticyanin, it has to be searched amongst the 779 and 366 sequences retrieved. From Table [4](#T4){ref-type="table"} it is seen that plastocyanin has cyt b-heme (PS00192), cyt b QO(PS00193), photosystem1 PSAAB (PS00419), photosystem1 PSAGK(PS01026), Reiske 1 (PS00199) and Reiske 11(PS00200) as the signatures. As the names of the signatures suggest they are highly broad spectrum. The number of sequences picked out by these signatures as shown in Table [5](#T5){ref-type="table"} clearly indicates that most of these signatures are picking a lot more of other sequences other than plastocyanin and some of the signatures are missing out some plastocyanin sequences.
Designing functional protein signatures for the different blue copper proteins
------------------------------------------------------------------------------
As shown in \'Appendix 1 \[see [Additional file 1](#S1){ref-type="supplementary-material"}\]\' the newly designed signatures and peptides based on the ClustalW results for plastocyanin sequences of both eukaryotic and prokaryotic origin are shown in Table [6](#T6){ref-type="table"}. The same procedure as shown in Appendix 1 \[see [Additional file 1](#S1){ref-type="supplementary-material"}\] was followed for the other blue copper proteins and the newly designed signatures and peptides based on the ClustalW results are shown in Table [6](#T6){ref-type="table"}. The new signatures and peptides thus designed for the different blue copper proteins, picked out highly specific sequences from the PIR nREF database consisting of sequences from the PIR \[282,987 sequences\], SwissProt \[146,720 sequences\], TrEMBL \[1,069,649 sequences\], GenPept \[1,724,186 sequences\], Ref Seq \[756,736 sequences\] and PDB \[24,863 sequences\]. The number of sequences retrieved based on the new signature for each of the blue copper protein is shown in Table [6](#T6){ref-type="table"}.
Discussion
==========
The members of a protein family can be identified by collecting the matching sequences to profile or motif databases. Protein signatures are sequence motifs diagnostic to a protein family indicating function. Signatures are matched to protein sequences in the non redundant databases and is scored using a dynamic programming algorithm which permits permeability in gap distance and residue type \[[@B16]\]. Generating a signature involves identifying residues in a protein sequence that imparts functional properties to the protein. Protein signatures are efficient miners of related protein sequences having the same functional residues, which belong to the same class of proteins from the abundant sequences present in the non redundant databases. All the copper ions in the living cells are protein bound, as it is toxic in its free form. In most copper proteins, the copper ion having the ability to change valence state is mainly involved in catalysis of biological process, or the transport of electrons different proteins in a cell. Blue copper proteins also known as cupredoxins, have a type I copper site. They possess a single copper functional domain. The coordination of copper in most of the blue copper proteins is determined by the conformation of its three closest ligands, two histidine nitrogens and a cysteine sulfur and of a fourth more distant ligand a methionine sulfur \[[@B11]\]. In the case of auracyanin, stellacyanin and umecyanin the methionine is substituted by a glutamine residue, which binds as the fourth ligand to the copper atom.
By doing a keyword search, we get varied results from the different databases as indicated in Table [3](#T3){ref-type="table"} owing to different levels of redundancy. On using a functionally related protein signature only relevant related sequences are picked out from the non redundant database as seen from Table [6](#T6){ref-type="table"}. Thus protein signatures can play a great role in extracting out highly related sequences from different databases than keyword searches. The signatures already available for the blue copper proteins like the Cyt b/b6, Photosystem 1 PSAGK, Rieske Iron Sulfur protein, and type I copper blue signatures are broad spectrum signatures. PS00196 a type I blue copper signature which is an already existing signature, when fed in the PIR nREF database has picked out 589 sequences as indicated in the result in Table [5](#T5){ref-type="table"}. We have also ensured that the active site region involving amino acids bound to the copper atom is present in all our signatures. Protein signatures designed taking into account the active site region will be very efficient for annotation of uncharacterized proteins. In one study the authors have used metal binding patterns of metalloproteins present in Protein Data Bank to search gene banks for new metalloproteins \[[@B17]\].
The protein signatures in a way can be compared to primers used for amplification. The more specific and concise a primer, the more specific is the amplification, similarly more specific the protein signature more significant are the picks from the non redundant databases. Specific signatures in a way reduce the time taken to pool related sequences from the abundantly available sequences from the non redundant databases. For example as shown in Table [4](#T4){ref-type="table"} the Type 1 blue copper signature is present in plantacyanin, stellacyanin, umecyanin, cusacyanin, halocyanin, azurin, auracyanin and nitrite reductase amongst the sixteen different blue copper proteins. When this signature is used as a query in the Prosite database even if an unknown protein is annotated it can only be as a type 1 blue copper protein, but it cannot classify it as a particular blue copper protein. The newly designed signatures or peptides will help in classifying the uncharacterized protein to the exact subtype of blue copper proteins. In this study, we have assigned functional property based signatures, which have the amino acid residues binding to the copper atom. It may be concluded that we have been successful in designing functionally related protein signatures for the blue copper proteins.
Conclusions
===========
Signatures designed around the functionally important regions of a protein are valuable for annotation. In this study, specific signatures were designed around the active site regions of each of the blue copper proteins plantacyanin, plastocyanin, uclacyanin, stellacyanin, rusticyanin, sulfocyanin, amicyanin, halocyanin, pseudoazurin, azurin and nitrite reductase. These will be very useful for annotating uncharacterized proteins as blue copper proteins. Further, because of their high specificity to each subclass, they can be used in classifying the various subtypes of blue copper proteins.
Methods
=======
Differentiation of blue copper proteins based on source of origin and active site tabulation
--------------------------------------------------------------------------------------------
The blue copper proteins were distinguished based on the source of origin as prokaryotic and eukaryotic. The active site residues of the eukaryotic and prokaryotic blue copper proteins, which bind the copper metal atom, were identified from the Protein Data Bank and tabulated.
Keyword search for the specified blue copper proteins in different databases
----------------------------------------------------------------------------
The name of each of the blue copper protein was given as a query in the keyword searches at NCBI, SwissProt, TrEMBL, PIR, EMBL and PDB databases to check for the number of sequences retrieved from each database and the results were tabulated.
A search for the existing signatures for the blue copper proteins
-----------------------------------------------------------------
The signatures already existing for each of these blue copper proteins were identified from the Prosite motif database and tabulated. These already existing signatures were used as query patterns in the PIR Motif/Peptide match and a search was made against the PIR-nREF database. The PIR-nREF database consists of sequences from the PIR \[282,987 sequences\], SwissProt \[146,720 sequences\], TrEMBL \[1,069,649 sequences\], GenPept \[1,724,186 sequences\], Ref Seq \[756,736 sequences\] and PDB \[24,863 sequences\]. The number of protein sequences matching the query (already existing signatures for the blue copper proteins) was retrieved and the query results were tabulated.
Designing functional protein signatures for the different blue copper proteins
------------------------------------------------------------------------------
Each of the blue copper proteins from different sources were chosen from the different sequence databases and aligned using the multiple sequence alignment tool ClustalW. Conserved regions, which include the amino acids bound to the copper, reflecting the active site imparting a vital biological role of electron transport were chosen to design signatures. In regions showing 100% conserved sequences they were identified as conserved peptides. An example of how the functional protein signatures were designed is shown for plastocyanin in Appendix 1 \[see [Additional file 1](#S1){ref-type="supplementary-material"}\]. The signatures and peptides were then submitted to the Protein Information Resource \[PIR nREF\] database for the protein pattern and peptide match and the results were tabulated.
Authors\' Contributions
=======================
PG, AVG and SA participated in the design and coordination of the study. AVG carried out the bioinformatics search, the designing of the signatures and drafted the manuscript. PG and SA read and approved the final manuscript.
Supplementary Material
======================
::: {.caption}
###### Additional File 1
Designing protein signatures: Illustrated example Plastocyanin. Plastocyanin sequences of eukaryotic and prokaryotic origin were retrieved from the PDB and SwissProt databases. The eukaryotic sequences were subjected to a ClustalW multiple sequence alignment. Signatures were designed based on the conserved pattern around the active site region \[copper binding to four amino acids in plastocyanin\]. The same procedure was adopted for plastocyanin sequences of prokaryotic origin. The newly designed signatures were used as queries in the Pattern/peptide match search at the PIR database \[Protein Information Resource\]. The numbers of plastocyanin sequences retrieved are tabulated in Table 6. The results were compared with the already existing signatures for plastocyanins and the number of sequences that these signatures picked up from the PIR database \[data shown in Table 4 & 5\].
:::
::: {.caption}
######
Click here for file
:::
Acknowledgements
================
AVG thanks Council of Scientific and Industrial Research for a senior research fellowship. PG thanks the University Grants Commission, New Delhi for the financial support to carry out the study. PG also thanks BTIS for the facilities rendered.
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
a\) Rusticyanin bound to the copper atom as indicated by the blue colored ball. b) Copper binding active site of rusticyanin showing the four active site residues: Histidine at 85^th^position, Histidine at 143^rd^position, Cysteine at 138^th^position and Methionine at 148^th^position
:::
:::
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Amino acids bound to the copper atom of the blue copper proteins of eukaryotic origin. Plastocyanins are also found in prokaryotes. The \* indicates that crystal structures are as yet not available.
:::
**S. NO:** **PROTEIN NAME** **METAL BINDING ACTIVE SITES**
------------ ---------------------------------- -------------------------------- -------- -------- --------
1 PLANTACYANIN PDB: 1F56 34 HIS 74CYS 79 HIS 84 MET
2 PLASTOCYANIN PDB: 1AG6 37 HIS 84 CYS 87 HIS 92 MET
3 CUCUMBER BASIC PROTEIN PDB: 2CBP 39 HIS 79 CYS 84 HIS 89 MET
4 STELLACYANIN1JER 46 HIS 89 CYS 94 HIS 99 GLN
5 DICYANIN \* \* \* \*
6 UMECYANIN P42849 44 HIS 85 CYS 90 HIS 95 GLN
7 UCLACYANIN \* \* \* \*
8 CUSACYANIN P00303 39 HIS 79 CYS 84 HIS 89 MET
:::
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Amino acids bound to the copper atom of the blue copper proteins of prokaryotic origin.
:::
**S. NO:** **PROTEIN NAME** **METAL BINDING ACTIVE SITES**
------------ ----------------------------- -------------------------------- --------- --------- ---------
1 RUSTICYANIN PDB: 1A8Z 85 HIS 138 CYS 143 HIS 148 MET
2 SULFOCYANIN Q53765 110 HIS 171 CYS 176 HIS 181 MET
3 HALOCYANIN P39442 110 HIS 148 CYS 151 HIS 156 MET
4 AZURIN PDB: 1DYZ 46 HIS 112 CYS 117 HIS 121 MET
5 PSEUDOAZURIN PDB: 1ADW 40 HIS 78 CYS 81 HIS 86 MET
6 AURACYANIN PDB: 1QHQ 57 HIS 122 CYS 127 HIS 132 GLN
7 AMICYANIN PDB: 1AAC 53 HIS 92 CYS 95 HIS 98 MET
8 NITRITE REDUCTASE PDB: 1AS6 95 HIS 136 CYS 145 HIS 150 MET
:::
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Number of retrieved protein sequences from different databases on a keyword search
:::
**S. NO:** **PROTEIN** **NCBI** **SWISS PROT** **TrEMBL** **PIR** **EMBL** **PDB**
------------ ------------------------ ---------- ---------------- ------------ --------- ---------- ---------
1 PLANTACYANIN 18 1 4 10 9 2
2 PLASTOCYANIN 988 41 22 463 397 40
3 CUCUMBER BASIC PROTEIN 6 1 \* \* 4 1
4 STELLACYANIN 26 3 3 33 12 2
5 UMECYANIN 4 1 \* 1 1 \*
6 UCLACYANIN 23 1 5 9 9 \*
7 CUSACYANIN 2 1 \* 1 1 1
8 DICYANIN 1 \* 1 1 1 \*
9 RUSTICYANIN 52 2 8 22 25 7
10 SULFOCYANIN 14 1 5 6 6 \*
11 HALOCYANIN 15 1 4 7 5 \*
12 AZURIN 320 22 23 202 66 49
13 PSEUDOAZURIN 68 6 4 25 22 16
14 AURACYANIN 10 1 2 5 3 2
15 AMICYANIN 105 3 3 34 34 10
16 NITRITE REDUCTASE 1744 37 735 1027 1017 69
:::
::: {#T4 .table-wrap}
Table 4
::: {.caption}
######
Already existing signatures present in the Prosite motif database for the blue copper proteins
:::
**S. NO:** **PROTEIN** **PDOCOO-NO:** **PROSITE** **SIGNATURE**
------------ ------------------------ --------------------------------------- ---------------------------------------- --------------------------------------------------------------------------------------------
1 PLANTACYANIN PDOC00174 TYPE-1 COPPER BLUE 1\. PS00196 \[GA\]-x(0,2)-\[YSA\]-x(0,1)-\[VFY\]-x-\[C\]-x(1,2)-\[PG\]-x(0,1)-\[H\]-x(2,4)-\[MQ\]
2 PLASTOCYANIN PDOC00171 Cyt b/b6 1\. PS00192 -- Cyt b Heme \[DENQ\]-x(3)-\[G\]-\[FYMWQ\]-x-\[LIVMF\]-\[R\]-x(2)-H
2\. PS00193 -- Cyt b QO \[P\]-\[DE\]-\[W\]-\[FY\]-\[LFY\](2)
PDOC00347 Photosystem 1 psaA and psaB 1\. PS00419 -- Photosystem 1 PSAAB CDGPGRGGTC
PDOC00786 Photosystem 1 psaG and psaK 1\. PS01026 -- Photosystem 1 PSAGK \[GT\]-\[F\]-x-\[LIVM\]-x-\[DEA\]-x(2)-\[GA\]-x-\[GTA\]-\[STA\]-x-\[GH\]-x-\[LIVM\]-\[GA\]
PDOC00177 Reiske-Iron Sulfur 1\. PS00199 -- Reiske 1 \[C\]-\[TK\]-\[H\]-\[L\]-\[G\]-\[C\]-\[LIVST\]
2\. PS00200 -- Reiske 11 \[C\]-\[P\]-\[C\]-\[H\]-x-\[GSA\]
3 CUCUMBER BASIC PROTEIN \* \* \*
4 STELLACYANIN PDOC00174 Type 1 Blue Copper 1\. PS00196 \[GA\]-x(0,2)-\[YSA\]-x(0,1)-\[VFY\]-x-\[C\]-x(1,2)-\[PG\]-x(0,1)-\[H\]-x(2,4)-\[MQ\]
5 UMECYANIN PDOC00174 Type 1 Blue Copper 1\. PS00196 \[GA\]-x(0,2)-\[YSA\]-x(0,1)-\[VFY\]-x-\[C\]-x(1,2)-\[PG\]-x(0,1)-\[H\]-x(2,4)-\[MQ\]
6 UCLACYANIN \* \* \*
7 CUSACYANIN PDOC00174 Type 1 Blue Copper 1\. PS00196 \[GA\]-x(0,2)-\[YSA\]-x(0,1)-\[VFY\]-x-\[C\]-x(1,2)-\[PG\]-x(0,1)-\[H\]-x(2,4)-\[MQ\]
8 DICYANIN \* \* \*
9 RUSTICYANIN PDOC00076 Multiple Copper Oxidase 1\. PS00079 -- Copper Oxidase \[G\]-x-\[FYW\]-x(LIVMFYW)-x-\[CST\]-x(8)-\[G\]-\[LM\]-x(3)-\[LIVMFYW\]
2\. PS00080 -- Multiple Copper Oxidase \[H\]-\[C\]-\[H\]-x(3)-\[H\]-x(3)-\[AG\]-\[LM\]
10 SULFOCYANIN \* \* \*
11 HALOCYANIN PDOC00174 Type 1 Blue Copper 1\. PS00196 \[GA\]-x(0,2)-\[YSA\]-x(0,1)-\[VFY\]-x-\[C\]-x(1,2)-\[PG\]-x(0,1)-\[H\]-x(2,4)-\[MQ\]
12 AZURIN PDOC00174 Type 1 Blue Copper 1\. PS00196 \[GA\]-x(0,2)-\[YSA\]-x(0,1)-\[VFY\]-x-\[C\]-x(1,2)-\[PG\]-x(0,1)-\[H\]-x(2,4)-\[MQ\]
13 PSEUDOAZURIN \* \* \*
14 AURACYANIN PDOC00174 Type 1 Blue Copper 1\. PS00196 \[GA\]-x(0,2)-\[YSA\]-x(0,1)-\[VFY\]-x-\[C\]-x(1,2)-\[PG\]-x(0,1)-\[H\]-x(2,4)-\[MQ\]
15 AMICYANIN \* \* \*
16 NITRITE REDUCTASE PDOC00174 Type 1 Blue Copper PS00196 \[GA\]-x(0,2)-\[YSA\]-x(0,1)-\[VFY\]-x-\[C\]-x(1,2)-\[PG\]-x(0,1)-\[H\]-x(2,4)-\[MQ\]
:::
::: {#T5 .table-wrap}
Table 5
::: {.caption}
######
Number of protein sequences retrieved from the PIR nREF database for the already existing signatures for the blue copper proteins
:::
**PROSITE ID** **PROSITE PATTERN SEARCH RESULTS**
---------------- ------------------------------------
PS00079 779
PS00080 366
PS00192 18593
PS00193 13818
PS00196 589
PS00199 158
PS00200 284
PS00419 348
PS01026 3
:::
::: {#T6 .table-wrap}
Table 6
::: {.caption}
######
Newly designed protein signatures/peptides for the different blue copper proteins. The number of protein sequences retrieved from the PIR nREF database for each of the newly designed signatures.
:::
**S. NO:** **NAME OF THE PROTEIN** **SIGNATURE /PEPTIDES** **NO: OF RELATED PICKS** **NO: OF FALSE PICKS**
------------ ------------------------------------- -------------------------------------------------------------------------------------- -------------------------- ------------------------
1 PLANTACYANIN \[F\]-\[I\]-\[C\]-\[NST\]-\[F\]-\[PG\]-x-\[H\]-\[C\] 10 NO
2 PLASTOCYANIN \[eukaryotic source\] \[C\]-x-\[P\]-\[H\]-x-\[GS\]-\[A\]-\[GN\]-\[M\] 80 1
3 PLASTOCYANIN \[prokaryotic source\] \[Y\]-\[C\]-x-\[P\]-\[H\]-\[R\]-\[G\]-\[A\]-\[G\]-\[M\]-\[V\]-\[G\] 21 NO
4 PLASTOCYANIN \[prokaryotic source\] PHRGAGMVG 21 NO
5 STELLACYANIN \[H\]-\[C\]-x-\[NL\]-\[G\]-\[MQ\]-\[K\]-\[LV\]-x-\[VI\]-\[NRQ\]-\[V\] 7 1
6 UCLACYANIN \[P\]-\[G\]-x-\[R\]-\[Y\]-\[F\]-\[I\]-\[C\]-\[G\] 3 NO
7 UCLACYANIN RYFICG 11 NO
8 RUSTICYANIN \[G\]-\[M\]-\[YF\]-\[G\]-\[K\]-\[I\]-\[V\]-\[V\] 8 NO
9 SULFOCYANIN \[C\]-\[G\]-\[I\]-\[AL\]-\[G\]-\[H\]-\[A\]-\[VAQ\]-\[SA\]-\[G\]-\[M\]-\[W\] 5 1
10 SULFOCYANIN FNFNGTS 5 1
11 AMICYANIN \[AP\]-\[G\]-\[SAT\]-\[FVY\]-\[D\]-\[YF\]-\[FHIY\]-\[C\]-\[RT\]-x-\[H\]-\[P\] 10 1
12 HALOCYANIN \[C\]-\[TN\]-\[P\]-\[H\]-x-\[AT\]-x-\[G\]-\[M\]-x-\[G\]-\[A\] 2 NO
13 PSEUDOAZURIN \[K\]-\[C\]-\[TA\]-\[P\]-\[H\]-x-\[GAM\]-\[M\]-\[GS\]-\[M\] 18 NO
14 AZURIN \[D\]-x-\[R\]-\[V\]-\[LI\]-\[A\]-\[HYF\]-\[T\]-x-\[VIL\]-\[VIL\]-\[G\]-\[GAS\]-\[G\] 54 NO
15 NITRITE REDUCTASE \[P\]-\[ST\]-\[HY\]-\[VIGA\]-\[VL\]-\[FM\]-\[N\]-\[G\] 235 NO
:::
|
PubMed Central
|
2024-06-05T03:55:47.838296
|
2004-9-9
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517927/",
"journal": "BMC Bioinformatics. 2004 Sep 9; 5:127",
"authors": [
{
"first": "Anuradha Vivekanandan",
"last": "Giri"
},
{
"first": "Sharmila",
"last": "Anishetty"
},
{
"first": "Pennathur",
"last": "Gautam"
}
]
}
|
PMC517928
|
Background
==========
In the United States and temperate regions throughout the world, the family Rosaceae ranks third in economic importance. The most important fruit producing crops include apple (*Malus*), pear (*Pyrus*), raspberries/blackberries (*Rubus*), strawberries (*Fragaria*), and stone fruits (*Prunus*) such as peach/nectarine, apricot, plum, cherry and almond \[[@B1]\]. Additionally, Rosaceae contains a wide variety of ornamental plants including roses, flowering cherry, crabapple, quince and pear. Peach is being developed as a model species for Rosaceae because of its small genome size \[haploid size of 300 Mb \[[@B3]\]\], approximately twice that of *Arabidopsis*and other characteristics: a relatively short juvenile period (2--3 yrs) and extensive genetics and genomics resources such as molecular marker maps, interesting mutants and clone library resources \[[@B1]\]. In addition, it has been demonstrated that molecular marker tools developed in peach are easily applied to other species in the family \[[@B5]-[@B8]\]. Developing genetic resources for a model organism can greatly accelerate the genetic understanding of the individual member species in the same family. The utilization of rice physical mapping resources in the study of other crops within Poaceae is an excellent example of the usefulness of a comparative genomics approach \[[@B2]\]. Two major efforts to develop peach as a model for genomics of Rosaceae have been initiated: (1) Structural genomics -- the development of a complete physical map of the peach genome and the anchoring of the genetic markers of many of the economically important Rosaceae species maps on this physical map (2) Functional genomics -- the development of an extensive EST database for fruit, shoot and seed tissues and integration of the tentative unigene set onto the physical and genetic maps of peach.
The volume and the complexity of the data being produced by these peach genomics projects, in addition to the rapidly accumulating genomics and genetics data for other important rosaceous species, necessitate the development of a properly curated and integrated scientific database. Such a database will help scientists to efficiently access, analyze, integrate and apply the data to their own research in a timely manner. RoseDB, which focused on apple genetics and cherry genomics, has been decommissioned and now only exists as a mirror site at INRA. To meet the major need for a centralized and integrated web-database for genomics and genetics research in Rosaceae, the Genome Database for Rosaceae (GDR; <http://www.genome.clemson.edu/gdr/>) has been initiated. The goals of the GDR are (1) to develop an organized and integrated web resource for peach genomics data to facilitate the gene discovery in other member species by a comparative mapping approach, (2) to collect and integrate all Rosaceae genomics data, (3) to develop online tools and resources for the Rosaceae community. In this paper, we describe the structure and content of the database, we review the database access utility and tools and we report a case study where we mapped publicly available Rosaceae sequences to the peach physical and genetic maps by sequence similarity.
Construction and content
========================
GDR data
--------
### EST data source and annotation
An international cooperative project is in progress to develop an extensive peach EST database from a variety of vegetative and reproductive tissues of peach and almond. Currently, GDR contains 9984 ESTs from developing fruit of peach and 2794 ESTs from developing seed of almond. This translates into 3843 tentative unigenes for peach and 773 for almond.
The peach and almond ESTs are being processed at the Clemson University Genomics Institute (CUGI) utilizing publicly available software, integrated in a fully automated in-house developed script (CUGIEST). The processing occurs in three stages: trace file processing to identify a filtered, high quality clone library, assembly of high quality sequences to produce longer transcripts and reduce redundancy, and sequence annotation. Annotation consists of pairwise comparison of both the filtered clone library and the EST contig consensus sequences against the GenBank nr protein database using the fastx3.4 algorithm \[[@B9]\]. The ten most significant matches with the expectation values (EXP) less than 1 × e^-9^, for each contig and individual clone in the library are recorded. The unigene data set is then derived by selecting the clone that best represents each contig (the clone with the most significant EXP for the homology search) and the singletons that have either unique protein matches or no known significant matches. Peach ESTs were further annotated by Gene Ontology (GO) assignment based on the single \"best hit\" match against the SWISS-PROT database. Of the 1552 sequences from the putative peach unigene set that had matches with the SWISS-PROT database, 1439 could tentatively be assigned GO classifications. Additional sequence annotation includes computational analysis for simple sequence repeats (SSR) and open reading frame (ORF) on both the filtered clone library and the contig library. SSR analysis was preformed using a modified version (CUGISSR) of a Perl script SSRIT \[[@B10]\] with parameters set to detect di- to pentanucleotide with length greater than 18 bp. To examine the location of SSRs in the EST sequences in relation to the putative coding region, CUGISSR uses the FLIP \[[@B11]\] program which is available at the OGMP (Organelle Genome Megasequencing Project), Biochemistry department, University of Montreal <http://megasun.bch.umontreal.ca/aboutflip.html>. FLIP is a UNIX C program that finds/translates ORFs (open reading frames) in sequences. Using the FLIP output, CUGISSR selects the longest ORF as the putative coding region and reports the location of SSRs in relation to the putative coding region.
In addition to the peach and almond ESTs processed by CUGI, all the publicly available Rosaceae EST data are daily downloaded from GenBank dbEST and annotated with the top ten most significant matches (EXP \< 1 × e^-9^) following a monthly homology search of GenBank nr protein database using the fastx34 algorithm.
### Genetically anchored physical map and transcript map data
The genetically anchored physical map for peach is under development using peach BAC libraries \[[@B1]\]. It is being constructed using an approach that employs a combination of hybridization of mapped markers and BAC fingerprinting \[[@B12]\]. For BAC fingerprinting, FPC \[[@B13]\] is used for automatic assembly of the bands. Hybridization of mapped markers to BAC clones aids in the physical mapping process and also enables researchers to identify the BACs containing these markers. To date, over 250 genetic markers such as RFLPs, AFLPs and SSRs from several molecular genetic maps have been hybridized to BAC clones. Through this, the peach physical map has been anchored on the general *Prunus*map \[[@B5]\]. Additional 3,000 peach ESTs from the unigene set are currently being mapped to the peach physical map to develop a transcript map of peach fruit ESTs. The EST hybridization is being done as an international cooperative project to develop a functional genomic database for peach. The EST hybridization results are sent to the peach physical mapping team in Clemson University. The overall BAC fingerprinting results and EST/marker hybridization data, stored in an FPC output file and/or spread sheets, are submitted to GDR by the Clemson peach physical mapping team.
Database and software design and implementation
-----------------------------------------------
The GDR is a relational database implemented using Oracle Database Management System version 9.2.0. Currently, the database is composed of 28 tables which store all the data for EST processing, assembly and annotation, SSR analysis, BAC clones, libraries, genetic markers and maps that are used for BAC hybridization, results of the hybridization of markers and ESTs to BAC clones, contact information, and publications.
EST data processing, annotation, and uploading of the database are fully automated using a series of scripts written in Perl version 5.8.2. Daily download, annotation and upload of GenBank Rosaceae ESTs are also automatically performed by a series of Perl scripts. Data for BAC hybridization, genetic maps and markers which are submitted from researchers are examined by a curator for any potential errors and then uploaded using Perl scripts. BAC contig data for the developing peach physical map are uploaded directly from the FPC output file to our oracle database using Perl scripts.
Web interfaces for database query and the query result pages are mostly developed using Java Server Page (JSP). JSPs are more efficient, easier to use, more powerful and more portable than traditional CGI and many alternative CGI \[[@B4]\]. BAC contigs of the developing peach physical maps are displayed using WebFPC and WebChrom which are downloaded from an Arizona Institute of Genomics web site <http://www.genome.arizona.edu/software/fpc/download_web/>. We have developed a map viewer to provide users with a convenient access to the integrated genetic, physical and transcript map information. Our map viewer is developed using Scalable Vector Graphics (SVG). The SVG viewer plug-in can be freely downloaded from the Adobe Website <http://www.adobe.com/svg/viewer/install/main.html> and the system requirements can be found at their website <http://www.adobe.com/svg/systemreqs.html>. Our map viewer program accesses our underlying relational database to dynamically generate an integrated genetic and transcript map with a direct link to the WebFPC physical map from each marker.
Utility and discussion
======================
Database access and tools
-------------------------
The GDR website is composed of general information pages, database query/browse interfaces and other tools such as map viewer and sequence similarity server. The GDR web pages are extensively linked such that users can easily access the data of interest regardless of the navigation starting point. For example, the EST detail pages have links to the BAC detail pages, marker detail pages or map viewer for the ESTs that are anchored to BACs, markers or maps. Similarly, the BAC detail pages have links to EST detail page, marker detail page, WebFPC and map viewer. Users can also access the data detail pages from the map viewer or WebFPC/WebChrom. Instead of displaying the entire EST or BAC data in one page, we used the right hand side navigation bars to help users find specific information easily and quickly. A general GDR navigation tool bar is also included in each page to help provide a more user-friendly interface.
### Database search interface
The generic search site allows users to select data types such as EST, BAC and Marker, and search by name. Users can also follow the link to perform more detailed search for each data type. In the EST search site, users can search either the CUGI peach EST database or Rosaceae EST database downloaded from GenBank. ESTs can be searched by their name(s) and annotation features such as whether the EST belongs to a contig, is a unigene, is used as a probe and has SSRs, or any combination thereof. The EST details page, instead of displaying all the details in one page, initially displays the clone information and the sequence with a side bar containing links to library detail, assembly/unigene information, sequence homology, SSR information, Map position and anchored BACs. Each page linked from this side bar has the same side bar for easy navigation between the features. The Sequence homology page shows the most significant matches (EXP \< 1e-9) in the Genbank nr protein database from the fastx sequence similarity search. The SSR information page shows the sequence along with the computationally derived SSRs to help users in the primer design for SSR marker development. The longest putative open reading frame (ORF) is also marked in color in the sequence along with the SSRs. SSRs in the non-coding region tend to be more polymorphic and those in the coding region tend to be more transferable among species, so the information of SSR position in a gene structure will be useful for marker development. The Map position page allows users to view the ESTs\' map position using our Map Viewer. Users can retrieve the anchored BAC clones for the EST of interest and all the other ESTs and markers that hybridized to the same BAC through the anchored BACs page. The assembly/unigene information page displays the assembly results which include the contig name and the unigene clone that best represents the contig. The contig name is linked to a contig page that displays the contig sequence with a side bar containing links to the comprising ESTs, sequence homology and SSR information. As ESTs with no match to the GenBank proteins or with no SSRs can still assemble into contigs with a match or SSRs, users may get further annotation results of their ESTs of interest by visiting the contig detail site. In addition, contigs may have longer sequences surrounding the SSRs, allowing more flexibility in the primer design for marker development.
In the BAC search site, users can search BACs by name or by probe specifications used for BAC hybridization. The search results site and the linked sites provide users with all the data about the BAC, such as the BAC contigs that the BAC belongs to, other BACs in the contig, probes that hybridized to the BACs, the detailed data about the probes, and link to the WebFPC physical map. Markers can be searched by name or features such as map name, type, and source organism. Similarly with the BAC search result sites, the maker search results sites leads users to pages with the marker information, anchored BACs, other markers and ESTs hybridized to the same BACs and link to the Map Viewer and the WebFPC physical map.
### Graphical interface to maps
GDR hosts peach WebFPC and WebChrom to allow users to view the developing peach FPC contigs. Peach WebChrom displays the eight linkage groups of the general *Prunus*map and each linkage group has a link to a page where the developing contigs are located by the linkage group. Each contig has a direct link to WebFPC in which the individual BAC clones are displayed (Figure [1A](#F1){ref-type="fig"}). GDR also provides a graphical tool for users to access the integrated genetic, transcript and physical map information. The map viewer displays the general *Prunus*map \[[@B5]\] with the number of ESTs anchored to each locus (Figure [1B](#F1){ref-type="fig"}). The EST details page is linked from the map so that users can get all the data about the ESTs that are anchored to the loci of interest. When a locus is selected, a box appears to display marker type, the number of anchored BACs and the number of other probes that share the same BACs. Each number entry has links to a page where the detailed information is displayed. Also shown in the box are BAC contig names that are anchored to the loci. The BAC contig names have links to WebFPC so that users can directly access the physical map via this route (Figure [1B](#F1){ref-type="fig"}).
### Sequence similarity server
GDR also has a BLAST and FASTA sequence similarity search server that allows users to conduct homology searches between their sequences of interest and the various sequence data sets including annotated sequences in GDR. Users can select the database (e.g. peach ESTs, peach unigenes, mapped peach unigenes, GenBank Rosaceae ESTs, GenBank Rosaceae proteins etc) and various search parameters. Users can upload batch sequence files and the parsed results from the search are formatted in a spread sheet and sent to users by email. When the query sequence has a match to the annotated GDR sequences, users can retrieve all the information such as putative function, SSRs, and the anchored map positions via a hyperlink in the excel spreadsheet. Our sequence similarity server, specifically designed for Rosaceae researchers, will help users utilize the developing peach resources in the studies of other Rosaceae species. For example, as described in the case study below, sequences derived from other Rosaceae species could be immediately anchored to the various Rosaceae maps and the physical map when the query sequences show significant similarity to the mapped peach ESTs.
Case study: Mapping of Rosaceae sequences onto Rosaceae maps by sequence similarity
-----------------------------------------------------------------------------------
We report here a case study illustrating the utility of our sequence similarity server and other integrated GDR web resources. In this study, we performed a sequence similarity search using the FASTA algorithm with the non-peach Rosaceae sequences against the mapped peach ESTs to annotate Rosaceae sequences with map positions. A fasta formatted file with a total of 16258 publicly available non peach Rosaceae sequences was uploaded to the GDR FASTA server. We selected the mapped peach database and used the default parameters. The search results returned from the server are formatted in a spread sheet for easy browsing and the match names are hyperlinked to both GenBank and the GDR web site (Figure [2](#F2){ref-type="fig"}). By following the GDR link, users can get the anchored position in the genetic and physical maps as well as other annotation results such as putative function (Figure [2](#F2){ref-type="fig"}). To summarize our results, we used 259 query/match pairs which have a percent identity over 95 and an align-length greater than 100 nucleotides. The majority of the query sequences that showed high similarity to peach ESTs were *Prunus*sequences such as apricot (*Prunus armeniaca*), almond (*Prunus dulcis*) and sour cherry (*Prunus cerasus*). This was expected as peach also belongs to the genera *Prunus*. The 259 query/match pairs consisted of 209 Rosaceae sequences and 61 mapped peach ESTs. The matching of multiple Rosaceae sequences to single peach sequences was expected since the Rosaceae sequences were not assembled and therefore potentially contains multiple sequences representing the same gene. The 209 Rosaceae sequences were anchored to 38 different loci in four different Rosaceae maps. The number of sequences from each Rosaceae species that anchored to each map is shown in Figure [3](#F3){ref-type="fig"}. This study demonstrates the usefulness of applying a comparative genomics approach to Rosaceae genomics using the GDR as a data mining tool. The entire data for the mapped Rosaceae sequences with anchored map positions are available at <http://www.genome.clemson.edu/gdr/anchoredrosaceae/>.
Future development
------------------
We plan to incorporate more Rosaceae genomics and genetics data from researchers worldwide as well as data from the ongoing *Prunus*genomics projects. Data to be added in the near future include apple ESTs, strawberry ESTs, rose ESTs and apricot map/marker data from collaborators. When the genomics projects from *Prunus*are finished, we will host 10--15,000 unique ESTs from a variety of vegetative and reproductive tissues of peach and almond, the complete peach physical map with anchored genetic markers and unique ESTs. In addition to adding new data, future development efforts will focus on improving the tools and functionality of the web interface such as an advanced search site with options for search/display categories, full sequence processing facilities for Rosaceae researchers, a newsgroup for the Rosaceae community, a site for Rosaceae literature, and more analysis tools such as an interactive contig viewer and a comparative map viewer.
Conclusions
===========
The GDR is initiated to support the genomics and genetics research in Rosaceae, which contains numerous economically important fruit trees and horticultural plants. Currently GDR contains all the genomics data for the Rosaceae model peach, maps and markers of Rosaceae species and all the publicly available Rosaceae ESTs. Our integrated database provides users with easy access and retrieval of the annotated data, and the web tools enable them to further analyze their data. With future plans, including more data acquisition and tool developments, GDR will play an important role in the timely and efficient analysis of the data, the exchange of results and ideas among researchers worldwide, the support of Rosaceae labs worldwide with Bioinformatics tools and the utilization of the data from the model species in the study of other Rosaceae species. The methodology and tools applied to develop GDR should be easily applied to develop other comparative genomic databases for different families.
Availability
============
The GDR is publicly available and can be accessed at <http://www.genome.clemson.edu/gdr/>.
List of abbreviations used
==========================
AFLP: Amplified Fragment Length Polymorphism
BAC: Bacterial Artificial Chromosome
CGI: Common Gateway Interface
EST: Expressed Sequence Tag
EXP: EXpectation Value
HTML: HyperText Markup Language
HTTP: HyperText Transfer Protocol
INRA: Institut National de la Recherche Agronomique
RFLP: Restriction Fragment Length Polymorphism
SSR: Simple Sequence Repeat
XML: eXtensible Markup Language
Authors\' contributions
=======================
SJ performed web interface design and programming for html pages and JSP search pages, participated in the database construction, carried out database curation, designed the Map Viewer and performed the case study. CJ wrote scripts for database upload and sequence processing, programmed Map Viewer and implemented WebFPC and WebChrom. MS participated in the database construction and wrote scripts for data upload and search pages for Genbank Rosaceae sequences. SF performs database administration. IC developed the application prototype for servlet-database connection and participated in the database construction. AA conceived of the project and participated in its design and coordination. ZD developed the sequence similarity server application. JT participated in the coordination of the project. DM conceived and supervised the project, participated in the database construction, carried out EST analysis, and provided input in the web interface design. All authors read and approved the final manuscript.
Acknowledgements
================
This work was supported by an award (\#0320544) from the National Science Foundation. Any opinions, findings and conclusions or recommendations expressed herein are those of the authors and do not necessarily reflect the views of the National Science Foundation.
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Graphical interface to maps. A. Peach WebChrom and peach WebFPC: a. the opening page of peach WebChrom with eight linkage group of the general *prunus*map; b. an example of individual linkage group pages (linkage group 6) with the associated markers and the contigs; c. an example of the directly linked FPC page with the developing BAC contigs and anchored probes (contig \#185). B. Map Viewer: Map viewer displays the general *Prunus*map with anchored ESTs and direct link to WebFPC.
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Case Study: Hyperlink to map viewers from the sequence similarity search result. This figure shows snapshots of hyperlinked pages to illustrate that users can obtain putative genetic and physical map positions of the query sequences when the sequences have match to mapped peach ESTs. A. A spread sheet with sequence similarity search results B. EST detail page with map position C. Map Viewer D. WebFPC.
:::
:::
::: {#F3 .fig}
Figure 3
::: {.caption}
######
Case Study result: Number of anchored Rosaceae sequences to various Rosaceae genetic maps T × E: \'Texas\' × \'Earlygold\'; F or T: F × T (\'Ferragnes\' × \'Tuono\'); P × F: (\'IF310828\' × P. ferganensis) × \'IF310828\'; SC × B: \'Suncrest\' × \'Bailey\'
:::
:::
|
PubMed Central
|
2024-06-05T03:55:47.842423
|
2004-9-9
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517928/",
"journal": "BMC Bioinformatics. 2004 Sep 9; 5:130",
"authors": [
{
"first": "Sook",
"last": "Jung"
},
{
"first": "Christopher",
"last": "Jesudurai"
},
{
"first": "Margaret",
"last": "Staton"
},
{
"first": "Zhidian",
"last": "Du"
},
{
"first": "Stephen",
"last": "Ficklin"
},
{
"first": "Ilhyung",
"last": "Cho"
},
{
"first": "Albert",
"last": "Abbott"
},
{
"first": "Jeffrey",
"last": "Tomkins"
},
{
"first": "Dorrie",
"last": "Main"
}
]
}
|
PMC517929
|
Background
==========
There are several commercial microarray systems currently available on the market for genome-scale gene expression analysis. Different microarray manufacturers provide distinct underlying technologies, protocols and reagents specific to each system \[[@B1]\]. Despite the widespread use of microarrays, much ambiguity regarding data analysis, interpretation and correlation of the different technologies exists. There is a need for standardization that will facilitate comparison of microarray data from different platforms \[[@B2]\]. Comparison and cross-validation between microarray platforms would greatly increase the understanding and value of the wealth of data generated from each microarray experiment \[[@B3]\]. A number of cross platform comparisons have reported a failure to demonstrate an acceptable level of correlation between different microarray technologies \[[@B4]-[@B7]\]. Some of the difficulties in correlating data can be attributed to fundamental differences between cDNA and oligonucleotide based microarray technologies. For example, target preparation differences and single vs. dual labeling techniques complicate the comparisons. Furthermore, cDNA arrays have difficulty in distinguishing between splice variants and highly homologous genes, while oligonucleotide arrays can make these distinctions if designed appropriately. However, when considering oligonucleotide platforms, which have widespread popularity, direct comparisons between different platforms should be less complex and more direct. We assert that differences in platform sensitivity, reproducibility and annotation cross-referencing accuracy account for a majority of the irreconcilable differences previously reported between different platforms \[[@B4]-[@B7]\]. When considering these factors we demonstrate a strong correlation between expression ratio data from two different commercially available short oligonucleotide based microarray technologies. This paper provides a comprehensive guideline for microarray analysis, interpretation and cross-platform correlation.
There are two commercially available high-density microarray platforms that use short oligonucleotides for expression profiling. CodeLink (GE Healthcare formerly Amersham Biosciences, Chandler, AZ) and GeneChip (Affymetrix, Santa Clara, CA) microarray platforms utilize oligonucleotide gene target probes of 30 and 25 bases, respectively. Some of the notable differences between the GeneChip and CodeLink systems are, respectively, multiple probes vs. one pre-validated probe per gene target, two-dimensional surface vs. three-dimensional array matrix, and *in situ*synthesized oligonucleotides vs. pre-synthesized, non-contact oligonucleotide deposition. We restricted our comparative analysis to these two platforms because these systems are most similar with respect to oligonucleotide length, target preparation, and single color indirect labeling methodology. Since these commercial assays are similar, and systematic variables were isolated by using the same total RNA starting material for all target preparations, we expected disparity in performance to reflect differences inherent to the microarray platforms. To provide data for comparison of the platforms, five technical replicates of brain and pancreas were processed on each platform and the results were compared for reproducibility, sensitivity, and similarity of results. Standard manufacturer-recommended protocols and settings were employed to obtain the raw data from each platform. In the case of Affymetrix GeneChip, a recent cross-platform microarray evaluation \[[@B7]\] used two additional algorithms \[[@B8],[@B9]\] for analysis of the GeneChip data and found the same level of discordance across the three analysis algorithms as was observed in the cross-platform microarray comparisons \[[@B7]\]. We therefore restricted our analysis of the GeneChip data to the Affymetrix recommended MAS 5.0 software \[[@B10]\]. This methodology was followed to simulate the results users would achieve by following current protocols supplied with each microarray system.
Results
=======
Two different tissue types were compared in this study to ensure a large number of differentially expressed genes, and provide expression ratios across a wide dynamic range for derivation of the correlation coefficient between the two platforms. The array-to-array precision of each microarray platform was calculated from the five replicates within each tissue sample.
The pair-wise array-to-array precision of each microarray platform is illustrated in Figure [1](#F1){ref-type="fig"} with respective noise levels for both CodeLink and GeneChip. In these graphs all 10,763 uniquely represented genes, common between both microarray platforms, are illustrated. The GeneChip comparisons display a wider distribution relative to CodeLink at the lower end of the fluorescence detection range. While this wider distribution could be interpreted as indicating a lower level of precision relative to CodeLink, precision should only be assessed for the population of genes with expression values above the noise calculation (i.e. \'present\' on the arrays being considered). Due to the variation in noise and specificity level between expression detection systems, each system must individually define its own threshold level cutoff for resultant confidence in signals above technical noise. In addition, in a multi-oligonucleotide detection system, a defined algorithm must be set to determine the method for combining individual probe data to yield a final gene expression level. Therefore, we used each manufacturer\'s indications for gene signals that should be considered confidently above system noise. The wider distribution observed in the GeneChip platform is within the noise population and therefore should not penalize the overall precision measurements. Qualitatively, CodeLink and GeneChip showed similar levels of precision when concordantly \'absent\' genes were excluded within each platform, as illustrated by the blue data points representing the true signal range (Figure [1](#F1){ref-type="fig"}).
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Pair-wise array precision of CodeLink and GeneChip with illustration of respective noise levels. The representative scatter plots show precision of normalized expression values relative to noise. All 10,763 overlapping gene probes are represented in these plots. Values highlighted in red were concordantly \'absent\' (noise) calls on both arrays compared. Orange lines show two-fold limits, while the black line represents equality.
:::
:::
Precision measurements were calculated from signals above noise across the arrays being compared (Tables [1](#T1){ref-type="table"} and [2](#T2){ref-type="table"}) to obtain a quantitative assessment. For the five array replicates, within each tissue, a total of 10 pair-wise combinations were made for all genes above noise (i.e. \'present\'). Ratios were made in cases where the gene was called \'present\' on both arrays being compared. False-change rates of CodeLink and GeneChip were calculated from each pair-wise array comparison between arrays processed with the same starting material. The percentage of ratios derived from the population of concordantly \'present\' genes, which fall outside 2-fold (i.e. \|log~2~ratio\| \> 1), is defined as the false-change rate. Table [1](#T1){ref-type="table"} shows the average and standard deviation of the false-change rate that was calculated for each of the 10 pair-wise array combinations within a sample. The false-change rates between microarray platforms were very similar, however the performance of CodeLink was slightly better with only 0.32% and 0.20% of ratios falling outside 2-fold for brain and pancreas, respectively. GeneChip showed 0.69% and 1.28% ratios outside 2-fold for brain and pancreas, respectively. To assess the level of tightness in the intensity distribution for each platform, we calculated the pair-wise ratio range within which 95% of all ratios fall for each platform (Table [2](#T2){ref-type="table"}). For CodeLink, 95% of ratios are below 1.36 and 1.27 for brain and pancreas, respectively. On the other hand, 95% of GeneChip ratios are below 1.49 and 1.64 for brain and pancreas, respectively. Taken together, this data illustrates the precision for CodeLink is slightly higher than GeneChip for both samples tested.
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
False-change rate for GeneChip and CodeLink microarray platforms. The false-change rate is defined as the percentage of ratios, derived from the population of concordantly \'present\' genes, which fall outside 2-fold (i.e. \|log~2~ratio\| \> 1). The table above contains the average and standard deviation of the false-change rate, calculated across the 10 pair-wise array combinations within a sample. False-change rate was calculated from signals above noise across the arrays being compared.
:::
**Array Platform** **Tissue** **AVG** **STDEV**
-------------------- ------------ --------- -----------
CodeLink Brain 0.32% 0.13%
Pancreas 0.20% 0.14%
GeneChip Brain 0.69% 0.27%
Pancreas 1.28% 0.17%
:::
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Precision ratio summary for GeneChip and CodeLink microarray platforms. Precision measurements were calculated from signals above noise across the arrays being compared. For CodeLink, there were 7,882 and 6,603 ratios, on average, for each pair-wise array-to-array comparison, within brain and pancreas respectively. For GeneChip, there were 6,734 and 5,137 ratios, on average, for each pair-wise array-to-array comparison, within brain and pancreas respectively. For each of the 10 pair-wise combinations, the ratio range within 95% of the ratios fall was calculated. This table contains the average and standard deviation, in which 95% of ratios fall within, across all 10 pair-wise array combinations within a sample.
:::
**Array Platform** **Tissue** **AVG** **STDEV**
-------------------- ------------ --------- -----------
CodeLink Brain 1.36 0.09
Pancreas 1.27 0.01
GeneChip Brain 1.49 0.05
Pancreas 1.64 0.03
:::
In addition to pair-wise array precision, we calculated coefficients of variation (CV) for each platform as a function of intensity, across all replicates. In Figure [2](#F2){ref-type="fig"}, CV is represented as a percentage calculated as the gene\'s signal standard deviation divided by mean signal across all array replicates. Genes that are concordantly \'absent\' are shown in red. Concordantly \'absent\' refers to genes called \'absent\' by the manufacturer\'s software on all 5 replicate arrays tested. The black line represents the 100-probe moving average of all data points. The precision of all \'present\' signals is similar between CodeLink and GeneChip, as illustrated by the moving-average level within the blue region. The median percent CV for the population of \'present\' genes was 8% for both platforms. However, as gene intensity decreases, the average variance increases earlier in the distribution for GeneChip relative to CodeLink, as illustrated by the 100-probe moving average, at the boundary between red and blue data points. It is expected that variance would naturally increase at this boundary and since the rise in variance coincides with the level of concordantly \'absent\' signals, demonstrating that noise is more than likely being identified correctly by each platform\'s image quantification software. Notably, Figures [1](#F1){ref-type="fig"} and [2](#F2){ref-type="fig"} illustrate a higher level of noise for GeneChip relative to CodeLink.
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Coefficients of variation for each platform as a function of intensity, across all replicates. Genes which are concordantly \'absent\' are shown in red. The black line represents the 100-probe moving average.
:::
:::
Differential expression ratios were compared between platforms to determine the cross-platform correlation. As shown in Figure [3](#F3){ref-type="fig"}, when all 10,763 uniquely overlapping genes are compared between platforms, the correlation is weak (r = 0.62, where \'r\' represents the Pearson correlation coefficient). However, when removing the population of concordantly \'absent\' signals, the correlation is r = 0.70 between microarray platforms. When limiting the comparison to those values which are called \'present\' on at least 3 of the 5 replicates across tissues and platforms, the correlation improves further to 0.74. If we further limit our comparison to only genes called concordantly \'present\' (i.e. \'present\' on all 5 replicates across both tissues and platforms) the correlation r = 0.79.
::: {#F3 .fig}
Figure 3
::: {.caption}
######
Correlation of differential expression ratios between CodeLink and GeneChip. Pearson correlation coefficients (r) are shown for each comparison. (A.) When all 10,763 overlapping genes are compared between platforms the correlation is 0.62. (B.) All values for genes concordantly \'absent\' were removed prior to making the cross-platform correlation. In this case, 3,362 genes are called \'present\' on at least 1 of the 5 replicates across both tissues and platforms. (C.) 2,569 genes called \'present\' on at least 3 of the 5 replicates across both tissues and platforms. The correlation improves further to 0.74. (D.) Genes called present on all 5 replicates across both tissues and platforms. For these 1,760 genes the correlation is 0.79.
:::
:::
The improvement in the correlation coefficient from 0.62 to 0.79 achieved by excluding noise underscores the value in identifying the population of signals above noise for cross-platform comparisons. The \'volcano plots\' in Figure [4](#F4){ref-type="fig"} further confirm this point. Each data point represents a probe from the uniquely common set of 10,763 gene probes between the platforms relative to ratio and significance value. Data points highlighted in blue represent genes that are concordantly \'present\' in both tissues. Hence, these blue data points are the genes called \'present\' on all replicates across both tissues (n = 10). The mean log~10~ratio of expression (brain/pancreas) is shown on the x-axis and the p-value, from a two-tailed Student\'s t-tests on normalized log-transformed intensities, is shown on the y-axis. The vertical dashed lines represent 2-fold change ratios, which are commonly used in the field as significance levels for non-replicated array experiments. The horizontal dashed line represents the statistical-significance level where p = 0.01 (an uncorrected lenient level, used to error on the side of inclusion). The lower right- and left-hand corners of each graph contain the genes that showed a large fold-change but fail to achieve statistical significance (p \> 0.01). GeneChip results show a larger number of genes in these regions as compared to the CodeLink data. The data points located in the upper-central region of each graph represent genes that were statistically significant (p \< 0.01) despite modest fold-changes (\< 2-fold). The minimal-detectable statistically significant fold-change was tighter for CodeLink relative to GeneChip as illustrated by the distance across the \'volcano\' plot at the 0.01 significance level. In addition, the number of genes above the 0.01 significance level was greater for CodeLink relative to GeneChip. The distribution difference between the red and blue data points demonstrates the advantage of identifying signals above noise for making ratio calculations.
::: {#F4 .fig}
Figure 4
::: {.caption}
######
\'Volcano plots\' for CodeLink and GeneChip. Each point represents a gene from the uniquely common set of 10,763 genes between platforms. Data points highlighted in blue represent genes which are concordantly \'present\' in both tissues. The log~10~ratio of expression (brain/pancreas) is shown on the x-axis and the p-value, from a two-tailed Student\'s t-tests on normalized log-transformed intensities, is shown on the y-axis. The vertical dashed lines represent 2-fold change ratios and the horizontal dashed line represents the statistical-significance level where p = 0.01.
:::
:::
The \'volcano\' plots are translated into Venn diagrams of statistically significant differentially expressed genes for each platform in Figure [5](#F5){ref-type="fig"}. Statistically significant (p \< 0.01) expression ratios were determined using the entire set of 10,763 uniquely common genes between platforms. The total number of statistically significant differentially expressed genes detected by both platforms from this common set was 8,393. The intersection of the two platforms represents 50% of the total number of significantly differentially expressed genes. It is important to note that using the method described here, only probes considered above system noise are utilized for the correlation calculation. This leaves a set of probes which are discrepant calls and require further analysis to determine the accuracy of detection. The CodeLink platform called 5,322 genes concordantly present across the two tissues while the GeneChip platform called 3,691 genes (figure [5B](#F5){ref-type="fig"}, top panel). The union represents 2,569 concordantly present calls common to both platforms, where n = 3 or more. In addition, the set of 1,760 concordantly \'present\' gene probes, across both platforms and tissues, was used to create a Venn diagram of ratios derived from signals concordantly above noise. The intersection of the two platforms represents 69% of the total number of differentially expressed genes. There are a higher percentage of commonly significantly changed genes between platforms when noise is excluded from ratio calculations. In both cases CodeLink shows a larger percentage of statistically differentially expressed genes at a p value less than 0.01.
::: {#F5 .fig}
Figure 5
::: {.caption}
######
Venn diagrams of differential expression calls and statistical significance across both microarray platforms. A two-sample two-tailed t-test on normalized log-transformed intensities was performed for each microarray platform. (A) The entire set of 10,763 uniquely common genes between platforms was used to determine the number of statistically significant (p \< 0.01) expression ratios. Genes above and below noise were included in the analysis. (B) Statistical significance determined from the set of 2,569 genes which are \'present\' on at least 3 arrays in both tissues. Expression values below noise (\'absent\') were not included in the analysis. (C) Statistical significance determined from the set of 1,760 genes which are \'present\' on all 5 arrays in both tissues (i.e. concordantly \'present\').
:::
:::
A power analysis was conducted on each microarray platform to estimate the number of technical replicates needed to achieve a reasonable level of statistical confidence when noise was either included or excluded from the dataset (Figure [6](#F6){ref-type="fig"}). Evaluating the power of each platform at the level of technical replication allows researchers to gauge the underlying system variance before introducing biological variance in their studies. From our analysis, to achieve a power of 0.90 using all 10,763 genes, 3 array replicates are minimally necessary for CodeLink while 8 replicates are required for GeneChip. However, when noise is excluded, both CodeLink and GeneChip require only 1 array to achieve this same level of power. In fact, when noise is excluded, 1 array for both GeneChip and CodeLink has a 0.99 level of power in detecting two-fold differences in expression. The significant improvement in power by excluding noise provides considerable value to microarray users since fewer arrays are required to resolve desired differences in expression. By identifying and removing noise both systems can detect differential expression ratios less than 2-fold with a high level of power. However, more genes are lost on the GeneChip platform as a result of the higher level of noise relative to CodeLink. Additionally, when noise is excluded, 1.5-fold changes in expression can be detected, at a 0.90 power, using 2 CodeLink or 3 GeneChip technical replicates.
::: {#F6 .fig}
Figure 6
::: {.caption}
######
Power analysis estimating the number of technical array replicates needed to achieve a reasonable level of statistical power or confidence for CodeLink (blue) and GeneChip (red) when noise was included (solid diamonds) or excluded (open diamonds). For both graphs the alpha was set at 0.01. (A) Relationship between power and arrays necessary to statistically discriminate two-fold changes in expression. To achieve a power of 0.90 using all 10,763 genes, 3 arrays are minimally necessary for CodeLink while 8 are required for GeneChip. However, when noise is excluded, both GeneChip and CodeLink require only 1 array to achieve this same level of power. In fact, when noise is excluded, 1 array for both GeneChip and CodeLink has a power of 0.99 to detect two-fold changes in expression. B.) In order to detect 1.5 fold changes in expression, at a 0.90 power, when noise is excluded, CodeLink minimally requires 2 arrays while GeneChip requires 3.
:::
:::
The accuracy of CodeLink and GeneChip differential-expression ratios were compared to quantitative real-time PCR (qrtPCR). Microarray expression ratios were measured against results from qrtPCR for a randomly selected subset of 25 genes (Table [3](#T3){ref-type="table"}) and plotted in Figure [7](#F7){ref-type="fig"}. Both microarray platforms correlated well to this alternative expression-profiling technology with Pearson correlation coefficients of 0.92 and 0.79 for CodeLink and GeneChip, respectively.
::: {#F7 .fig}
Figure 7
::: {.caption}
######
Accuracy of CodeLink and GeneChip differential-expression ratios relative to qrtPCR. Expression ratios for each microarray platform were measured against results from qrtPCR for a randomly selected subset of 25 genes. Pearson correlation coefficients (r) are shown for each comparison.
:::
:::
Discussion
==========
Increased access and utilization of microarray data through core facilities and affordable commercial microarray systems is driving the need for direct comparisons of data between the different available platform technologies. The ability to exchange data across different platforms gives the research community the ability to cross-validate results and extend understanding of biological processes through integration of published data collected with different technologies. The results presented here demonstrate that we are closer to reaching this goal than previously reported \[[@B4]-[@B7]\].
We have compared two commercial platforms and in doing so present several steps required for making comparisons between short oligonucleotide microarray data sets. First, one must normalize annotation. Unfortunately, despite the completion of the human, rat and mouse genome sequencing projects, accurate and stable gene annotation information is not available. The existence of inaccurate sequence information, absence of an exact gene count, incomplete understanding of splicing variations, and the complexity of highly homologous gene sequences all contribute to the challenges of generating a controlled vocabulary for uniquely and constantly annotating genes at the present time. In addition, when considering commercially available arrays, the consumer is left to rely on the manufacturer to provide a probe with a one to one correlation to the intended gene target. Furthermore, until recently manufacturers have withheld the release of the exact probe sequences to researchers \[[@B7]\]. Now that with a simple disclosure agreement probe sequences from the major manufacturers are readily available to the users, discrepancies in some results will be explained by differences in actual probe and probe sets targets as defined by sequence homology. Some probes target different or multiple splice variants and some probes are not specific to a single gene, but instead, target multiple homologous genes. Since the use of GeneChip probe sequences for deriving inter-platform overlap is currently prohibited by Affymetrix for publication purposes, we needed to rely upon public annotation to determine the overlap between products rather than more informative sequence-based comparisons. We believe that the use of probe sequences will help to further refine the accuracy of the gene overlap set, and increase the already strong correlation between platforms demonstrated here. In addition, without the use of sequence information, we filtered the data to include only those probes and probe sets that identify a specific gene target or common regions of splice variants of a single gene target. Both manufacturers in some cases carry multiple probes or probe sets per target gene. Trying to determine which probes to compare in this case without the use of sequence information is nearly impossible. Therefore, only uniquely represented gene probes by both manufacturers were used for comparisons. By employing this conservative methodology, we reduce the risk of inappropriately comparing data from probes designed to detect different transcripts or genes despite having a similar annotation. Importantly, we used a common build of UniGene cluster IDs to find unique gene probes which overlap between the two products.
When comparing between the two platforms using tissue ratio data without regard for noise, the correlation between platforms is not very strong (r = 0.62, Figure [3A](#F3){ref-type="fig"}), similar to what was reported by Tan *et al.*2003 \[[@B7]\]. This brings us to the second step, removing background signals. Considering background noise has random sources and sources that are different in nature for the two platforms, one would not expect to find a strong correlation when using noise values in platform comparisons. Each manufacturer warns users to be critical of confidence in calls that are below the defined threshold or considered \'absent\'. Therefore, we removed noise and made correlations based only on calls that were \'present\' in both tissue samples and microarray systems. Kuo *et al.*made a limited but similar attempt to reduce noise by using what they termed a \"variance filter\" \[[@B4]\]. Our process of filtering noise reduced the overlap of 10,763 genes to 3,362, 2,569 or 1,760 genes if one accepts \'present\' calls on at least 1, 3 or all 5 of the array replicates, respectively, across both tissues and platforms. Using this methodology, however, we found a stronger ratio correlation between the two platforms (r = 0.70, 0.74 or 0.79, Figure [3B,3C,3D](#F3){ref-type="fig"}). We have found that when limiting the comparison set to those probes which are uniquely represented, specific for their targets of interest, and called \'present\' in the samples tested on each platform, the correlation between technologies is very reasonable for data sharing. Supporting this methodology, a recent study found a substantial improvement in the correlation between spotted long-oligo arrays and the Affymetrix platform with data filtering by removing low intensity signals below the median \[[@B11]\]. Interestingly, when Barczak and colleagues removed low intensity signals, the Pearson correlation coefficient improved from 0.60 to 0.80, which is in the same range as in our study \[[@B11]\]. Rather than removing all low intensity signals below the median, we recommend data filtering by using each manufacturer\'s standard software package to identify those genes which are within noise. This approach to filtering noise offers great value to microarray users since our recommendation does not require the immediate loss of 50% of the data in making cross-platform comparisons.
Finally, an alternative expression-profiling technology, qrtPCR, was used to follow up on a smaller subset of the concordantly correlated set to demonstrate that the data generated here was not merely an anomaly specific to oligonucleotide arrays (Figure [7](#F7){ref-type="fig"}). Both platforms correlated well to this alternative expression-profiling technology with r values of 0.92 and 0.79 for CodeLink and GeneChip, respectively. Previous studies have found agreement between genes screened with microarray technology and subsequent qrtPCR verification of those expression measurements \[[@B12],[@B13]\]. We are in the experimental process of using qrtPCR with a larger set of genes as an independent method to resolve discordant gene expression results between the two microarray platforms.
The comparison described here parses the data into three sets: *(1.)*Concordantly \'present\' which was used to calculate the correlation comparisons; *(2.)*Concordantly \'absent\', where both platforms agree that the transcript is not \'present\' in the samples tested; and *(3.)*\'Present\' on one microarray platform but not the other, which are considered a separate set of discrepant results. In the studies presented here, the CodeLink platform generates a higher percentage of detectable signals above noise (Figures [1](#F1){ref-type="fig"}, [2](#F2){ref-type="fig"}, and [5](#F5){ref-type="fig"}). This finding is consistent for all replicate arrays across both tissues analyzed. Previously, Ramakrishnan *et al.*2002 reported detection down to an estimated sensitivity level between 1:750,000 and 1:900,000 for the CodeLink platform \[[@B14]\]. However, biological validity of these low level calls by qrtPCR or other method have not been confirmed the results. In addition, a significant number of signals were detected by the GeneChip platform and were not detected by the CodeLink platform. Therefore, follow up studies are necessary to definitively determine which of the discordant calls are biologically relevant and which may be potential false positive calls. It would be informative to understand the underlining basis of the discordant calls. Assigning cause such as differences in sensitivity, analysis algorithms, or characteristics of the two platforms would be of great values to furthering comparative studies.
Discrepant calls between the two platforms may derive from differences in the GeneChip and CodeLink platform technologies. The platforms differ in the oligodeoxyribonucleotide probe length and number of probes per gene. A microarray study, using covalently attached oligodeoxyribonucleotides, found that 30- and 35-mer oligodeoxyribonucleotides generated signals two- to five-fold higher than 25-mers \[[@B15]\]. Relogio *et al.*suggested that 30-mers offered the best compromise between sensitivity and specificity \[[@B15]\]. However, the GeneChip platform offers multiple probes per gene, potentially offsetting the need for longer probes through multiple hybridization points. The CodeLink platform contains one pre-validated probe per gene that was screened for performance from an original panel of three probes per gene. Previous research has demonstrated that one probe per gene is sufficient to accurately measure differential expression \[[@B16]\]. Having one pre-validated probe per gene rather than a panel of probes per gene on a microarray platform may be advantageous towards improving sensitivity since there is no requirement that many probes within a gene must agree for expression to be detected and called. A single probe must, however, be very accurately designed to cover the range of splice variants feasible, and must reside in an area accessible to the RNA or DNA fragments hybridizing. Variation in signals may also derive from the nature of the substrate for probe attachment. Previous publications have indicated that the use of a three-dimensional matrix coated slide results in a larger number of potential attachment sites than modified glass \[[@B17]-[@B19]\]. Stillman and Tonkinson \[[@B20]\] have shown higher specific hybridization signals on a three-dimensional matrix compared with glass. In addition, it has been demonstrated that the CodeLink three-dimensional matrix allows for reduced steric hindrance and increased availability of the entire oligonucleotide for hybridization with its intended target \[[@B21]\]. Side-by-side comparisons of the performance of the same probe set and analysis technique would be required to confirm any contribution to discrepant results observed in this study.
Discrepant calls between the two platforms may also likely derive from differences in the GeneChip and CodeLink analysis algorithms. The use of mismatches on the GeneChip platform may limit detection since others have reported that, in general, one third of GeneChip mismatches are higher in signal than their perfect match counterparts \[[@B9],[@B22],[@B23]\]. Alternative analysis methodologies that do not utilize the mismatch controls may alter the discordant set, but as described earlier, there is a large potential variation in the different methodologies and a lack of a single majority method. Therefore, we chose to analyze the dataset in this study with the MAS 5.0 algorithms, as recommended by Affymetrix. It is likely that each of the aforementioned factors, in addition to annotation differences, contribute to variable results, and taken together account for the set of discrepant calls observed between the GeneChip and CodeLink platforms (Figure [5](#F5){ref-type="fig"}).
Conclusions
===========
This paper highlights the value of separating signal from noise in order to improve microarray cross-platform correlations. We also demonstrate a stronger correlation between platforms than previously reported based on our data filtering and parsing methodology. We believe there is strong similarity in calls by each system and differences in sensitivity and levels of noise are largely responsible for lower levels of correlation. Furthermore, as a standardized annotation system develops and freely open access to the use of microarray probe sequences is realized, it will help clear up discrepancies on a case by case basis.
Methods
=======
Array design and fabrication
----------------------------
CodeLink UniSet Human 20 K Bioarray (Amersham Biosciences, Chandler, AZ) contains a collection of approximately 20,289 probes within a single reaction chamber on each individual slide. All oligonucleotide probes are 30 bases in length. The core of the CodeLink platform is a glass slide coated with a polyacrylamide gel matrix to create a three-dimensional aqueous hybridization environment. Modified 5\'-amine-terminated oligonucleotides are deposited onto the polymer using piezoelectric dispensing robots and then covalently attached to activated functional groups within the gel matrix. Oligonucleotides are co-dispensed with a fluorescein-derivative dye, which enables scanning and inspection of every feature element on every slide after the dispensing. Additional sites are then blocked and slides are washed, rinsed and dried prior to attachment of an integrated, proprietary, polypropylene hybridization chamber. All probes appearing on the final product have been pre-validated for performance and screened from an original panel of up to three probes per gene.
The HG-U133 GeneChip Set from Affymetrix (Santa Clara, CA, USA) contains 44,928 probes, on 2 chips, that represent 42,676 unique sequences from the GenBank database corresponding to 28,036 unique UniGene clusters. The GeneChip technology is based on a photolithographic *in situ*synthesis. Individual probes consist of 25 base DNA sequences.
Target preparation and array hybridization
------------------------------------------
One lot of human brain and pancreas total RNA (brain lot\#033P010402009A and pancreas lot\#022P0102B from Ambion) was assessed for quality using the Agilent 2100 Bioanalyzer and split equally between Amersham Biosciences in Chandler, Arizona and the Genomics Shared Service at the Arizona Cancer Center. The Affymetrix target preparations and hybridizations were performed entirely at the Arizona Cancer Center to ensure that these microarrays were run by an independent party with GeneChip expertise. In addition, an aliquot from these lots of total RNA was saved and subsequently used in qrtPCR reactions for verifying the expression profiles obtained by each microarray platform.
For each Affymetrix GeneChip, double-stranded cDNA was synthesized from 5 ug of total RNA with the SuperScript Double-Stranded cDNA Synthesis Kit (Invitrogen) and dT24-T7 primer (Operon) according to the manufacturer\'s instructions. Biotin-labeled cRNA was prepared by *in vitro*transcription using the BioArray High Yield RNA Transcript Labeling Kit (Enzo). The dsDNA was mixed with 1× HY reaction buffer, 1× biotin labeled ribonucleotides (NTPs with Bio-UTP and Bio-CTP), 1× DTT, 1× RNase inhibitor mix and 1× T7 RNA polymerase. The mixture was incubated at 37°C for 5 hours. The labeled cRNA was then purified using an RNeasy mini kit (Qiagen) according to the manufacturer\'s protocol and ethanol precipitated. Fragmentation of cRNA, hybridization, washing, staining, and scanning were performed as described in the Affymetrix GeneChip Expression Analysis Technical Manual \[[@B24]\]. Briefly, the purified cRNA was fragmented in 1× fragmentation buffer (40 mM Tris-acetate, 100 mM KOAc, 30 mM MgOAc) at 94°C for 35 minutes. For hybridization with GeneChip cartridge (Affymetrix), 15 ug of fragmented cRNA was incubated with 50 pM control oligonucleotide B2, 1× eukaryotic hybridization control (1.5 pM *BioB*, 5 pM *BioC*, 25 pM *BioD*, and 100 pM *cre*), 0.1 mg/ml herring sperm DNA, 0.5 mg/ml acetylated BSA and 1× manufacturer recommended hybridization buffer, and hybridization was performed with a GeneChip Fluidic Station (Affymetrix) using the appropriate antibody amplification, washing and staining protocol. The phycoerythin-stained array was scanned, resulting in a digital image file. In all, 5 replicates of U133A and U133B were processed for each total RNA sample. Therefore, 10 target preparation reactions were performed for each of the two tissues to generate the necessary cRNA for this study.
For each CodeLink Bioarray, double-stranded cDNA and subsequent cRNA was synthesized from 5 ug of total RNA using the CodeLink Expression Assay Kit (Amersham Biosciences) according to manufacturer\'s instructions \[[@B25]\]. Briefly, cRNA was prepared by *in vitro*transcription using a single, labeled nucleotide, biotin-11-UTP in the IVT reaction at a concentration of 1.25 mM. Unlabeled UTP was present at 3.75 mM, while GTP, ATP, and CTP were at 5 mM. The mixture was incubated at 37°C overnight for 14 hours. The labeled cRNA was then purified using an RNeasy^®^mini kit (Qiagen). Fragmentation of cRNA, hybridization, washing, staining, and scanning were performed as described \[[@B26]\]. Briefly, the purified cRNA was fragmented in 1× fragmentation buffer (40 mM Tris-acetate pH 7.9, 100 mM KOAc, 31.5 mM MgOAc) at 94°C for 20 minutes. For hybridization with CodeLink bioarrays (Amersham Biosciences), 10 ug of fragmented cRNA in 260 ul of hybridization solution was added to each bioarray via the Flex Chamber port and incubated for 18 hours at 37°C, while shaking at 300 r.p.m. in a New Brunswick Innova™ 4080 shaking incubator. The 10 bioarrays, in this study, were processed in parallel using the CodeLink Shaker Kit and CodeLink Parallel Processing Kit (Amersham Biosciences). Bioarrays were stained with Cy5™-streptavadin (Amersham Biosciences) and scanned using a GenePix^®^4000 B scanner (Axon Instruments).
Deriving expression values and classifying probes within noise (\'absent\') for each platform
---------------------------------------------------------------------------------------------
For the U133 GeneChip technology, each gene is represented by 11 probe pairs containing both a perfect match probe (PM) and a mismatch probe (MM) where the middle (13^th^) base of each 25-mer probe is incorrect. The MM probe is designed to give an indication of the degree of nonspecific hybridization \[[@B26]\]. The MAS 5.0 software uses both PM and MM values for the expression calculation, one that avoids the production of negative values. MAS 5.0 employs a scenario-based approach to expression calculations and in general hypothesizes that MM probes should show lower hybridization signal than the corresponding PM probes. A decision process is used when this PM \> MM assumption is broken. When all MM values are less than their PM counterparts, an expression value is calculated using a one-step bi-weight estimate of the log(PM -- MM) values for each probe pair. However, when the MM value for a probe pair is greater than the PM value, two differing scenarios are applied. 1.) If the values of the PM probes are sufficiently large and separable from the background and MM signals, then the MM value is replaced with a value calculated as typical for the probe set. 2.) If it is difficult to separate the probe signals from background then the MM signal is substituted with a value slightly less than the PM signal. Once an expression value is calculated for each probe set the next step is the calculation of a Detection *p*-value and the comparison of each Discrimination score to the user-definable threshold (Tau). Tau is a small positive number that can be adjusted to increase or decrease sensitivity and/or specificity of the analysis (default value = 0.015). The One-sided Wilcoxon\'s Signed Rank test is the statistical method employed to generate the Detection *p*-value. It assigns each probe pair a rank based on how far the probe pair discrimination score is from Tau. The user-modifiable Detection *p*-value cut-offs, Alpha 1 (α1) and Alpha 2 (α2) provide boundaries for defining \'Present\', \'Marginal\' or \'Absent\' calls. At the default settings (α1 = 0.04 and α2 = 0.06), any p-value that falls below α1 is assigned a \'Present\' call, and above α2 is assigned an \'Absent\' call. \'Marginal\' calls are given to probe sets which have *p*-values between α1 and α2. In our study, the MAS 5.0 default parameters were retained. For a complete description of the MAS 5.0 algorithms and statistical tests please refer to the Affymetrix manuals \[[@B10],[@B27],[@B28]\].
For the CodeLink bioarrays, spot signals are quantified using ImaGene 5.5 software (BioDiscovery, Marina Del Ray, CA). The mean intensity is taken for each spot and background corrected by subtracting the surrounding median local background intensity. A spot is considered \'absent\' (within noise) if the spot\'s signal mean is less than its corresponding local background mean plus one standard deviation of local background pixels. For each probe the local background is comprised of a circular area of pixels surrounding the segmented signal. The image segmentation and quantification process is outlined in the ImaGene 5.5 user\'s manual \[[@B29]\].
Cross-platform comparisons of expression data
---------------------------------------------
To facilitate comparisons between data sets, CodeLink probes and GeneChip probe sets were mapped to specific sequence clusters according to the NCBI Human UniGene build \#166 relative to the manufacturer\'s provided NCBI accession numbers. Multiple probe or probe sets targeting a single UniGene cluster or single probe or probe sets targeting multiple clusters were removed from consideration. The overlapping and uniquely represented UniGene clusters were used to identify 10,763 gene probes for comparison between platforms. Gene-expression values were global linearly normalized according to manufacturers\' standard normalization procedure \[[@B9],[@B26]\]. The 96% trim-mean of the entire GeneChip array was used for Affymetrix normalization while CodeLink values were normalized against the array median. The globally normalized data from both platforms were scaled to 1.0 in order to bring both platforms to the same intensity range for comparative purposes. The analysis was performed using SAS statistical software and Microsoft Excel.
Power analysis of CodeLink and GeneChip platforms
-------------------------------------------------
A power analysis is a computational tool used to determine the replication needed to achieve a desired level of confidence in results from a particular experiment \[[@B30]-[@B32]\]. Determining the number of microarray replicates necessary for classification of expression profiles has been presented as an important issue \[[@B33],[@B34]\] and should be one of the first things to consider when designing any experiment. Fore each tissue we hybridized the same target on each of five microarrays; therefore the expected fluorescence values for each independent probe should be the same from each array to array replicate, making the expected fold change equal to 1 (i.e. μ~1~= μ~2~). The power analysis was modeled from log~2~transformed ratios derived from all pair-wise array-to-array combinations across the five replicates within the brain sample, since this tissue had the greatest similarity in performance between microarray platforms. Expression profiling of the pancreas sample showed many more genes within noise (\'absent\') for the GeneChip platform relative to CodeLink. The power analysis was conducted as previously described \[[@B35],[@B36]\] for the population of all 10,763 genes within each platform and the population of genes above noise (\'present\').
Real-time PCR
-------------
The TaqMan^®^One-Step RT-PCR Master Mix Reagent Kit (Applied Biosystems, Foster City, CA, USA) was used with each custom designed, gene-specific primer/probe set to amplify and quantify each transcript of interest. Optimal primer/probe sets were selected using Primer Express software version 1.0 B6 (Applied Biosystems). Reactions (25 ul) contained 100 ng of total RNA, 300 nM forward and reverse primers, 200 nM TaqMan probe, 12.5 uL 2X Master Mix without the enzyme uracil DNA glycosylase (UNG), 0.625 mL MultiScribe™ and RNAase Inhibitor Mix, and 6.875 uL RNAse-free water. RT-PCR amplification and real-time detection were performed using an ABI PRISM 7700 Sequence Detection System (Applied Biosystems) for 30 min at 48°C (reverse transcription), 10 min at 95°C (AmpliTaq Gold activation), 38 cycles of denaturation (15 s at 95°C), and annealing/extension (60 s at 60°C). Data were analyzed using ABI PRISM Sequence Detection Software version 1.6.3 and then further processed using Microsoft^®^Excel (Microsoft, Redmond, WA). Cyclophilin (PPIE) served as the endogenous control for the normalization of input target RNA. Raw C~T~values, qrtPCR primer/probe sequences, and corresponding array probe names are available in supplementary material \[see [additional files 1](#S1){ref-type="supplementary-material"}, [2](#S2){ref-type="supplementary-material"}, and [3](#S3){ref-type="supplementary-material"}, respectively\].
Competing interests
===================
RS, TJS, RL, TK-K and CP are employees of GE Healthcare.
Authors\' Contributions
=======================
RS planned and designed the study, conducted the micoarray experiments with the CodeLink platform, analyzed the data, generated all of the figures, and drafted the paper. TJS helped with writing of the paper, deriving the overlap between platforms, provided overall technical guidance and coordination. RL designed, conducted, and analyzed the quantitative PCR experiments, performed bioinformatics support, and edited the manuscript. CP read the manuscript and provided comments. TK-K edited the manuscript. GW helped with the experimental design and was responsible for generating all of the GeneChip data as well as editing the manuscript. JA provided guidance with the statistical power analysis and additions to the manuscript. All authors read and approved the final manuscript.
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
List of genes evaluated using qrtPCR. For each gene, the microarray and qrtPCR brain/pancreas log~2~ratios are listed. Raw C~T~values, qrtPCR primer/probe sequences, and corresponding array probe names are available in supplementary material \[see additional files 1, 2, and 3, respectively\].
:::
**Gene** **NCBI Acc** **Description** **qrtPCR** **CodeLink** **GeneChip**
----------- -------------- -------------------------------------------------------------- ------------ -------------- --------------
MLP NM\_023009.1 MARCKS-like protein 2.33 2.08 4.20
COX7A2L NM\_004718.1 cytochrome c oxidase subunit VIIa polypeptide 2 like 1.19 0.10 -0.31
COL6A3 NM\_004369.1 collagen, type VI, alpha 3, transcript variant 1 -4.80 -4.75 -5.02
PRDX3 NM\_006793.1 peroxiredoxin 3, nuclear gene encoding mitochondrial protein 0.82 0.81 -0.42
CDKN1A NM\_000389.1 cyclin-dependent kinase inhibitor 1A -3.25 -2.89 -3.47
NUTF2 NM\_005796.1 nuclear transport factor 2 1.25 1.25 -0.12
CEBPD NM\_005195.1 CCAAT/enhancer binding protein, delta -0.54 0.41 -0.07
COL9A3 NM\_001853.1 collagen, type IX, alpha 3 2.62 2.35 2.22
GLDC NM\_000170.1 glycine dehydrogenase 5.93 3.33 2.85
TGFA NM\_003236.1 transforming growth factor, alpha 2.44 1.54 1.43
GALK2 NM\_002044.1 galactokinase 2 0.64 1.73 -0.39
ESR1 NM\_000125.1 estrogen receptor 1 0.03 0.39 -0.28
FMO3 NM\_006894.2 flavin containing monooxygenase 3 -1.06 -0.49 1.22
AKT1 NM\_005163.1 v-akt murine thymoma viral oncogene homolog 1 0.14 0.40 0.34
PRPS1 D00860.1 phosphoribosyl pyrophosphate synthetase subunit I 1.53 0.62 -0.04
RPA3 NM\_002947.1 replication protein A3 1.30 0.57 -0.97
SLIT2 NM\_004787.1 slit homolog 2 (Drosophila) 2.81 1.64 0.51
HIC AF054589.1 HIC protein isoform p40 and HIC protein isoform p32 0.70 1.83 -0.22
HSA275986 NM\_018403.1 transcription factor SMIF 1.51 1.41 -0.06
TFCP2L1 NM\_014553.1 transcription factor CP2-like 1 -1.55 -1.23 -0.66
PPIE NM\_006112.1 peptidylprolyl isomerase E (cyclophilin E) 0.00 -0.29 -1.10
FLJ14800 NM\_032840.1 hypothetical protein FLJ14800 0.97 1.41 1.20
MGC24039 AL137364.1 cDNA DKFZp434E0626 2.70 1.92 2.29
USF1 X55666.1 late upstream transcription factor 2.18 0.81 -0.86
B4GALT7 NM\_007255.1 xylosylprotein beta 1,4-galactosyltransferase, polypeptide 7 0.45 -0.41 -0.44
:::
Supplementary Material
======================
::: {.caption}
###### Additional File 1
This file contains gene names, sample designations, C~T~values for triplicates, mean C~T~values, median C~T~values, standard deviation of replicates, and coefficient of variation of replicates for each gene evaluated by qrtPCR.
:::
::: {.caption}
######
Click here for file
:::
::: {.caption}
###### Additional File 2
This file contains gene names, oligonucleotide sequences, and oligonucleotide type (FORWARD PRIMER, HYB OLIGO, and REVERSE PRIMER) for each gene evaluated by qrtPCR.
:::
::: {.caption}
######
Click here for file
:::
::: {.caption}
###### Additional File 3
This file contains gene names, descriptions, GenBank accessions, log2 ratios (qrtPCR, CodeLink, and GeneChip), CodeLink probe names, and GeneChip probe set names for each gene examined by all three technologies.
:::
::: {.caption}
######
Click here for file
:::
Acknowledgements
================
Affymetrix GeneChip analyses were performed by the Genomics Shared Service at the Arizona Cancer Center, supported by grant CA23074.
|
PubMed Central
|
2024-06-05T03:55:47.844233
|
2004-9-2
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517929/",
"journal": "BMC Genomics. 2004 Sep 2; 5:61",
"authors": [
{
"first": "Richard",
"last": "Shippy"
},
{
"first": "Timothy J",
"last": "Sendera"
},
{
"first": "Randall",
"last": "Lockner"
},
{
"first": "Chockalingam",
"last": "Palaniappan"
},
{
"first": "Tamma",
"last": "Kaysser-Kranich"
},
{
"first": "George",
"last": "Watts"
},
{
"first": "John",
"last": "Alsobrook"
}
]
}
|
PMC517930
|
Background
==========
Insulin-like growth factors (IGF-I and II) have a broad range of biological activities that include the stimulation of mitogenesis and differentiation, and insulin-like effects on glucose uptake and lipogenesis \[[@B1]\]. These activities are modulated by a family of six binding proteins, termed the IGF-binding proteins (IGFBPs 1--6) that bind IGF-I and IGF-II with high affinity (for review see \[[@B2]\]). IGFBP-1 binds and inhibits the activity of IGF-I and IGF-II in plasma, by regulating their bioavailability \[[@B3]\]. Administration of excess IGFBP-1, or overexpression of IGFBP-1 in transgenic mice, leads to glucose intolerance and hyperinsulinaemia \[[@B4],[@B5]\]. Meanwhile, IGFBP-1 expression can be dynamically regulated by nutritional status, increasing during fasting, malnutrition and diabetes but decreasing upon re-feeding or insulin treatment \[[@B6]-[@B8]\]. Hepatic IGFBP-1 gene transcription is rapidly and completely inhibited by insulin \[[@B9],[@B10]\], however, the signalling pathway(s) that mediates this effect is less well defined. Insulin induces multiple intracellular signalling pathways in liver. Stimulation of the small G-protein Ras leads to activation of a protein kinase cascade consisting of Raf-1, MAP kinase kinase-1, p42/p44 MAP kinases and p90Rsk, while the activation of phosphoinositide (PI) 3-kinase promotes the generation of 3-phosphoinositides that induce the activity of protein kinases such as 3-phosphoinositide dependent kinase (PDK1) and protein kinase B (PKB) \[[@B11],[@B12]\]. PKB subsequently phosphorylates glycogen synthase kinase -3 (GSK-3) at an N-terminal serine residue (Ser-21 on GSK-3α and Ser-9 on GSK-3β) rendering it inactive \[[@B13],[@B14]\]. This PKB-mediated inhibition of GSK-3 contributes to insulin activation of glycogen and protein synthesis \[[@B14],[@B15]\].
Studies using inhibitors of PI 3-kinase have demonstrated a requirement for this enzyme in insulin regulation of IGFBP-1 \[[@B16]\]. Indeed, overexpression of an active mutant of PKB mimics the effects of insulin on the IGFBP-1 promoter \[[@B16]\]. This effect, at least in part, is mediated through the inhibition of a Thymine-rich Insulin Response Element (TIRE) that lies between residues -120 and -96 relative to the transcription start site of the human gene promoter. Phosphoenolpyruvate carboxykinase (PEPCK) and Glucose-6-Phosphatase (G6Pase), rate-controlling enzymes of hepatic gluconeogenesis, possess a related regulatory element within their gene promoters \[[@B17]\]. Interestingly, members of the FOX(O) family of transcription factors (FKHR/FKHR-L1/AFX) have been linked to the regulation of the TIRE\'s found in these promoters \[[@B18],[@B19]\]. The expression of all of these genes, as well as the regulation of FOX(O), is inhibited by insulin through a PI 3-kinase-dependent mechanism \[[@B20]-[@B24]\], suggesting that a common signalling pathway is utilised by insulin to regulate these related TIREs. However, insulin regulation of IGFBP-1 but not G6Pase or PEPCK gene expression is sensitive to an inhibitor of the mammalian Target of Rapamycin (mTOR) \[[@B10],[@B25]\]. In addition, agents that strongly induce the MAPK pathway (e.g. phorbol esters) \[[@B26]\], as well as the protein phosphatase inhibitor okadaic acid \[[@B27]\], reduce the sensitivity of the IGFBP-1, but not the G6Pase and PEPCK promoters to insulin. Therefore, aspects of the signalling networks used by insulin to repress each of these TIRE containing promoters appear distinct. Recently, we observed that GSK-3 activity was required for both PEPCK and G6Pase promoter activity \[[@B28]\]. Selective inhibitors of GSK-3 reduce PEPCK and G6Pase gene transcription without requiring the activation of PKB. Indeed, the inhibition of GSK-3 may explain some of the effects of PKB overexpression on PEPCK and G6Pase gene expression. However, it was not clear why inhibition of GSK-3 should repress these promoters, whether inhibition of GSK-3 was actually required for insulin regulation of the genes, and whether the effect of GSK-3 inhibition was mediated through the TIRE.
In the present study, we have examined the role of GSK-3 in the regulation of a third TIRE-containing gene promoter, namely IGFBP-1. We demonstrate that four different classes of inhibitors of GSK-3 can mimic the action of insulin and reduce IGFBP-1 gene expression. Furthermore, we find that inhibition of GSK-3 reduces the activity of a heterologous promoter containing the IGFBP-1 TIRE, and propose that this mechanism underlies the repression of all three promoters by inhibitors of GSK-3. Finally, we demonstrate for the first time a requirement for inhibition of GSK-3 in the insulin regulation of the TIRE, and hence IGFBP-1 expression.
Results
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Lithium ions reduce IGFBP-1 gene expression in H4IIE cells
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Treatment of H4IIE cells with insulin completely inhibits both basal and glucocorticoid-induced IGFBP-1 gene expression. Lithium chloride, an inhibitor of GSK-3 *in vivo*, reduces both basal and glucocorticoid-induced IGFBP-1 gene expression (Fig [1](#F1){ref-type="fig"}). The effect of 20 mM lithium is not as complete as observed with insulin, resulting in only a 60--70% reduction of IGFBP-1 gene expression. However, treatment of H4IIE cells with the same concentration of potassium chloride has no effect on IGFBP-1 expression. The cyclophilin mRNA levels remain unchanged throughout these experiments. This highlights a role of a target of lithium ions in the specific regulation of IGFBP-1 gene expression.
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Figure 1
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######
*Lithium ions reduce IGFBP-1 gene expression*. H4IIE cells were starved overnight prior to a 3 h incubation with insulin,10 nM; lithium chloride or potassium chloride at the concentrations indicated with or without dexamethasone, 500 nM; (A-B). Total cellular RNA was isolated and an RNase protection assay was performed as described in material and methods. Results are presented as percentage gene expression (A) or fold induction (B) relative to control and are means ± standard error of two experiments performed in duplicate (upper panels). Representative experiments (lower panels) are also shown. \*\*\*, p \< 0.001, \*\*, p \< 0.01 and NS, not significant
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More selective inhibitors of GSK-3 also reduce IGFBP-1 gene expression
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SB 214763 and SB 415286 are cell-permeable maleimide compounds that selectively inhibit GSK-3 \[[@B29]\]. Treatment of H4IIE cells with either compound reduces IGFBP-1 gene expression (Fig [2](#F2){ref-type="fig"}). Expression is more sensitive to SB 214763 than SB 415286 (consistent with its lower IC-50 towards GSK-3 *in vitro*\[[@B29]\]). Importantly, cyclophilin mRNA levels remain unchanged in the presence of these compounds. Furthermore, under these conditions the regulatory phosphorylations of PKB and FOXO-1 are unaffected by SB214763, SB415286 or lithium \[[@B28]\]. In addition, SB214763 or SB415286 do not affect the phosphorylation of Ser-9 (GSK-3β) or Ser-21 (GSK-3α). Similarly, MAPK and S6K activity are not significantly affected by these compounds, as judged by the phosphorylation status of these insulin-regulated signalling molecules (Fig [3](#F3){ref-type="fig"}). Hence, the effects seen with these compounds on IGFBP-1 are likely to be due to the inhibition of GSK-3 rather than as a consequence of down/up-regulation of PKB, FOXO-1, MAPK or the mTOR pathway, which are known to effect IGFBP-1 gene expression.
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Figure 2
::: {.caption}
######
*SB216763 and SB415286 reduce IGFBP-1 gene expression*. H4IIE cells were starved overnight prior to a 3 h incubation with insulin, 10 nM ; dexamethasone, 500 nM; plus or minus SB216763 (A) or SB415286 (B) at the concentrations shown. Total cellular RNA was isolated and an RNase protection assay was performed, as described in material and methods. Results are presented as fold induction relative to control (serum free) and are means ± standard error of two experiments performed in duplicate (upper panels). Representative experiments are also shown (lower panels). \*\*\*, p \< 0.001 and \* p \< 0.05
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::: {#F3 .fig}
Figure 3
::: {.caption}
######
*Inhibition of GSK-3 does not affect the phosphorylation of MAPK or regulation of the mTOR pathway*. H4IIE cells were serum starved overnight prior to incubation with insulin, 10 nM; lithium chloride, 20 mM; SB216763, 30 μM; or SB415286, 100 μM for 15 min (A) or 3 h (B). Cells were lysed, and the lysates subjected to SDS PAGE as described in materials and methods, transferred to nitrocellulose and immunoblotted with antibodies as labelled (Phospho; phosphospecific antibody). Similar results were obtained from two experiments carried out in duplicate
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Paullones are potent inhibitors of GSK-3 that reduce IGFBP-1 gene expression
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Paullones are a family of benzazepinones that are potent (IC50; 20--200 nM), ATP-competitive inhibitors of cyclin-dependent kinases (CDKs) and the closely related neuronal CDK5/p25 \[[@B30]-[@B32]\]. Subsequently, they have been shown to be very potent inhibitors of GSK-3β \[[@B33]\]. Two members of this family, kenpaullone and alsterpaullone, reduce IGFBP-1 gene expression in a dose dependent manner (Fig [4](#F4){ref-type="fig"}). Alsterpaullone is much more potent than kenpaullone, reducing IGFBP-1 mRNA levels by 90% at 5 μM compared to a 50% reduction seen with 10 μM kenpaullone (Fig [4](#F4){ref-type="fig"}). Once more, this is consistent with the lower IC50 of alsterpaullone toward GSK-3 *in vitro*\[[@B33]\]. Alsterpaullone (like the maleimides) does not affect the phosphorylation of PKB, FOXO-1, MAPK, S6K or S6 (Fig [5](#F5){ref-type="fig"}). Similarly, phosphorylation at residues Ser-9 (GSK-3β) and Ser-21 (GSK-3α) of GSK-3 is unaffected by alsterpaullone treatment (Fig [5](#F5){ref-type="fig"}). Phosphorylation of Thr-308 (PKB) correlates with the activation of PKB while phosphorylation of Ser-9 (GSK-3β), Ser-21 (GSK-3α) and Thr-32 (FKHRL1) is indicative of inhibition of these PKB substrates.
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Figure 4
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######
*Paullones reduce IGFBP-1 gene expression*. H4IIE cells were serum starved overnight prior to a 3 h incubation with insulin,10 nM; dexamethasone, 500 nM; plus or minus kenpaullone (A) or alsterpaullone (B) at the concentrations shown. Total cellular RNA was isolated and an RNase protection assay was performed, as described in material and methods. Results are presented as fold induction relative to control (serum free) and are means ± standard error of two experiments performed in duplicate (upper panels). Representative experiments are also shown (lower panels). \*\*\*, p \< 0.001 and \*\* p \< 0.01
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::: {#F5 .fig}
Figure 5
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######
*Alsterpaullone does not affect the regulatory phosphorylation sites of PKB, FOXO-1, MAPK, and components of the mTOR pathway*. H4IIE cells were serum starved overnight prior to incubation with 10 nM insulin, or alsterpaullone at the concentrations shown for 30 min (A) or 3 h (B). Cells were lysed, and the lysates subjected to SDS PAGE, transferred to nitrocellulose and immunoblotted with antibodies as labelled (Phospho; phosphospecific antibody). Similar results were obtained from two experiments carried out in duplicate
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CHIR99021, the most specific GSK-3 inhibitor reported to date, also represses IGFBP-1 gene expression
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Although alsterpaullone, kenpaullone, SB214763, and SB415286 are potent inhibitors of GSK-3, they also exhibit activity against CDKs. However, the aminopyrimidine CHIR99021 shows 350-fold selectivity toward GSK-3 compared to CDKs (Jenny Bain and Sir Philip Cohen, University of Dundee, personal communication), and exhibits a Ki of \< 10 nM in vitro \[[@B34]\]. It is the most selective inhibitor of this enzyme reported to date \[[@B34],[@B35]\]. Treatment of H4IIE cells with CHIR99201 dramatically reduced basal and glucocorticoid-induced IGFBP-1 gene transcription, at concentrations between 1 and 10 μM (Fig [6](#F6){ref-type="fig"})
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Figure 6
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######
*CHIR99021 reduces IGFBP-1 gene expression*. H4IIE cells were serum starved overnight prior to a 3 h incubation with insulin,10 nM; dexamethasone, 500 nM; 8CPT-cAMP, 0.1 mM; plus or minus CHIR99021 at the concentrations shown. Total cellular RNA was isolated and an RNase protection assay was performed to measure IGFBP-1 and cyclophilin mRNA, as described in material and methods. Representative experiments are shown (A), while results are presented (B) as % expression (after correction for cyclophilin expression), relative to control (serum free) and are means ± standard error of two experiments performed in duplicate.
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CHIR99021 reciprocally regulates β-catenin activity and IGFBP-1 gene transcription
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H4IIE cells were transiently transfected with a luciferase-reporter construct containing TCF/LEF binding sites, whose activity is regulated by the GSK-3 substrate, β-catenin. Inhibition of GSK-3 results in the accumulation of β-catenin in the cytoplasm where it can form complexes with TCF/LEF. The complex translocates to the nucleus and activates transcription of target genes. Treatment of transfected H4IIE cells with CHIR99021 results in a dose-dependent increase in luciferase activity, regulated by the β-catenin/TCF complex (Fig [7A](#F7){ref-type="fig"}). The β-catenin mediated transcription is induced two-fold by 2 μM CHIR99021, reaching six to seven-fold at 10 μM. Therefore the concentration required to induce β-catenin activity is equivalent to that required for reduction of endogenous IGFBP-1 mRNA (Fig [6](#F6){ref-type="fig"}).
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Figure 7
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*CHIR99021 regulates both β-catenin activity and TIRE containing promoter activity*. H4IIE cells were transfected with TOPFlash (A) or alternatively with BP-1 WT or BP-1 DM5 (B) reporter constructs. Cells were incubated for 24 h with 10 nM insulin or CHIR99021 at the concentrations shown, prior to lysis and luciferase assays as described in materials and methods. Results are presented as fold induction relative to basal luciferase activity (no inhibitor) (A) or % luciferase activity relative to basal (serum free) luciferase expression (B) and are the means ± standard error of at least two experiments performed in triplicate. The basal activity of BP-1 WT and BP-1 DM5 is not significantly different.
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Meanwhile, insulin treatment of H4IIE cells previously transfected with a luciferase reporter construct under the control of a thymidine kinase promoter containing the IGFBP-1 TIRE (BP-1WT), reduces luciferase expression by 60% (Fig [7B](#F7){ref-type="fig"}). This effect is abolished by a two base pair mutation of the TIRE (BP-1DM5) (Fig [7B](#F7){ref-type="fig"} and \[[@B36]\]). Interestingly, 2 μM CHIR99021 reduces BP-1 WT activity by around 50% (Fig [7B](#F7){ref-type="fig"}), while 10 μM inhibits luciferase expression by 70%, with no effect on BP-1 DM5 activity. This demonstrates that CHIR99021 reduces TIRE activity, at a concentration that also induces β-catenin-mediated gene transcription (2--10 μM). This strongly argues that the effects of CHIR99021 on TIRE activity are mediated through inhibition of GSK-3.
Enhanced expression of GSK-3 reduces insulin regulation of the IGFBP-1 TIRE
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In order to assess the requirement for inhibition of GSK-3 in insulin regulation of the IGFBP-1 TIRE we over expressed wild-type GSK-3 (GSK-3β-WT), insulin-insensitive GSK-3 (GSK-3β-S9A) or control protein (β-galactosidase) in H4IIE cells using adenoviral vectors. Infected cells were subsequently transfected with BP-1-WT and treated with or without insulin (Fig [8A](#F8){ref-type="fig"}). The inhibitory effect of insulin on the BP-1 TIRE was significantly reduced when GSK-3 was over expressed (Fig [8A](#F8){ref-type="fig"}), demonstrating that inhibition of GSK-3 is required for full repression of this element by insulin. Both wild-type (p \< 0.001) and S9A-GSK-3 (p \< 0.001) over expression (around 3 to 5-fold increase in expression) reduced insulin regulation of this element. Meanwhile, adenoviral expression of GSK-3β-S9A also reduced the ability of insulin to repress IGFBP-1 mRNA in the H4IIE cells (Fig [8B](#F8){ref-type="fig"}).
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Figure 8
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*Overexpression of GSK-3β reduces insulin regulation of the IGFBP-1 TIRE*. H4IIE cells were infected with adenovirus expressing either β-Galactosidase (control), GSK-3β (GSK-3wt), or insulin-insensitive GSK-3β (GSK-3S9A). A) Cells were incubated for 16 hours before transfection with 10 μg of BP-1 WT as described under the Methods section. After 24 hours at 37°C +/- insulin (10 nM) cells were lysed and either luciferase assays performed (upper panel) or GSK-3 levels determined by Western Blot (lower panel). Results in the upper panel are presented as % insulin repression of luciferase expression and are the means +/- S.E.M. of at least five experiments performed in duplicate or triplicate. Basal luciferase expression is 3-fold higher in WT and S9A-GSK-3 infected cells compared with control. The lower panels provide a representative analysis of expression of GSK-3 (in triplicate) in each treatment. There was a significant reduction in the effect of insulin on BP-1 WT when either GSK-3 WT (\*\*\*p \< 0.001, control vs WT) or GSK-3 S9A (\*\*\*p \< 0.001, control vs S9A) was overexpressed. There is no significant difference between the WT and S9A data sets (p = 0.160). B) After infection cells were incubated for 24 hr prior to a 3 hr incubation with hormones as indicated. Cells were lysed and IGFBP-1 and cyclophilin mRNA levels assessed by RNase Protection Assay. A representative experiment is shown (lower panel), while relative mRNA levels ± SEM are presented for two experiments performed in duplicate in the upper panel.
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CHIR99021 does not regulate FOXO-1 transactivation potential
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BP-1 TIRE activity can be regulated by co-expression of FOXO-1 \[[@B22],[@B36]\]. Therefore, we examined the effect of CHIR99021 on the ability of FOXO-1 to regulate TIRE activity. When FOXO-1 is co-expressed with BP-1 WT in H4IIE cells, the expression of luciferase is induced around 3-fold (Fig [9](#F9){ref-type="fig"}). Insulin inhibits this FOXO-1-induced luciferase activity, while sensitivity to 2 μM CHIR99021 is completely lost in the presence of co-expressed FOXO-1 (Fig [9](#F9){ref-type="fig"}). The concentration of FOXO-1 used is less than maximal for induction of the BP-1 WT. This data suggests that FOXO-1 overexpression desensitises the TIRE to CHIR99021 and therefore that GSK-3 does not significantly regulate FOXO-1 activity.
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Figure 9
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*CHIR99021 does not affect FOXO-1 transactivation potential*. H4IIE cells were transfected with BP-1WT along with pEBG2T or pEBG2T-FOXO-1. Cells were incubated with 10 nM insulin or 2 μM CHIR99021 for 24 h prior to lysis and luciferase assays as described in materials and methods. Results are presented as % luciferase activity relative to basal (serum free) luciferase expression and are the means ± S.E. of two experiments performed in triplicate. NS; not significant.
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Discussion
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GSK-3 activity is required for IGFBP-1 promoter activity through direct regulation of the TIRE
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This study demonstrates that six agents, of four different chemical classes, which share an ability to inhibit GSK-3 mimic the effect of insulin on IGFBP-1 gene expression. This is reminiscent of the effect of lithium ions, SB216763 and SB415286 on two other insulin repressed gene promoters, PEPCK and G6Pase \[[@B28]\]. Indeed, a heterologous promoter containing the IGFBP-1 TIRE (a related sequence is common to all three of these insulin-regulated gene promoters), is also inhibited by CHIR99021 (Fig [7B](#F7){ref-type="fig"}). Similar promoter sequences are important for the insulin regulation of the tyrosine aminotransferase \[[@B37]\], aspartate aminotransferase \[[@B38]\], IRS-2 \[[@B39]\], and HMG CoA Synthase \[[@B40]\] gene promoters. Our data would predict that all of these genes, and any other promoters containing a TIRE, are likely to be repressed by treatment of cells with inhibitors of GSK-3. This provides an apparent paradox since we and others have found that insulin does not regulate every TIRE-containing gene promoter by an identical mechanism. For example, insulin regulation of the IGFBP-1 (but not the PEPCK or G6Pase) gene promoter requires mTOR activity \[[@B10],[@B25],[@B26]\]. Meanwhile, FOXO-1 is a TIRE-binding protein that has been proposed to regulate these three genes. However, cells that stably overexpress FOXO-1 show increased G6Pase but not PEPCK expression \[[@B41]\], and genetic manipulation of FOXO-1 has differential effects on these three gene promoters \[[@B19]\]. These data demonstrate that distinct signalling mechanisms control the regulation of these three TIRE-containing genes. Therefore, each TIRE structure may require GSK-3 activity for function but distinct signalling networks link each gene promoter with the insulin receptor. The common requirement for GSK-3 activity suggests that a GSK-3 substrate is key for the initiation of gene transcription for each TIRE-containing promoter.
Inhibition of GSK-3 is required for full inhibition of the IGFBP-1 TIRE by insulin
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Insulin induces PKB activity, promoting phosphorylation of Ser-21 of GSK-3α and Ser-9 of GSK-3β, thereby reducing total GSK-3 activity by between 20 and 80%, dependent on cell type. Therefore, expression of a mutant GSK-3β with Ser-9 replaced by alanine renders cellular GSK-3 activity insensitive to insulin \[[@B14]\]. Indeed, expression of this mutant significantly reduces the ability of insulin to repress BP-1 WT (Fig [8A](#F8){ref-type="fig"}), or the endogenous gene promoter (Fig [8B](#F8){ref-type="fig"}), demonstrating that insulin requires to inhibit GSK-3 for full repression of this gene promoter element. Similarly, four to five fold over expression of wild-type GSK-3β antagonises insulin repression of the BP-1 WT (Fig [8A](#F8){ref-type="fig"}). Although insulin will promote phosphorylation and inhibition (50--60% in H4IIE cells) of this recombinant GSK-3 in cells, the overall activity remains higher than un-stimulated control cells. This suggests that insulin must reduce GSK-3 activity below a threshold in order to fully repress BP-1 WT. This is the first demonstration of an absolute requirement for GSK-3 inhibition in insulin regulation of gene transcription.
What is the molecular link between GSK-3 and the TIRE?
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The GSK-3 inhibitors regulate IGFBP-1 gene expression in the absence of regulation of PKB, MAP kinase, FOXO-1 or mTOR (\[[@B28]\] and Figs [3](#F3){ref-type="fig"} and [4](#F4){ref-type="fig"}), known regulators of the IGFBP-1 promoter. This suggests a more direct regulation of this element, possibly of a TIRE-interacting protein itself. There are numerous transcription factors that have been proposed to be substrates for GSK-3 *in vitro*and in some cases *in vivo*(for review see \[[@B42]\]). These include β-catenin, c-jun, CREB, glucocorticoid receptor (GR) and c-myc. The phosphorylation of β-catenin \[[@B43],[@B44]\], c-jun \[[@B45],[@B46]\], GR \[[@B47]\] and c-myc \[[@B48]\] by GSK-3 promotes their destruction or reduces their activity, while the phosphorylation of CREB (at Ser-129) is thought to increase CREB activity \[[@B49]\], although this has been subsequently questioned \[[@B50]\]. Since inhibition of GSK-3 reduces TIRE activity, one presumes that GSK-3 mediated phosphorylation of a TIRE-binding protein would result in its activation (although possibly a permissive effect allowing activation by an additional mechanism), nuclear localisation or stabilisation. This would seem to rule out β-catenin, c-jun, GR and c-myc in the GSK-3-mediated regulation of the TIRE. Meanwhile CREB does not bind directly to a TIRE *in vitro*. The only known GSK-3 substrates that have been demonstrated to bind to or regulate the TIRE are members of the CAAT-enhancer binding protein (C/EBP) family of transcription factors. GSK-3 phosphorylates C/EBPα at Thr-222/Thr-226 \[[@B51]\] while C/EBPβ can regulate TIRE activity and is itself regulated by insulin \[[@B52]\]. The reported regulation of C/EBPβ by insulin is PI 3-kinase and PKB-dependent but is mediated through phosphorylation of the co-regulator protein p300/CBP \[[@B52]\]. We are currently examining whether the GSK-3 inhibitors regulate C/EBP and p300 phosphorylation and/or activity. Meanwhile, Granner and colleagues have found that insulin treatment of H4IIE cells increases the cellular levels of LIP (an inhibitory form of C/EBPβ that lacks the p300/CBP binding and activation domain) \[[@B53]\]. LIP subsequently replaces LAP (the activating form of C/EBPβ) on the endogenous PEPCK promoter. This prevents the recruitment of RNA polymerase II and p300/CBP, eventually leading to the repression of PEPCK gene expression. However, the LIP/LAP interacting elements within the PEPCK promoter are distinct from the TIRE \[[@B53]\]. Finally, our data suggests that the effect of GSK-3 inhibitors is independent of regulation of FOXO-1 (Figs [4](#F4){ref-type="fig"} and [9](#F9){ref-type="fig"}), the best characterised TIRE-binding protein. Therefore, much more work will be required to identify the GSK-3 substrate that regulates this DNA element.
GSK-3 inhibitors as therapeutics
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Agents that mimic the physiological processes that are regulated by insulin have the potential to be of therapeutic value for the treatment of insulin resistant states such as diabetes. Lithium chloride, SB216763, SB415286 and CHIR99021 inhibit GSK-3 and therefore mimic many of the actions of insulin. For instance, lithium chloride stimulates glucose transport and glycogen synthesis in adipocyte and muscle cell lines \[[@B54]-[@B56]\], while SB216763 and SB415286 stimulate glycogen synthesis in hepatocytes \[[@B29]\]. Meanwhile, CHIR99021 potentiates insulin activation of glucose transport and utilisation in vitro and in vivo \[[@B34]\], and related compounds reduce muscle insulin resistance \[[@B57]\] in animal models of diabetes. We have found that GSK-3 inhibitors also mimic the ability of insulin to repress key metabolic genes such as PEPCK, G6Pase and IGFBP-1 (\[[@B28]\] and Figs [1](#F1){ref-type="fig"}, [2](#F2){ref-type="fig"} and [4](#F4){ref-type="fig"}). Studies in animal models of diabetes suggest that these agents alleviate hyperglycaemia through both activation of glycogen synthesis and inhibition of hepatic glucose production \[[@B58],[@B59]\]. However, a vast number of biological processes are known to be regulated by GSK-3, thereby questioning their long term use as regulators of glucose homeostasis. Importantly, GSK-3 associates with and regulates proteins linked to the development of colonic cancer (APC, axin and β-catenin). Meanwhile, ablation of one of the two genes for GSK-3 (GSK-3β) in mice proved to be fatal due to increased hepatic sensitivity to TNFα-induced apoptosis \[[@B60]\]. Despite all of the potential problems that may be associated with GSK-3 inhibitors, deleterious effects of such compounds in animals remain to be formally reported. Currently, GSK-3 inhibitors are being investigated for the treatment of numerous psychiatric disorders \[[@B61],[@B62]\], neurodegeneration \[[@B63],[@B64]\] and even hair loss \[[@B65]\].
Conclusions
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The work presented herein demonstrates for the first time that inhibition of GSK-3 is required for complete insulin regulation of IGFBP-1, while we have identified the DNA element by which GSK3 targets this gene promoter. As such, GSK-3 inhibition will mimic the insulin regulation of IGF1 bio-availability, as well as reducing the expression of hepatic gluconeogenic genes. It remains to be seen how many other insulin-regulated (and/or TIRE-containing) gene promoters are sensitive to these inhibitors.
Methods
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Materials
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Radioisotopes were obtained from Amersham, Bucks, UK ({γ^32^P}-ATP) and ICN, Thame, Oxfordshire, UK ({α^32^P}-UTP). Insulin was purchased from Novo Nordisk, (Crawley, West Sussex, UK), kenpaullone and alsterpaullone from Calbiochem (La Jolla, CA) and the RNase Protection Assay Kit II from AMS Biotech/Ambion, (Austin, Texas). All other chemicals were of the highest grade available.
Synthesis of CHIR 99021
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CHIR99021 (6-{2-\[4-(2,4-Dichloro-phenyl)-5-(4-methyl-1*H*-imidazol-2-yl)-pyrimidin-2-ylamino\]-ethylamino}-nicotinonitrile) was synthesized in 7% overall yield using a convergent approach from 2,4-dichlorobenzoyl chloride and 6-chloro nicotinonitrile respectively (\[[@B66]\] and refs within).
Cell Culture
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The rat hepatoma cell line H4IIE was maintained in Dulbecco\'s Modified Eagle\'s medium (DMEM) containing 1000 mg/l glucose, 5% (v/v) foetal calf serum, as described previously \[[@B67]\]. Cells were incubated with hormones, at 37°C, for the times and at the concentrations indicated in the figure legends.
RNA isolation and RNase protection assay
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H4IIE cells were serum-starved overnight and treated with hormone/inhibitor for the times and at the concentrations indicated in the figure legends. Total cellular RNA was isolated using TriReagent™ (Sigma) following the manufacturer\'s instructions. An RNase Protection Assay (RPA) was performed to determine the relative amounts of IGFBP-1 and cyclophilin mRNA in each sample \[[@B26]\]. Band intensity was quantified on a phosphorimager (Fuji), data calculated as a ratio of IGFBP-1 to cyclophilin mRNA and presented as fold activation (for induced samples) where the intensity of control samples were set at one, or as % gene expression (for non-induced samples) where the level of gene expression in untreated cells is set at 100%.
Preparation of cell extract for western blot
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H4IIE cells were incubated in serum-free medium with hormones and inhibitors for the times and at the concentrations indicated in the figure legends. Cells were then scraped into ice-cold lysis buffer (25 mM Tris/HCl, pH 7.4, 50 mM NaF, 100 mM NaCl, 1 mM sodium vanadate, 5 mM EGTA, 1 mM EDTA, 1% (v/v) Triton X-100, 10 mM sodium pyrophosphate, 1 mM benzamidine, 0.1 mM PMSF, 0.27 M sucrose, 2 μM microcystin and 0.1% (v/v) 2-mercaptoethanol). Cell debris was removed by centrifugation at 13000 × g for 5 min and the protein concentration determined by the method of Bradford, using BSA as an internal standard.
Antibodies for western blot analysis
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Antibodies to phospho ribosomal protein S6 (Ser-235), phospho-FKHR-L1 (Thr-32) and GSK-3β were purchased from Upstate (Lake Placid, USA), while the phospho-specific Ser9/Ser21 GSK-3, Thr-308 PKB, Thr389-S6K1, and Thr-183/Tyr185 p42/p44 MAPK antibodies were purchased from Cell Signalling Technologies (Hertfordshire, UK). H4IIE cell lysates were prepared following incubation with hormones as described in figure legends and analysed by Western blot analysis.
Plasmids
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The plasmids BP-1 WT and BP-1 DM5 were a gift from Dr Robert Hall and Professor Daryl K. Granner (Vanderbilt University, TN, USA) \[[@B36]\]. The BP-1 WT plasmid represents a luciferase reporter construct under the control of a thymidine kinase promoter containing the IGFBP-1 TIRE wild-type sequence (5\'-CAAAACAAACTTATTTTG). Two base pair mutations of the wild-type TIRE sequence at residues equivalent to position 5 of each A and B site (5\'-CAAAA[G]{.underline}AAACTT[C]{.underline}TTTTG) produces a mutant promoter (BP-1 DM5) that is no longer responsive to insulin \[[@B36]\]. The FOXO-1 constructs have been described previously (10).
Transient transfections
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The TOPflash reporter plasmid kit were obtained from Upstate Biotechnology (Lake Placid, USA). TOPflash has Tcf binding sites driving luciferase expression. Tranfections were performed using the calcium phosphate procedure as described previously \[[@B10]\]. H4IIE cells were transfected in 10 cm dishes with BP-1 WT (10 μg), BP-1 M5 (10 μg), TOPFlash (10 μg), plus or minus 2 μg of GST-FOXO-1 as indicated. Cells were then incubated for 24 h in serum free media with or without hormones or inhibitors as described in figure legends. Cells were lysed in 300 μl lysis buffer (Promega, UK), the cell debris removed by centrifugation at 13000 × g for 2 min and the supernatant stored at -70°C. Luciferase assays were performed using the firefly luciferase assay system (Promega, UK), as per manufacturer\'s instructions, with luciferase activity being corrected for the protein concentration in the cell lysate.
Adenoviral infection
--------------------
H4IIE cells were infected with virus between a titre of 10^8^and 10^9^plaque forming units per ml, incubated at 37°C for 16 hr. Cells were then transfected with 10 μg of BP-1 WT as described above and incubated for a further 24 hr in the presence or absence of 10 nM insulin. Luciferase was harvested and assayed or cell extracts were prepared for western blot analysis, as described earlier.
Statistical analyses
--------------------
As a measure of statistical significance of differences in experimental groups, student t-tests were performed and 5% confidence limits applied.
Abbreviations
=============
G6Pase, glucose 6-phosphatase; IGFBP-1, IGF-binding protein-1; phosphatidyl inositol 3, kinase, PI 3-kinase; TIRE, thymine rich insulin response element; PKB, protein kinase B; PEPCK phosphoenolpyruvate carboxykinase; GSK-3, Glycogen synthase kinase 3
Authors contributions
=====================
The majority of the data was obtained in equal measure by D.F. and S.P, the CHIR99021 was synthesised, purified and analysed by N.S. and R.M., the adenoviral vectors were produced and characterised by L.M.D. and C.J.R., while the project was conceived and supervised by C.S.
Acknowledgements
================
We thank Professor Daryl K. Granner (Vanderbilt University, Nashville, TN), Dr Graham Rena (University of Dundee, UK) and Dr Matthew Coghlan (AstraZeneca, Alderly Edge UK) for reagents, and Laura Burgess for technical assistance. This work was supported by a BBSRC CASE award (SP, industrial partner Glaxo Smith Kline), while CS is a recipient of a Diabetes UK Senior Fellowship (RD02/0002473). The work was also supported by generous donations from the DDS Trust, The Royal Society, Tenovus and the Anonymous Trust in Scotland.
|
PubMed Central
|
2024-06-05T03:55:47.849348
|
2004-9-6
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517930/",
"journal": "BMC Mol Biol. 2004 Sep 6; 5:15",
"authors": [
{
"first": "David",
"last": "Finlay"
},
{
"first": "Satish",
"last": "Patel"
},
{
"first": "Lorna M",
"last": "Dickson"
},
{
"first": "Natalia",
"last": "Shpiro"
},
{
"first": "Rodolfo",
"last": "Marquez"
},
{
"first": "Chris J",
"last": "Rhodes"
},
{
"first": "Calum",
"last": "Sutherland"
}
]
}
|
PMC517931
|
Background
==========
Sounds are first converted into neuronal signals in the inner ear and then conveyed to the cerebral cortex via a number of discrete brain areas including the inferior colliculus. Each of these areas receives ascending pathways carrying signals from one or both ears and descending pathways from higher brain centres. The current knowledge of the neurochemical events occurring at each of these brain centres is limited \[[@B1],[@B2]\]. In the inferior colliculus studies have been carried out to characterise the role of GABAergic neurons especially in sound localisation which is believed to be one of the main functions of this brain area \[[@B3],[@B4]\]. Additionally the inferior colliculus has ben implicated in audiogenic seizures and aversive behaviour in which GABAergic neurons may also play an important role. \[[@B5],[@B6]\]
The neuronal communication occurring in the inferior colliculus is likely to be influenced by modulatory systems such as those of peptidergic neurotransmitters. Opiate receptor gene expression, immunoreactivity and activity in the inferior colliculus have been described \[[@B7]-[@B10]\] although detailed studies on the effect of opiate on GABA neurotransmitter release in this brain regions have not been carried out.
Three classes of opiate peptides endorphins, dynorphins and enkephalins activate μ, κ and δ-opiate receptors subtypes respectively \[[@B12]\]. Recently a fourth related receptor ORL1 activated by the peptide nociceptin has been identified and its distinct pharmacology has been described \[[@B13]\]. All opiate receptors are associated with either Go or Gi subunits and they mediate inhibitory actions including pre-synaptic inhibition of neurotransmitter release. Different mechanisms of inhibition of neurotransmitter release have been reported in various tissues and neurons \[[@B14]\]. For example, in the periaqueductal gray stimulation of opiate receptors and their associated G-proteins results in the activation of potassium channels \[[@B15]\] while in the hippocampus, inhibition of the GABAergic activity by opioid is independent of potassium channel activation \[[@B16]\].
In previous work we have established the presence and distribution of opiate receptors in the adult and developing rat cochlea suggesting that the opiate system has a role in hearing function \[[@B17],[@B18]\]. In order to extend our knowledge of the role of opiate system in hearing it is necessary to characterise its presence and role also in the auditory pathways. Our hypothesis was that opiate peptides can modulate synaptic function in the auditory pathways by pre-synaptically altering the release of other neurotransmitters. To test this hypothesis we have used opiate drugs to inhibit the release of \[^3^H\]GABA from inferior colliculus slices
Results and Discussion
======================
KCl-induced \[^3^H\]GABA release
--------------------------------
Inferior colliculus slices pre-incubated with \[^3^H\]GABA were perfused for 30 min and stimulated twice with 25 mM KCl to elicit neurotransmitter release. The eluate was collected in 1 ml fractions and the released radioactivity was assessed by scintillation counting. Figure [1](#F1){ref-type="fig"} shows two examples of typical release profiles from slices perfused with either Krebs buffer throughout (control) or with Krebs buffer for fractions 1--7 and with Krebs containing 1 μM morphine for the remaining fractions, where both samples were stimulated with KCl at the time corresponding to fraction 4 and 12. The two peaks were referred to as S1 and S2 and occured approximately 2 fractions after the application of KCl due to the buffer volume contained in the tubes feeding into the incubation chamber. Values of the radioactivity eluted are expressed as fractional release which is the ratio of the radioactivity released in a particular fraction divided by the total amount of radioactivity contained in the tissue immediately prior to that fraction. The variation in the value of S1 of the two profiles shown in Fig [1](#F1){ref-type="fig"}, both induced by KCl alone, reflects the variation in amount of tissue present in each of the elution chambers and illustrates the need for utilising the ratio of the two peaks (S2/S1) of each elution profile as a mean to detect the effect of the modulating drug.
Morphine modulation of KCl induced \[^3^H\]GABArelease
------------------------------------------------------
The effect of different concentrations of morphine on KCl-induced \[^3^H\]GABA release is shown in Figure [2](#F2){ref-type="fig"}. Both 1 μM and 5 μM but not 100 nM morphine caused a significant decrease of \[^3^H\]GABA release from the inferior colliculus slices. The effect of 1 μM morphine was antagonised by the antagonist naloxone (10 μM) which was perfused from one fraction before the addition of morphine. The perfusion of naloxone alone did not cause a significant effect on \[^3^H\]GABA release. These data strongly indicate that morphine modulates the release of \[^3^H\]GABA via activation of opiate receptors. The reduction in \[^3^H\]GABA release calculated as the change in S2/S1 ratios in the presence and absence of morphine during S2 was 16% (p \< 0.01). These data agree with previous reports on the presence of both GABA neurons and opiate receptors and peptides in the inferior colliculus \[[@B7]\]. In addition a functional inter-relationship is established between the two systems which could be of physiological significance.
Specific role of μ opiate receptors
-----------------------------------
In order to establish which of the opiate receptor subtypes are involved in the modulation of the \[^3^H\]GABA release, morphine was substituted by either 1 μM DAMGO, DADLE or U69593 which specifically activate μ, δ and κ opiate receptors respectively (Fig. [3](#F3){ref-type="fig"}). Only DAMGO (1 μM) had a significant effect on \[^3^H\]GABA release, an effect that was again antagonised by naloxone. DAMGO, as well as morphine, reduced the amount of \[^3^H\]GABA release by 16% (p \< 0.01) indicating that only μ opioid receptors participate in the regulation of GABA release. Higher concentrations of DAMGO (5 μM) did not have greater effects on \[^3^H\]GABA release (not shown). Data from our lab (unpublished) and from others \[[@B9],[@B10]\] indicate that mRNA transcripts or receptor binding for all three opiate receptor subtypes are present in the inferior colliculus. Further work is required to establish the roles of the δ - and κ-opioid receptors in the inferior colliculus.
Receptor desensitisation
------------------------
A possible explanation for the relatively low effect of opiate agonist on \[^3^H\]GABA release (16%) could be that during the exposure to opiate agonists, down-regulation of the opiate receptors may occur \[[@B19]\]. To address this possibility experiments were carried out in the presence of the protein kinase C inhibitor bisindolylmaleimide I (BIM). BIM has been shown to inhibit receptor desensitisation \[[@B20],[@B21]\] and to reverse tolerance to opiate drugs which involves opiate receptor desensitisation. \[[@B22],[@B23]\]. Because BIM is solubilised in DMSO additional control assays were carried out to check for the effect of the solvent. The results indicate (Fig. [4](#F4){ref-type="fig"}) that BIM had no effect on the extent of morphine inhibition of \[^3^H\]GABA release. While there is no direct proof that BIM had its reported effect on the tissue, the data indicate that receptor desensitisation may not be the cause of the relatively low percentage effect of morphine.
Co-localisation of μ-opiate receptors and GABAergic neurons
-----------------------------------------------------------
Another possible explanation for the small (16%) reduction of \[^3^H\]GABA release by opiate agonists may be the limited number of GABAergic neurons that express opiate receptors. To address this question inferior colliculi slices were double labelled with guinea pig antibodies against μ-opioid receptors and with rabbit antibodies against glutamic acid decarboxylase (the enzyme uniquely responsible for the synthesis of GABA) Species specific secondary antibodies conjugated to red and green fluorochromes allowed the detection of both antigens on the same slide (Fig. [5](#F5){ref-type="fig"}). Although these results were qualitative it was evident that staining of glutamic acid decarboxylase was more extensive than that of μ-opiate receptors and that only a few GABAergic neurons showed co-localisation of μ-opiate receptors. These data are consistent with the proposal that only a sub-population of GABAergic neurons are under the influence of opiate receptors. Establishing the nature of the GABAergic neurons that express opiate receptors will be an important task in understanding the role of opiate signalling in the inferior colliculus.
Conclusions
===========
This study has demonstrated that in the rat inferior colliculus slices opiate agonists can inhibit KCl-induced \[^3^H\]GABA release via activation of the μ-opiate receptor subtype. The amount of \[^3^H\]GABA released in presence of opiate agonists was 16% lower than in control slices. This relatively low level of decrease is probably not due to receptor desensitization occurring during the assay but rather to a relatively small population of GABAergic neurons in the inferior colliculus expressing μ-opiate receptors. The small effect of the opiate compounds could also indicate that modulation of GABA release is not their major role, but it could still be of physiological significance.
Together with its reported role in audiogenic seizures and aversive behaviour, the inferior colliculus is an important neuronal centre for auditory processing containing both ascending and descending fibres. The identification of the role of opiate peptides and possibly other modulatory system in the inferior colliculus and other areas of the auditory pathway may allow a better understanding of the mechanism of the hearing system and possibly offer a target for therapeutic intervention in hearing dysfunction. Alternatively, elucidation of the role opiate peptides in the inferior colliculus could provide information about regulation of audiogenic seizures and aversive behaviour.
Methods
=======
Materials
---------
Opiate agonist and antagonists, (Morphine, DAMGO \[d-Ala(2), N-Me-Phe(4), Gly(5)-ol\]-enkephalin, DADLE \[D-Ala2, D-Leu5\]-enkephalin, U69593 and naloxone were purchased from SIGMA, UK. Antibodies against μ-opiate receptor AB1774 (guinea pig polyclonal) and glutamic acid decarboxylase AB1511 (rabbit polyclonal) and species specific pre-absorbed secondary antibodies (donkey anti rabbit IgG FITC and donkey anti guinea pig IgG rhodamine) were purchased from Chemicon UK. Both antibodies were raised against synthetic peptides, and have been used in several immunocytochemical investigations of rat tissue. \[[@B24],[@B25]\] AB1511 recognises the two isoforms of the enzyme in a Western blot (65/68 KDa) while antibody AB1511 recognises μ-opiate receptors immunocytochemically in the same tissues as other simlilar antibodies and by insitu hybridisation (Chemicaon data sheets, <http://www.chemicon.com>) Krebs carbonate buffer: NaCl 118 mM, KCl 4.84 mM, CaCl~2~2.4 mM, NaHCO~3~25 mM, MgSO~4~1.8 mM KH~2~PO~4~1.2 glucose 9.5 mM.
Animals
-------
Sprague Dawley rats, approximately 200 g, were obtained from UCL Biological Services. All animal experiments were carried out in accordance to the Animal (Scientific Procedure) Act 1986, UK.
Slices preparations
-------------------
Rats were stunned and killed by cervical dislocation. The skull was opened and the whole brain removed. The inferior colliculus was dissected out by two coronal transections, the first between the cerebellum and the inferior colliculus and the second between the inferior colliculus and the superior coliculus. The slice was placed horizontally and medullar tissue ventral to the inferior colliculus was removed. The inferior colliculus was then placed on a tissue chopper and sliced into 250 μm coronal sections. Individual slices were separated under a dissecting microscope in Krebs buffer.
Neurotransmitter release
------------------------
As previously described, slices were incubated in 5 ml oxygenated (95% 0~2~/ 5% CO~2~) Krebs buffer containing GABA transaminase inhibitor aminooxyacetic acid (100 μM) at 32°C for 5 min \[[@B26]\]. \[^3^H\]GABA was added to give a final concentration of 11 nM and incubated in a shaking water bath for 30 min. Slices were distributed into 6 superfusion chambers between filter papers (Brandel Superfusion System) and perfused at 0.5 ml/min with oxygenated Krebs buffer. Following a 30 min perfusion required to reach a steady state (non-stimulated) \[^3^H\]GABA release, 2 min fractions (1 ml) were collected. In order to evoke sub-maximal GABA release the slices were perfused for 2 min with 25 mMKCl at 6--8 min and 22--24 min of the fractionation time (fraction 4 and 12). At the end of each experiment (17 fractions) the tissue and the filter papers were collected and incubated with 500 μl Soluene-350 for 20 min and neutralised with 200 μl of glacial acetic acid. Scintillant (Packard, Ultima Gold, 3 ml) was added to all tissue samples and eluted fractions and the radioactivity was measured by scintillation counting (Wallac 1409). Each drug treament was repeated in several experiments as indicated in the figures and the ratios of the S2/S1 peaks were averaged. Statistical significance of the effect of treatments was analysed by one way ANOVA using Excel (Microsoft, USA)
Immunocytochemistry
-------------------
Inferior colliculi were dissected as decribed above and fixed in 4% paraformaldehyde in phosphate buffer saline (PBS: 137 mM NaCl, 2.7 mM KCl, 4.3 mM Na~2~HPO~4~.7H~2~O, 1.4 mM KH~2~PO~4~pH 7.3) for 1 hour, washed 3 times in PBS and incubated overnight at 4°C in 30%sucrose in PBS. Coronal sections (20 μm) were cut with a cryostat and collected on poly-lysine coated glass slides and allowed to dry. The sections were blocked in 10% normal donkey serum diluted in PBS containing 0.25% bovine serum albumin and 0.1% Triton X-100 (PBS-A) for 30 min at room temperature. Subsequently, they were incubated for 12 hours at 4°C with the combination of primary antibodies (rabbit anti GAD and guinea pig anti mu opioid receptor) diluted 1:500 in PBS containing 1% bovine serum albumin and 0.3% Triton X-100 (PBS-B).. Slides were washed 3 × 10 min with PBS-B and incubated with secondary antibodies diluted 1:200 in PBS-B, for 2 hours at room temperature. The secondary antibodies used were donkey anti rabbit conjugated with fluorescein (AP182F) and donkey anti guinea pig conjugated with rhodamine (AP182R). Finally, the sections were rinsed in PBS-B for 10 min and in PBS for 2 × 10 min and then mounted in Citifluor (Agar). The immunoreactivity was visualized under the confocal microscopy (LSM 510 META Carl Zeiss, Germany).
Authors\' contributions
=======================
WT carried out the majority of the experiments, NJ carried out initial experiments and established assay conditions, JC provided expertise in neurotransmitter release studies and participated in the design of the study and analysis of the data, PP provided expertise in the double labelling studies, HD, AF and PG participated in the design of the study and analysis of the data, SOC conceived of the study and participated in its design and coordination. All authors read and approved the final manuscript.
Acknowledgements
================
WT was supported by Royal Golden Jubilee Award from the Thailand Research Fund. The work was supported by a CRIG Wellcome Grant (072145) to PG, AF, PP, SOC.
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Elution profile of KCl-stimulated \[^3^H\]GABA release from inferior colliculus slices. Inferior colliculus slices were incubated with 11 nM \[^3^H\]GABA for 30 min and perfused (0.5 ml/min) with Krebs buffer for 30 min in a Brandel superfiltration apparatus. Fractions (1 ml) were then collected every 2 min. Krebs buffer containing 25 mM KCl was loaded into the system at times corresponding to fraction 4 and 12 (short black lines) which elicited \[^3^H\]GABA release peaks in fractions 6--7 and fraction 14--15. Krebs buffer containing modulating drugs (1 μM morphine-long blue line) was added from the time corresponding to fraction 8. Scintillation fluid (3 ml) was added to the each fractionated eluate and to the solubilized tissue samples and counted. Data are expressed as fractional release which is calculated as the radioactivity released in one fraction divided by the amount of radioactivity present in the tissue just before that fraction. The two peaks from each elution profile are referred to as S1 and S2. The data from a representative experiment are shown.
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Effect of morphine on KCl-stimulted \[^3^H\]GABA release. The ratio of the integration of the peaks S2 over S1 was calculated for each elution profile. Morphine (0.1, 1 and 5 μM) and naloxone (10 μM) alone or together were perfused as described in figure 1 but naloxone perfusion was started one fraction earlier. Data represent averages ± SEM. Labels on the x-axis indicate concentration of drugs present during S2. Statistical difference was calculated using one-way ANOVA. The data indicates that 1 and 5 μM morphine caused a statistically significant 16% reduction of \[^3^H\]GABA release as compared to control (a) (p \< 0.01). This effect of morphine was blocked by the antagonist naloxone (c) which had no effect on its own (b).
:::
:::
::: {#F3 .fig}
Figure 3
::: {.caption}
######
Effect of subtype-specific opoid peptides on KCl-stimulted \[^3^H\]GABA release. DAMGO, DADLE and U69593 (1 μM) were perfused as described for morphine in Figure 1. Data represent averages ± SEM. Labels on the x-axis indicate concentration of drugs present during S2. Only the μ-opioid receptor specific neuropeptide DAMGO produced a statistically significant effect (p \< 0.01, One way ANOVA) on KCl-stimulted \[^3^H\]GABA release as compared to the controls (a) where no opiate drug was used. The effect of DAMGO was antagonised by 10 μM naloxone which was perfused from one fraction before the perfusion of DAMGO (b).
:::
:::
::: {#F4 .fig}
Figure 4
::: {.caption}
######
Effect of protein kinase C inhibitor bisindolylmaleimide I (BIM) on morphine modulation of \[^3^H\]GABA release. BIM is reported to reduce receptor desensitization and was used here to test whether morphine would elicit a bigger effect on \[^3^H\]GABA release in the presence of BIM. BIM is initially dissolved in DMSO whose effect on \[^3^H\]GABA release was also tested. BIM (1 μM) was present throughout the perfusion where indicated. Data represent averages ± SEM. Labels on the x-axis indicate concentration of morphine present during S2. The data show that morphine caused a reduction of \[^3^H\]GABA release as shown in Figure 2 but there was no statistical difference between experiments with or without BIM (One way ANOVA).
:::
:::
::: {#F5 .fig}
Figure 5
::: {.caption}
######
Confocal microscopy of cryosection of inferior colliculus slices stained with anti glutamic acid decarboxylase (green) and anti μ-opioid receptor antibodies (red). A : Central nucleus of inferior colliculus. B: Pericentral nucleus of inferior colliculus. Arrow head: example of GABAergic neurons not containing μ-opioid receptor (Green). Arrows: example of GABAergic neuron containing μ-opioid receptor (Yellow).
:::
:::
|
PubMed Central
|
2024-06-05T03:55:47.852104
|
2004-9-7
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517931/",
"journal": "BMC Neurosci. 2004 Sep 7; 5:31",
"authors": [
{
"first": "Walaiporn",
"last": "Tongjaroenbungam"
},
{
"first": "Nopporn",
"last": "Jongkamonwiwat"
},
{
"first": "Joanna",
"last": "Cunningham"
},
{
"first": "Pansiri",
"last": "Phansuwan-Pujito"
},
{
"first": "Hilary C",
"last": "Dodson"
},
{
"first": "Andrew",
"last": "Forge"
},
{
"first": "Piyarat",
"last": "Govitrapong"
},
{
"first": "Stefano O",
"last": "Casalotti"
}
]
}
|
PMC517932
|
Background
==========
In rat, deafferentation of one labyrinth (unilateral labyrinthectomy) results in a characteristic syndrome of ocular motor and postural disorders. These disorders have been divided into two categories : One category of symptoms, called static, includes head rotation in both the frontal and horizontal planes and ocular nystagmus \[[@B1]\]. The other category, called dynamic, corresponds to a decreased gain of the vestibulo-ocular and vestibulo-spinal refelxes \[[@B1]\]. Behavioral recovery (e.g., diminished symptoms), encompassing 1 week after unilateral labyrinthectomy, has been termed vestibular compensation \[[@B2]\]. Moreover, the time course of recovery is very different for static and dynamic reflexes: static deficits disappear in one week but dynamic deficits tend to take several months to normalize. Because unilateral labyrinthectomy results in a permanent loss of vestibular inputs from the lesioned side, the compensatory process is assumed to be attributable to the reorganization of the neural network in the central vestibular system \[[@B3],[@B4]\]. Many brain regions including, the medial vestibular nucleus (MVe), are implicated in this process of recovery \[[@B5]-[@B7]\].
The focus of our study is the histamine H~3~receptor that was initially characterized as an autoreceptor controlling histamine synthesis and release \[[@B8],[@B9]\]. Subsequently, as a heteroreceptor, the H~3~receptor was found to mediate presynaptic inhibition of release of histamine, noradrenaline, serotonin, dopamine, glutamate, GABA and tachykinins \[[@B10]-[@B13]\], presumably by inhibiting calcium channels \[[@B14]-[@B16]\]. The histamine H~3~receptor was recently cloned from human \[[@B17]\], monkey \[[@B18]\], rat \[[@B19]\], mouse \[[@B20]\], and guinea pig \[[@B21]\]. Moreover, the receptor was found to have several isoforms \[[@B21]-[@B26]\] with differential coupling to second messenger systems and a variation in their distribution in a region-specific manner. The isoforms are formed by alternative splicing of the messenger RNA (mRNA; \[[@B22],[@B24]\]). This study involves analysis of trends observed in mRNA expression levels for the H~3~receptor (H~3X~, the oligonucleotide probe detecting all H~3~receptor mRNAs characterized so far) as well as three of the known functionally active isoforms (H~3A~, H~3B~, and H~3C~), described by Drutel et al. \[[@B24]\], during the process of post-lesional plasticity in the central nervous system (CNS).
The primary source of histamine (e.g., ligand for H~3~receptors) are histaminergic perikarya located exclusively in the tuberomammillary nuclei of the posterior hypothalamus \[[@B27],[@B28]\]; these same neurons send axonal projections to many areas of the brain including the vestibular nuclear complex in rat \[[@B29]-[@B32]\]. The fact that the rat vestibular nuclear complex is endowed with the H~3~receptor was established by use of ligand binding \[[@B33],[@B34]\] and in situ hybridization methods \[[@B34]\].
Evidence suggesting that the H~3~receptor plays a key role in vestibular compensation comes from studies indicating that betahistine, a histamine-like drug that acts as both a partial histamine H~1~receptor agonist and an H~3~receptor antagonist \[[@B14],[@B35]\], accelerates the process of vestibular compensation \[[@B32],[@B36]\]. Furthermore, studies have shown that betahistine treatment results in a reduction of \[3H\]*N*-α-methylhistamine labelling in the vestibular nuclear complex \[[@B37]\]; these findings suggest that betahistine increases histamine turnover and release by blocking presynaptic H~3~receptors and inducing H~3~receptor downregulation \[[@B37]\]. It is noteworthy that dynamic vestibular functions can be modulated by H~3~receptor ligands, e.g., thioperamide \[[@B38]\]; moreover, thioperamide can affect tonic vestibular functions as well with its demonstrated ability to attenuate barrel rotation in rats following unilateral labyrinthectomy \[[@B39]\]. The forementioned studies make tenable the view that further elucidation of H~3~receptor regulation is required to fully understand the process of vestibular compensation.
The detailed aim of this study was to characterize the patterning of mRNA expression levels for all possible mRNA splice variants of the H~3~receptor (H~3X~; as described in \[[@B24]\]) and its isoforms which display different variations of the third intracellular loop (H~3A~, H~3B~, and H~3C~; as described in \[[@B24]\]) in the medial vestibular nucleus (MVe) during the process of vestibular compensation.
Moreover, in this study, we compared the aforementioned trend in mRNA expression levels with H~3~receptor binding densities to reveal the possible plastic changes in the H~3~receptor which is responsible for significant constitutive activity also *in vivo*\[[@B40]\], histamine-mediated regulation of neurotransmitter release, and therapeutic effects of betahistine.
Results
=======
Expression patterns of total H~3~receptor and H~3~receptor isoforms (H~3A~, H~3B~, and H~3C~)
---------------------------------------------------------------------------------------------
Changes in mRNA expression levels for H~3~receptor and the three H~3~receptor isoforms (Figure [1A,1B,1C](#F1){ref-type="fig"} and [1D](#F1){ref-type="fig"}, respectively) occured bilaterally; that is, there were no significant differences detected between the ipsilateral and contralateral medial vestibular nuclei of animals in all groups studied (e.g., control, 4 h post-lesion, 24 h post-lesion, 48 h post-lesion \[n = 4, for each group\], and 1 week post-lesion \[n = 5\]).
We compared the total H~3~receptor mRNA expression levels (using probe H~3X~) in ipsilateral MVe of control animals to that of test animals from the four time points (Fig. [1A](#F1){ref-type="fig"}). Fig. [2B](#F2){ref-type="fig"} shows scanned X-ray film depiction of H~3X~expression in a representative animal 24 h post-lesion. We found no significant rise in H~3X~mRNA levels in the ipsilateral MVe 4 hours after lesioning. Significant increases in H~3X~mRNA levels were found to occur at 24 and 48 hours post-lesion. After 1 week post-lesion, H~3~receptor mRNA expression levels (as indicated by probe H~3X~) returned to normal levels. The trend observed was similar when comparing H~3X~mRNA levels in contralateral MVe of control animals with that of test animals from the four time points. There was no significant change in total H~3~receptor mRNA levels detected in contralateral MVe 4 hours post-lesion, but we found a significant increase in H~3X~mRNA levels detected in contralateral MVe both 24 hours and 48 hours post-lesion. Finally, a return to normal levels in total H~3X~receptor mRNA level was detected in contralateral MVe 1 week post-lesion.
No significant increases in H~3A~mRNA expression levels were detected when we compared ipsilateral MVe in control animals with ipsilateral MVe 4 hours, 24 hours, and 48 hours post-lesion (Fig. [1B](#F1){ref-type="fig"}). Fig. [2D](#F2){ref-type="fig"} shows scanned X-ray film depiction of H~3A~expression in a representative animal 24 h post-lesion. On the other hand, a significant decrease of H~3A~mRNA levels does occur in the ipsilateral MVe 1 week after lesioning. The trend was identical when comparing H~3A~mRNA levels in contralateral MVe of control animals with H~3A~mRNA levels in contralateral MVe of animals from the four time points: There was no significant increase in H~3A~mRNA levels when comparing to contralateral MVe 4 hours, 24 hours, and 48 hours post-lesion; on the other hand, there is a significant decrease in H~3A~mRNA levels when comparing to contralateral MVe 1 week after lesioning.
No significant changes in H~3B~mRNA expression levels were detected when we compared ipsilateral MVe in control animals to ipsilateral MVe 4 hours post-lesion (Fig. [1C](#F1){ref-type="fig"}). Fig. [2F](#F2){ref-type="fig"} shows scanned X-ray film depiction of H~3B~expression in a representative animal 24 h post-lesion. Significant decreases in mRNA levels were found in the ipsilateral MVe 24 hours, 48 hours, and 1 week after lesioning. When comparing contralateral MVe of control animals to contralateral MVe of animals in the other time points, there was a significant increase detected 4 hours post-lesion and this was followed by significant decreases detected at 24 hours, 48 hours after lesion, and 1 week post-lesion.
No significant changes in H~3C~mRNA levels were detected when we compared ipsilateral MVe in control animals to ipsilateral MVe 4 hours post-lesion (Fig. [1D](#F1){ref-type="fig"}). Fig. [2H](#F2){ref-type="fig"} shows scanned X-ray film depiction of H~3C~expression in a representative animal 24 h post-lesion. A significant increase was detected when comparing ipsilateral MVe of control animals to ipsilateral MVe 24 hours post-lesion; moreover, the decrease in H~3C~mRNA levels in the ipsilateral MVe 48 hours post-lesion was not significantly different from those of the ipsilateral MVe in control animals. Finally, in comparison to the ipsilateral MVe in controls, there was a decrease in mRNA levels that was found to be significant in the ipsilateral MVe 1 week post-lesion. Results were similar when comparing the contralateral MVe in control animals to contralateral MVe from the other time points: There was no significant increase in H~3C~mRNA levels when comparing to contralateral MVe 4 hours post-lesion, there was a significant increase detected when comparing to contralateral MVe 24 hours post-lesion, the decrease was not significant comparing to contralateral MVe 48 hours post-lesion, and a significant decrease was detected when comparing to contralateral MVe 1 week post-lesion.
\[^125^I\]iodoproxyfan Binding Densities
----------------------------------------
No significant changes were found in H~3~receptor binding densities (Fig. [3](#F3){ref-type="fig"}) between ipsilateral MVe in control animals (n = 3) and ipsilateral MVe of animals of different time points. The results were identical when H~3~receptor binding densities in contralateral MVe in control animals were compared to that of contralateral MVe at different times post-lesion. On the other hand, when comparing the ipsilateral to contralateral MVe 48 hours post-lesion, a significant increase in binding densities occurred on the ipsilateral side (Fig. [4](#F4){ref-type="fig"} shows an example of H~3~receptor binding densities in a representative animal 48 h post-lesion).
Discussion
==========
Knowing that there is no reliable method to determine the efficiency of a probe for its targetted sequence in an mRNA of interest, this study focuses instead on the pattern of expression for the total H~3~receptor (detected by using probe H~3X~) and its isoforms (H~3A~, H~3B~, and H~3C~) occurring during the process of post-lesional plasticity in the CNS. Moreover, the probes used in this study were designed to detect unique areas in the transcripts (H~3A~), or junctional areas in deletion isoforms (probes H~3B~and H~3C~) which would make it highly unlikely for non-specific hybridization would occur. This study also includes a comparison of the aforementioned patterns of expression with binding densities for the H~3~receptor.
The prepositus nuclei are delineated and mentioned in legends for figures [2](#F2){ref-type="fig"} and [4](#F4){ref-type="fig"}. These nuclei are delineated for the sole purpose of giving the reader an idea of the dorsoventral extent of the MVe at the levels depicted in figures [2](#F2){ref-type="fig"} and [4](#F4){ref-type="fig"}. Noteworthy, is that these nuclei are not included in the main functional projections in the vestibulo-ocular and vestibulo-spinal pathways from the brainstem vestibular nucleus in mammals reviewed by Smith and Curthoys \[[@B2]\].
There are three previously described types of neurons in the medial vestibular nucleus \[[@B41],[@B42]\]; in vitro, all three types are depolarized by histamine \[[@B43],[@B44]\]. Moreover, this depolarization has been shown to be exclusively mediated through postsynaptic H~2~receptors \[[@B43],[@B44]\] suggesting a presynaptic localization of H~3~receptors in the medial vestibular nuclei \[[@B38]\]. Consequently, there are three possible locations for H~3~receptors in the MVe: 1) On the histaminergic or other incoming fibers innervating the MVe \[[@B29]-[@B32]\]. 2) On terminals of the inhibitory interneurons in the MVe that make synaptic contacts on second order excitatory neurons-defined as neurons in the vestibular nuclei that receive inputs from sensory afferents \[[@B45]\]. 3) On the terminals of second order excitatory MVe neurons making cross-commissural synaptic contacts on contralateral MVe inhibitory interneurons \[[@B45]\]. With respect to MVe on the lesioned side, an H~3~receptor mediated inhibition of GABA release from inhibitory interneurons or glutamate release from terminals of second order excitatory MVe neurons may underlie the restoration of resting activity in the deafferentated MVe; more precisely, H~3~receptor action would result in disinhibition of neurons in the deafferentated MVe
With respect to the first possible location, it has been established that histamine fibers are endowed with H~3~receptors that function as autoreceptors and inhibit histamine release \[[@B11],[@B13]\]. Support for the notion that H~3~receptors are at the next two possible locations (i.e., either at the terminals of the inhibitory interneurons or at the terminals of second order MVe neurons) comes from work showing that betahistine antagonizes the excitatory effect of histamine on vestibular neurons from *in vitro*slice preparations of the dorsal brainstem of the rat \[[@B46]\]. This finding is significant given that H~3~receptors mediate presynaptic inhibition of release of other neurotransmitters including: noradrenaline, serotonin, dopamine, glutamate, GABA and tachykinins \[[@B10]-[@B13]\]. Unilateral labyrinthectomy induced changes in expression levels of receptors for glutamate (e.g., NR1 and NR2A-D subunits of the NMDA receptor \[[@B47]\] and GluR2-4 subunits of the AMPA receptor \[[@B48]\]) have been studied in the vestibular nuclei. Moreover, the existence of both GABA~A~and GABA~B~receptors in the vestibular nuclei and their involvement in vestibular compensation has been demonstrated by either unilateral perfusion or microinjection of GABAergic agonists and antagonists (e.g., GABA, muscimol, and bicuculline) \[[@B49]\].
Consequently, an H~3~receptor antagonist such as betahistine could either facilitate GABA release from inhibitory interneurons located in the MVe that make synaptic contacts with second order neurons or facilitate glutamate release from terminals of second order MVe neurons that synapse on inhibitory interneurons in the contralateral MVe \[[@B31],[@B45]\]. Either scenario would lead to an inhibition of second order neurons in the MVe and this would explain the observation that betahistine antagonizes the excitatory effect of histamine on vestibular neurons \[[@B46]\].
On the other hand, betahistine administration is reported to induce recovery with a time benefit of 2 weeks relative to control animals after unilateral vestibular neurectomy \[[@B32],[@B36]\]; this is thought to be due to a bilateral increase in histamine release in the MVe \[[@B32],[@B37]\]. The increased histamine would be bound by H~2~receptors on the perikarya of MVe neurons ipsilateral and contralateral to the lesion resulting in a bilateral increase in activity. This should facilitate behavioral recovery as it is thought that an imbalance in discharge of MVe neurons (30--40 spikes/s in normal animals \[[@B4]\]) ipsilateral and contralateral to the lesion underlies the static postural and occulomotor deficits triggered by unilateral labyrinthectomy \[[@B45]\]. Yet, as stated before, the actions of betahistine would also extend to H~3~receptors located on glutamatergic terminals of contralateral MVe neurons or on GABAergic terminals of inhibitory MVe interneurons. Antagonism of H~3~receptors at either site may also act to speed recovery by increasing the amount of GABA output from terminals of inhibitory interneurons and, as a consequence, equalizing neuronal discharge activity of ipsilateral and contralateral MVe.
The trends toward bilateral increases (24 h post-lesion) followed by decreases (48 h post-lesion) in total H~3~receptor and H~3A~, and H~3C~isoform mRNA levels, with H~3B~mRNA levels already increasing at 4 hours post-lesion and decreasing at 24 h post-lesion, coinciding with a significant increase in H~3~receptor binding densities in the ipsilateral MVe detected 48 hours post-lesion suggests the occurrence of one or a combination of events in the ipsilateral MVe: 1) an increase in translation has occurred. 2) A change in receptor trafficking between intracellular stores and cell membrane has occurred so that it can be detected as an increase in H~3~receptor receptor binding densities. In either case, an increase in functional H~3~receptor protein coupled with an increase in receptor activity may lead to a restoration of resting activity in the deafferentated MVe by scenarios already mentioned in this section.
Conclusions
===========
Our findings are significant given that normalization of resting activities in neurons located in the ipsilateral MVe has been shown to occur 48 hours after unilateral labyrinthectomy \[[@B50]\]. Moreover, by 48 hours post-lesion, commissural disinhibition has been observed to occur \[[@B51]\]. Placement of H~3~receptors at the terminals of either GABAergic inhibitory MVe interneurons or on terminals of glutamatergic second order MVe neurons with contralateral projections should result in the observed commissural disinhibition as increased H~3~receptor activity would result in an inhibition of synaptic release of neurotransmitters.
Our data would thus suggest that H~3~receptors are involved in presynaptic mechanisms resulting in a normalization of resting activities in ipsilateral MVe neurons which would balance discharge activity in MVe on both sides.
Methods
=======
Animals and surgery
-------------------
This study was approved by the Local Committee for Animal Experiments and the Provincial State Office of Western Finland; in addition, animal experiments were in accordance with the European Convention (1986) guidelines and approved by the Animal Ethics Committee of Abo Akademi Unviversity. Adult male Sprague Dawley rats (200--250 g) were used. Intraperitoneal (ip) injection of pentobarbital (45 mg/kg ip; Mebunat, Orion, Finland) was used as an anesthetic; in addition, local anesthetic Lidocain (Orion, Finland) was infiltrated under the skin and periosteum prior the procedure. Three steps initiated the surgical procedure to left side of the animal\'s head: retroauricular skin incision, opening of the middle ear bulla with a drill, and removal of the ossicular chain with the aid of a microscope. Unilateral labyrinthectomy was carried out by opening the horizontal semicircular canal duct in the temporal bone, drilling through the horizontal and anterior semicircular canal ampullae and aspirating the contents of the vestibule. 100% ethanol was injected into the opened labyrinth to finalize the procedure; finally, the wound was sutured. The sham operation entailed opening the middle ear bulla and leaving the ossicular chain intact prior to suturing the wound, as described in Cameron and Dutia \[[@B52]\]; the control animals (n = 4) that underwent the sham operation were killed 4 h later. The method is explained hereafter. All rats included in the experiments displayed symptoms characteristic of animals that have undergone unilateral labyrinthectomy (e.g., barrel rotation, circling behavior, and spontaneuos nystagmus). These symptoms gadually disappeared during the first two or three days and were completely absent within one week. Animals were stunned by CO~2~gas and killed by decapitation 4 h (n = 4), 24 h (n = 4), 48 h (n = 4) and 1 week (n = 5) after labyrinthectomy.
Tissue preparation
------------------
After the mentioned decapitation, brains were removed, frozen in isopentane (-25°C), and stored at -70°C. Tissues were then cut to 20 μm thick cryosections, thaw mounted onto poly-L-lysine coated slides (Menzel-Gläser, Germany), and stored at -70°C until used.
In-situ hybridization histochemistry
------------------------------------
The oligonucleotide probes used for in situ hybridization were designed so that they specifically recognized the different H~3~receptor isoform mRNAs (H~3A~, H~3B~, and H~3C~; as described in \[[@B24]\]); an additional oligonucleotide probes was used to detect all characterized H~3~receptor isoforms (H~3X~; as described in \[[@B24]\]). Sequences for H~3X~, H~3A~, H~3B~, and H~3C~probes have been previously published \[[@B24]\]. It is noteworthy that the isoform-specific probes detect selectively the various deletion forms of the third intracellular loop, but do not differentiate between the possible alternative C-termini of the H~3~receptor isoforms \[[@B53]\]. However, it has been shown that the differences in the third intracellular loop are significant for coupling to intracellular second messengers \[[@B24]\]. As a control, we used a normal hybridization mixture with a 100-fold excess of unlabeled specific probes. As an additional control, we used a *Staphylococcus aureus*chloramphenicol acetyltransferase-specific oligonucleotide probe. The hybridization procedure used has been described before and was used with minor modifications \[[@B54],[@B55]\]. All probes were labeled with \[^35^S\]deoxyadenosine 5\'-α(-thio) triphosphate (New England Nuclear, USA) at their 3\' ends using terminal deoxynucleotide transferase (Promega, USA). Nonincorporated nucleotides were removed by purification through Sephadex G-50 columns.
Before hybridization, cryosections were taken from the -70°C environment and kept at room temeprature for 10 min and treated with UV light for 5 min. The hybridization (10^7^cpm/ml) was carried out at 50°C for 16 to 20 hours in a humidified chamber. Posthybridization washes were carried out as described previously \[[@B55]\]. Brain sections from control animals and animals 4 h, 24 h, 48 h, and 1 week post-lesion were treated simultaneously with their respective oligonucleotide probe. Sections and carbon-14 standards were exposed to Kodak BioMax X-ray films (Kodak, USA) for 10 days.
Receptor binding autoradiography
--------------------------------
Autoradiographic localization of \[^125^I\]iodoproxyfan binding sites has been described before \[[@B56]\]. Briefly, slide mounted tissue sections were preincubated for 15 min in 50 mM Na~2~HPO~4~-KH~2~PO~4~phosphate buffer, pH 6.8, containing 0.1% bovine serum albumin and 1 μM S132 (a 1-substituted imidazole derivative displaying a very low affinity at H~3~receptors and used to decrease non-specific labelling). The sections were then incubated for 1 hour at room temperature in the same buffer containing 15 pM \[^125^I\]iodoproxyfan (Amersham Pharmacia Biotech UK Limited, England). Non-specific binding was determined by incubating consecutive sections in the presence of 1 μM (R)α-methylhistamine (Sigma-Aldrich, Germany). At the completion of incubation, the tissues were washed four times (4 min each) in the same fresh ice-cold buffer, dipped into ice-cold water, and dried under a current of air. Brain sections from control animals and animals 4 h, 24 h, 48 h, and 1 week post-lesion were treated simultaneously. Dried sections, along with standards, were exposed to Kodak BioMax X-ray films (Kodak, USA) for 2 days.
Image analysis and statistics
-----------------------------
Autoradiographic films were quantified by digitizing the film images with a computer based MCID 5+ image analysis system (Imaging Research, Canada) and by measuring gray scale pixel values. The relative optic density was converted to integrated optic density (IOD) based on a standard curve derived from standards exposed to films. Gray scale values were determined from four sections for each animal, measurements from white matter of each respective section were subtracted to obtain the final values, and the data were analyzed using either a paired t-test or one-way ANOVA combined with Bonferroni\'s Multiple Comparison Test as a post-hoc test. Significance was determined when p \< 0.05.
Authors\' contributions
=======================
AL assisted with the surgeries and tissue collection, sectioned all of the brains, carried out the *in situ*hybridization and binding studies, performed all of the image and statistical analyses, and participated in the design of the study. AAA performed the surgeries, assisted with tissue collection, assisted with image analyses, and participated in the design of the study. KK established the method of *in situ*hybridization in the lab, designed the oligonucleotide probes, assisted with surgeries and tissue collection, and participated in the design of the study. HS synthesized and supplied rare chemicals required for the binding study. PP acquired funding, coordinated the study, and participated in its design. All authors read and approved the final manuscript.
Acknowledgements
================
Supported by the Academy of Finland (AFL and PP), Magnus Ehrnrooth\'s Foundation (AFL), Alcohol Research Foundation (AFL and PP), and Korvatautien tutkimussäätiö (AAA)
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
**A, B, C, and D -- Expression levels of the total histamine H~3~receptor (using probe H~3X~) and its three isoforms (H~3A~, H~3B~, and H~3C~) at 4 h, 24 h, 48 h, and 1 week post-lesion.**Data are presented as mean IOD ± SEM. Abbreviations are as follows: ipsi, ipsilateral; contra, contralateral; cntrl, control (n = 4); 4 h, animals sacrificed 4 h post-lesion (n = 4); 48 h, animals sacrificed 48 h post-lesion (n = 4); and 1 wk, animals sacrificed 1 week post-lesion (n = 5). \*\*\*p \< 0.001 and \*\*p \< 0.01 when compared to ipsilateral control. \#\#\#p \< 0.001, \#\#p \< 0.01, and \#p \< 0.05 when compared to contralateral control.
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
**A) Location of the MVe as visualized on cresyl violet stained section and on x-ray images of parallel sections used in *in situ*hybridization experiments with the various oligonucleotide probes: B) H~3X~C) H~3X~blocking control D) H~3A~E) H~3A~blocking control F) H~3B~G) H~3B~blocking control H) H~3C~I) H~3C~blocking control.**Sections are from a representative animal sacrificed 24 h post-lesion. Abbreviations are as follows: MVe, medial vestibular nucleus and Pr, prepositus nucleus. Scale bars are 100 μm.
:::
:::
::: {#F3 .fig}
Figure 3
::: {.caption}
######
**\[^125^I\]iodoproxyfan binding densities in MVe of labyrinthectomized rats.**Data are presented as mean IOD ± SEM. Abbreviations are as stated in Figure 1 legend. Sample sizes are as follows: control, n = 3; 4 h post-lesion, n = 4; 24 h post-lesion, n = 4; 48 h post-lesion, n = 4; 1 week post-lesion, n = 5. \*p = 0.0193.
:::
:::
::: {#F4 .fig}
Figure 4
::: {.caption}
######
**A) Location of the MVe as visualized at high magnification and B) at magnification used in analyses on cresyl violet stained section and C) on x-ray images of parallel sections used in \[^125^I\]iodoproxyfan binding experiments; D) non-specific binding control is represented in this image.**Sections are from a representative animal sacrificed 48 h post-lesion. Abbreviations are as stated in Figure 2 legend. Scale bars are 100 μm.
:::
:::
|
PubMed Central
|
2024-06-05T03:55:47.854098
|
2004-9-10
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517932/",
"journal": "BMC Neurosci. 2004 Sep 10; 5:32",
"authors": [
{
"first": "Adrian F",
"last": "Lozada"
},
{
"first": "Antti A",
"last": "Aarnisalo"
},
{
"first": "Kaj",
"last": "Karlstedt"
},
{
"first": "Holger",
"last": "Stark"
},
{
"first": "Pertti",
"last": "Panula"
}
]
}
|
PMC517933
|
Background
==========
Colorectal adenocarcinoma is a neoplasm in which prognosis is mainly determined by the histological stage. However, the prognosis of certain patient groups, especially those of intermediate stages, remains vague \[[@B1]\]. The main weakness of the currently used prognostic markers in colorectal adenocarcinoma, is their inability to point out patients without metastases, whose clinical course will progress unfavorably and patients with metastatic disease who will have a relatively better outcome \[[@B1]\]. Therefore, development of new prognostic markers is essential, as they might help in the planning of more effective treatment modalities. Markers of the host\'s immune response could potentially be helpful in this field.
Natural killer (NK) cells play a pivotal role in innate immunity and immunological surveillance. Their cytotoxic effects may be initiated without prior immunization and thus NK cells have been considered as a first line of defence of the host against a developing cancer \[[@B2],[@B3]\]. In spite of their small presence in tissue samples from colorectal adenocarcinomas, NK cells manifest a potent cytotoxic anti-tumor effect \[[@B3]-[@B5]\]. Expression of various protein surface markers is essential for these cells to perform their activities \[[@B2]\]. Among these markers, CD16 is used to identify active NK cells in immunohistochemical studies, while CD57 is expressed on NK cell-like elements.
The aim of this study was to evaluate tissue presence of NK cells in a series of colorectal adenocarcinomas and to attempt to correlate their presence with clinical and pathological variables and prognostic markers of colorectal cancer.
Methods
=======
From June 1997 to May 2000, 82 patients from our Department underwent colectomy, due to a diagnosis of colorectal adenocarcinoma of conventional histologic type. NK cell presence was examined via standard 3-step immunohistochemical analysis (ABComplex), which was performed on formalin-fixed, paraffin-embedded tissue sections. Briefly, two appropriate monoclonal antibodies were used (anti-Fc Gamma Receptor II, CD16 and an equivalent to Leu-7, specific for CD-57, Dako, Glostrup, Denmark) at dilutions of 1/200 with overnight incubation. Antigen retrieval was necessary and was performed by usual microwave treatment. In the examined samples, tissue identification of NK cells was based on strong CD16 immunostaining, which was frequently accompanied by CD57 immunoreactivity. Tissue sections from hypertrophic tonsils were used as positive markers. Diaminobenzidine tetrahydrochloride 0.06% in phosphate-buffered saline buffer containing 0.03% hydrogen peroxide was used as a chromogen. Images were acquired using a Zeiss Axiolab microscope (Carl Zeiss GmbH, Jena, Germany) with a mechanical stage, fitted in a Sony-iris CCD video camera (Sony, Tokyo, Japan). The video camera was connected to a Pentium II PC, loaded with the appropriate image analysis software (Sigma Scan Pro, Science, Erkrath, Germany). Slides were examined at a ×200 magnification. The ratio, expressed in percentile proportion (%), between the number of immunohistochemically positive-stained cells and the total number (stained and unstained) of lymphocytes was calculated. All tumors had been characterized according to the following classical clinical and pathological variables: patient gender (male 52, female 30, 63.4% and 36.6%, respectively) and age (mean: 75.9, median: 76, ranging between 35--95 years), tumor location (rectum 27, 32.9%, sigmoid 26, 31.7%, descending colon 4, 4.8%, transverse colon 5, 6%, ascending colon 10, 12.1%, cecum 10, 12.1%), size (mean diameter: 4.4 cm, median diameter: 4 cm, ranging between 1.2--10 cm), grade (I: 24 cases, 29.3%, II: 48 cases, 58.5%, III: 10 cases, 12.2%), bowel wall invasion (present in 66 cases, 80.5%), lymph node metastases (present in 33 cases, 40.2%) and Dukes\' stage (A: 5, 6.1%, B: 44, 53.7%, C: 29, 35.4%, \"D\": 4, 4.9%). All \"D\" Dukes\' stage cases involved hepatic metastases. The tumors were categorized according to their location into two larger groups: those involving the rectum as well as the left colon (57 cases, 69.5%) and those involving the right colon (25 cases, 30.5%). This was performed for reasons of statistical analysis.
Moreover, positive cases were divided into two groups: those in which immunopositive cells ranged from 0--9% of the total number of lymphocytes (\"weak\" tissue presence of NK cells) and those in which they were ≥10% (\"strong\" NK cell presence). This was performed somewhat arbitrarily, as we considered that the cutoff level of 10% is in accordance to what a pathologist would consider to be the cutoff level between \"negative\" and \"positive\" cases in a qualitative examination, and in order to perform statistical analysis. Associations of NK cell presence with the patients\' sex, tumor location, grade, and presence of bowel wall invasion, as well as lymph node metastases and Dukes\' stage were examined using chi-square statistics; associations with the patients\' age and tumor size were determined using the Mann-Whintey U test.
Results
=======
NK cells were detectable in the primary tumor site of 79 cases (96.3%); their percentages were up to 32% of the primary site lymphocytes (Figure). Of the 33 cases with metastatic lymph nodes, NK cells were found in 27 cases (81.8%); moreover, NK cells were found among liver lymphocytes in 3 of the total 4 cases with hepatic metastases (75% of stage \"D\" cases).
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Presence of NK cells within cancerous formations. (ABC, magnification ×250).
:::
:::
Forty-nine of the 82 primary tumors (59.8%) had a \"weak\" tissue presence of NK cells (0--9%), whereas the remaining 33 primary tumors (40.2%) had a \"strong\" NK cell presence (≥10%). Of the 33 cases with metastatic lymph nodes, 18 cases (54.5%) had \"weak\" and 15 \"strong\" NK cell presence.
NK cell presence in the primary tumor site was not associated with the patients\' sex (chi-square, p = 0.462), tumor size (Mann-Whintey U test, p = 0.377), tumor location (chi-square, p = 0.262), tumor differentiation (chi-square, p = 0.556), wall invasion (chi-square, p = 0.999), the presence of metastatic lymph nodes (chi-square, p = 0.720), or Dukes\' stage (chi-square, p = 0.992). However, a negative association between the presence of NK cells at the primary tumor site with the patients\' age was noticed (Mann-Whitney U test, p = 0.031).
Moreover, the presence of NK cells in the metastatic lymph nodes was not associated with the patients\' sex (chi-square, p = 0.999), age (Mann-Whintey U test, p = p = 0.212), tumor size (Mann-Whintey U test, p = 0.729), tumor location (chi-square, p = 0.442), tumor differentiation (chi-square, p = 0.872), wall invasion (chi-square, p = 0.999), or Dukes\' stage (C or D) (chi-square, p = 0.308).
Discussion
==========
Although colorectal adenocarcinoma has been characterized as a model neoplasm in which clinical prognosis is mainly determined by the histological stage, pathologic markers often fail to predict the prognosis of a great number of patients. This has necessitated the evaluation of several alternative prognostic markers \[[@B1]\]. Immunohistochemical studies have proved useful in the evaluation of such potential markers; although they are relatively cheap and easy-to-perform, they may be as effective as other advanced molecular techniques in determining the role of several molecules in human carcinogenesis \[[@B6]\].
CD16 and CD57 were chosen in the present study, as they are markers of the presence of NK cells, a cellular line which could reasonably play a significant role in the pathophysiology of colorectal adenocarcinoma. NK cells were considerably present in the primary tumor site, as well as the metastatic lymph nodes of many cases in our series. This observation is in line with data deriving from the literature \[[@B7]\]. NK cell presence had no correlation with the clinical or pathological variables of our series, besides a negative association between their presence at the primary tumor site and the patients\' age (p = 0.031), i.e. less NK cells were found in the stroma of the primary tumor site in the older patients of our study. Reports concerning alterations of the number and/or the cytotoxicity of NK cells in patients of older ages seem to be controversial \[[@B8]-[@B14]\]; this has been attributed to the diversity of the parameters examined in these studies \[[@B8]\]. In most reports, advanced age results in an increase of the number of circulating NK cells \[[@B8]-[@B10]\]; however, other studies point out that although total levels of NK cells actually remain steady, some of their biologically active sub-populations actually diminish \[[@B11],[@B12]\]. The cytotoxicity of NK cells on the other hand, has been reported to increase \[[@B13]\], remain steady \[[@B8],[@B14]\] or diminish \[[@B12]\] in patients of older age; some reports connect presence of certain nutrients and hormonal factors with the maintenance of NK cytotoxicity in these patients \[[@B8],[@B14]\].
However, what seems to be pivotal for rapid and efficient migration of NK cells from the circulation to the tumor stroma, is the expression of appropriate adhesion molecules \[[@B15]\]. As expression of adhesion molecules in lymphocytes, monocytes and the interstitial tissue decreases with age \[[@B16]\] this might result in decreased adhesion molecule-mediated migration of NK cells to the tumor stroma in the older-aged patients of our series; this could possibly explain the negative association observed in our study \[[@B5],[@B15]\].
In conclusion, our findings suggest that less NK cells are found in the stroma surrounding the primary tumor site in older patients with colorectal adenocarcinoma. This could possibly be attributed to decreased adhesion molecule-mediated migration; however, this hypothesis needs to be further investigated through more studies.
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1471-230X/4/20/prepub>
|
PubMed Central
|
2024-06-05T03:55:47.856740
|
2004-9-13
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517933/",
"journal": "BMC Gastroenterol. 2004 Sep 13; 4:20",
"authors": [
{
"first": "Ioannis S",
"last": "Papanikolaou"
},
{
"first": "Andreas Ch",
"last": "Lazaris"
},
{
"first": "Periklis",
"last": "Apostolopoulos"
},
{
"first": "Nikos",
"last": "Kavantzas"
},
{
"first": "Maria G",
"last": "Papas"
},
{
"first": "Christos",
"last": "Mavrogiannis"
},
{
"first": "Efstratios S",
"last": "Patsouris"
},
{
"first": "Athanasios",
"last": "Archimandritis"
}
]
}
|
PMC517934
|
Background
==========
Brain Cell Membrane Protein 1 (BCMP1) cDNA was fortuitously isolated from a thyroid cDNA library \[[@B1]\]. It encodes a 181aa-long putative four-transmembrane domain protein which appears related to both Peripheral Myelin Protein 22 / Epithelial Membrane Proteins and Claudins protein families, and exhibits significant similarities to the *Caenorhabditis elegans*VAB-9 protein, a protein that has recently been shown to be involved in the control of cell adhesion and epidermal morphology \[[@B2]\]. The protein sequence itself has been extremely well conserved during evolution, as exemplified by the observation that human and canine sequences are identical and differ from the mouse sequence at only 2 positions. The corresponding gene has now been renamed TM4SF10 in man and mouse, and is located on the X chromosome in both species, as well as in the other mammalian species investigated to date \[[@B1]\].
Initial Northern blot analysis of TM4SF10/BCMP1 gene transcripts distribution in adult dog tissues revealed very high expression in the brain, and lower but clearly detectable levels of expression in most of the tissues examined \[[@B1]\]. Data mining in the SAGEmap database \[[@B3]\] confirmed this observation in man, as elevated tag counts have been reported in brain astrocytoma (SAGE H127 library), brain ependymoma (SAGE ependymoma 353 and 582 libraries) and normal spinal cord (SAGE normal spinal cord library) as compared to other tissues. Together with its localization on the X chromosome, the high expression level detected in the brain and the putative role of the encoded protein in specific cell contacts raised the possibility that the TM4SF10 gene may be involved in X-linked mental retardation (XLMR) in man.
Initially, the TM4SF10 gene was assigned to Xp11.4 \[[@B1]\]. As the integration between human cytogenetic and DNA sequence-based maps is still evolving, the gene has been reassigned to band p21.1. It is noteworthy that TM4SF2, another gene encoding a four-transmembrane domain protein, is located at the p11.4-p21.1 border on human chromosome X, in the very close vicinity of TM4SF10, and constitutes a known XLMR gene \[[@B4],[@B5]\]. Recent compilations of XLMR families \[[@B6]-[@B8]\] mention several conditions mapped to the Xp11.4-p21.1 region. We report the result of mutation screening of TM4SF10 in a cohort of XLMR patients whose gene was mapped to this region of the X chromosome and does not correspond to TM4SF2.
Methods
=======
Blood genomic DNA was collected from 16 patients (14 unrelated) and 5 unrelated healthy volunteers using a standard procedure \[[@B9]\]. The patients were affected males from families with definite, or possible, linkage to the region at Xp11.4-p21.1. Patients belonged to the following published MRX(S) families: MRX9 \[[@B10]\], MRX10 \[[@B11]\], MRX11 \[[@B11]\], MRX12 \[[@B11]\], MRX18 \[[@B12]\], MRX56 \[[@B6]\] and MRXS10 \[[@B13]\]. Additional patients were from an XLMR family with epilepsy \[[@B14]\] and 4 other XLMR families (C.S., F.K., J.G., unpublished), a MRXS family with macrocephaly and large ears (C.S., unpublished), and another MRXS family (J.G., unpublished). Chromosomal linkage data and major phenotypic traits are described in table [1](#T1){ref-type="table"}. All samples were studied anonymously and all procedures met the standards of our institutional ethics committee.
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Description of the patients included in the study
:::
Patient Family Linkage data Phenotype
--------- -------------------------------------- ------------------------------- ----------------------------------------------------------------------------------------------------------
P1, P2 XLMR family (F.K., now MRX79) chromosome X X-linked mental retardation
P3, P4 MRXS10 Xp11.21-Xp11.4 Mental retardation, choreoathetosis, abnormal behavior
P5 XLMR family (F.K.) Chromosome X, pericentromeric Non-syndromic mental retardation
P6 MRX9 Xp11.22-Xp11.4 Non-syndromic mental retardation
P7 MRX10 Xp11.3-Xp21.2 Non-syndromic mental retardation
P8 MRX11 Xp11.3-Xp21.2 Non-syndromic mental retardation
P9 MRX12 Xp11.21-Xp21.2 Non-syndromic mental retardation
P10 MRX18 Xp11.3-Xp21.2 Non-syndromic mental retardation
P11 XLMR family with epilepsy Xp11.23-Xp22.22 Non-syndromic mental retardation, epilepsy
P12 MRXS family (J.G.) Xp21.3-Xq21.3 Non-syndromic mental retardation
P13 XLMR family with macrocephaly (J.G.) Xp11.4-Xq13.1 Macrocephaly, moderate to profound mental retardation
P14 XLMR family (C.S.) Xp11.3-Xp21.1 Seizures, ataxia, aggressive and hyperactive behavior, speech delay, mild to moderate mental retardation
P15 MRXS (C.S.) Xp22.22-Xq24 Macrocephaly, prominent ears and moderate to severe mental retardation
P16 MRX56 Xp11.21-Xp21.1 Non-syndromic mental retardation
:::
PCR reactions were performed in a final volume of 100 μl containing 200 ng of genomic DNA, 1 μg of each primer (see table [2](#T2){ref-type="table"} for primer sequences), 200 μM of each dNTP, 1X PCR buffer (QIAGEN) and 2.5 units of Taq polymerase (QIAGEN). Additionally, 10% DMSO or 20% Q solution (QIAGEN) were also included in some reactions (see table [2](#T2){ref-type="table"}). After an initial denaturation step (93°C, 45 sec.), 35 cycles were conducted as follows: 93°C, 45 sec.; annealing temp. (see table [2](#T2){ref-type="table"}), 45 sec.; 72°C, 45 sec. (amplicons Ex1--Ex3) or 1 min. (amplicons 3\'UTR F1--F4). A final extension step (72°C, 3 min.) was done at the end of the reaction. PCR products were purified using the QIAquick PCR purification kit (QIAGEN) before sequencing. Purified PCR fragments were roughly quantitated by agarose gel electrophoresis using SmartLadder molecular weight marker (EUROGENTEC) as a quantitative reference.
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
PCR conditions and primer sequences used to amplify TM4SF10 gene fragments from total genomic DNA
:::
Amplicon Size Primer sequence PCR conditions
----------- --------- ------------------------------------------------------------- ---------------------------------
Ex1 442 bp fw: AGAGCCCCGAGGGAGCGA, rev: GGGGACAGGCGGTGACTG T~anneal~= 55°C, 10% DMSO
Ex2 447 bp fw: AAATCCTAGCAAACCCCTGG, rev: TCTGCATAGGAAAGGAAGATGG T~anneal~= 50°C
Ex3 447 bp fw: CCATCTAGAACAAGCCATCTTTAA, rev: TAAATCAACTGAGCAAACTGCTTG T~anneal~= 50°C
3\'UTR F1 959 bp fw: GGCCTGGGGTGCAACTATAT, rev: TAGGCAAATGTATGTGGAGGGT T~anneal~= 55°C, 10% DMSO
3\'UTR F2 1101 bp fw: ATTGGTGCCTCAGCCCTATCTA, rev: GCAACCATTCTTAAGACAAGCT T~anneal~= 57°C, 20% Q solution
3\'UTR F3 1130 bp fw : CAGTATGTTCTGGTTTTGGCCC, rev : TATCTAACAATGGGTTTGTGGC T~anneal~= 57°C, 20% Q solution
3\'UTR F4 1097 bp fw : CCTTCTCAGCAAAGAGCCCTAC, rev : AAGGATCTTGGGAGATAATTTG T~anneal~= 57°C, 20% Q solution
:::
About 50--100 ng of purified PCR fragment was used in a DNA sequencing reaction using a nested, internal primer. DNA sequencing was performed using ABI PRISM BigDye Terminator Cycle Sequencing Ready Reaction kit (Applied Biosystems) on an Applied Biosystems 3100 automatic DNA sequencer. The sequences of the primers are given in table [3](#T3){ref-type="table"}.
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Sequences of the primers used for sequencing of TM4SF10 gene fragments
:::
Amplicon Primer sequence
----------- ------------------------------------------------------------------------------------------
Ex1 fw: CCGAGGGAGCGAGTCCCC
Ex2 fw: CACATCTGTTGAGCCACTGC
Ex3 rev: GATGCTCCACAAGTGTTTTAGA
3\'UTR F1 fw : TGCCTGAACCCTAAGAACTATG, rev : GGAGGGTTAGGGAACAACTTAT
3\'UTR F2 fw : CTGCATGAGTTGCTTTTGTACC, rev : GCAACCATTCTTAAGACAAGCT
3\'UTR F3 fw : TCTGTTAAGAGCAGGACCACAT, rev1: ACTCGAGATGTGATGATATTGG, rev2 : TATCTAACAATGGGTTTGTGGC
3\'UTR F4 fw : AACATGAAAATTGTTGCTTCTC, rev : AAGGATCTTGGGAGATAATTTG
:::
Results and discussion
======================
Sequencing of TM4SF10 coding region
-----------------------------------
The human TM4SF10 gene is composed of 3 exons and produces a 4 kb-long mRNA. The short coding region (543 bp) is interrupted by 2 introns and the last and the largest exon also contains a 3 233 bp-long 3\'UTR (see Figure [1](#F1){ref-type="fig"}). Initially, we sequenced the coding region and exon-intron junctions of the gene in the DNAs from 16 XLMR patients and from one normal male (amplicons Ex1--Ex3, Figure [1](#F1){ref-type="fig"}). No mutations were identified. One silent polymorphism was observed at position 186 in the cDNA sequence (clone DKFZp761J17121; GenBank accession number AL136550), corresponding to the 3^rd^base of the codon Arg59, where a C residue was present in half of the sequences and a G residue in the other half. Individual single nucleotide polymorphism (SNP) data are shown in table [4](#T4){ref-type="table"}. It is noteworthy that patients P3 and P4 who belong to the same family exhibit a difference in their TM4SF10 gene sequence at this level. This observation argues against a causal role of the gene in this family. The 186C\>G polymorphism in the TM4SF10 gene had been previously reported \[[@B15]\].
::: {#F1 .fig}
Figure 1
::: {.caption}
######
**Schematic of the TM4SF10 gene and single nucleotide polymorphisms identified in the study.**The structure of the gene is outlined with exons represented as light-blue boxes and the coding region as dark-blue areas within the boxes. The 3\' end of the gene is also enlarged (bottom). Amplified regions are delineated and locations of sequence primers (arrows) used in this study are depicted. Identified SNPs are indicated (dotted lines) with reference to genomic contig (GenBank accession number NT\_011757) sequence coordinates and cDNA (clone DKFZp761J17121; GenBank accession numberAL136550) sequence coordinates (italics) when relevant. Numbers in parentheses indicate the occurrences of the nucleotide in the individual sequences. The 3 novel SNPs identified in the work appear in red.
:::
:::
::: {#T4 .table-wrap}
Table 4
::: {.caption}
######
Description of the individual TM4SF10 gene SNP haplotypes determined in this study
:::
Exon 1: 186 (Arg59), \[21589434\] 3\' UTR: 705, \[21562747\] 3\' UTR: 2870, \[21560583\] 3\' UTR: 2907, \[21560546\] 3\' intergenic: \[21559611\]
----- ----------------------------------- ---------------------------- ----------------------------- ----------------------------- ------------------------------
N1 C C G T C
N2 (n.d.) C C C C
N3 (n.d.) C C T C
N4 (n.d.) T C T T
N5 (n.d.) C C T C
P1 C T C T T
P2 C T C T T
P3 G C C T C
P4 C C C T C
P5 G C C T T
P6 G C C T T
P7 G C C T C
P8 G C C T C
P9 G C C T C
P10 C C C T T
P11 C T C T T
P12 G C C T C
P13 G C C T C
P14 C C C T T
P15 C T C T T
P16 G C C T C
The first row identifies the source of the DNA, either a normal individual (Nx) or a patient (Px; see also table 1 for the detailed description of the patients). The individual bases found at each polymorphic position in the DNA sequence (identified by the nucleotide position in the cDNA sequence and/or in the genomic contig sequence \[in square brackets\]; see also figure 1) are given in the following rows. (n.d.): not determined.
:::
Sequencing of the 3\'UTR
------------------------
The long 3\'UTR sequence of the TM4SF10/BCMP1 transcript is highly conserved, with an overall score of 72% when human, dog, mouse and rat sequences are compared. As the 3\'UTR of mRNAs may contain regulatory sequences that participate in the control of gene expression, we decided to screen this part of the gene as well. The entire region, including the sequences around the polyadenylation site, was subdivided into four overlapping fragments of approximately 1 kb in length (3\'UTR F1--F4, Figure [1](#F1){ref-type="fig"}) and sequenced from both ends. In fragment 3\' UTR F3 the presence of a stretch of 12 consecutive A residues on the sense strand resulted in difficulties in proper reading of the sequences located downstream of this motif. In order to overcome this problem, an additional sequence primer (rev2) was used to obtain overlaps between the 3 separate sequences for each individual fragment. In the cDNA sequence AL136550 the motif is composed of 13 A residues, which is a likely sequence artefact.
TM4SF10 sequence was obtained from 16 patients and 5 controls. Four SNPs were identified in the non-coding part of the gene: 3 of them were located in the 3\'UTR of the mRNA while the fourth one was located downstream of the polyadenylation site (Figure [1](#F1){ref-type="fig"}). Only this last one (C21559611T) had been previously reported in the SNP database \[[@B15]\], the other three representing novel SNPs in the TM4SF10 gene. The individual SNP haplotypes determined here are described in table [4](#T4){ref-type="table"}. It is also noteworthy that during the course of our investigation, the genetic defect of one of the unpublished XLMR family included in the study (see top of table [1](#T1){ref-type="table"}) has been identified and mapped to Xq28, within the MECP2 gene \[[@B16]\].
Conclusions
===========
In this study, we have investigated the majority of the known MRX families linked to the TM4SF10 gene region. In the absence of mutations detected, our results indicate that alterations in the transcribed region of TM4SF10 are not a frequent cause of XLMR. Although the gene promoter has not been identified and screened yet, it appears very unlikely that all mutations would be there.
This work also identified three novel SNPs in the TM4SF10 gene, which adds to our knowledge of SNP occurrence within this gene.
Competing interests
===================
None declared.
Authors\' contributions
=======================
CCH performed/managed the PCR and sequencing reactions, and analyzed the DNA sequences. FK, JG, MJA, EHF and CS provided the DNA samples. These authors also participated in the writing of the manuscript. DC conceived and supervised the study, and drafted the manuscript. All authors read and approved the final manuscript.
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1471-2350/5/22/prepub>
Acknowledgements
================
We thank G. Hoganson for providing material on his MRXS family. We also thank Nathalie Celio and François Gensale for expert technical assistance. This work was supported by the Belgian program \"Pôles d\'Attraction Interuniversitaires\" (PAI, Prime Minister\'s Office, Science Policy Programming) and the Fonds National de la Recherche Scientifique (FNRS-FRSM, Belgium). C.S. is supported by NIH grant HD26202. D.C. is a research director of the Belgian FNRS.
|
PubMed Central
|
2024-06-05T03:55:47.857728
|
2004-9-2
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517934/",
"journal": "BMC Med Genet. 2004 Sep 2; 5:22",
"authors": [
{
"first": "Christiane",
"last": "Christophe-Hobertus"
},
{
"first": "Frank",
"last": "Kooy"
},
{
"first": "Jozef",
"last": "Gecz"
},
{
"first": "Marc J",
"last": "Abramowicz"
},
{
"first": "Elke",
"last": "Holinski-Feder"
},
{
"first": "Charles",
"last": "Schwartz"
},
{
"first": "Daniel",
"last": "Christophe"
}
]
}
|
PMC517935
|
Background
==========
The H-Reflex evaluates S~1~radiculopathy \[[@B1]\]. The measured latency, however, is neither specific nor sensitive for S~1~spinal nerve disease, as it traverses a long pathway. Pease et al \[[@B2]\] were the first who described the central loop of the gastrocnemius-soleus H-Reflex latency (Central S~1~loop latency or T~c~) and suggested it might be promising in the diagnosis of S1 radiculopathy \[[@B1],[@B2]\].
Unfortunately, T~c~has been the subject of few studies, and as far as we know, only 5 articles \[[@B2]-[@B6]\] have been published on this issue so far. Among them, two have specifically evaluated the constitutional factors contributing to T~c~. Leg length has been shown to have a significant effect on T~c~. It is controversial whether age entails a similar effect. Wang et al \[[@B5]\] found a direct correlation between age and Tc. This observation was not confirmed by Ghavanini et al in an independent study \[[@B6]\].
The current study has been performed to determine the influence of leg length and age on T~c~.
Methods
=======
We enrolled 46 volunteers to this study after obtaining informed consent. Following a standard history taking, all of them underwent physical examination and a brief electrophysiologic evaluation \[[@B7]\] to rule out asymptomatic polyneuropathy, including determination of: right peroneal nerve conduction velocity (PNCV), distal motor latency of right deep peroneal nerve (PDML) and standard gastrocnemius-soleus H reflex latency (T~p~). We defined our exclusion criteria as: history of sacral radiculopathy or diabetes mellitus or any other disease with potential to cause neuropathy, any abnormality in neurological or musculoskeletal physical examination, or any of the following findings: PNCV less than 40 m/s, PDML more than 5 ms or prolonged T~p~(according to Braddom and Johnson\'s study \[[@B8]\].
Since we were supposed to rule out subclinical peripheral neuropathy and one component of the related electrodiagnostic study was measuring the distal motor latency for the deep peroneal nerve, the temperature at the dorsum of the foot was kept almost at 32°Celsius.
The leg length of each person was measured as the distance from middle of the midpopliteal crease to the point at the most proximal part of the medial malleolus, in centimeters.
Subject\'s age to the nearest year was also recorded.
For obtaining T~c~, we used DANTEC 2000 c equipment, the sensitivity, sweep, and filter were set at: 0.2--1^mv/div^, 5^ms/div^, and 2--10,000^Hz^respectively. The technique was the same as described in the Literature \[[@B1],[@B2]\]. Briefly: the volunteers lied prone on the examining table with the feet off the edge of the plinth. The E~1~was placed at the middle of the line connecting midpoint of popliteal crease to the point at the most proximal part of the medial malleolus, and the E~2~over the Achilles tendon (both were surface electrodes). The ground electrode was posed proximal to E~1~and a disc electrode (anode) was placed on the anterior superior iliac spine. Then we inserted a monopolar 70^mm^needle (cathode) at a point 1^cm^medial to the posterior superior iliac spine, perpendicular to the frontal plane, and retracted it just a little after reaching the sacrum. Stimulus duration of 1 ms at 0.5 HZ was then applied while increasing current intensity to obtain both H and M waves simultaneously. M wave is the earlier wave and H is the later one. The interpeak latency was measured in milliseconds (ms) and recorded as T~c~. This measurement was only performed on the right lower extremity.
Descriptive statistics were applied to depict Mean ± SD of age, leg length and Tc. The independent effect of leg length and age on T~c~was assessed by multiple regression model. The analyses were performed using SPSS 10.0 software. Kolmogrov-Smirnov test was used for evaluating the normal distribution of the variables.
Results
=======
From 46 subjects who volunteered to participate in this study; five cases were excluded after history taking and physical examination (two because of history of sacral radiculopathy, two because of diabetes mellitus and one because of asymmetry in ankle reflexes) and one case after electrophysiologic evaluation; thus we completed the study with 40 subjects. Subjects\' characteristics are shown in table [1](#T1){ref-type="table"}.
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
subjects\' characteristics
:::
-------------------------- ---------------------------
Number of subjects 40 (26 males, 14 females)
Age range (years) 19--65
Leg length (centimeters) 29.5--43
T~c~± SD 6.78 ± 0.3
-------------------------- ---------------------------
:::
The group consisted of 26 males (65%) and 14 females (35%). Kolmogrov-Smirnov test showed normal distribution of the variables.
You are provided with the information below: (Mean ± SD) Age: 37.0 ± 10.7 years (range: 19--65); leg length: 36.4 ± 3.4 cm (range: 29.5--43); Tc= 6.78 ± 0.3 There was a significant correlation between T~c~and leg length (P value = 0.003, r= 0.49, CI 95% = 0.59--0.88).
There was no correlation between T~c~and age (p value = 0.48, r = 0.11) We also found this regression equation: T~c~= 0.04L + 5.28 (L is leg length in centimeters, T~c~is represented in milliseconds.)
Discussion
==========
In this study we found a significant correlation between leg length and Tc, but we were unable to show such a relation between age and T~c~.
Pease et al were the first, studied T~c~\[[@B2],[@B4]\], and reported Mean ± SD of 7 ± 0.3^ms^which is very close to our results (Tc= 6.78 ± 0.3). They didn\'t specifically consider the leg length, age or any other potential confounding variables to T~c~.
Zhu et al \[[@B3]\] evaluated 60 persons and reported Mean T~c~: 6.8 ms and its SD: 0.33 ms, again close to our results. They also reported that T~c~and person\'s height were correlated but didn\'t study any correlation between age and T~c~.
Wang et al \[[@B5]\] evaluated 40 persons and found this regression equation:
T~c~= 0.02A + 0.003H + 0.92 (H: Height and A: Age), and stated that age is a contributing factor on T~c~.
Another research was performed by Ghavanini et al \[[@B6]\], in which 39 subjects were evaluated. The reported T~c~± SD was 6.9 ± 0.4; two regression equations were also suggested: T~c~= 0.097Tp + 4.045 and Tc = 0.051L + 4.92 (L=leg length in centimeters); results are close to ours, and age was not found to affect T~c~.
A summary of the above data plus detailed demographic data are provided in the table [2](#T2){ref-type="table"}.
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
comparing related studies
:::
Subjects\' characteristics Tc
--------------------------- ---------------------------- ------ -------------------- ----------------- ------ ------ ---------------
Present study 40 37.0 36.4 M:38.1 F:33.2 ? 6.78 0.3 No-?-0.49
Pease et al \[2\] 20 ? ? ? 7.0 0.3 ?-?-?
Zhu et al \[3\] 60 43 ? 169 6.8 0.33 No-0.54-?
Wang et al \[5\]\* 40 ? ? ? ? ? ?-?-?
Ghavanini et al \[6\]\*\* 39 41 M:39.8 F:37.0 M:172.2 F:159.5 6.9 0.4 No-0.56--0.62
A: age (yr); L: leg length (cm); H: height (cm); Tc: central loop of the H-reflex latency (ms); M: male; F: female; No: no correlation was found; ?: not reported
\*: suggested a regression equation: Tc = 0.02A+0.03H+0.92
\*\*: Suggested two regression equations: Tc = 0.051L+4.928; Tc = 0.097Tp+4.04
:::
Limitations
===========
In this study we focused on age and leg length as potential contributing factors on the T~c~. we didn\'t control, randomize or observe other possible confounding (contributing) factors with potential to affect this parameter.
We observed a significant correlation between leg length and T~c~(P value = 0.003, r= 0.49, CI 95% = 0.59--0.88), that is compatible to a previous published work \[[@B3]\] (r = 0.54, p value less than 0.01).
Had we found any association between T~c~and age, the question might have been raised that subclinical neuropathy of old age could have been contributive; obviously, this is not the case in our study.
Although F-wave has been used to evaluate the possibility of proximal neuropathy; it was not measured in this study. Alternatively, we measured H-reflex latency to exclude proximal neuropathy \[[@B11]\].
It should be emphasized that noninvasive methodologies for the diagnosis of subclinical S1 radiculopathy are now available \[[@B12]\]. It is also acceptable to stimulate the S1 spinal nerve at the S1 foramen by magnet, instead of deep tissue needling; nevertheless, we used more popular techniques for this study.
Conclusions
===========
We found that between age and leg length, only the latter can affect T~c~. It may be reasonable to consider leg length for calculating T~c~and to \"narrow\" the normal limits.
Further studies with larger sample sizes are required for detecting other contributing factors and standardizing T~c~according to leg length.
Competing interests
===================
None declared.
Abbreviations
=============
T~c~: central loop of the gastrocnemius-soleus H-Reflex latency
T~p~: gastrocnemius-soleus H-Reflex latency
PNCV: right peroneal nerve conduction velocity
PDML: right peroneal nerve distal motor latency
Authors\' contribution
======================
SS: examining the cases, calculation of TC, writing the paper.
MRAG: suggesting the research, supervision and helping with calculation of TC.
AA: examining the cases, calculation of TC
PJ: statistical consultant (data analysis)
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1471-2377/4/11/prepub>
Acknowledgements
================
The authors would like to thank:
Ali Bidari, MD, assistant professor of rheumatology, Iran university of medical sciences, for his great help in the revision of the manuscript
Mojtaba Mahjoob, MD, resident of surgery, and Masoome Rostamzade, English instructor, for translating the manuscript.
|
PubMed Central
|
2024-06-05T03:55:47.859208
|
2004-9-3
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517935/",
"journal": "BMC Neurol. 2004 Sep 3; 4:11",
"authors": [
{
"first": "Shahram",
"last": "Sadeghi"
},
{
"first": "Mohammadrezaalavian",
"last": "Ghavanini"
},
{
"first": "Alireza",
"last": "Ashraf"
},
{
"first": "Peyman",
"last": "Jafari"
}
]
}
|
PMC517936
|
Background
==========
Lung cancer causes approximately one million deaths each year worldwide \[[@B1]\]. Treatment of these patients is based on surgery, but at diagnosis approximately 80 % of NSCLC patients are inoperable \[[@B2]\]. These inoperable patients are treated with radiotherapy and/or chemotherapy. Several studies have tried to improve survival through introducing new chemotherapeutic treatment combinations \[[@B3]\] or applying different radiation fractionation schedules \[[@B4]\], resulting in modest improvements in survival.
The continuous progress in the field of lung cancer biology has resulted in gradually increased insights into the intricate processes resulting in development and progression of malignancy. One of the first proteins whose occurrence was thought to affect prognosis was p53. This protein was identified during the late 1970s \[[@B5]\] and the corresponding gene was localized on the short arm of chromosome 17 \[[@B6]\]. Endogenous p53 protein is maintained at very low levels within the cell, but when the cell is exposed to hypothermia, oncogene activation, hypoxia or DNA damage, a rapid elevation of p53 levels is found, resulting in cell cycle arrest, DNA repair or induction of apoptosis \[[@B7]\]. If mutations are present in the p53 gene, these functions might be disturbed. In patients with NSCLC, p53 mutations are common, with mutation frequencies between 45--75% \[[@B8],[@B9]\].
The question if mutations within the p53 gene are correlated to radiosensitivity is not defined. In an in vitro study from our group, we found that p53 mutations located in exon 7 were associated with significantly higher radiosensitivity than in those cell lines expressing p53 mutations in other exons \[[@B10]\]. In a clinical study performed on breast cancer patients with axillary lymph node metastases, the authors found that irradiation prolonged life in patients with p53 mutations compared with patients with wild type p53 \[[@B11]\].
Antibodies against p53 can be detected in sera from patients with cancer and a correlation exists between mutations in the p53 gene and antibodies against p53 in sera \[[@B12]\]. In a study from our group, investigating 67 patients with NSCLC, we found that the presence of anti-p53 antibodies prior to radiation therapy predicted increased survival (p = 0.025) \[[@B13]\].
In the present study, we included 84 patients with stage III-IV, donating 529 serum samples with the intention to investigate if predictions concerning outcome can be made and to investigate whether or not increased amounts of anti-p53 antibodies develop during disease progression, a question that, according to our knowledge, has not been explored previously.
Methods
=======
Serum samples from patients with NSCLC admitted to the Department of Oncology, University Hospital, Uppsala, Sweden, during 1983--1996 were studied. All patients gave informed consent prior to the collection of blood samples and the samples were stored at -70°C until analyzed. The study was reviewed and approved by the research ethics committee, Uppsala University, Uppsala, Sweden. The inclusion criteria were: a verified histology of NSCLC, advanced NSCLC defined as stage IIIA-IV according to TNM and a minimum of three serum samples donated from each patient during progression of the disease. The patients included were all followed from admittance until death.
The first serum samples from 67 patients included in this study had previously been investigated for the presence of antibodies against p53 \[[@B13]\]. In the present study, only patients with stages III and IV were included and the number of serum samples was enlarged with serum samples obtained during follow-up.
The clinical parameters investigated were: age, gender, histology, performance status, weight reduction, smoking, tumour volume (according to RECIST criteria), objective response, subjective response (defined from the clinical charts as either: feeling better after treatment or feeling worse after treatment) and the presence of anti-p53 antibodies. Complete information concerning clinical parameters could not be obtained due to inadequate information in the clinical charts.
Anti-p53 antibody investigation
-------------------------------
Blood was collected in 7 ml serum tubes without additive (367609, Becton Dickinson, Rutherford, NJ). Anti-p53 abs were measured using a sandwich ELISA (Dianova, Hamburg, Germany). Human recombinant p53 was bound to microtiter plates. Standards and samples were pipetted into the wells. After incubation and washing, a horseradish peroxidase conjugated polyclonal goat anti-human IgG was added. After renewed incubation and washing, a chromogenic substrate was added and the colour intensity was measured at 450 nm in a Titertek Multiskan. A relative index for patient sera was calculated as follows: E450 (sample) - E450 (low control)/E450 (high control) - E450 (low control). The ELISA assays were performed without knowledge of clinical data. According to the manufacturer\'s instructions, serum samples with an anti-p53 antibody index \>1.1 were considered positive, whereas a serum sample with an index \<0.9 was considered negative. Serum samples with an index between 0.9--1.1 were considered intermediately positive.
Statistics
----------
Survival was estimated using the Kaplan-Meier product limit method, where univariate analysis was performed using a log-rank test. Cox regression analysis was performed to investigate if certain continuous factors had a significant effect on survival or to perform multivariate survival analyses. Spearman\'s rank order correlation was utilised for tests of associations between factors. The survival analysis together with the descriptive statistics is based on the first serum sample collected for each patient, whereas the correlation analyses were performed using all sera samples.
In order to investigate if the levels of anti-p53 antibodies increased during the progression of the disease a statistical model was designed. In the model, time zero was set to be the date of pathological diagnosis and time one was set to time of death, i.e. the time to death was standardized for all patients. Using a fixed effect leased square estimator to allow for individually different starting values of anti-p53 antibodies, the effect on anti-p53 antibodies from diagnosis to death was calculated.
In the descriptive statistics, range was defined as the minimum and maximum. Throughout the paper a 5% significant level was used.
Results
=======
The median value of anti-p53 antibodies was 0.06 (range 0 -- 139.8). Seventeen percent of the investigated NSCLC first serum samples expressed elevated levels of anti-p53 antibodies according to the manufacturer\'s instructions. From the time of pathological diagnosis until the time of death, no statistically significant effect on levels of anti-p53 antibodies was found (p = 0.8).
Anti-p53 antibodies were not correlated to tumour volume (p = 0.19) or platelets (p = 0.27). A numerically higher median value of anti-p53 antibodies was found for adenocarcinoma patients (index level: 0.12) than for squamous cell carcinoma patients (index level: 0.08).
The median anti-p53 antibody level, prior to therapy, was statistically significantly elevated in comparison with serum samples were collected during follow-up (p \< 0.001) (Fig [1](#F1){ref-type="fig"}). No statistically significant difference was found when the other groups were compared.
Descriptive data including survival, median and range for anti-p53 antibodies, as well as univariate analysis (based on the first serum sample for each patient), are shown in Table [1](#T1){ref-type="table"}.
Analysis concerning histology and the presence of anti-p53 antibodies showed that patients with adenocarcinoma had a significantly poorer survival if they expressed anti-p53 antibodies (n = 23, p = 0.01). This was not found for patients with squamous cell carcinoma (n = 59, p = 0.13).
Survival analysis based on when the first serum sample was collected in relation to therapy revealed that anti-p53 antibodies collected prior to radiation therapy (continuous variable) were not associated with survival (n = 53, p = 0.14). In patients from whom blood samples were collected during radiation therapy, a statistically significant correlation towards poorer survival was found (n = 13, p = 0.05). However, no correlations to survival were found when the first serum sample was taken during chemotherapy (5 patients), or during follow-up (n = 12, p = 0.68).
Survival analysis showed that increased amounts of anti-p53 antibodies were not associated with survival according to univariate analysis (p = 0.29) (Fig [2](#F2){ref-type="fig"}).
Discussion
==========
In the present study, anti-p53 antibodies have been investigated and correlated to various clinical parameters with the intention of studying if predictions concerning a more favourable outcome can be made for NSCLC patients, based on the presence or absence of these antibodies.
Correlation analysis showed that anti-p53 antibodies were not correlated with tumour volume (measured according to RECIST criteria). These results support results of a previous study from our group, in which we neither did find a correlation between anti-p53 antibodies and tumour volume in patients with NSCLC prior to thoracic surgery \[[@B14]\].
The clinical utility of anti-p53 antibodies in NSCLC patients with advanced disease has not yet been defined. In a previous study by our group, the presence of anti-p53 antibodies did not correlate to survival but the presence of anti-p53 antibodies prior to radiation therapy resulted in increased survival for anti-p53 positive patients \[[@B13]\]. In the present study, patients from the previous study were included and the number of patients, as well as the amount of investigated serum samples, were increased. According to our knowledge, the present study is currently one of the largest studies in patients with advanced NSCLC concerning the amounts of investigated anti-p53 antibodies in sera. We were unable to find a correlation between survival and anti-p53 antibodies (p = 0.29) but differences in survival were observed between the different histologies and the presence of anti-p53 antibodies. Patients with adenocarcinoma had poorer survival if expressing anti-p53 (p = 0.01), whereas this was not found for squamous cell carcinoma patients. In a study by Gao et al., examining p53 mutations through exons 5--8 in patients with squamous cell carcinoma and adenocarcinoma of the lung \[[@B15]\], it was shown that patients with adenocarcinoma expressed mutational hotspots at codons 248 and 249, whereas patients with squamous cell carcinoma had mutational events spread throughout exons 5--8. Further, the authors concluded that mutations in the p53 gene in adenocarcinoma patients resulted in production of a more rigid p53 protein. In the present study, although, no significant survival differences were found between these two histological subgroups, it may be speculated that immunogenic differences exist between adenocarcinoma and squamous cell carcinoma histologies, differences that might explain our results.
In the present study, the presence of anti-p53 antibodies was not correlated to survival when analyzed prior to radiation therapy, possibly because only patients with stages IIIA-IV were included, whereas our previous study also included patients with stages I-II. In patients where the first serum sample was collected during radiation therapy, a correlation to poorer survival was found (p = 0.05). Naturally, since the number of investigated patients was small, the obtained results should be interpreted with caution.
The issue of using anti-p53 antibodies in monitoring NSCLC patients has not yet been determined. Zalcman et al. used anti-p53 antibodies in NSCLC patients during follow-up in order to detect relapse \[[@B16]\], and concluded that anti-p53 antibodies in sera might be of clinical usefulness during follow-up of NSCLC patients. In the present study, serum samples were collected prior to, during, and after treatment. The distribution of serum samples was not homogeneously distributed during the different treatments, as seen in Fig [1](#F1){ref-type="fig"}. A change in antibody titer was observed during treatment and the levels of anti-p53 antibodies seemed to be higher during chemotherapy. These results should be interpreted with caution since the number of investigated serum samples was small. However, these results are intriguing, since anti-p53 antibodies have been correlated with the half-life of IgG1 and IgG2 \[[@B12]\]. Since patients receiving chemotherapy as well as radiation therapy often develop immunogenic deprivation, a subsequent reduction of anti-p53 antibodies seems reasonable, but this was not found. The results might be explained by tumour lysis causing increased exposure to the p53 antigen and, consequently, increased production of anti-p53 antibodies. Another hypothesis is that this elevation in the levels of anti-p53 antibodies during chemotherapy might be due to chemotherapy effects on normal tissues, thus explaining the difference between serum samples collected during radiation treatment and serum samples collected during chemotherapy treatment. A statistically significant difference was found between mean values of anti-p53 antibodies, prior to therapy and during follow-up (p \< 0.001). However, since the investigated number of serum samples differs between the groups, no general conclusions can be made.
Conclusion
==========
The result of the present retrospective study indicates that anti-p53 antibodies are not suitable for predictions concerning selection of patients with a more favourable outcome. Further prospective studies are, though, needed to fully elucidate this issue.
Authors\' contributions
=======================
The authors have fulfilled the criteria for authorship according to rules stated and used in medical journals.
Competing interests
===================
None declared.
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1471-2407/4/66/prepub>
Acknowledgements
================
The authors are in debt to Anita Klinga for skilful technical assistance and we gratefully acknowledge the funding of this study by grants from the Research Fund of the Department of Oncology, Uppsala, Sweden.
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Distribution of anti-p53 antibodies according to treatment and the number of investigated serum samples are defined in the figure text
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Survival analysis and the presence of anti-p53 antibodies
:::
:::
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Descriptive data concerning survival (in days) as well as distribution of anti-p53 antibodies for investigated clinical parameters. The reported p-values relates to survival according to univariate analysis for the investigated clinical parameters
:::
**Variables** **Number of patients** **Median Surv (days)** **SD\*** **Anti p53 abs *Median/Range*** **P-value**
----------------------------- ------------------------ ------------------------ ---------- --------------------------------- -------------- --
*Gender* 0.75
Male 62 330 582 0.08 (0--140)
Female 22 363 257 0.1 (0--32)
*Stage* 0.63
3a 47 324 660 0.02 (0--140)
3b 25 332 203 0.23 (0--43)
4 12 383 226 0.04 (0--25)
*Performance status* 0.77
0 53 312 286 0.04 (0--43)
1 21 359 392 0.23 (0--140)
2 8 319 160 0.3 (0--32)
*Smoking* 0.29
Yes 53 387 339 0.05 (0--140)
Ex-smoker 22 294 228 0.24 (0--43)
No 5 290 158 0.12 (0--6)
*Weight reduction. kg* 0.78
Yes 42 348 293 0.20 (0--140)
No 21 281 317 0.0 (0--10)
*Histology* 0.73
Squamous carcinoma 59 324 321 0.08 (0--140)
Adenocarcinoma 23 347 839 0.12 (0--25)
Bronchioalv. ca 2 452 375 0.03 (0--0.05)
*Tumour volume (recist)* **0.007**
\<50 18 446 433 0.04 (0--6)
\>50 21 290 142 0.22 (0--140)
*Subjective improvement* 0.95
Yes 41 306 333 0.12 (0--140)
No 11 306 146 0 (0--32)
*Objective improvement* 0.73
Stable disease 5 551 371 0.06 (0--13)
Regress of tumour 3 684 252 0 (0--0)
Progress of tumour 2 526 333 0.55 (0--1.1)
*Anti-p53 antibodies* 0.29
Continuous
*Anti-p53 antibodies index* 0.96
neg 68 334 543
intermediate 2 486 390
pos 14 330 410
:::
|
PubMed Central
|
2024-06-05T03:55:47.860588
|
2004-9-14
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517936/",
"journal": "BMC Cancer. 2004 Sep 14; 4:66",
"authors": [
{
"first": "Michael",
"last": "Bergqvist"
},
{
"first": "Daniel",
"last": "Brattström"
},
{
"first": "Anders",
"last": "Larsson"
},
{
"first": "Patrik",
"last": "Hesselius"
},
{
"first": "Ola",
"last": "Brodin"
},
{
"first": "Gunnar",
"last": "Wagenius"
}
]
}
|
PMC517937
|
Background
==========
Non-invasive monitoring of respiratory function is an area of increasing research interest, resulting in the appearance of new monitoring devices \[[@B1]\]. At present, the most utilised non-invasive method for continuous quantitative monitoring of breathing pattern is respiratory inductive plethysmography. This technique allows the study of various breathing pattern parameters such as respiratory frequency, but it is based on an averaged measurement of the whole thoracic-abdominal movement. On the other hand, the use of mouthpieces or face masks in pneumotacography, influences in the tidal volume and respiratory frequency \[[@B2]-[@B4]\]. Other systems like piezoelectric contact sensors measure the system acceleration when placed on body surfaces. In previous works we have shown that the beginning and end of diaphragmatic contraction can be determined by inflexion points in the thoracic cage motion signal acquired with a contact sensor \[[@B5]-[@B7]\].
The purpose of this study is to evaluate a non-invasive method to study the timing of the diaphragmatic function, using an animal model (dogs). Accordingly, the present study was designed to test whether the use of contact (non-invasive) piezoelectric sensors, placed on the dogs\' costal wall, could be useful in monitoring the diaphragm contraction period in different respiratory conditions, comparing it with other physiological signals such as transdiaphragmatic pressure, diaphragm length measured by sonomicrometry, and respìratory airflow. Diaphragm contraction time is expected to be very close to inspiratory time, which is one of the most utilized parameters in the studies of breathing pattern under experimental or clinical conditions.
Methods
=======
Three mongrel dogs (15--20 kg) were surgically instrumented under general anesthesia given via a femoral vein catheter (pentobarbital sodium, 25 mg/kg). Respiratory flow was recorded with a Fleisch pneumotachograph. Diaphragm shortening was measured via two piezoelectric crystals (Sonomicrometer, Triton Tech. Inc., m. 120), as described in \[[@B8]\]. The diaphragm was exposed by a midline abdominal incision, and the two piezoelectric crystals were implanted along the rib diaphragm fibres. An anterior midline incision was made in the neck to allow the left C5 and C6 phrenic nerve roots to be isolated. Motion of the thoracic cage surface was recorded by a piezoelectric contact sensor (HP 21050A) positioned on the costal wall and fixed to the skin by an elastic band. Maximal deflection of the accelerometer following a unilateral phrenic nerve electrical pulse was measured on the 6--7 intercostal space area of the rib cage, where the diaphragmatic fibres are directly apposed to its inner surface, thereby minimizing the distance between the accelerometer and the muscle. Transdiaphragmatic pressure was measured in the usual way as the difference between gastric and esophageal pressures, each recorded with the conventional balloon-catheter technique \[[@B9]\]. The electromyogram of the diaphragm (EMGdi) was recorded with two (parallel) 10 mm long single filament copper wires (1 mm in diameter) attached 20 mm apart on a semi-rigid plastic plate, as described in \[[@B10]\]. Measurements were made at a similar level of anaesthesia (corneal reflex just suppressed). All animals were in supine position during the study, and spinal anaesthesia was applied as a means to isolate diaphragmatic function by eliminating the activity of the intercostal muscles. To that effect, with the animal lying down with its head and neck raised, a hyperbaric Tetracaine solution (Sigma) was injected into the subarachnoid space at the lumbar level (bolus of 1 ml). The injection of tetracaine was halted when intercostals EMG activity was abolished below intercostals spaces 3--4 on both sides of the cage (as determined by needle electrodes recording from the parasternals). With the head and neck elevated, the animal was then turned over to the supine position. All dogs performed spontaneous ventilation before the use of spinal anaesthesia (SVN), and spontaneous ventilation (SVW) and respiration with an inspiratory resistive load (ILW) with spinal anaesthesia. The duration and respiratory frequency of the tests varies in function of the dog analyzed. Table [I](#T1){ref-type="table"} shows the number of cycles and the duration of the respiratory tests performed by the three dogs.
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Number of cycles and duration of the respiratory tests in the three dogs.
:::
**Spontaneous ventilations without anaesthesia (SVN)** **Spontaneous ventilations with anaesthesia (SVW)** **Inspiratory load with anaesthesia (ILW)**
---------- -------------------------------------------------------- ----------------------------------------------------- --------------------------------------------- ----- ----- -----
**DOG1** 45 180 40 160 159 400
**DOG2** 19 180 29 140 194 600
**DOG3** 11 60 8 30 46 220
:::
All analogical signals were amplified (HP 8802A), filtered and digitised with a 12 bit A/D system at a sampling rate of 4 kHz. Inspiratory airflow (FL), diaphragm length (DL), thoracic cage motion (TM), transdiaphragmatic pressure (DP) and diaphragmatic electromyography (EMGdi) signals were decimated at a new sampling rate (FL, DL, DP: 100 Hz ; TM: 200 Hz; EMGdi: 1200 Hz) and digitally filtered (FL, DL, DP: DC-40 Hz ; TM: DC-80 Hz; EMGdi: 10--480 Hz). The sampling frequencies and filter bands were selected to be adapted to the frequency content of the signals. Figure [1](#F1){ref-type="fig"} shows a typical strip-chart recording of the five signal acquired, during 8 seconds (2 respiratory cycles) of the ILW respiratory test of the second dog.
::: {#F1 .fig}
Figure 1
::: {.caption}
######
**Respiratory Signals.**Example of the five signals acquired during 8 seconds (two respiratory cycles) during the inspiratory load with spinal anaesthesia (ILW) respiratory test of the second dog.
:::
:::
In order to detect the initial and final diaphragm contraction times (*t*~*i*~, *t*~*f*~), the integral of TM signal and the first derivative of the DL, FL and DP signals were computed. Initial contraction time is detected when these signals reach 10 % of the maximum. In a similar way, final contraction time is detected when the signals reach 10 % of their minimum. We also computed contraction period (*T*~*C*~= *t*~*f*~- *t*~*i*~). The EMGdi signal was included initially in the study but later was rejected because the postinspiratory activity present in this signal hindered the detection of the end of the diaphragm shortening contraction time (as seen in Fig. [1](#F1){ref-type="fig"}). One representative experimental record of TM, DL, FL and DP signals is shown in Fig. [2](#F2){ref-type="fig"}. Furthermore, the integral of the TM signal is presented, as well as the first derivative of the DL, FL and DP signals.
::: {#F2 .fig}
Figure 2
::: {.caption}
######
**Diaphragmatic contraction time detection.**Morphologies of thoracic cage motion signal and its integral (a), diaphragmatic length (b), respiratory airflow (c) and transdiaphragmatic pressure (d) and their first derivatives. Vertical lines mark initial and final instants of diaphragmatic contraction.
:::
:::
Statistical Analysis
--------------------
Differences between contraction periods obtained with DL signal and the other three signals were summarized by the mean (MEAN), standard deviation (STD). DL signal was used as a goldstandard (reference signal) for muscle shortening, since it is a direct measure of the reduction of the diaphragm muscle length, contrary to flow and trandiaphragmatic pressure which are more remote markers of muscle contraction.
Relationships between contraction periods obtained by means DL and TM signals, DL and FL, and DL and DP were analyzed by diverse statistical methods. Different correlation coefficient were calculated: the Pearson correlation coefficient (r), the intra-class correlation coefficient (or reliability coefficient: R) \[[@B11]\], the slope of the linear regression line (p), and the Spearman\'s rank-order correlation coefficient (r). Furthermore the Bland-Altman method for agreement analysis was performed \[[@B12]\]; in this graphical method the differences between two measures or techniques are plotted against the averages of the two techniques.
Results
=======
The obtained results of the comparison of contraction period estimated with the DL signal (a direct measure of diaphragm shortening) with the contraction periods estimated with the TM, FL and DP signals, are shown in Tables [2](#T2){ref-type="table"}, [3](#T3){ref-type="table"} and [4](#T4){ref-type="table"}, and in Figs. [3](#F3){ref-type="fig"} and [4](#F4){ref-type="fig"}.
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Differences between contraction period measured with diaphragmatic length (DL) and contraction period measured with thoracic motion (TM), respiratory airflow (FL) and transdiaphragmatic pressure (DP).
:::
**DL vs. TM** **DL vs. FL** **DL vs. DP**
----------------- --------------- --------------- --------------- ------ ------- ------ ------- ------- ------- ------ ------- -------
**Dog 1 (SVN)** 0.15 0.05 0.05 0.26 -0.25 0.08 -0.39 -0.01 -0.19 0.07 -0.32 -0.05
**Dog 2 (SVN)** 0.03 0.03 -0.02 0.09 -0.00 0.04 -0.09 0.08 0.01 0.03 -0.05 0.06
**Dog 3 (SVN)** 0.04 0.03 -0.01 0.10 0.03 0.04 -0.05 0.11 -0.00 0.04 -0.07 0.07
**Dog 1 (SVW)** -0.00 0.03 -0.05 0.06 0.02 0.03 -0.04 0.08 0.02 0.04 -0.05 0.10
**Dog 2 (SVW)** 0.03 0.03 -0.03 0.08 -0.04 0.04 -0.12 0.04 -0.02 0.02 -0.06 0.02
**Dog 3 (SVW)** -0.03 0.02 -0.08 0.02 -0.00 0.03 -0.06 0.05 -0.02 0.05 -0.11 0.08
**Dog 1 (ILW)** 0.09 0.02 -0.04 0.13 0.02 0.02 -0.02 0.06 0.03 0.02 -0.00 0.07
**Dog 2 (ILW)** 0.04 0.02 -0.00 0.08 -0.01 0.05 -0.10 0.08 0.01 0.02 -0.02 0.04
**Dog 3 (ILW)** -0.01 0.02 -0.04 0.02 -0.01 0.02 -0.04 0.03 0.04 0.02 -0.00 0.08
MEAN: Mean difference; SD: standard deviation; MEAN ± 2SD: limits of agreement of the Blond and Altman analysis; SVN: spontaneous ventilation without anaesthesia respiratory test, SVW: spontaneous ventilation with anaesthesia respiratory test; ILW: inspiratory load with anaesthesia respiratory test.
:::
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Correlation coefficients between contraction period measured with diaphragmatic length (DL) and contraction period measured with thoracic motion (TM), respiratory airflow (FL) and transdiaphragmatic pressure (DP).
:::
----------------- --------------- --------------- --------------- ------ --------- ------- ------ ------ --------- ------- ------- ------
**DL vs. TM** **DL vs. FL** **DL vs. DP**
***r*** R p *ρ* ***r*** R p *ρ* ***r*** R p *ρ*
**Dog 1 (SVN)** 0.61 -0.44 0.43 0.58 0.12 -0.82 0.71 0.23 0.14 -0.74 0.059 0.15
**Dog 2 (SVN)** 0.91 0.77 1.00 0.84 0.72 0.73 0.65 0.81 0.90 0.89 0.76 0.87
**Dog 3 (SVN)** 0.77 0.39 0.68 0.79 0.63 0.45 0.72 0.65 058. 0.56 0.38 0.53
**Dog 1 (SVW)** 0.62 0.62 0.60 0.64 0.54 0.39 0.42 0.55 0.37 0.23 0.32 0.42
**Dog 2 (SVW)** 0.69 0.47 0.80 0.66 0.51 0.15 0.74 0.51 0.85 0.69 0.94 0.83
**Dog 3 (SVW)** 0.60 0.23 0.55 0.58 0.59 0.62 0.71 0.56 0.26 0.24 0.46 0.32
**Dog 1 (ILW)** 0.99 0.92 0.99 0.99 1.00 0.99 1.00 0.99 1.00 0.98 0.99 0.99
**Dog 2 (ILW)** 0.97 0.79 1.04 0.96 0.91 0.85 1.31 0.93 0.98 0.97 1.00 0.96
**Dog 3 (ILW)** 0.98 0.97 0.94 0.98 0.98 0.97 1.01 0.97 0.97 0.86 0.99 0.97
----------------- --------------- --------------- --------------- ------ --------- ------- ------ ------ --------- ------- ------- ------
r: Pearson correlation coefficient; R: reliability coefficient; p: slope of the linear regression line; *ρ*: Spearman\'s rank-order correlation coefficient; SVN: spontaneous ventilation without anaesthesia respiratory test, SVW: spontaneous ventilation with anaesthesia respiratory test; ILW: inspiratory load with anaesthesia respiratory test.
:::
::: {#T4 .table-wrap}
Table 4
::: {.caption}
######
Differences and correlation coefficients between contraction period measured with diaphragmatic length (DL) and contraction period measured with thoracic motion (TM), respiratory airflow (FL) and transdiaphragmatic pressure (DP), for all the respiratory cycles analysed.
:::
***r*** ***R*** ***p*** ***ρ*** *MEAN(s)* *SD(s)* *MEAN - 2SD (s)* *MEAN + 2SD (s)*
----------------- --------- --------- --------- --------- ----------- --------- ------------------ ------------------
**DL vs TM^1^** 0.98 0.95 1.01 0.98 0.055 0.050 -0.045 0\. 156
**DL vs FL^1^** 0.94 0.93 0.86 0.91 -0.021 0.080 -0. 180 0\. 138
**DL vs DP^1^** 0.96 0.96 0.86 0.94 0.001 0.064 -0. 127 0\. 129
**DL vs TM^2^** 0.99 0.96 0.96 0.98 0.044 0.040 -0.032 0.125
**DL vs FL^2^** 0.99 0.99 0.97 0.98 -0.001 0.040 -0.080 0.077
**DL vs DP^2^** 0.99 0.99 0.94 0.99 0.018 0.026 -0. 034 0.070
^1^Including all the respiratory cycles analysed; ^2^Without the respiratory cycles corresponding to the spontaneous ventilations without anaesthesia test. r: Pearson correlation coefficient; R: reliability coefficient; p: slope of the linear regression line; *ρ*: Spearman\'s rank-order correlation coefficient; MEAN: Mean difference; SD: standard deviation; MEAN ± 2SD: limits of agreement of the Blond and Altman analysis; SVN: spontaneous ventilation without anaesthesia respiratory test, SVW: spontaneous ventilation with anaesthesia respiratory test; ILW: inspiratory load with anaesthesia respiratory test.
:::
::: {#F3 .fig}
Figure 3
::: {.caption}
######
**Relationships and Bland and Altman analysis.**Relationship and Bland and Altman plot of the contraction period estimated with thoracic motion (TC-TM), respiratory airflow (TC-FL) and transdiaphragmatic pressure (TC-DP) signals versus contraction period estimated with diaphragmatic length signal (TC-DL), for the three dogs in the spontaneous ventilations without anaesthesia (SVN), spontaneous ventilations with anaesthesia (SVW) and inspiratory load with anaesthesia (ILW) respiratory tests. The solid black continuous line is the identity function (desired relationship). Each dot represents a respiratory cycle.
:::
:::
::: {#F4 .fig}
Figure 4
::: {.caption}
######
**Relationships and Bland and Altman analysis (all cycles together).**Relationship and Bland and Altman plot of the contraction period estimated with thoracic motion (TC-TM), respiratory airflow (TC-FL) and transdiaphragmatic pressure (TC-DP) signals versus contraction period estimated with diaphragmatic length signal (TC-DL), for all the respiratory cycles analyzed in the three dogs and the three respiratory tests. The solid black continuous line is the identity function (desired relationship). Each dot represents a respiratory cycle. The cycles corresponding to the spontaneous ventilation without spinal anaesthesia respiratory test of the Dog 1 are encircled in the Bland and Altman plot.
:::
:::
In the Fig. [3](#F3){ref-type="fig"} is shown graphically the relationship among the periods of contraction obtained by means the different estimation methods, for each animal and each respiratory test. This relationship is showed in two formats: a plot of the data with the line of equality (all points would lie in this line), and a Bland and Altman plot \[[@B12]\] with the mean difference and agreement limit lines.
In Table [2](#T2){ref-type="table"}, are shown the values of the mean difference (MEAN), the SD of the difference, and the agreement limits of the Bland and Altman plots. The mean error obtained with the three indirect measures of diaphragm shortening were lower than 0.1 seconds and the SD of the difference was lower than 0.05 seconds, except in the SVN test of Dog 1 (in this test it has been observed a great variability in the values obtained by means the four signal analyzed, as is could be seen in the first graph of Fig. [5](#F5){ref-type="fig"}). Furthermore the Bland and Altman agreement limits are always lower than 0.13 seconds.
::: {#F5 .fig}
Figure 5
::: {.caption}
######
**Diaphragmatic contraction period monitoring.**Contraction period (TC) estimated with thoracic cage motion (MT: thin solid line), diaphragm length (DL: thick solid line), respiratory airflow (FL: dotted line) and transdiaphragmatic pressure (DP: dashed line) signals versus duration of the respiratory tests in seconds, for the three dogs in the spontaneous ventilations without anaesthesia (SVN), spontaneous ventilations with anaesthesia (SVW) and inspiratory load with anaesthesia (ILW) respiratory tests.
:::
:::
Table [3](#T3){ref-type="table"} shows values of the correlation coefficient (r), the reliability coefficient (R), the slope of the linear regression line (p), and the Spearman\'s rank correlation coefficient between DL and TM contraction periods, between DL and FL contraction periods, and between DL and DP contraction periods for the three dogs for SVN, SVW and ILW respiratory tests. The relationships in the ILW respiratory test were nearly linear (r \> 0.91), with reliability coefficients indicating a high reliability in the measurements (R \> 0.79), slopes of the linear regression line very close to equality line (except in the flow of the second dog), and Spearman rank-order coefficient showing a strong link between the variables analyzed (r \> 0.93).
In the SVN and SVW respiratory tests (except for the SVN test of the first dog), results showed a moderate relationship, but, in general, correlation coefficients estimated in TM signal were better than estimations in FL and DP signal. Relationship between the contraction period estimated with TM signal and contraction period estimated with DL signal showed Pearson correlation coefficients between 0.60 and 0.91, reliability coefficients between 0.23 and 0.77, slope of the linear regression lines between 0.55 and 1, and Spearman\'s rank-order correlation coefficient between 0.58 and 0.84.
In Fig. [4](#F4){ref-type="fig"} and Table [4](#T4){ref-type="table"} are shown the results obtained analyzing all the respiratory cycles together. In both correlation analysis and Bland-Altman plots it is seen that respiratory cycles corresponding to the SVN test of Dog 1 (marked with a circle in Fig. [4](#F4){ref-type="fig"}) have different behaviour than the rest. For that reason in the first 3 rows of Table [4](#T4){ref-type="table"} it are shown the parameters obtained with all the cycles and in the last 3 rows are shown the parameters obtained excluding the respiratory cycles of the SVN test of the first dog. Excluding these respiratory cycles, the contraction period estimated with the TM signal tends to give a lower reading than the measure made with the DL signal, with a mean of 0.04 seconds (0.06 without the exclusion), a standard deviation of 0.04 seconds (0.05 without the exclusion), and limits of agreement between -0.03 and 0.12 seconds (between -0.05 and 0.16 without the exclusion). These results are slightly worse than the results obtained from the comparison with the FL signal or the DP signal. The correlation coefficients are very similar in the three signals.
Finally, Figure [5](#F5){ref-type="fig"} shows the evolution of the diaphragm contraction periods estimated with the four signals throughout the SVN, SVW and ILW respiratory tests for the three dogs studied. It is seen that, in all cases, the behaviour of contraction time estimated with the four signals is very similar (although the MEAN difference of the SVN test of the first dog is unsatisfactorily great, as seen in Table [2](#T2){ref-type="table"}).
Discussion
==========
In the present work we have compared the rib cage motion recorded by surface sensors with the changes in diaphragm activity registered by sonomicrometry, transdiaphragmatic pressure and airflow recorded in dogs during spontaneous and inspiratory load breathing. Diaphragmatic time contraction measured with a surface sensor has a good correlation with the rest of signals, especially during the inspiratory load test.
In a recent study we observed that the beginning and the end of diaphragmatic contraction were indicated with inflexion points in the thoracic cage motion signal, acquired with a piezoelectric contact sensor placed on the costal wall of the thorax \[[@B6],[@B7]\]. An algorithm was implemented and validated to detect the initial and final instants of diaphragm contraction, and the results were compared with the direct measurement of the diaphragmatic muscle length changes made by sonomicrometry \[[@B8]\]. In the present work we have compared the contact sensor signal with other transducer signals to test the monitoring capacity of contact sensors in different respiratory patterns. Three different tests have been studied: spontaneous ventilation before the use of spinal anaesthesia, spontaneous ventilation (SVW) after spinal anaesthesia, and breathing through a resistive inspiratory load (ILW).
Spinal anaesthesia was used in the present study as a means to isolate diaphragmatic activity by eliminating the activity of the intercostals muscles. In this way, TM, FL and DP signals are directly related with the contraction of diaphragm muscle in the SVW and ILW respiratory tests (as well as DP signal). In the SVN test the morphologies of TM, FL and DP signals are influenced by the activity of intercostal muscles. However, time differences between contraction periods measured in SVN and SVW respiratory tests were very similar (except for the SVN test of the first dog). This could be explained taking into account that during spontaneous breathing the activity of intercostals and respiratory accessory muscles is minimal \[[@B6],[@B7]\].
A close relationship between the different methods of diaphragm contraction time estimation has been found during the inspiratory load test. However, during spontaneous ventilation, the correlation was lower than that obtained in the resistive load test. This difference could be explained by the fact that during spontaneous ventilation, the motion of the respiratory system is very low and in consequence, the signal recorded by the contact sensor (and in general, all the respiratory signals) has not sufficient intensity to detect with the same precision the beginning and ending of diaphragmatic activity. Besides, during inspiratory resistive loading, there is a marked distortion of the rib cage (in particular when the intercostal muscles are paralyzed) and this produces a more marked thoracic-cage motion signal.
Another important finding of this work was that time contraction differences between signals were less than 0.1 s for spontaneous ventilation and inspiratory load (except in the irregular case of the SVN respiratory test of the first dog), which indicates that the application of contact sensors constitutes an indirect way to detect the diaphragmatic activity. This could be seen in the graphs of Fig. [5](#F5){ref-type="fig"}, in which we observed that practically in all cases the behavior of the diaphragmatic contraction time estimated with the four signals is very similar, being appropriate for diaphragmatic contraction period monitoring. The TM signal has the advantage with respect to other signals in that it is non-invasive and does not affect the breathing pattern \[[@B2]-[@B4]\]. Therefore, it is suitable for continuous monitoring of breathing pattern parameters such as respiratory frequency and diaphragmatic contraction time (which is very close to inspiratory time). Thus, the usefulness of TM signal for non-invasive diaphragmatic contraction period monitoring is demonstrated. A particular case is the SVN test of the first dog. In this case the breathing was very weak, causing that beginning of the contraction was very slow and irregular. This generated difficulties to determine the beginning of the contraction, provoking great differences in the contraction time estimated with the four signals. Nevertheless, the evolution of contraction time throughout the respiratory tests is very similar.
The contraction of the costal diaphragm acts to displace the rib cage through its insertions at the costal margins and by changing the pressure on the inner surface of the rib cage in the area of apposition. The crural diaphragm is not inserted on the rib cage, but it is considered to have an action through the central tendon. Therefore, in spontaneous respiration the crural part has an important inflationary action on the lower rib cage \[[@B13]\], and although we only registered costal muscle length changes, we believe that the contact sensor shows the activity of both diaphragm components.
Finally, to acquire the diaphragm shortening signal, it has been necessary to surgically isolate their diaphragms. The effect of diaphragm isolation could be to favour the operation of the piezoelectric contact sensor to measure diaphragmatic contraction timing. This should be kept in mind when extrapolating these results to human.
Conclusions
===========
The technique presented in this work represents a non-invasive method to assess the timing of diaphragm contraction in dogs. We believe that in the future this technique could provide a new potentially useful method for non-invasive respiratory timing monitoring in humans.
Competing interests
===================
None declared
Authors\' contributions
=======================
JAF, JM, RJ and AG conceived the study, and participated in its design and coordination. JAF and AG designed and conducted the experiments. AT participated in the design of the study and performed the signal processing and statistical analysis. BG and JG provided advice on analysis of the data and manuscript writing. JAF, AT and RJ wrote the first draft of this manuscript. All authors read and approved the final manuscript.
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1471-2466/4/8/prepub>
Acknowledgements
================
This study was supported in part by grants from the MSC of Spain (BEFI: Exp. 98/9682), from CICYT (TIC97-0945-C02-01), SEPAR97, Red Respira de investigación (ISCiii-RTIC-03/11).
|
PubMed Central
|
2024-06-05T03:55:47.862879
|
2004-9-8
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517937/",
"journal": "BMC Pulm Med. 2004 Sep 8; 4:8",
"authors": [
{
"first": "José Antonio",
"last": "Fiz"
},
{
"first": "Raimon",
"last": "Jané"
},
{
"first": "Abel",
"last": "Torres"
},
{
"first": "Josep",
"last": "Morera"
},
{
"first": "Batxi",
"last": "Galdiz"
},
{
"first": "Joaquín",
"last": "Gea"
},
{
"first": "Alejandro",
"last": "Grassino"
}
]
}
|
PMC517938
|
Background
==========
Renal cancer accounts for 3% of adult malignancies. An estimated 35,710 new cases are expected to occur in the U.S. in the current year and 12,480 patients will die of this disease \[[@B1]\]. The majority of renal cancers arises from the proximal tubular epithelium, with a characteristic clear or granular cell appearance by light microscopy, and is referred to as renal cell carcinoma (RCC).
Recent evidence suggests that solid renal parenchymal tumors arising in the distal portion of the nephron, such as oncocytomas, chromophobe renal cell carcinomas and collecting duct carcinomas represent an heterogeneous group of neoplasm from both clinical and biological perspectives \[[@B2]\]. Collecting duct carcinoma (CDC), also known as Bellini duct carcinoma, is a rare but highly aggressive renal neoplasm arising from the distal portion of the nephron, and represents approximately 2% of all the RCCs \[[@B3],[@B4]\]. Clinically, CDC appears as a renal mass often accompanied by flank pain and hematuria and is frequently mistaken for RCC or transitional cell carcinoma of the renal pelvis \[[@B3],[@B5],[@B6]\]. CDC, however, can be identified based on gross, microscopic, histochemical, and immunohistochemical features. Macroscopically, CDCs are often located at the confluence of the medulla and renal pelvis, and show a characteristic gray-white-tan color, with absence of foci of necrosis and hemorrhage \[[@B7]\]. Histologically, CDC presents a tubulo-papillary morphology, often accompanied by desmoplasia, atypia in collecting ducts, and intratubular spread \[[@B7]\], features rarely seen in RCC.
Histochemically, CDC cells contain intracytoplasmic mucicarminophilic material, where RCCs do not \[[@B7]\]. CDCs are also positive by immunohistochemical staining with high-molecular-weight keratin and lectin, proteins typically expressed in the epithelium of the distal tubules \[[@B8],[@B9]\]. Conversely, almost all other renal carcinomas express antigens widely expressed in the cells of the proximal tubules, such as low molecular weight cytokeratins and vimentin \[[@B9]\]. Although little is known about the genetic profile of CDCs, a DNA flow cytometry study has demonstrated aneuploidy in 90% of these tumors \[[@B5]\], and cytogenetics has shown frequent monosomy of chromosomes 1, 6, 8, 14, 15, and 22 \[[@B10],[@B11]\].
Loss of heterozygosity (LOH) analysis in six CDCs revealed allelic loss at chromosomes 8p and 13q in 50% of the tumors, and rarely at the short arm of chromosome 3 \[[@B12],[@B13]\]. This data suggests that distinct genetic alterations from those observed in RCC, in which 3p LOH is common \[[@B14]\], occur in the development of this rare renal tumor.
To improve our understanding of the biology of CDC and to explore the possibility that different genes may be involved in the etiology and prognosis of this neoplasm, we analyzed by immunohistochemistry eleven cases of CDC for the expression of five genes (Fez1, Fhit, p53, p27, and bcl2) often involved in the development of many common cancers. These findings were correlated with conventional clinical-pathological features including clinical outcome.
Methods
=======
Patients
--------
Eleven patients with primary CDC (two women and nine men; age range 40 to 84 years, mean 62) underwent radical nephrectomy between 1983 and 2000 in the Department of Urology, University of Padua, Italy. Tissue specimens from these tumors were registered in the Department of Pathology at the same institution. All eleven patients had an adequate clinical follow up and were included in our study. Eight of the 11 patients had metastatic disease, five with lymph node metastasis and five with distant metastases at the time of surgery. None of these eleven patients received any systemic therapy before surgery. Samples were fixed in 10% buffered formalin for routine histological processing and were stained with hematoxylin and eosin.
Pathological study
------------------
Immunohistochemical reactions using anticytokeratin (Keratins 5, 8, 10, an 18) monoclonal antibodies, and *Ulex Europaeus Lectin*, polyclonal antibody were performed as previously described \[[@B15]\]. The tumors were classified histologically according to standardized criteria \[[@B3],[@B5]-[@B7]\] and staged according to the guidelines of the tumor-node-metastasis (TNM) classification of malignant tumor \[[@B16]\].
Immunohistochemistry
--------------------
Paraffin sections containing non-neoplastic kidney as well as neoplastic areas were deparaffinized according to standard procedures followed by rehydration through graded ethanol series, and mounted on positively charged slides. Immunostaining was performed as previously described \[[@B17]\]. Briefly for Fez1, Fhit, p53, and p27 immunostaining, slides were immersed in citrate buffer \[0.01 M sodium citrate (pH6.0)\] and heated in a microwave oven at 600 W (three times for 5 min each) to enhance antigen retrieval. For retrieval of Bcl2 oncoprotein, we used the target retrieval solution, high pH from DAKO (Carpinteria, CA, USA) per manufacturers instructions. The primary antibodies used in this study were: anti-Fez1 rabbit polyclonal antibody \[[@B17]\], anti-Fhit rabbit polyclonal antibody (Zymed Laboratories, San Francisco, CA) at 1:1,000 dilution, anti-p53, anti-p27, anti-Bcl2 (DAKO, Carpinteria, CA, USA) at dilution of 1:25, 1:50, and 1:40 respectively, as specified by the manufacturers. The primary antibodies were omitted and replaced with pre-immune serum in the negative controls. Sections were reacted with biotinylated anti-rabbit or anti mouse antibodies and streptavidin-biotin-peroxidase (Histostain-SP Kit; Zymed laboratories, San Francisco, CA). Diaminobenzidine (DAB) was used as a chromogen substrate to visualize staining. Finally, sections were washed in distilled water and weakly counterstained with Harry\'s modified hematoxylin. The immunostaining was evaluated by two pathologists in a blinded fashion (A.V.; R.B.). For statistical analysis, cases were scored as positive if they had more than 20% (p53) or more than 40% (Fez1 and p27) of positive cells. Fhit and bcl2 cases showed either all positive or all negative cells and were scored accordingly.
Statistical analysis
--------------------
We evaluated the association between each marker\'s expression (positive or negative) and each clinical-pathological outcome (metastasis and stage) with Fisher\'s exact test. For survival, we used the Kaplan-Meier method and log-rank test, as well as Cox proportional hazards regression.
Results
=======
Pathological study
------------------
All cases showed several common microscopic features. The main tumor consisted of a tubulo-papillary carcinoma showing pleomorphism and a high mitotic rate with several bizarre mitotic figures, and presence of small cystic spaces surrounded by a highly desmoplastic stroma.
Two cases showed a predominant papillary pattern accompanied with dilated and atypical changes in the epithelium of the collecting ducts in the adjacent renal medulla, which was the most convincing feature supporting a collecting duct origin of these tumors. Metastases, when available for examination, were histologically similar to the infiltrating part of the primary tumors. Immunocytochemically, tumor cells from all cases examined did not express keratin 10, while strong positivity to anti-keratin 5, 8, and 18 antibodies, and anti-UEL antibody was observed. The positivity to high molecular weight keratin and UEL further substantiate the diagnosis of CDC. The clinical-pathological features and protein expression of the study\'s 11 cases are shown in Table [1](#T1){ref-type="table"}.
Fez1 expression
---------------
Our results showed that Fez1 protein expression was undetectable in six of the eleven (55%) cases. One case showed a substantial reduction of expression with 60% of the tumor cells negative, while the remaining four showed diffuse positivity for Fez1 immunostaining (Figures [1A](#F1){ref-type="fig"} and [1B](#F1){ref-type="fig"}). Overall 64% of the cases showed absence or reduction of Fez1 expression. Loss and reduction of Fez1 were correlated with a higher prevalence of lymph node metastases (71% vs. 0%, p = 0.061), although the same was not true for distant metastases or tumor stage. Fez1-negative tumors also tended to have higher mortality than Fez1-positive tumors. Median survival time was estimated to be 17 months for the former group, while median survival was not reached for the latter group during the course of the study (i.e., fewer than half of the patients died) (p = 0.078; Figure [2A](#F2){ref-type="fig"}). This corresponds to an estimated 5-fold increase in mortality risk for the Fez1-negative CDCs (hazard ratio of 5.5).
Fhit expression
---------------
Fhit protein was absent in three of eleven cases (27%), and the remaining eight showed diffuse immunoreactivity (Figure [1C](#F1){ref-type="fig"}). Reduction of Fhit protein expression did not correlate with any of the clinicopathological features of the tumors. There was a tendency for Fhit-negative cases to have worse survival than Fhit-positive cases (median survival times of 17 vs. 35 months, respectively; hazard ratio of 2.7), although the difference was not statistically significant (p = 0.206: Figure [2B](#F2){ref-type="fig"}).
p53 expression
--------------
p53 protein was found to be overexpressed mainly in the nucleus in four of eleven cases (36%) (Figure [1D](#F1){ref-type="fig"}). One of the four positive cases showed overexpression in 85% of the cancer cells, whereas the remaining three showed 20%, 30% and 50% of positive cancer cells, respectively. p53 was not detectable in seven of eleven cases (63%) as well as in the normal renal epithelium adjacent to tumor. Overexpression of p53 was not related to histologic grade, tumor stage, lymph node status, and survival.
p27 expression
--------------
Immunoreactivity for p27 was observed in the nuclei of most glomerular and tubular cells in the normal kidney. p27 immunostaining in CDC showed high variability. Protein expression was absent in five of eleven cases (45.5%). All the remaining six carcinomas showed a high percentage (\> 40%) of p27 positive cells. The expression of p27 protein was detected exclusively in the cytoplasm in five of the six positive cases (90%) while a mixture of nuclear and cytoplasmic protein staining was observed in the last case (Figure [1E](#F1){ref-type="fig"}). Overall, we observed lack or subcellular compartmentalization of p27 in 90% of the cases. The status of p27 did not correlate to any of the clinical-pathological parameters tested.
Bcl2 expression
---------------
Bcl2 protein expression in 100% of the CDC tumor cells was observed in four of eleven cases (36%) (Figure [1F](#F1){ref-type="fig"}), while the remaining seven (64%) were negative. Statistical analysis did not reveal any significant correlation between Bcl2 expression and other clinical-pathological parameters.
Clinical-pathological features as well as immunohistochemistry results are listed in Table [1](#T1){ref-type="table"}. The proportion of marker expression ranged from 36% (Fez1 and Bcl2) to 73% (Fhit). Marker expression tended to be positively correlated, with the correlation between Fhit and p27 being the strongest (0.67), followed by that between Fhit and Fez1 and Fhit and Bcl2 (both 0.46).
Discussion
==========
The application of the most recent molecular cytogenetic techniques revealed that renal parenchymal tumors can be classified into distinct subtypes based on the combination of specific genetic alterations \[[@B18]\]. The pathological and immunohistochemical description as well as the cytogenetic abnormalities support the hypothesis that CDC is more similar to urothelial carcinoma than to clear cell carcinoma of the kidney. Indeed, whereas allelic deletion of the short arm of chromosome 3 is considered a genetic hallmark of clear cell carcinoma, LOH at chromosomes 8p, 9p, and 17p has been frequently described in both transitional cell carcinoma and CDC. Here, we have reported the results of our immunohistochemical analysis of the expression of five genes (*FEZ1*, *FHIT*, *P53*, *P27*^*kip*1^, and *BCL2*) in a relatively large series of CDCs (eleven cases), considering the rarity of this tumor.
*FEZ1/LZTS1*(leucine zipper tumor suppressor 1) is a putative tumor suppressor gene located at 8p22 \[[@B19]\]. Studies have indicated this chromosomal region is the location of an important tumor suppressor gene (TSG) \[[@B20]\]. LOH at 8p has been described in 50% of the CDCs studied \[[@B12]\], suggesting that a TSG in this region may also play a role in the development of this rare tumor. In our study, we found loss of Fez1 expression in the majority of CDCs studied and a correlation with the presence of lymph node metastasis. Furthermore, lack of Fez1 protein correlated with a poorer prognosis in 90% of patients with median survival of 17 months.
*FEZ1*encodes a 67-kDa leucine-zipper protein with a region of similarity to cAMP-dependent activated protein \[[@B19]\]. Mutations of *FEZ1*gene have been reported in several solid tumors, including prostate, breast, esophageal, and gastric carcinomas \[[@B17],[@B19]\]. In addition, reduced Fez1 expression is associated with high-grade transitional cell carcinoma of the bladder \[[@B21]\]. Recent studies have shown that the introduction of *FEZ1*into Fez1 null cancer cells reduced cell growth with the accumulation of cells at late S to G~2~/M phase of the cell cycle. Conversely, inhibition of Fez1 expression stimulated cells growth \[[@B22]\]. Furthermore, LOH at the chromosomal region where the *FEZ1*gene lies (8p21-22) has been also associated with the invasive behavior of breast cancer \[[@B23]\] and with prostate cancer progression \[[@B24]\]. These data are consistent with an important role of *FEZ1*in several human cancers including CDC.
The tumor suppressor gene *FHIT*maps to the short arm of chromosome 3 (3p14.2), encompasses the common *FRA3B*fragile region, and encodes for a protein of 16.8 kDa, with diadenosine triphosphate hydrolase activity \[[@B25]\]. Reduction of Fhit protein expression as consequence of alteration of the *FHIT*gene has been observed by immunohistochemistry in many types of cancers \[[@B26],[@B27]\]. Although Shoemberg et al. did not detect LOH involving chromosome 3p \[[@B12]\], Hadaczek et al. reported LOH at 3p in two cases of CDC \[[@B13]\]. The same authors described a correlation between reduced Fhit expression and 3p allelic loss in renal carcinomas, particularly in CDCs \[[@B28]\]. While in our study Fhit inactivation does not seem to be a common event in CDC, an involvement of the *FHIT*gene in tumorigenesis of this rare tumor cannot be excluded.
The *TP53* tumor suppressor gene maps to chromosome 17p13.1 and plays a major role in DNA transcription, cell growth, proliferation and apoptosis process \[[@B29]\]. In normal cells, expression of wild type p53 protein is generally below the detection level when studied by immunohistochemical method. However, p53 gene point mutations occur frequently (22--76%) in different solid neoplasms. Mutated p53 protein, being more resistant to degradation, accumulates in the cells and can be detected by immunohistochemistry. Although an association between p53 protein overexpression and tumor stage, grade and survival has been observed in RCC \[[@B30]\] our data suggest that involvement of p53 alterations does not occur with the same frequency in CDC.
P27 is a member of the universal cyclin-dependent kinase inhibitor (CDKI) family. The expression of this important protein is regulated by cell to cell contact inhibition as well as by specific growth factors, such as transforming growth factor (TGF-β). In addition to its role as a CDKI, p27 is considered a putative tumor suppressor gene, a major regulator of drug resistance in solid tumors, and a promoter of apoptosis. p27 acts also as a safeguard against inflammatory injury and has a role in cell differentiation \[[@B31]\]. It has been suggested that loss of the p27 negative cell cycle regulation may contribute to oncogenesis and tumor progression in several tumor types. In renal cell carcinoma, Kamai et al. reported that low level of p27 protein was associated with tumor invasion and unfavorable prognosis, suggesting p27 as a powerful prognostic marker for survival in urinary tract cancer \[[@B32]\]. Masuda et al. indicated that p27 has an independent predictive prognostic value for transitional cell carcinoma of the renal pelvis \[[@B33]\]. Our results show that p27 loss or subcellular compartmentalization represents a frequent feature in CDCs. Previous studies have noted that cytoplasmic localization of p27 lead to an inactivation of its normal function as negative cell cycle regulator \[[@B34]\].
Nevertheless, we did not find statistical correlation to assess its involvement in CDC biology, possibly due to the limited number of tumors studied.
The proto-oncogene *BCL2*, implicated in the regulation of cell death by inhibiting apoptosis, seems to be vital in normal kidney morphogenesis. In fact, Bcl2 deficient mice develop polycystic kidneys characterized by dilated proximal and distal tubules \[[@B35]\]. High levels of Bcl2 protein expression have been found in many different types of cancer, suggesting a possible role for Bcl2 deregulation of apoptosis and malignant tissue transformation. Expression of Bcl2 has also been associated with poor prognosis in patients with various cancers including prostate cancer \[[@B36]\]. In the present study, Bcl2 expression was not associated with any clinical-pathological variables.
Our results suggest a potential association between FEZ1 expression and CDC pathology and prognosis. No similar patterns were seen for any of the other markers studied. Even so, the statistical power of the study was limited and negative findings should not be construed as evidence that these markers are not important. Rather, a larger study would need to be carried out to further investigate their role in CDC.
Conclusions
===========
Our results suggest that Fez1 expression may be associated to both clinical-pathological features and survival in patients with CDC. *FEZ1*gene alterations may be linked to the high frequency of LOH found at 8p22, where *FEZ1*resides. The lack of similar association for the other four genes studied may be due to the low statistical power of the study.
Competing interests
===================
None declared.
Abbreviations
=============
CDC, Collecting Duct Carcinoma; RCC, renal cell carcinoma; LOH, loss of heterozygosity
Authors\' contributions
=======================
A.V. carried out the immunohistochemical analysis and reviewed the slides, he also contributed to the draft of the manuscript. T.P.G. was responsible for the clinical study. M.G. carried out the original histopathological diagnosis. H.I. participated in the immunohistochemical analysis and statistical analysis. E.G. participated in the immunohistochemical analysis and statistical analysis. F.P. was responsible for the clinical study. L.G.G. participated in designing the study and in drafting the manuscript. C.M.C. participated in designing the study. R.B. participated in the original design and coordination of the study, and in writing the manuscript
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1471-2490/4/11/prepub>
Acknowledgements
================
This work was supported partially by U.S. Public Health Service Grants to C.M.C. and by the Sidney Kimmel Foundation award to R.B. We thank Constantine Daskalakis, ScD, of the Biostatistics Section, Thomas Jefferson University, for statistical help on the manuscript.
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Representative examples of immunohistochemical analysis of Fez1, Fhit, p53, p27 and bcl2 proteins in primary Bellini\'s duct carcinoma of the kidney. **A**, Normal renal parenchyma shows uniform, cytoplasmic positive staining for Fez1 (×400). **B**, Fez1 protein is absent in this CDC (Case 1; ×400). An adjacent dysplastic distal duct (*red arrow*) shows strong Fez1 immunoreacticity. **C**, CDC section showing diffuse cytoplasmic staining for Fhit protein (Case 2; ×400). **D**, CDC neoplastic glands display strong nuclear immunoreaction for p53 oncoprotein (Case 5; ×400). Case 9 shows p27 immunoreactivity in both nucleus and cytoplasm **(E)**and bcl2 cytoplasmic immunostaining, *red arrow***(F)**(×400).
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Kaplan-Meier survival curves and associated log-rank test p-values for of eleven patients with collecting duct carcinoma of the kidney based on Fez1 (A), and Fhit (B) expression. (+); positive expression; (-) = negative expression; ■ and **o**= Event times.
:::
:::
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Clinical-pathological features and protein expression.
:::
**PZ ID** **T** **N** **M** **STAGE^a^** **Fez1** **Fhit** **P27** **Bcl2** **P53** **Survival (months)**
----------- ------- ------- ------- -------------- ---------- ---------- --------- ---------- --------- -----------------------
**1** 3 1 0 3 -\* \- \- \- +^1^ 17^+^
**2** 4 2 0 4 \- \+ \- \+ \- 8^+^
**3** 3 0 1 4 \- \- \- \- \- 2^+^
**4** 4 2 1 4 \- \+ Cyt \- +^2^ 35^+^
**5** 3 0 0 3 \- \+ Cyt \- +^3^ 12^+^
**6** 3 1 1 4 \- \- \- \- \- 18^+^
**7** 2 0 0 2 \+ \+ \- \- \- 58^\#^
**8** 3 0 0 3 \+ \+ Cyt \+ +^4^ 55^\#^
**9** 3 0 1 4 \+ \+ Cyt\^ \+ \- 8^+^
**10** 2 0 1 4 \+ \+ Cyt \- \- 16^\#^
**11** 3 1 0 3 \- \+ Cyt \+ \- 7^\#^
^a^staged following the guidelines of the tumor-node-metastasis (ref 16)
\* Tumor showed 60% of the cells negative for Fez1 expression
\^ Nuclear p27 was also detected in this case
^1,2,3,4^: Showed 85,20,30,50 % of the cells positive for p53 expression, respectively
^+^Dead
^\#^Alive
:::
|
PubMed Central
|
2024-06-05T03:55:47.866842
|
2004-9-9
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517938/",
"journal": "BMC Urol. 2004 Sep 9; 4:11",
"authors": [
{
"first": "Andrea",
"last": "Vecchione"
},
{
"first": "Tommaso Prayer",
"last": "Galetti"
},
{
"first": "Marina",
"last": "Gardiman"
},
{
"first": "Hideshi",
"last": "Ishii"
},
{
"first": "Enrico",
"last": "Giarnieri"
},
{
"first": "Francesco",
"last": "Pagano"
},
{
"first": "Leonard G",
"last": "Gomella"
},
{
"first": "Carlo M",
"last": "Croce"
},
{
"first": "Raffaele",
"last": "Baffa"
}
]
}
|
PMC517939
|
Background
==========
Molecular biological studies of plants require high-quality DNA. Several DNA extraction procedures for isolating genomic DNA from various plant sources have been described, including the salt extraction method and the cetyltrimethyl ammonium bromide (CTAB) method \[[@B1]\] and its modifications \[[@B2],[@B3]\]. The need for a rapid and simple procedure is urgent, especially when hundreds of samples need to be analyzed.
Most methods require the use of liquid nitrogen \[[@B4]\] or freeze-drying (lyophilization) \[[@B5],[@B6]\] of tissue for the initial grinding, and these processes are unavailable in many regions of the world. After grinding the tissues in various extraction buffers, DNA is extracted with phenol-chloroform, or the extract is dialyzed against EDTA and a buffered Tris-HCl solution \[[@B7]\]. After extraction, the aqueous phase is concentrated, either by ethanol or isopropanol precipitation \[[@B8],[@B9]\], or with microconcentrators (*e.g*., the Wizard genomic DNA purification system; Promega, USA). However, these methods are not time efficient for consistently obtaining PCR-quality DNA from calluses and plants, since they require that the tissues be ground in liquid nitrogen, followed by precipitation of the DNA pellet in ethanol, washing and drying the pellet, etc.
In our laboratory, we investigate the stability of transgenes expressed in calluses or plants transformed by nuclear or chloroplast transformation in tobacco, lettuce, potato, etc. In addition, we need high-quality genomic DNA for Southern blot analysis to confirm homologous recombination in chloroplast transformation \[[@B10]\]. For our purposes, we desire a simple and fast procedure for obtaining plant genomic DNA for PCR, and good-quality DNA for complete enzyme digestion for Southern blot analysis. Therefore, we present a protocol for extracting genomic DNA from fresh calluses and plant leaves that is applicable to a variety of organisms, regardless of the complexity of their genomes. In addition, we present a rapid and reliable procedure for extracting genomic DNA for PCR or Southern blot analysis from a small amount (\~0.5 cm^2^) of leaf tissue.
Results and discussion
======================
We describe a simple and reproducible procedure for RAPD or PCR amplification of transgenes from various plant sources. Three different variations of the genomic DNA extraction protocol for RAPD analysis were compared. After simple plant leaf and callus tissue homogenization with DNA extraction buffer using a hand-operated homogenizer, the leaf and callus cells were lysed with 20% SDS. Then, genomic DNA was extracted with the same volume of phenol/chloroform/isoamyl alcohol (25:24:1). An aliquot of the supernatant (\~5 μl) was diluted 5 fold with sterile dH~2~O, and PCR was performed using 1 μl of the diluted supernatant as a template (Figure [1](#F1){ref-type="fig"}, lane 1). Alternatively, after phenol/chloroform/isoamyl alcohol (25:24:1) extraction, the supernatant was transferred to a fresh tube for a second phenol/chloroform/isoamyl alcohol (25:24:1) extraction followed by a chloroform extraction. An aliquot of the supernatant (\~5 μl) was diluted 5 fold with sterile dH~2~O, and PCR was performed using 1 μl of the diluted supernatant as the DNA template (Figure [1](#F1){ref-type="fig"}, lane 2). In the third variation, after chloroform extraction the supernatant was transferred to a fresh tube and precipitated with two volumes of ethanol. After washing the DNA pellet with 70% ethanol, the DNA pellet was dissolved in 50 μl of sterile dH~2~O containing 20 μg ml^-1^DNase-free RNase A. For PCR, 50 ng of the DNA were used as the template (Figure [1](#F1){ref-type="fig"}, lane 3).
DNA samples prepared using the three different extraction procedures (lanes 1, 2, and 3 in Figure [1](#F1){ref-type="fig"}) were subjected to PCR amplification using two 10-mer random primers: RAPD-1 and RAPD-2 (Genotech, Korea) (Figure [1](#F1){ref-type="fig"}). All the genomic DNA samples produced a clear, sharp, and reproducible PCR product when primer RAPD-1 was used for PCR amplification (Figure [1A](#F1){ref-type="fig"}). Although three variations of the DNA extraction procedure were used, there was little difference between lanes 1, 2, and 3. Only a difference in the intensity of the band was observed, which may be due to the different template concentrations used for the PCR reaction. This result suggests that the supernatant after the first phenol treatment (protocol 1) was sufficiently pure to be used as the DNA template for PCR amplification. Therefore, PCR amplification with another random primer, RAPD-2, was performed using the DNA template extracted using the simplest protocol (Figure [1B](#F1){ref-type="fig"}). The PCR amplification was successful, and the same banding pattern was seen when we repeated the PCR amplification. Therefore, we confirmed that the DNA template extracted using the simplest method was sufficient for RAPD, and it was used as the DNA template to amplify specific DNA or transgenes from transgenic calluses or plants.
To examine the presence of *bar*\[[@B11],[@B12]\] or the LTB gene \[[@B13]\] at a directed site in the chloroplast DNA after homologous recombination in transplastomic tobacco plants, putative transformants were screened by PCR analysis (Figure [2](#F2){ref-type="fig"}). PCR amplification using primer combinations Bar-F/Bar-R, 1-F/1-R, and LTB-F/LTB-R resulted in 550-, 1700-, and 380-bp fragments, respectively. Primers 2-F/2-R produced 2200- or 1900-bp fragments containing *bar*and LTB, respectively, which confirmed the site-specific integration in the chloroplast genome (Table [1](#T1){ref-type="table"}). No detectable product was produced using genomic DNA from wild-type plants (Figure [2B](#F2){ref-type="fig"}, lane 1), demonstrating the specificity of these primers and genomic DNA extracts. Therefore, we concluded that chloroplast DNA was also amplified, although we did not use liquid nitrogen, but simply used a hand-operated homogenizer with a plastic tip. We also successfully amplified specific foreign genes from transgenic tobacco plants transformed using the nuclear transformation method, including the α-interferon (550 bp) \[[@B14]\], the core epitope of the PEDV gene (420 bp) \[[@B15],[@B16]\], the LTB gene (380 bp) \[[@B17]\], and the A plus B subunit of the *Helicobacter pylori*urease gene (2450 bp) \[[@B18]\] (Figure [3](#F3){ref-type="fig"}). Specific PCR amplification was also conducted using transgenic calluses as well as transgenic plants. In transgenic calluses derived from Siberian ginseng plants, α-interferon was successfully amplified, showing a 580-bp fragment in 1% agarose gels.
Using the third protocol, the DNA concentrations obtained were between 20 and 30 μg/0.5 cm^2^plant leaf, and the absorbance ratios (A~260~/A~280~) were between 1.7 and 2.0. However, the DNA concentrations from rice, maize, and poplar were relatively low (\< 3 μg). This may be because homogenization using a hand-operated homogenizer with a plastic tip is incomplete, since the leaves of these plants are stronger than the leaves of tobacco, potato, cabbage, lettuce, and Siberian ginseng. Genomic DNA from various plant sources was electrophoresed on 1% agarose gels, and high-molecular-weight DNA was obtained (Figure [4A](#F4){ref-type="fig"}). When the genomic DNA was digested with *Eco*RI and *Hin*dIII, the DNA was completely digested, and could be used for Southern blot analysis. Therefore, we concluded that the purity and quality of the genomic DNA was sufficient for enzyme digestion.
There are many advantages in using our genomic DNA extraction method to obtain template for PCR amplification. Many different plants could be amplified using the same DNA extraction method and the same PCR protocol. Using this protocol, we successfully amplified DNA repeatedly from all eight plant sources examined. Our procedure is not only very simple, but is also time and cost effective. After homogenization in DNA extraction buffer using a hand-operated homogenizer, the template DNA for PCR could be extracted by phenol/chloroform/isopropyl alcohol treatment. Since this method does not require liquid nitrogen, expensive commercial DNA extraction kits, or ethanol precipitation to produce DNA template for PCR, we can save considerable time and expense. The time required for our DNA extraction method is less than 30 min, which is extraordinary compared with other genomic DNA extraction methods. With our procedure, leaf tissue (\~0.5 cm^2^) is put in a 1.5-ml microfuge tube and homogenized directly; consequently, a very small sample is required for DNA extraction. There is no sample waste with our method, whereas much larger samples are required when plant samples are ground in a mortar and pestle with liquid nitrogen and transferred to a tube. Previously reported techniques require several steps \[[@B19]\], use of expensive enzymes such as proteinase K \[[@B20]\], or beads and shakers \[[@B21]\]. Although the protocol for one-step plant DNA isolation was developed by Burr et al. \[[@B22]\], if plant material more than 1 mm^2^was used in the extraction, co-extracts (e.g., chlorophyll) were extracted alongside the DNA and inhibited the PCR. On the contrary, our protocol does not require appropriate sample size to extract DNA. Warner et al. \[[@B23]\] also reported a rapid DNA extraction method in barley, which requires NaOH. However, the extracted DNA samples were easily degraded. The DNA samples extracted by our protocol were very stable and could be stored for a long time without degradation.
We find the new method very useful in our laboratory, since limited transgenic plant tissue or callus is sometimes available in a culture bottle. Therefore, the simplicity, efficiency, speed, and lack of a requirement for expensive facilities make our method an attractive alternative to existing methods of genomic DNA extraction.
Conclusions
===========
Our objective was to extract genomic DNA with a simple and fast procedure for PCR and enzyme digestion. The present protocol is for extracting genomic DNA from fresh calluses or plant leaf tissues that is applicable to a variety of organisms, regardless of the complexity of their genomes. Our procedure is not only very simple, but is also time and cost effective. Since this method does not require liquid nitrogen, expensive commercial DNA extraction kits, or ethanol precipitation to produce DNA template for PCR, we can save considerable time and expense. In addition, a very small sample is required for DNA extraction.
Methods
=======
Plant material
--------------
We examined plant material from plant collections commonly used for foreign gene expression: tobacco (*Nicotiana tabacum*), potato (*Solanum tuberosum*), cabbage (*Brassica oleracea*), rice (*Oryza sativa*), lettuce (*Lactuca sativa*), maize (*Zea mays*), poplar (*Populus nigra*), and Siberian ginseng (*Eleutherococcus senticosus*). The plants used for genomic DNA extraction were grown in a culture room or greenhouse. Tobacco, potato, cabbage, lettuce, and Siberian ginseng were grown in a culture room. Seeds were surface-sterilized with 70% ethanol for 3 min, and then with 10% sodium hypochlorite for 15 min. The seeds were washed five times in sterile water and placed in Petri dishes containing 4.6 g l^-1^MS salts \[[@B24]\], 30 g l^-1^sucrose, and 7.5 g l^-1^bactoagar at pH 5.7. The seeds were grown in a controlled environment at 25°C on a 16-h continuous light and 8-h dark daily cycle. Rice, maize, and poplar plants were grown in a greenhouse for genomic DNA extraction. Transgenic tobacco plants and Siberian ginseng calluses were also used to extract genomic DNA and to confirm foreign gene insertion by PCR amplification.
DNA extraction (Figure [5](#F5){ref-type="fig"})
------------------------------------------------
We tested three different variations of the genomic DNA extraction procedure. About 0.5 cm^2^of culture room- or greenhouse-grown plant leaves were put in a 1.5-ml microfuge tube. The leaf tissue was homogenized in 50 μl DNA extraction buffer (500 mM NaCl, 100 mM Tris-HCl pH 7.5, and 50 mM EDTA pH 7.5), using a hand-operated homogenizer (Sigma, Z35997-1) with a plastic pestle, for 15\~20 s. After an initial homogenization, another 150 μl of DNA extraction buffer were added and homogenized with the same homogenizer for 15\~20 s. Then, 20 μl of 20% SDS were added and vortexed for 30 s. The samples were incubated at 65°C for 10 min for cell lysis. At this point, three different DNA extraction protocols were used for PCR amplification. Protocol 1: An equal volume of phenol/chloroform/isoamyl alcohol (25:24:1) was added to the samples, mixed by vortexing for 30 s, and then centrifuged at 10,000 g for 3 min at 4°C. The supernatant was diluted 5 fold, and 1 μl of the supernatant was used as the DNA template for PCR analysis. Protocol 2: The supernatant from protocol 1 was transferred to a fresh tube and extracted one more time with phenol/chloroform/isoamyl alcohol (25:24:1) and then with chloroform. The supernatant was diluted 5 fold, and 1 μl of the supernatant was used as the DNA template for PCR analysis. Protocol 3: The supernatant from protocol 2 was transferred to a fresh tube, and a double volume of ethanol was added to each sample, mixed well, and the samples were incubated at -20°C for 30 min. The samples were then centrifuged at 10,000 g for 10 min at 4°C. The pellet was washed with 70% ethanol, dried, and resuspended in sterile dH~2~O containing 20 μg/ml DNase-free RNase A. The concentration and purity were determined from the A~260~/A~280~ratio using a spectrophotometer. Five micrograms of each genomic DNA sample were incubated at 37°C for 3 h for complete digestion with 20 U of *Eco*RI and *Hin*dIII (Life Technologies, USA) in a total volume of 100 μl and analyzed on 1.0% agarose gels using 15 μl aliquots of the reaction mixture.
Analysis of DNA and PCR amplifications
--------------------------------------
Five micrograms of each genomic DNA sample measured by spectrophotometer were incubated at 37°C for 3 h for complete digestion with 20 U of *Eco*RI and *Hin*dIII in a total volume of 100 μl and analyzed on 1.0% agarose gels using 15 μl aliquots of the reaction mixture. By using the genomic DNA isolated from the leaves or calluses of wild-type and transgenic plants, PCR amplifications were performed on a Perkin Elmer GeneAmp PCR System 2400 (Biorad, USA) in a total volume of 25 μl containing 1 × PCR buffer, 0.2 mM dNTP, 10 pmol of each primer (Table [1](#T1){ref-type="table"}), 50 ng template DNA from plants, and 0.25 U Ex-Taq DNA polymerase (Takara, Japan) using the following profile: a 3-min denaturation at 94°C and 40 cycles of 1-min denaturation at 94°C, 1-min annealing at 37°C for RAPD or 55°C for specific transgene amplification, and a 2-min extension at 72°C, followed by a final extension at 72°C for 7 min. The PCR products were resolved by electrophoresis in 1.0% agarose gels.
Authors\' contributions
=======================
TJK developed the method and performed majority of the experiments. MSY provided technical assistance, funding and supervision for the work. All authors have read and approved the final manuscript.
Acknowledgements
================
This research was supported by a grant for international cooperation from the Ministry of Science and Technology, South Korea.
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
**RAPD fingerprints of all the DNA samples with primers (A) RAPD-1 (5\'-CCACAGCAGT-3\') and (B) RAPD-2 (5\'-AAGCCCGAGG-3\').**(A) Lane 1, the DNA template was the supernatant from the first phenol:chloroform:isoamyl alcohol extraction (protocol 1); lane 2, the DNA template was the supernatant after two phenol:chloroform:isoamyl alcohol extractions and one chloroform extraction (protocol 2); lane 3, the DNA template was prepared with an additional ethanol precipitation (protocol 3). (B) PCR products amplified using only the DNA template from protocol 1. 1 kb, DNA molecular weight ladder.
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
**Schematic diagram of the chloroplast genome transformed with the bar or LTB gene and PCR analysis of wild-type and chloroplast transformants.**(A) Map of the chloroplast targeting region in transplastomic plants. Arrows indicate the direction of transcription. Primer 1F is located in the native chloroplast DNA; 1R, aadA; 2F, aadA; 2R, trnA. (B) The PCR products of transplastomic plants. Lane 1, wild-type plant with primers Bar-F/Bar-R; lane 2, primers Bar-F/Bar-R produce a 550-bp fragment; lanes 3 and 6, primers 1-F/1-R produce a 1700-bp fragment; lane 4, primers 2-F/2-R produce a 2200-bp fragment containing the bar gene; lane 5, primers LTB-F/LTB-R produce a 380-bp fragment; lane 7, primers 2-F/2-R produce a 1900-bp fragment containing the LTB gene. 1 kb, DNA molecular weight ladder.
:::
:::
::: {#F3 .fig}
Figure 3
::: {.caption}
######
**PCR amplification products from transgenic plants and calluses.**Lane 1, α-interferon in transgenic calluses from Siberian ginseng; lane 2, Core epitope of PEDV; lane 3, LTB; lane 4, A plus B subunits of *Helicobacter pylori*urease. 1 kb, DNA molecular weight ladder.
:::
:::
::: {#F4 .fig}
Figure 4
::: {.caption}
######
**Agarose gel electrophoresis of undigested and digested genomic DNA.**(A) Genomic DNA from five different plants with 5 μg of genomic DNA loaded from each sample. (B) Genomic DNA digested with the restriction enzymes *Eco*RI and *Hin*dIII. 1 kb, DNA molecular weight ladder.
:::
:::
::: {#F5 .fig}
Figure 5
::: {.caption}
######
Three different DNA extraction protocols for calluses and plants
:::
:::
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Primers used in this study
:::
**Primer Name** **Target Amplified** **Size of Product** **Primers (5\'-3\')**
----------------- ------------------------------------------------- --------------------- -----------------------------
RAPD-1 Random CCACAGCAGT
RAPD-2 Random AAGCCCGAGG
1-F Chloroplast 1700 bp AAAACCCGTCCTCAGTTCGGATTGC
1-R CCGCGTTGTTTCATCAAGCCTTACG
2-F Chloroplast 1900 bp(LTB) CTGTAGAAGTCACCATTGTTGTGC
2-R 2200 bp (*bar*) TGACTGCCCACCTGAGAGCGGACA
Bar-F *Bar* 550 bp CGAGACAAGCACGGTCAACTTC
Bar-R AAACCCACGTCATGCCAGTTC
LTB-F B subunit of *E. coli*heat-labile enterotoxin 380 bp ATGGCTCCCCAGTCTATTACAG
LTB-R CTAGTTTTCCATACTGATTGC
PEDV-F Porcine epidemic diarrhea virus 420 bp TCTATGGTTACTTTGCCATC
PEDV-R AATTAAACGTCTGTGATACC
Ure-F A and B subunits of *Helicobacter pylori*urease 2450 bp GCCACCATGAAACTCACCCCAAAAG
Ure-R GGTACCCTAGAAAATGCTAAAGAGTTG
IFN-F α-Interferon 580 bp ATGGCCTCGCCCTTTGCTTTAC
IFN-R CTCTTATTCCTTCCTCCTTAATC
F, forward primer; R, reverse primer
:::
|
PubMed Central
|
2024-06-05T03:55:47.869315
|
2004-9-2
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517939/",
"journal": "BMC Biotechnol. 2004 Sep 2; 4:20",
"authors": [
{
"first": "Tae-Jin",
"last": "Kang"
},
{
"first": "Moon-Sik",
"last": "Yang"
}
]
}
|
PMC517940
|
Background
==========
Osteoporosis has recently been recognized as a major public health problem by some governments and health care providers. In the European community, the number of men and women aged 65 years of older will increase steadily and the most dramatic changes will occur in the very elderly, in whom the incidence of osteoporotic fracture is greatest \[[@B1]\]. As the populations gets older, morbidity, mortality and financial costs attributed to osteoporosis are expected to rise. The economic costs related to osteoporotic fractures are substantial and will almost certainly increase further unless effective preventive interventions are widely implemented \[[@B2]\].
Peak bone mass is achieved soon after puberty, and bone is lost with various \"insults\", including ageing and postmenopausal changes. Factors influencing peak bone mass and loss range from nutrition, to lifestyle, to certain medical disorders. Educational level may also have an effect on bone mineral density since there is relationship between educational level and reproductive factors such as pregnancy and lactation and other lifestyle factors \[[@B3]-[@B7]\].
In developed countries a higher prevalence of most chronic diseases has been recognized among lower socio economic levels and in less educated subjects \[[@B8]-[@B14]\]; however, only a few and conflicting data are available for osteoporosis \[[@B15]-[@B18]\].
Since many risk factors for osteoporosis, such as diet, deficiency of trace minerals, reproductive factors, inactivity and tobacco use, are lifestyle variables related to social and cultural background \[[@B18]-[@B25]\], the influence of formal educational level on bone mineral density \[BMD\], together with establishment of a relationship between formal educational level and bone mineral density in postmenopausal women are the main concern of this study.
Patients were compared according to years of formal education. We used formal education because it may be regarded as a composite or surrogate variable for overall socioeconomic status \[[@B10]\], and level of education \[years of completed education) allows comparison between countries more readily than other socioeconomic indicators \[[@B13]\].
Purpose of this study was to evaluate the influence of formal education on BMD and investigating the relationship between educational level and bone mineral density in the postmenopausal women.
Methods
=======
In Department of Physical Medicine and Rehabilitation, of the total 701 consecutive women screened, 132 were excluded. This study was undertaken in Dicle University, Diyarbakir, Turkey. The study protocol was reviewed and approved by the Dicle University Ethics Committee, and informed consent was obtained from all participants. A detailed history was taken from each woman including relevant life-style parameters and risk factors, and their weight and height measurements were recorded. The following exclusion criteria were applied for further analyses: (1) fractures after the age of 25; (2) menopause before the age of 40; (3) amenorrhoea greater than 6 months; (4) chronic conditions affecting bone density; (5) any use of corticosteroids.
A total of 569 postmenopausal women, at 45 to 86 years of age (mean age of 60.43 ± 7.19 years) were considered. BMD of the spine and hip (neck, trochanter, and ward\'s triangle) were measured by dual-energy x-ray absorptiometry (NORLAND, 6938CE, New York, USA). According to the WHO \[[@B26]\] osteoporosis was defined as a lumbar BMD value more than 2.5 SD below the T-score, corresponding to 0.759 g/cm^2^\[[@B27]\]. The variation coefficient for consecutive determinations on spine and femur images in our laboratory was 1.9% at the lumbar spine and 1.6 % at the femur region. All spinal scans were reviewed for evidence of vertebrae with collapse or focal sclerosis by an experienced radiologist.
In order to standardize the procedure, the patients all answered the same specially developed questionnaire supervised by the doctor (revised from the MEDOS Form) \[[@B28]\]. A standardized interview was used at the follow-up visit to obtain information on demographic, life-style, reproductive and menstrual histories such as age at menarche, age at menopause, number of pregnancies, number of abortions, duration of menopause, duration of fertility, and duration of lactation.
The level of education is categorized in four groups according to the number of school years and the highest qualification received; no education (Group 1 = 209 patients), elementary (8 years or less, Group 2 = 222 patients), high school (9--11 years, Group 3 = 79 patients), and university (12 years or more, Group 4 = 59 patients). Body mass index (BMI; weight / height^2^) was obtained through height and weight measurements by using a wall-mounted ruler and a digital scale.
Recent dietary calcium intake (past 12 months) was assessed using standardized food models to estimate portion sizes \[[@B24]\]. Dietary calcium intakes were analyzed in two groups as inadequate (\<500 mg/day) and adequate (500--1000 mg/day) \[[@B25]\]. The number of drinks consumed per week in the past 30 days, was used as the measure of current alcohol consumption (never use, very rare, frequently). Women who had smoked at least ten cigarettes per day during the five postmenopausal years were classified as smokers \[[@B25]\]. All patients classified, in terms of their reported current and life long smoking, into such group: 1) never use, 2) less than 1 packet, 3) 1--2 packet, and 3) more than 2 packets per day. They were also classified, in terms of their reported current and life-long caffeine use, into such groups: 1) never use, 2) 2 or below cup caffeinated coffee per day, 3) 3 or above cups caffeinated coffee per day. Physical activity is assessed by inquiring about the reported number of 20-min sessions of leisure-time physical activity per week and physically active behavior is defined as participation in more than two sessions per week; job-related physical exercise is not taken into account.
Statistical analyses
--------------------
The statistical analyses were carried out with the SPSS/ PC-program. Differences in proportions for categorical variables were tested by chi-square test. The data are expressed as means ± SD. Statistical significance was tested using one way-ANOVA test and post-hok Bonferroni test for comparison of different groups. Pearson correlation test were computed to measure the association between the variables studied. The statistical significant set if the p-value was less than 0.05.
Results
=======
Their reproductive and demographic characteristics are shown in Table [1](#T1){ref-type="table"}. When comparing the adequate calcium intake, the most educated women showed a statistically significant higher percentage than that of the other groups (p \< 0.05). The mean ages of groups were 59.75 ± 7.29, 61.42 ± 7.50, 60.23 ± 749, and 58.72 ± 7.46, respectively. There was no significant difference among all groups with respect to age, BMI, age at menarche, age at menopause, and duration of menopause (p \> 0.05) (Table [2](#T2){ref-type="table"}).
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Values for various reproductive and personal characteristics among 569 women screened for osteoporosis according to education level
:::
**Variable** **No Education (Group 1 = 209)** **Elementary (Group 2 = 222)** **High school (Group 3 = 79)** **University (Group 4 = 59)**
-------------------------------------------- ---------------------------------- -------------------------------- -------------------------------- -------------------------------
**Menstrual cycle pattern, (%)**
Regular cycles 159 (76) 151 (68) 66 (84) 43 (73)
Irregular cycles 50 (24) 71 (22) 13 (16) 16 (27)
**Menopausal status, (%)**
Natural 171 (82) 189 (85) 72 (91) 40 (69)
Iatrogenic 38 (18) 33 (15) 7 (9) 19 (31)
**Premenopausal HRT, (%)**
Never use 195 (93) 195 (88) 59 (75) 51 (86)
Ever use 14 (7) 27 (12) 20 (25) 8 (14)
**Postmenopausal HRT, (%)**
Never use 201 (96) 203 (91) 63 (79) 52 (88)
Ever use 8 (4) 19 (9) 16 (21) 7 (12)
**Physical daily activity, (%) Childhood**
Inactivity 6 (3) 33 (15) 14 (18) 8 (14)
Mild activity 100 (48) 118 (53) 59 (75) 32 (54)
Serious activity 103 (49) 71 (32) 6 (7) 19 (32)
**Adolescent**
Inactivity 8 (4) 35 (16) 15 (19) 9 (15)
Mild activity 60 (29) 105 (47) 54 (68) 19 (32)
Serious activity 141 (67) 82 (37) 10 (13) 31 (53)
**Adult**
Inactivity 56 (27) 83 (37) 38 (48) 22 (37)
Mild activity 94 (45) 97 (44) 36 (46) 21 (36)
Serious activity 59 (28) 42 (19) 5 (6) 16 (26)
**Calcium intake, (%)**
Adequate 102 (49) 107 (48) 36 (46) 45 (76)\*
Inadequate 107 (51) 115 (52) 43 (54) 14 (24)
**Smoking, (%)**
Never use 203 (97) 185 (83) 59 (75) 40 (69)
\< 1 packet 4 (2) 18 (8) 6 (7) 9 (15)
1--2 packet 2 (1) 9 (4) 10 (13) 1 (2)
\> 2 packet \- 10 (5) 4 (5) 8 (14)
**Coffee, (%)**
Never use 117 (56) 102 (46) 43 (54) 20 (34)
2 or below cup 88 (42) 85 (38) 20 (25) 23 (39)
3 or above cup 4 (2) 35 (16) 16 (21) 16 (26)
**Alcohol, (%)**
Never use 203 (97) 204 (92) 64 (81) 40 (68)
Very rare 2 (1) 12 (5) 10 (13) 14 (24)
Frequently 4 (2) 6 (3) 5 (6) 5 (8)
\*Significant different from other groups (p \< 0.05).
:::
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Comparison of reproductive characteristics of 569 women according to education level
:::
**No Education** **Elementary** **High school** **University**
------------------------------------ ------------------------- ---------------------- ----------------- ----------------
Age (years) 59.75 ± 7.29 61.42 ± 7.50 60.23 ± 7.49 58.72 ± 7.46
Body Mass Index 27.18 ± 5.14 28.23 ± 5.63 27.72 ± 6.14 28.45 ± 5.56
**Age at menarche (years)** 13.77 ± 1.36 13.75 ± 1.28 14.09 ± 0.83 13.22 ± 1.38
**Age at menopause (years)** 45.26 ± 5.57 45.22 ± 6.72 47.25 ± 4.69 45.38 ± 5.25
**Duration of fertility (years)** 31.48 ± 5.73 31.47 ± 6.79 33.25 ± 4.81 32.16 ± 5.61
**Duration of menopause (years)** 14.49 ± 7.8 13.20 ± 8.17 12.02 ± 8.02 12.41 ± 8.73
**Number of abortions** 1.31 ± 1.51^b,\ c^ 0.94 ± 1.64 0.51 ± 1.17 0.19 ± 0.54
Number of pregnancies 7.11 ± 3.38^a,\ b,\ c^ 4.93 ± 3.61^d,\ e^ 2.27 ± 1.91 2.29 ± 1.39
**Duration of lactation (months)** 133.2 ± 54.3^a,\ b,\ c^ 93.62 ± 50.66^d,\ e^ 45.76 ± 38.83 57.77 ± 35.36
Values are shown as mean ± standard deviation (SD) for all variables.
^a^Significant different from elementary group, ^b^Significant different from high school group, ^c^Significant different from university group, ^d^Significant different from high school group, and ^e^Significant different from university group (p \< 0.05).
:::
Number of abortions was higher in group 1 and 2 than those of group 3 and 4 (p \< 0.05). There was no significant difference with respect to number of pregnancies and duration of lactation between group 3 and 4 while there was a significant difference among other groups (p \< 0.05), and number of pregnancies and duration of lactation were found to be the highest in Group 1 and 2. Number of pregnancies and duration of lactation in Group 1 were 7.11 ± 3.38 and 133.23 ± 54.34 months and in Group 2 were 4.93 ± 3.61 and 93.62 ± 50.66 months (Table [2](#T2){ref-type="table"}).
Spine BMD was significant lower in Group 1 than that of other groups (p \< 0.05). Trochanter and ward\'s BMD were the highest in Group 4 and there was a significant difference between Group 1 and 4 (p \< 0.05). The prevalence of osteoporosis showed an inverse relationship with level of education, ranging from 18.6% for the most educated to 34.4% for the no educated women (p \< 0.05) (Table [3](#T3){ref-type="table"}).
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Comparisons of bone mineral density of 569 women according to education level
:::
**No Education** **Elementary** **High school** **University**
-------------------------- ------------------------ ------------------ ----------------- ----------------
**L2-4 BMD** 0.62 ± 0.29^a,\ b,\ c^ 0.74 ± 0.19 0.77 ± 0.17 0.76 ± 0.33
**Femoral Neck BMD** 0.64 ± 0.19 0.61 ± 0.24 0.62 ± 0.24 0.64 ± 0.21
**Trochanter BMD** 0.49 ± 0.18^c^ 0.53 ± 0.19 0.56 ± 0.16 0.61 ± 0.12
**Ward\'s triangle BMD** 0.45 ± 0.17^c^ 0.49 ± 0.18 0.49 ± 0.20 0.58 ± 0.10
**Osteoporosis (%)** 72 (34.4)^a,\ b,\ c^ 62 (27.9)^d,\ e^ 17 (21.5) 11(18.6)
Values are shown as mean ± standard deviation (SD) for all variables except percentage of osteoporosis.
^a^Significant different from elementary group, ^b^Significant different from high school group, ^c^Significant different from university group (p \< 0.05).
:::
Additionally, there was a significant correlation between educational level and spine BMD(r = 0.20, p \< 0.01), trochanter BMD (r = 0.13, p \< 0.01), and ward\'s BMD (r = 0.14, p \< 0.01) but wasn\'t neck BMD (r = -0.02, p \> 0.05).
Discussion
==========
The health care costs, morbidity and mortality excess related to osteoporotic fractures are a major health problem in western countries \[[@B29],[@B30]\]. In order to reduce these medical, social and economic burdens, which are expected to rise in forthcoming years, there is a need for preventive strategies based on health promotion campaigns \[[@B31]\]. To change health behavior related to modifiable risk factors for osteoporosis and to design targeted and more effective health messages \[[@B32]\], the programs have to take into account the socioeconomic and cultural background of the population strata in which the risk for osteoporosis is particularly prominent \[[@B15]\].
Although mechanisms of association between education and osteoporosis remain partly unexplained, most of the risk factors examined have shown distinct trends according to educational level. Although educational level may be an imperfect measure for socio economic status, many studies have clearly established that this marker acts as a good predictor not only for most chronic diseases \[[@B10],[@B11],[@B14]\] but also for many related risk factors \[[@B22],[@B23]\].
In a study by La Vecchia et al., they found that education is a strong determinant of several chronic conditions, and the pattern of health care utilization also varied extensively according to education \[[@B11]\].
Varenna et al. evaluated 6160 postmenopausal women referred for their first densitometric evaluation and they found age at menarche, past exposure to oral contraceptives, prevalence of chronic diseases, physical activity, overweight and smoking showed significant trends according to years of education \[[@B15]\]. Also, as they had a cohort of postmenopausal women as the study group, they could show differences in the prevalence of osteoporosis among educational classes and the protective role played by increases in formal education.
The present study showed that there was no significant difference among all groups with respect to age, BMI, age at menarche, age at menopause, and years since menopause. But there were statistically significant differences among groups in respect to number of pregnancies, duration of lactation, bone mineral density and percentage of osteoporosis.
The comparison with studies performed in other countries can be misleading since eating habits are strongly influenced by ethnic and geographical backgrounds \[[@B7]\]. The meaning of the lower calcium intake observed in the least educated women could be referred to a real difference, taking into account the low sensitivity of the questionnaire used to assess calcium intake. During pregnancy and lactation the growing fetal and neonatal skeletons make major demands for calcium, respectively. There is good evidence now that during lactation a substantial part of this calcium demand is mobilized from the maternal skeleton even despite high dietary calcium. This effect could be especially important with multiple pregnancies and extended lactation.
Magnus et al. undertook a random sample of 1514 Norwegian women and men to investigate knowledge of osteoporosis and attitudes towards methods for preventing this disease, and they concluded that in both men and women, increased knowledge of osteoporosis was correlated to a high level of education \[[@B33]\].
In several studies, authors have found that reproductive history has an inverse relation to bone density \[[@B3]-[@B6],[@B34]-[@B41]\]. The bone density is adversely affected by both high rate of live birth and long period of breast feeding, common in the region where this study was carried out. The lower birth rate and short period of breast feeding found with the group having university or high school degree, may suggest that both birth rate and the breast feeding period may be associated with educational level. Furthermore, the calcium intake in the group with highest educational level was also found to be considerably higher than that of the other groups. The higher BMD values found with the group of highest educational level, may be attributed to the sufficient amount of calcium intake as was the case with this group
Though the effect of formal educational level on bone mineral density has not yet been well established, the above findings may suggest some hypothetical comments. The findings of this study imply that osteoporosis which is related to bone mineral density, may be related to the educational level and the risks due to higher birth rate, excessive breast-feeding and insufficient calcium intake, and may be controlled through an improvement in educational level.
Because of several limitations, caution must be exercised in interpreting the results of our study. Except for densitometric assessment, the results depend on self-reports. Even though self-report diagnoses have been shown to be valid \[[@B6]\], the level of formal education could bias the report about habits and health practices. Moreover, the sample was not randomly selected and it cannot be considered representative of postmenopausal women in Turkey.
Similar studies are recommended to be carried out in different communities in an effort to confirm whether these findings can be generalized or yield a more complete insight into pathogenetic mechanisms. The knowledge of which population strata may be at greater risk of osteoporosis should be considered carefully for the purpose of health care planning and preventive strategies, making it possible to design tailored and culturally appropriate public health intervention programs.
The protective role played by educational level, which increases with the years of formal education, could be due to other overall determinants can be indirectly inferred from our data, such as a better health status, a more positive attitude to taking drugs and a more efficient use of health care resources. All these determinants can be considered in the light of a greater concern by the women about their own health status, probably related to a different impact of health promotion messages.
Conclusions
===========
In conclusion, the results of the study suggest that there is a significant correlation between educational level and BMD, and shows differences in the prevalence of osteoporosis among educational classes and the protective role played by increases in formal education. Losses in BMD for women of lower educational level tend to be relatively high, and losses in spine and femur BMD showed a decrease with increasing educational level. Although mechanisms of association between education and low bone mineral density remain partly unexplained, most of the risk factors examined have shown distinct trends according to educational level.
Competing interests
===================
None declared.
Financial competing interests
=============================
None declared.
Authors\' contributions
=======================
AG participated in the design of the study and performed the statistical analyses.
AJS conceived of the study, and participated in its design and coordination.
KN and RC participated in the sequence alignment and screened of subjects.
All authors read and approved the final manuscript.
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1471-2296/5/18/prepub>
|
PubMed Central
|
2024-06-05T03:55:47.871022
|
2004-9-6
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517940/",
"journal": "BMC Fam Pract. 2004 Sep 6; 5:18",
"authors": [
{
"first": "Ali",
"last": "Gur"
},
{
"first": "Ayşegül Jale",
"last": "Sarac"
},
{
"first": "Kemal",
"last": "Nas"
},
{
"first": "Remzi",
"last": "Cevik"
}
]
}
|
PMC517941
|
Background
==========
At present, the prognosis of anaplastic thyroid carcinomas is very poor \[[@B1],[@B2]\]. Since they are usually unable to concentrate radioiodine, the therapeutical approach is based on combination of aggressive surgery, external beam radiations and chemotherapy. Only rarely, however, this treatment results effective especially for treating metastatic disease \[[@B1],[@B2]\]. A major limit of the chemotherapeutic agents presently used in these tumours, including doxorubicin, paclitaxel and various drug combinations \[[@B1],[@B2]\], is represented by their low therapeutic index. Thus, the identification of systemic antineoplastic drugs effective against these carcinomas has particularly relevant implications.
Gemcitabine is a new fluorinated nucleoside analogue provided with a potent anti-tumour activity, tested in vitro and in vivo against a variety of solid malignancies \[[@B3]-[@B6]\]. In addition, gemcitabine is a potent radiosensitizing agent \[[@B7]\]. In a preclinical study, gemcitabine showed a marked cytotoxic activity against poorly differentiated human thyroid carcinoma cell lines \[[@B8]\]. In contrast, no appreciable response was observed in four patients with aggressive thyroid anaplastic carcinoma treated with combination of gemcitabine and vinorelbine \[[@B9]\]. Since hematological and other toxicities have been reported when effective anti-tumour doses of gemcitabine were tested \[[@B10]\], the aim of this study was to verify the possibility of maintaining the drug cytotoxicity at lower doses, by using a liposomal drug delivery system. Our data demonstrate that incorporation of gemcitabine in liposomes enhances the cytotoxic effect of the drug against a well-established human thyroid cancer cell line, as compared to the free drug.
Methods
=======
Chemicals
---------
Gemcitabine (2,2^1^-difluorodeoxycytidine) hydrochloride (HPLC purity \>99%) was a kind gift of Eli-Lilly Italia S.p.A. (Sesto Fiorentino, Firenze, Italy) and was used without further purification. Cholesterol was obtained from Sigma Chemicals Co. (St. Louis, USA). 1,2-dipalmitoyl-sn-glycero-3-phosphocholine monohydrate and N-(carbonyl-methoxypolyethyleneglycol-2000)-1,2-distearoyl-sn-glycero-3-phosphoethanolamine sodium salt (MPEG-2000-DSPE) were purchased from Genzyme products (Suffolk, United Kingdom). Double-distilled pyrogen-free water from Sifra S.p.A. (Verona, Italy) was used. Sterile saline was a product of Frekenius Kabi Potenza S.r.l. (Verona, Italy). All other materials and solvents were of analytical grade (Carlo Erba, Milan, Italy).
Liposome preparation
--------------------
Liposome formulations were made up of DPPC/Chol/MPEG-2000-DSPE (8:3:1 molar ratio). To maximize the entrapment efficiency of a hydrophilic molecule such as gemcitabine, various liposome preparation procedures \[[@B11],[@B12]\] were applied together. Namely, liposome colloidal suspensions were prepared by dissolving the lipid mixture (40 mg) in chloroform-methanol (3:1 v/v). Organic solvent was removed by a rotavapor thus allowing the formation of a thin lipid film on the inner surface of a pyrex glass vial. To remove any trace of organic solvent, lipid films were stored overnight in a Büchi T-50 under high vacuum at 30°C in the dark. Lipid films were hydrated with a solution (2 ml) of 250 mM ammonium sulphate by vortexing at 45°C for 15 min. The resulting colloidal suspension of multilamellar vesicles was submitted to ten cycles of freeze in liquid nitrogen and thaw in warm (35°C) water in order to allow the homogenous distribution of the ionic species. The entrapped ammonium sulphate solution was removed by centrifugation at 14000 rpm (IEC, International Equipment Company, mod MP4R, equipped with a mod. 851 rotor) for 1 h at a temperature of 4°C. The pellet was re-suspended in 400 μl of a 1 mM gemcitabine aqueous solution and stored at room temperature for 3 h. Double-distilled pyrogen-free water (1.6 ml) was added to the liposome suspension and then a freeze-drying procedure was carried out (Edwards freeze-dryer Modulayo). Then, the non-incorporated gemcitabine was removed and the freeze-dried liposomes were re-suspended just before the experiments with 2 ml of the culture medium. Scalar dilutions were prepared in the same medium to obtain the final concentrations used in the experiments.
Liposome loading capacity
-------------------------
The loading capacity of liposomes was evaluated after removing the free gemcitabine (centrifugation at 14000 × g for 1 h at 4°C) from the vesicular colloidal suspension coming from the re-suspension of freeze-dried liposomes. The amount of gemcitabine in the supernatant was spectrophotometrically determined at 268.8 nm (Shimadzu UV-1601). UV calibration straight-line (*y*= 6.958 × 10^-3^+ 0.3971*x*, where *y*is the UV adsorbance and *x*is the drug concentration) presented a *r*^2^value of 0.9993. The amount of gemcitabine entrapped in liposomes was determined as a difference between the amount of drug added during liposome preparation and the amount of the entrapped drug present in the supernatant. The encapsulation efficiency was expressed as percentage of the total amount of gemcitabine that became entrapped.
Cell cultures and cell viability
--------------------------------
The ARO cells, from a human anaplastic thyroid carcinoma, were grown as previously described \[[@B13]\]. All experiments were performed in 12-well culture dishes, when cells reached approximately 50% confluence. Cell viability was evaluated by trypan bleu dye exclusion assay. Briefly, after incubation with gemcitabine or liposomes containing the drug at different doses, cells were trypsinized and the pellet re-suspended in a 0.4% trypan bleu buffer and counted in the hemocytometric chamber. Cell mortality was calculated as the percentage of stained cells over the total and expressed as the ratio between treated and untreated (control) cells. DNA cell content was assayed by using a fluorimetric DNA assay kit (Bio-rad laboratories, Segrate, Milano, Italy).
Results
=======
We first analysed the effects of different concentrations of gemcitabine on the viability of ARO thyroid cancer cells. As shown in Figure [1](#F1){ref-type="fig"} the cytotoxic effect was observed only after 48 or 72 h incubation of the drug. After 72 h, the cell mortality increased 4.6 and 7.9 fold over control using 1 and 100 μM of gemcitabine. In accordance with previous reports \[[@B8]\], no significant effect was visible after 24 h exposure (Fig. [1](#F1){ref-type="fig"}).
In order to improve the drug entry into the cells, gemcitabine entrapment in a liposome capsule was next performed, using a combination of various liposome preparation procedures. In particular, a pH gradient method was used \[[@B14]\]. Namely, the presence of ammonium sulphate in the internal compartments of liposomes provide an acidic environment that elicit the protonation of gemcitabine in order to drastically reduce the drug back-diffusion (leakage) from liposomes (Figure [2](#F2){ref-type="fig"}). The combination of various liposome preparation procedures together with the application of a pH gradient provided an encapsulation efficiency of \~90%.
The gemcitabine-loaded liposomes were then tested for their cytotoxic activity against ARO cell, and the results compared with those of gemcitabine alone. As shown in Figure [3](#F3){ref-type="fig"}, a cytotoxic effect appeared after 24 h incubation, with an initial increased cell mortality at 0.3 μM (2.4 fold over control), and a maximum at 10 μM (death of almost all the cells) (Figure [3](#F3){ref-type="fig"}). Similar results were obtained by analysing the DNA content of ARO cells treated with free or liposome-encapsulated gemcitabine (data not shown).
Discussion
==========
Despite an intense application of aggressive multimodal therapeutic regimens, no standardized protocol has shown success in the treatment of anaplastic thyroid carcinoma \[[@B2]\]. A critical need for new approaches is therefore vital for the systemic therapy of metastatic anaplastic thyroid carcinoma. At present one promising option is provided by the gene therapy. Studies are currently in progress attempting to: a. reintroducing iodine uptake by viral-driven Iodide/sodium symporter gene expression \[[@B15],[@B16]\]; b, inducing tumour cell death by expressing p53 or by suicide gene prodrug systems \[[@B17],[@B18]\]. An alternative approach is represented by increasing the effectiveness of chemotherapy, using novel agents, combination therapy or enhancing drug delivery inside the tumour cell.
The latter option has been taken advantages in the progress related to liposome research. Traditional dosage forms of anticancer drugs have the limitation of many potential obstacles (barriers) before they reach their target site, one of these is the large volume of distribution after i.v. administration. This situation elicits a low therapeutic index and a high toxicity in healthy tissues \[[@B19]\]. After encapsulation into liposomes similar to those used in our investigation the volume of distribution of a drug is reduced, and its concentration in the tumour tissue is increased \[[@B20]\]. In fact, liposomes can protect drugs from metabolic inactivation, and, due to size limitation, they are not able to transport encapsulated molecules across healthy endothelium, thus avoiding anticancer drug accumulation in a large extent in healthy tissues and hence a decrease of side-effects \[[@B21]\]. On the other hand, the increased permeability of the tumour endothelium allows the extravasation of liposomes, with a consequent accumulation of anticancer drugs in the site of action \[[@B22]\]. Furthermore, it should be considered that liposomes are non-toxic being mostly constituted by naturally occurring lipids.
In the last years, gemcitabine has emerged as a very potent anti-tumour drug and it is currently used, alone or in combination, in the treatment of patients with different malignancies, including ovarian, pancreatic, non-small cell lung and other cancers \[[@B3]-[@B6]\]. Despite its promising effectiveness derived from a preclinical study \[[@B8]\], no appreciable response was observed in a clinical study including four patients with aggressive thyroid anaplastic carcinoma treated with combination of gemcitabine and vinorelbine \[[@B9]\]. Although low, compared to other anti-neoplastic drugs, hematological and other toxicities appeared when effective anti-tumour doses of gemcitabine were tested.
In this study, we prepared a liposome formulation with a high entrapment efficiency of gemcitabine and tested its efficacy against a well established human poorly differentiated thyroid carcinoma cell line. Our data demonstrate that, in ARO cells, incorporation of gemcitabine in liposomes enhances the cytotoxic effect of the drug as compared to free gemcitabine, suggesting a more effective uptake of the drug inside the cells. This activity was demonstrated at concentrations even lower than serum levels obtained in clinical trials. In our knowledge, no data are available in the literature concerning the relationship between gemcitabine uptake and its cytotoxicity, since neither liposomes or other carrier system have been tested against tumour cells. Our preliminary experiments (unpublished observations) show that a similar effect (improved uptake and cytotoxicity at lower doses) may be obtained also in colon cancer cells. It is note worthing that the various component used for the preparation of the liposomal delivery device were already approved by regulatory offices to be used in the preparation of liposome-based formulations, i.e. Doxil^®^.
Conclusion
==========
The clinical predictive value of the in vitro cell line preclinical cancer model is well established \[[@B23]\] and the ARO cells are one of the cell model of anaplastic thyroid cancer more exploited both for investigating the mechanism of tumour progression and for testing new molecules with antiproliferative effect. However, these promising observations need to be confirmed in studies using in vivo xenograft cancer models, prior to propose the use of such preparations at lower (presumably side effect free) doses in a clinical trial of human thyroid tumours.
Competing interests (medicine)
==============================
None declared.
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1471-2407/4/63/prepub>
Acknowledgements
================
This work was supported by a MIUR Cofin 2003 grant to D. Russo, a MIUR Cofin 2002 grant to M. Fresta and by a grant from Italian Ministry of Health to S. Filetti.
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Cytotoxic effect of gemcitabine. ARO cells were grown to 50% confluence and treated with increasing concentrations of gemcitabine for different incubation time. Cell mortality was evaluated by trypan bleu dye exclusion assay (see Methods). In control cells, mortality was always lower than 5%. The values, expressed as the ratio over control, represent the mean ± SEM of at least three different experiments in triplicates.
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Schematic representation of the gemcitabine encapsulation process within liposomes by means of the presence of a pH gradient elicited by the co-encapsulation of a 250 mM ammonium sulphate solution.
:::
:::
::: {#F3 .fig}
Figure 3
::: {.caption}
######
Cytotoxic effect of gemcitabine-loaded liposomes. ARO cells were grown to 50% confluence and treated with increasing concentrations of either free gemcitabine or gemcitabine-loaded liposomes for 24 h. Cell mortality was evaluated by trypan bleu dye exclusion assay (see Methods). The values, expressed as the ratio over control, represent the mean ± SEM of at least three different experiments in triplicates.
:::
:::
|
PubMed Central
|
2024-06-05T03:55:47.873840
|
2004-9-13
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517941/",
"journal": "BMC Cancer. 2004 Sep 13; 4:63",
"authors": [
{
"first": "Marilena",
"last": "Celano"
},
{
"first": "Maria Grazia",
"last": "Calvagno"
},
{
"first": "Stefania",
"last": "Bulotta"
},
{
"first": "Donatella",
"last": "Paolino"
},
{
"first": "Franco",
"last": "Arturi"
},
{
"first": "Domenicoantonio",
"last": "Rotiroti"
},
{
"first": "Sebastiano",
"last": "Filetti"
},
{
"first": "Massimo",
"last": "Fresta"
},
{
"first": "Diego",
"last": "Russo"
}
]
}
|
PMC517942
|
Background
==========
The use of chemical fertilizers has been responsible for dramatic increase in the stem wood production of forest trees \[[@B1]-[@B4]\]. In an 8-year-old stand of loblolly pine growing on an infertile site in Scotland County, North Carolina, for example, stem volume increment increased 152% after the fourth year of fertilization treatment \[[@B4]\]. However, little is known about the mechanistic basis for such favorable effects of fertilization. One hypothesis is that improved nutrient availability leads to increases in leaf area growth and photosynthetic capacity, thus producing more photosynthate that can be allocated to the stem wood. This hypothesis has been supported by a number of physiological studies \[[@B5]-[@B7]\] and used as a conceptual model for plant nitrogen acquisition and cycling \[[@B8]\]. However, forest trees can consume as much as 60--80% of annual net primary productivity in the turnover of fine roots \[[@B3]\]. Fine roots are a tissue with high maintenance respiration tissue whose primary function is to absorb and metabolize water and nutrients from the soil \[[@B9]-[@B12]\]. A number of previous studies have shown that the production of fine roots is sensitive to the availability and distribution of nutrients within the soil \[[@B1],[@B4],[@B13],[@B14]\]. In this study, we test a second hypothesis that the capacity of fine roots to respond to nutrient availability, referred to as *phenotypic plasticity*, can potentially increase forest-tree productivity.
Phenotypic plasticity is the potential of an organism to alter its phenotype in changing environments \[[@B15]-[@B19]\]. Phenotypic plasticity may play an important role in plant adaptation and evolution by combining a physiological buffering to poor environmental conditions with an improved response to favorable conditions \[[@B20]\]. The understanding of how phenotypic diversity is generated by the coherent change of other integrated traits is a key challenge in evolutionary biology. In much plant literature, studies of adaptive phenotypic plasticity have focused mainly on morphological and fitness traits above ground \[[@B16]\]. It is unclear how phenotypic plasticity exerts a significant effect on plant growth and production through the alteration of root systems below ground. Studies strongly suggest that plant root systems are adapted to different environments \[[@B14]\], and their diversity represents one important form of morphological evolution \[[@B12]\]. Fine roots are unique organs with great environmental and developmental plasticity which are subject to strong natural selection and are amenable to genetic and developmental study \[[@B10]\].
Loblolly pine is the most important tree species for fiber production in the southern US \[[@B21]\]. Because of its wide natural distribution from the moist Atlantic Coastal Plain to the dry \"Lost Pines\" region of Texas, this species displays strong adaptability to a range of environmental conditions. However, detailed ecophysiological and developmental mechanisms for the adaptive response of loblolly pine from a perspective of fine roots remain unknown. In the study, we integrate the conceptual theory of phenotypic plasticity into the test of the hypothesis that the reduced production of fine roots under high fertilization can increase stem productivity in loblolly pine.
Results and Discussion
======================
After 4 weeks of treatment, trees receiving the high nutrient treatment displayed 22% (\"xeric\") and 47% (\"mesic\") greater stem biomass than those under the low fertilizer treatment (*P*\< 0.001). These values increased to 102% and 199% for these two ecotypes, respectively, when the trees were treated for 14 weeks (*P*\< 0.001).
Allometric analysis was used to evaluate the influences of foliage and fine-root biomass partitioning on stem growth which arise from differences in nutrient supply. On both harvesting dates, the proportion of foliage biomass to total plant biomass increased markedly, whereas the proportion of fine root biomass decreased significantly, with better nutrient supplies. As an illustration, we use Figure [1](#F1){ref-type="fig"} to demonstrate the phenotypic plasticity of stem growth (Fig. [1A](#F1){ref-type="fig"}) and biomass partitioning between two treatments (Fig. [1B](#F1){ref-type="fig"}) on the second harvesting date. However, the degree of plasticity, defined as the absolute difference between the two treatments \[[@B16]\], was strikingly greater for the fine-root proportion than foliage proportion, especially for the \"xeric\" ecotype. The significance levels for the treatment effect on stem biomass decreased when the proportion of foliage or fine-root biomass was held constant (*P*\< 0.01), as compared to the significance level when the proportion was not held constant (*P*\< 0.0001). These dependent relationships suggest that increased stem biomass due to better nutrient supplies was attributable to both increased foliage investment and decreased energetic costs of fine root construction.
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Different plant performance under the low and high nutrient treatments measured at 14 weeks of treatment. (**A**) Stem biomass. (**B**) The proportions of foliage (open bars) and fine-root (solid bars) biomass to total plant biomass.
:::
:::
We analyzed genetic differences in how foliage and fine-root biomass partitioning affect stem biomass through changes in nutrient level. We used correlations of family means in the two treatments to calculate path coefficients of the nutrient-induced plasticity of foliage and fine-root biomass partitioning to the plasticity of stem biomass. For \"mesic\" families, the plasticity of foliage biomass partitioning did not give rise to a change in stem biomass (*p*~*y*←1~= -0.09), whereas the plasticity of fine-root biomass partitioning, *i.e*., decreased partitioning of biomass to fine roots under higher fertilization, had a significant impact on the corresponding increase of stem biomass (*p*~*y*←2~= - 0.99, Fig. [2A](#F2){ref-type="fig"}). For \"xeric\" families, both increased biomass partitioning to foliage and decreased partitioning to fine roots as a consequence of more nutrients favorably affected stem biomass. The path coefficients derived from foliage and fine-root biomass partitioning accounted for most of the variation in stem biomass as indicated by a small residual effect (0.09--0.12), suggesting that no additional traits are required to explain stem biomass. Results from path analysis suggest that the two ecotypes have different physiological mechanisms that determine the nutrient-dependent influences of foliage and fine-root biomass partitioning on stem growth.
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Path diagrams representing the cause-and-effect relationship between the two predictor variables, foliage biomass and fine-root biomass proportions, and the response variable, stem biomass, that results from differences in nutrient supply. The variable residual is the undetermined portion. *p*and *r*denote path coefficients and correlation coefficients, respectively.
:::
:::
Foliage and fine roots have complementary roles in uptake of resources; the former in energy and carbon uptake and the latter in water and nutrient uptake \[[@B12],[@B22]\]. Mechanistic modeling of resource uptake suggests that the most efficient deployment of plant biomass is to form minimal fine roots that supply water and nutrients for the production of maximum leaf area \[[@B11]\]. However, there are important trade-offs in generating few fine roots. We used the ratio of foliage biomass to fine-root biomass (RFF) as an architectural trait to describe the allocation of biomass within ephemeral tissues. This ratio reflects the degree to which plants display a balance of resource investment vs. resource acquisition. It was highly plastic to nutritional levels and tree development. The ratio was larger in the high nutrient treatment (RFF = 6.0--7.0) than in the low treatment (RFF = 3.0--3.5). Under the higher nutrient treatment, trees tended to invest increased energy on foliage with their growth. All these trends differed between the two ecotypes, as shown by significant interaction effects between ecotypes, treatments and harvesting dates (*P*\< 0.001). Plasticity between different growth stages indicates the dependence of plastic responses on the timing and sequences of developmental events. Ecotypic variation in developmental plasticity represents different genetic bases involved in relevant developmental events \[[@B23]\].
Ecotypic differentiation of loblolly pine could be explained by limits of plasticity. Quantitative evolutionary genetic models predict that the phenotypic plasticity of a trait is costly or physiologically limiting when the trait is forced to respond to environmental variation (\"passive\" response). DeWitt et al. \[[@B24]\] delineated five costs (maintenance costs, production costs, information acquisition costs, developmental stability costs and genetic costs) and three limits (information reliability limits, lag-time limits and developmental range limits) of plasticity. A limit of plasticity occurs when facultative development cannot produce a trait mean as near the optimum as can fixed development. A negative relationship between the degree of plasticity and the fitness residuals (calculated from the regression of fitness on mean phenotype) identifies a limit of plasticity.
Our analysis suggests that the plasticity of fine-root biomass proportion is physiologically limiting, whereas the plasticity of foliage biomass proportion is not. The relationship of the shoot biomass residuals was positive with the degree of plasticity of foliage biomass proportion (Fig. [3A](#F3){ref-type="fig"}), but negative with the degree of plasticity of fine-root biomass proportion (Fig. [3B](#F3){ref-type="fig"}). Thus, when nutrient supply changes, foliage and fine roots will respond in different ways, with the former in a constitutive (active) way and the latter in an inducible (passive) way \[[@B24]\]. For both \"xeric\" and \"mesic\" ecotypes, the families that reduced fine root biomass the least had the highest stem biomass on the high nutrient treatment. Larger limits of fine-root plasticity for \"xeric\" than \"mesic\" (Fig. [3B](#F3){ref-type="fig"}) could explain why the stronger plasticity of fine root growth for the former ecotype did not result in more stem growth as expected (see Fig. [1A](#F1){ref-type="fig"}). Perhaps, for these \"Lost Pines\" from infertile sites, under improved nutritional conditions there is strong conflict between energetic savings due to reduced fine root production and energetic costs associated with higher efficiency of absorbing and metabolizing nutrients with fewer fine roots.
::: {#F3 .fig}
Figure 3
::: {.caption}
######
The relationships of shoot biomass residuals with the degree of the plasticity of biomass partitioning to foliage (**A**) and fine roots (**B**). In this study, shoot biomass is used as a surrogate of fitness, because great capacity of vegetative growth at early stages is advantageous for competing for growth resources and is suggested to be favored by natural selection \[15\]. The residuals of shoot biomass were calculated by differences between its observations and predictions estimated from foliage and fine-root biomass proportions using polynomial equations (see ref. 24 for a detailed description of this calculation approach). The degree of plasticity was represented as family difference between the nutrient treatments.
:::
:::
Forest tree form (biomass partitioning) is highly plastic in response to changes in nutrient levels. The carbon budgets for forest trees show a surprisingly large role of roots. Under low nutrient conditions that predominate in natural forests, 60--80% of photosynthate is allocated below ground, compared with 30% for high nutrient levels \[[@B3]\]. Our path analysis for loblolly pine seedlings showed that phenotypic plasticity of roots had a major influence on the plasticity of stem biomass, supporting the hypothesis that roots play a crucial role in forest productivity. Current selections when grown on high nutrient sites could have relative proportions of roots and stems and foliage that are unfavorable for high yield.
Progress towards domestication in trees will be slowed by long generation times, but is likely to be based on the exploitation of interactions between genotypes and yield associated with various types of agronomic methods (e.g., fertilizer levels), as have been shown for herbaceous crop plants. However, the environmental uncertainties during the long life span of trees have caused some breeders to consider the value of plasticity as a trait itself. And plasticity could obscure the relationship between phenotype and genotype, making selection less efficient. Efforts to domesticate forest trees will be enhanced by a deeper knowledge of phenotypic plasticity \[[@B20]\].
Conclusions
===========
Our study of biomass partitioning in relation to varying nutritional levels in loblolly pine supports the previous hypothesis, proposed by Linder and Axelson \[[@B1]\], that the reduced production of fine roots under fertilization results in the increase of stem production through the optimal use of energy. Yet, supporting this hypothesis does not imply that we should reject a more commonly accepted hypothesis that greater plant production due to fertilization stems from increased foliage and photosynthetic capacity. We explained the discrepancy of these two hypotheses from an ecophysiological perspective using a well-established conceptual model of phenotypic plasticity. The pattern of biomass partitioning is under environmental control and exhibits considerable ecotypic differentiation for the best utilization of available resources. In this study, we observed that biomass partitioning in loblolly pine is also under ontogenetic control, as well documented in other species \[[@B25],[@B26]\]. Although our study of fine roots was performed using young loblolly pine seedlings in controlled conditions, results promise to enhance a fundamental understanding of evolutionary changes of tree architecture under domestication and to design sound silvicultural and breeding measures for improving plant productivity.
Methods
=======
Plant material
--------------
Phenotypic plasticity was evaluated for fine roots and biomass partitioning of a commercially important forest tree species, loblolly pine (*Pinus taeda*L.). We used two contrasting loblolly pine ecotypes from regions that differ in soil resource availability. One of the ecotypes, known as the \"Lost Pines\" of Texas, is adapted to droughty conditions and low soil fertility and is denoted by \"xeric\", whereas the other, Atlantic Coastal Plain, is adapted to more moderate conditions and is denoted by \"mesic\". Adaptive differentiation between the contrasting \"xeric\" and \"mesic\" ecotypes has been previously characterized \[[@B21]\].
In May 1997, the seeds from the two ecotypes of loblolly pine were germinated in vermiculite, the seedlings were transplanted to 40 cm deep by 20 cm diameter plastic pots filled with pure sand, and placed in an open site at the Horticulture Field Laboratory at North Carolina State University, Raleigh. Pine seedlings from each ecotype were assigned to two different treatments: low nutrients and high nutrients \[[@B4]\]. The experiment was laid out in a complete randomized design with two different nutritional treatments and with five half-sib families from each ecotype in each level (8 seedlings were included per family per ecotype in each treatment). The seedlings in the high nutrient regime were fertilized at 50 ppm N solution (Peters 15-16-17) every morning, and those in the low nutrient level at 10 ppm N every other morning. The two treatments received the same amount of water. Half of the trees were harvested after 4 weeks of treatment, whereas the other half, after 14 weeks of treatment. Plants were separated into foliage, branches, stem, tap root, coarse roots and fine roots. Fine roots are defined as those of diameter ≤ 2 mm.
Data analysis
-------------
The differences of stem biomass between the two nutritional levels were statistically analyzed using an allometric model that characterizes allometric relationships between plant parts and wholes. The model is based on an exponential function, *y*= *ax*^*b*^, where *x*and *y*are total plant biomass and stem biomass, respectively, and *a*and *b*represent the coefficient and exponent of the allometric equation, respectively \[[@B27]\].
Path analysis was used to identify the cause-effect relationships in a complex system \[[@B28]\]. Path analysis partitions the correlation of component traits with a yield trait into two parts, direct and indirect. We performed path analysis to detect the direct and indirect effects of the plasticity of foliage biomass and fine root biomass on the plasticity of stem biomass. The path coefficients for foliage biomass (*p*~1←*y*~) and fine root biomass (*p*~2←*y*~) to stem biomass through the change of nutritional levels were estimated by solving the following regular equations:
*p*~1←*y*~+ *r*~12~*p*~2←*y*~= *r*~1*y*~
*r*~12~*p*~1←*y*~+ *p*~2←*y*~= *r*~2*y*~
where *r*~1*y*~and *r*~2*y*~are the family correlation coefficients of the plasticity of foliage biomass and fine-root biomass with the plasticity of stem biomass, respectively, and *r*~12~is the family correlation coefficient between the plasticity of foliage biomass and fine-root biomass. Residuals were estimated to evaluate the degree of determination for the path analysis \[[@B28]\]. All data analyses were performed using software SAS (SAS Institute 1988).
Authors\' Contributions
=======================
RW designed the study, carried out the experiment, analyzed the data and drafted the manuscript. JEG participated in the experiment. SEM participated in the design of the study. DMO participated in the design and coordination. All authors read and approved the final manuscript.
Acknowledgements
================
We thank Wen Zeng, Zhigang Lian, Anthony McKeand, Yi Li, Hongxiu Liu, Helen Chen, Paula Zanker and Jun Lu for technical assistance, Scot Surles for tipmoth control, and Mary Topa and Bill Retzlaff for helpful discussion regarding this study. We are especially grateful to Mary Topa and Bill Retzlaff for constructive comments on early versions of this manuscript. This research was supported by the United States Department of Energy. The publication of this manuscript was approved as Journal Series No. R-10425 by the Florida Agricultural Experiment Station.
|
PubMed Central
|
2024-06-05T03:55:47.874928
|
2004-9-7
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517942/",
"journal": "BMC Ecol. 2004 Sep 7; 4:14",
"authors": [
{
"first": "Rongling",
"last": "Wu"
},
{
"first": "James E",
"last": "Grissom"
},
{
"first": "Steven E",
"last": "McKeand"
},
{
"first": "David M",
"last": "O'Malley"
}
]
}
|
PMC517943
|
Background
==========
Rapid clearance of parasitaemia following transfusion of IgG from malaria immune adults to clinically ill recipients illustrates that naturally acquired antibodies have a parasite clearing role in human malaria infection \[[@B1]-[@B3]\]. Neither the nature of the protective immune response nor the target antigens and epitopes recognized by infection clearing antibodies are fully understood. Evidence is accumulating to suggest that the acquisition of antibodies binding the VSA on infected erythrocytes plays a major role in the development of age and exposure dependent immunity \[[@B4]-[@B8]\]. The evidence for protective anti-VSA responses is particularly strong for the PAM syndrome \[[@B9],[@B10]\].
PAM is characterized by the sequestration of *Plasmodium falciparum*infected erythrocytes in the intervillous spaces of the placenta. Infected erythrocytes adhere to low-sulphated forms of CSA present on the extracellular proteoglycan matrix of syncytiotrophoblasts \[[@B11]\]. *In vitro*selection of infected erythrocytes for adhesion to CSA concomitantly selects for expression of VSA that share characteristics with postnatal placental isolates. Thus plasma antibodies from malaria exposed pregnant, or multi-gravid women, recognize the VSA of CSA binding parasites (here referred to as VSA~PAM~). These sera can also block adhesion of CSA-selected infected erythrocytes to CSA *in vitro*\[[@B12]\]. Interestingly, antibodies that bind CSA-selected parasites and block adhesion are not acquired by malaria-exposed males. There is a striking female-specific antibody response recognizing both *in vitro*CSA-selected parasites \[[@B12],[@B13]\] and *P. falciparum*isolates taken from infected placentae at delivery \[[@B14]-[@B16]\]. Furthermore, the levels of CSA-adhesion blocking plasma IgG have been shown to increase with adult female parity. Recent immuno-epidemiological studies also show a strong positive correlation between the levels of antibodies that recognize the infected erythrocyte surface\[[@B15]\], the level of CSA-adhesion blocking antibody \[[@B17]\] and positive birth outcomes as measured by birth weight.
PAM is, thus, the clearest example in malaria pathology research of a strong association between infected erythrocyte sequestration and a particular disease syndrome. The VSA recognized by female-specific, parity-dependent antibodies are, therefore, rational and exceptionally interesting candidates for inclusion in an experimental vaccine to protect women against PAM, a major cause of stillbirth, maternal anaemia and low birthweight.
To date, the best characterized VSA is *P. falciparum*erythrocyte membrane protein 1 (PfEMPl), a polymorphic, high molecular weight membrane protein (200--450 kDa) encoded by the *var*multi-gene family \[[@B18]-[@B20]\]. Members of the PfEMP-1 family function as adhesion molecules binding to various host endothelial receptors. They are situated in the knob-like protrusions associated with the parasitized erythrocyte surface.
Since *var*genes encode large extracellular domains rich in lysine and arginine residues, it is not surprising that PfEMP-1 molecules and adhesion to endothelial receptors have been reported to be highly sensitive to trypsin treatment \[[@B18],[@B21]-[@B24]\]. Less expected was the finding that parasite adhesion to the placental receptor CSA, when immobilized \[[@B25]-[@B27]\] or when cell surface associated \[[@B28],[@B29]\], can be relatively trypsin resistant. This study investigates the protease-sensitivity profile of the VSA~PAM~expressed by CSA-selected parasite clone FCR3 with regard to recognition by antibodies acquired during PAM and adhesion to placental receptors.
Methods
=======
Parasite isolates
-----------------
Parasites were maintained in group O erythrocytes under standard conditions \[[@B30]\], using RPMI 1640 medium containing 25 mM HEPES, supplemented with 20 mM glucose, 2 mM glutamine, 25 μg/ml gentamycin and 10% pooled normal human serum. The pH was adjusted to between 7.2 and 7.4 with 1 M NaOH. Culture flasks at 5% haematocrit were gassed with 96% nitrogen, 3% carbon dioxide and 1% oxygen. The laboratory clone FCR3 originates from peripheral blood collected in the Gambia. FCR3CSA was obtained from the Malaria Research and Reference Reagent Resource Centre (ATCC) \[[@B31]\], and was confirmed, using genetic markers to be identical to the laboratory clone FCR3 kept in the original W.H.O. strain registry collection in Edinburgh (D. Walliker, pers. comm.). CSA binding was maintained by panning late stage infected erythrocytes fortnightly on bovine tracheal CSA (10 μg/ml) (Sigma) immobilized on polystyrene Petri dishes (Falcon), as previously described \[[@B26]\]. Prior to protease treatment and analysis by flow cytometry, cultures were synchronized by sorbitol treatment to obtain cultures enriched for late stage parasites.
Plasma donors
-------------
Serum samples from 20 men living in a malaria endemic region of Ghana were pooled to produce the male serum pool. Serum samples collected at the time of birth from the placentas of 15 women living in a malaria endemic region of Ghana were pooled to produce the pregnant female serum pool. This pool included five primigravidae, nine secundigravidae and one multigravid woman. Serum samples from six Scottish malaria naïve individuals were pooled and used as a control.
Protease treatment
------------------
Protease treatment of infected erythrocytes was carried out as previously described \[[@B26]\]. Briefly, samples containing 3 × 10^6^cells from sorbitol treated late stage cultures of 8--10 % parasitaemia were washed twice with phosphate-buffered saline (PBS) and then incubated with the appropriate concentration of trypsin-TPCK (Worthington Biochemicals) or pronase (Boehringer-Mannheim) in a final volume of 1.0 ml in PBS, for 10 minutes at 37°C. The reaction was terminated either by adding soybean trypsin inhibitor (Worthington Biochemicals) to a final concentration of 1 mg/ml or by adding 10% human serum. Cells were washed twice with PBS before further use.
Analysis of VSA specific antibodies by flow cytometry
-----------------------------------------------------
Flow cytometry was used to measure the levels of plasma IgG binding to the VSA of late stage parasites essentially following the method previously described by Staalsoe *et al*\[[@B13],[@B32]\]. 3 × 10^6^cells form late stage *P. falciparum*cultures of 8--10 % parasitaemia were washed twice with PBS. Cells were incubated sequentially with plasma antibodies diluted 1:20 in PBS, goat anti-human IgG diluted 1:200 in PBS (Dako) and fluorescein isothiocyante (FITC)-conjugated rabbit anti-goat (Dako) diluted 1:25 in PBS. All incubations were in a total volume of 100 μl for 30 minutes at room temperature and were followed by two washes with 1 ml of PBS. Samples were analysed immediately on a FACSCAN apparatus (Becton-Dickinson). FITC fluorescence due to cell surface antibody recognition was determined for 5000--10000 ethidium bromide gated infected erythrocytes.
Modified labeling procedure for FACS analysis
---------------------------------------------
In order to circumvent the non-specific labeling of the VSA by the tertiary antibody, new reagents have been introduced. The procedure follows the method detailed above with the following modifications. A biotinylated rabbit anti-human IgG antibody (DAKO) was used diluted 1:25 to replace the secondary antibody. In the place of a tertiary antibody, FITC-conjugated streptavidin (DAKO) was used at a 1:2000 dilution. In these experiments the control sera was a pool of malaria naïve Danish volunteer serum.
Binding assays
--------------
Human umbilical cord hyaluronic acid (Sigma) and bovine trachea CSA (Sigma) were used at a concentration of 10 μg/ml in PBS (pH 7.2). 20 μl of each receptor was spotted in triplicate onto 5 cm diameter petri dishes (Falcon). Receptors were adsorbed onto the plastic petri dishes overnight at 4°C. 10 μg/ml BSA in PBS was similarly adsorbed as a negative control. Plates were then blocked by removing the receptor solution and adding 20 μl of 2% BSA in PBS. Following the removal of this blocking solution late stage parasites, suspended in 2 ml of complete RPMI-HEPES medium (8--10% parasitaemia, 5% haematocrit), were added to the petri dish. Parasites were incubated with the immobilized receptor for 60 minutes at 37°C with occasional agitation. Unbound cells were removed by four gentle washes with incomplete RPMI-HEPES medium; bound cells were fixed with 0.5% (v/v) glutaraldehyde in PBS for 10 minutes and Giesma Stained. Bound cells were counted by light microscopy. Protease treatment of intact cells was carried out as described above.
Statistical analysis
--------------------
Statistical analyses were performed using Analyses of Variance in Minitab 13.30 (Minitab Inc.), using protease, protease concentration and serum pool as explanatory variables. Statistical models were tested for homogeneity of variance and normality of error distributions. Where possible, maximal models with interactions between these variables were fitted first, after which models were minimized by removing nonsignificant (p \> 0.05) terms.
Results
=======
Concomitant selection of a trypsin-resistant VSA following parasite selection for CSA adhesion
----------------------------------------------------------------------------------------------
It was first established that selection of clone FCR3 for adhesion to CSA resulted in the concomitant selection for VSA specifically recognized by plasma IgG from malaria exposed Ghanaian pregnant women (IgG*preg*) (figure [1](#F1){ref-type="fig"}). However there was no increase in the binding of IgG from a pool of plasma from malaria exposed Ghanaian men (IgG*male*). The unselected FCR3 clone expressed VSA that were equally well recognized by antibodies in the IgG*male*and IgG*preg*serum pools (figure [1](#F1){ref-type="fig"}). These interactions between serum antibody binding and selection for CSA adhesion were highly significant (F~2,24~9.5, P = 0.001).
::: {#F1 .fig}
Figure 1
::: {.caption}
######
**IgG recognition profiles of parasite clone FCR3 before and after selection for adhesion to CSA.**Following selection of parasite clone FCR3 for adhesion to CSA the expression of variant surface antigens was investigated using FACS. 5000--10000 late stage parasites were gated using ethidium bromide and FITC fluorescence due to serum IgG binding was measured. Serum samples from six Scottish malaria naïve individuals were pooled and used as a control (IgG*control*). Sera from 20 Ghanaian men were pooled to produce the malaria exposed male serum pool (IgG*male*). Sera collected at the time of birth from the placentas of 15 Ghanaian women were pooled to produce the malaria exposed pregnant female serum pool (IgG*preg*). The bar chart shows mean and standard error of the means for five independent experiments.
:::
:::
The trypsin sensitivity of this VSA/IgG binding interaction and of parasite adhesion to CSA was then measured. Parasitized erythrocyte surface trypsinization at a concentration of 0.1 mg/ml showed that the IgG*preg*binding of FCR3CSA was significantly more trypsin-resistant than was binding of the same serum to the unselected clone (figure [2A](#F2){ref-type="fig"} &[2B](#F2){ref-type="fig"}; F~1,4~16.4, p = 0.015). Although the mean surface fluorescence due to the IgG*preg*binding of FCR3CSA was slightly reduced by 0.1 mg/ml trypsin this reduction was not significant (figure [2A](#F2){ref-type="fig"}; F~1,2~11.3, p = 0.078). The effect of 0.1 mg/ml trypsin on VSA recognition by IgG*male*and IgG*control*was comparable before and after CSA selection of the parasite (figure [2](#F2){ref-type="fig"}).
::: {#F2 .fig}
Figure 2
::: {.caption}
######
**Serum IgG from malaria exposed pregnant women recognises trypsin-resistant surface epitopes.**Intact infected erythrocytes were treated with 0.1 mg/ml trypsin prior to FACS analysis. Panels A and B show serum IgG binding to the surface of FCR3CSA and FCR3 infected erythrocytes respectively. Serum pools are the same as those described in Figure 1. The bar chart shows mean and standard error of the means for two independent experiments.
:::
:::
The effect of a 10-fold higher trypsin concentration and the effect of the non-specific protease, pronase, on IgG recognition of FCR3CSA was also determined. Trypsinization with 1 mg/ml did not significantly reduce the mean surface fluorescence due to IgG*preg*binding to FCR3CSA (figure [3](#F3){ref-type="fig"}; F~1,4~0.35, p = 0.587). However, treatment of the intact infected erythrocyte with 0.1 mg/ml pronase did significantly reduce IgG*preg*recognition of FCR3CSA (figure [3](#F3){ref-type="fig"}). Pronase treatment also significantly reduced binding of the IgG*male*and IgG*control*serum pools (figure [3](#F3){ref-type="fig"}; F~4,18~3.1, p = 0.041).
::: {#F3 .fig}
Figure 3
::: {.caption}
######
**FCR3CSA expresses surface antigens exhibiting differential protease sensitivity.**Intact infected erythrocytes were treated with 1.0 mg/ml trypsin or 0.1 mg/ml pronase prior to FACS analysis. Serum pools are the same as those described in Figure 1. The bar chart shows mean and standard error of the means for three independent experiments.
:::
:::
Surprisingly, IgG*control*binding to the infected erythrocyte surface increased following CSA selection of the parasite (figure [1](#F1){ref-type="fig"}); however, this non-immune recognition was found to be significantly more trypsin sensitive than IgGpreg recognition (figure [3](#F3){ref-type="fig"}; F~4,18~3.11, p = 0.041). This indicates that the epitopes recognized by the IgG*control*serum pool and the epitopes recognized by the IgG*preg*serum pool are distinct entities. An increase in apparent non-immune immunoglobulin binding to the infected erythrocyte surface has been observed for a number of parasite clones after selection for adhesion to CSA (data not shown). The source of this background labelling of FCR3CSA by naïve sera was found to be due to non-specific binding by the FITC-labelled tertiary rabbit anti-goat antibody. By using the modified antibody labelling procedure, which employs a biotin-labelled secondary antibody and FITC-labelled streptavidin, binding of malaria naive IgG to FCR3CSA (mean fluorescence index = 16) was comparable to the unselected parasite (mean fluorescence index = 17). Thus the recognition of VSA~PAM~by malaria naive IgG was abolished (figure [4](#F4){ref-type="fig"}).
::: {#F4 .fig}
Figure 4
::: {.caption}
######
**A modified antibody labelling procedure for FACS analysis of CSA selected parasites.**In order to circumvent the non-specific labelling of FCR3CSA VSA seen when using the FITC rabbit anti-goat tertiary antibody, a biotinylated rabbit anti-human antibody in combination with FITC-conjugated streptavidin was used. Panels A and B show FCR3CSA and FCR3 infected erythrocytes respectively. In these experiments the control serum was a pool of sera from malaria naïve Danish volunteers, here shown as a solid grey histogram. The IgG*male*serum pool is shown as a lightweight line and the IgG*preg*serum pool as a heavyweight line.
:::
:::
Discordance between the protease sensitivity of the CSA adhesion interaction and IgG binding
--------------------------------------------------------------------------------------------
Following the identification of trypsin-resistant epitopes that appear to be concomitantly selected with CSA adhesion, the trypsin sensitivity of CSA adhesion itself was determined. FCR3CSA binding to immobilised CSA was markedly more sensitive to trypsin than IgG*preg*recognition of the infected erythrocyte surface (figure [5](#F5){ref-type="fig"}). Parasite adhesion was reduced by 81% and 91% following treatment with 0.1 mg/ml trypsin and 1 mg/ml trypsin respectively (figure [5](#F5){ref-type="fig"}). A trypsin concentration of 1 mg/ml reduced binding as efficiently as 0.1 mg/ml pronase, and although 0.1 mg/ml pronase significantly reduced cell surface fluorescence due to IgG*preg*antibody binding, 1 mg/ml trypsin had no significant effect on IgG*preg*antibody binding. There is, thus, significant discordance between the high trypsin sensitivity of CSA adhesion and the relatively trypsin-insensitive binding of IgG*preg*serum antibodies to the infected erythrocyte surface (F~1,8~14.4, p = 0.005).
::: {#F5 .fig}
Figure 5
::: {.caption}
######
**The effect of increasing concentrations of trypsin on parasite adhesion to immobilised CSA and HA.**Parasite adhesion to 10 μg/ml human umbilical cord HA and bovine trachea CSA, adsorbed onto the plastic petri dishes, was determined following protease treatment of the intact infected erythrocyte. Bound cells were Giemsa stained and counted by light microscopy. Panels A and B show receptor binding for FCR3 and FCR3CSA infected erythrocytes respectively. The bar chart shows mean and standard error of the means for three independent experiments.
:::
:::
Human umbilical cord hyaluronic acid (HA) was also included in these assays to investigate the binding capacity of the CSA selected clone with respect to this receptor. FCR3CSA was found to bind both HA and CSA, although binding to HA was significantly lower (figure [5B](#F5){ref-type="fig"}; F~3,19~20.44, p \< 0.001), at 71% that observed for CSA. Interestingly, as has previously been shown for other *P. falciparum*isolates \[[@B27]\], the trypsin-sensitivity of parasite adhesion to HA and CSA differed at low trypsin concentrations (0.01 mg/ml) (figure [5B](#F5){ref-type="fig"}; F~1,8~7.7, p = 0.024). Parasite adhesion to hyaluronic acid was found to be more sensitive to trypsinization than adhesion to CSA.
Discussion
==========
The acquisition of antibodies to the surface of placental isolates correlates with protection from malaria in pregnancy and the targets of these antibodies are potential vaccine candidates \[[@B13],[@B15]\]. Two variants of the well characterized VSA, PfEMPl, have been shown to have distinct CSA-binding domains \[[@B29],[@B33]\] and antibodies raised against these domains have been reported to recognize the infected erythrocyte surface \[[@B34]\] and in some cases block parasite adhesion \[[@B35],[@B36]\]. However, in a recent study of *var*gene transcription in CSA-selected clones, a third potential CSA-binding PfEMPl (var2csa) was identified. Var2csa is predicted to possess distinctly different DBL domains and appears to be the major *var*expressed by CSA-selected parasites that are recognized by parity-dependent antibodies \[[@B14]\]. Proteomic analysis of CSA-selected parasites has also identified four additional potential CSA binding PfEMPl molecules \[[@B37]\]. The molecular identity of the surface antigens expressed at the infected erythrocyte surface remains unclear \[[@B38]\]. However, the differential protease sensitivity of the epitopes described here would allow treatment of the infected erythrocyte surface with trypsin thereby simplifying the surface complexity, thus, potentially making proteomic approaches more straightforward.
Although PfEMPl-mediated CSA adhesion appears to play a role in placental malaria the molecular interactions triggering this syndrome are more complex than initially thought. Several studies implicate additional receptors and binding phenotypes of placental parasites, such as non-immune IgM \[[@B39]\], hyaluronic acid \[[@B25],[@B27],[@B40]\] and non-immune IgG \[[@B41]\]. CSA-binding laboratory clones and placental CSA binding isolates also appear to express some parasite encoded surface antigens other than PfEMPl, such as ring surface proteins 1 and 2 (RSP 1 and 2) \[[@B42]\]. Interestingly, a gene \'knock-out\' of the CSA binding *var*(FCR3*var*CSA) in parasite clone FCR3 abolishes CSA binding, but the \'knock-out\' parasites still bind the syncytio-trophoblast of *ex vivo*placental cryosections \[[@B43]\]. Monoclonal antibodies raised against the CSA binding DBLγ domain also show this domain to be sensitive to surface proteolysis using relatively low trypsin concentrations (100 μg/ml) \[[@B34]\]. It is certainly possible that the trypsin-resistant VSA described here are not of the PfEMPl/CSA binding type.
Surface epitopes of the FCR3CSA parasite are both highly resistant to trypsin and are recognized by antibodies from malaria-exposed pregnant women. This agrees with a number of studies that have found parasite adhesion to placental receptors to be resistant to surprisingly high trypsin concentrations. However, binding assays with the parasite clone used in this study showed CSA and HA adhesion to be relatively trypsin-sensitive. This is also compatible with the results of Beeson and his colleagues who demonstrated trypsin-resistant CSA adhesion to be a clone dependent phenomenon \[[@B27]\]. Another recent study by the same group showed sera that is strongly reactive to the surface of CSA selected parasites is not always capable of inhibiting CSA adhesion \[[@B44]\]. Thus this study supports the view that erythrocyte surface epitopes distinct from those involved in CSA adhesion may be targets of the antibodies acquired during PAM and suggests that these two epitopes could be on different molecules. One further implication for vaccine development is that a candidate vaccine raising only CSA adhesion blocking antibodies may not mimic protective surface reactive gender-specific immune responses.
Conclusion
==========
This study supports the view that major differences exist between VSA~PAM~and previously characterized VSA. Apart from being recognized only by female sera in a parity-dependent manner, VSA~PAM~show other distinct characteristics such as; i) VSA~PAM~rarely form infected erythrocyte rosettes when compared to CD36 binding VSA \[[@B27],[@B45]\], ii) with the exception of rosetting isolates, non-immune IgM binding is a phenomenon only seen with CSA-binding clones \[[@B39]\], iii) VSA~PAM~do not generally mediate adhesion to CD36 \[[@B27],[@B46]\], and iv) VSA~PAM~mediated adhesion to the placenta and CSA can be resistant to concentrations of trypsin known to remove most PfEMPl molecules from the infected cell surface. In combination with the findings of this study, these distinct properties of VSA~PAM~suggest the involvement of either an unusually protease-resistant PfEMPl structure, such has been shown to exist in the A4tres PfEMPl molecule \[[@B47]\] or an alternative class of VSA in placental adhesion. The differential protease sensitivity exhibited by VSA~PAM~can be exploited in comparative proteomic analysis to aid in the identification of the molecules whose phenotype is described here.
List of abbreviations
=====================
TPCK -- L-(tosylamido-2-phenyl) ethyl chloromethyl ketone, CSA -- chondroitin sulphate A, PfEMPl -- *P. falciparum*erythrocyte protein 1, PAM -- Pregnancy associated malaria, VSA -- variant surface antigens, VSA~PAM~-- variant surface antigens expressed by placental or CSA binding parasites, IgG -- immunoglobulin G, DBL-γ-Duffy like binding domain-gamma, FITC -- fluorescein isothiocyanate.
Authors\' contributions
=======================
LS conceived of the study, maintained *P. falciparum*culture, performed FACS analysis and binding assays, AE performed the modified labelling FACS experiments and participated in manuscript preparation, MS participated in the design of the study, TS helped develop some methodologies used in this study. DA helped conceive and fund the study and write the manuscript. All authors read and approved the final manuscript.
Declaration
===========
None declared.
Acknowledgements
================
LS is sponsored by a Wellcome Trust Studentship. This work was also supported by EU PAMVAC contract QLK2-CT-2001-01302. We thank Andrew Sanderson for his help with performing the FACS analysis, David Walliker for his help in strain genotyping, Mike Ofori, Maja Lundquist, Edmund Nii-Laryea Browne and Victoria Bam for serum collection. Jaap de Roode helped with statistical analysis and Alex Rowe, Lars Hviid and anonymous reviewers gave helpful comments and suggestions on an earlier version of this manuscript.
|
PubMed Central
|
2024-06-05T03:55:47.876818
|
2004-9-6
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517943/",
"journal": "Malar J. 2004 Sep 6; 3:31",
"authors": [
{
"first": "Lisa",
"last": "Sharling"
},
{
"first": "Anders",
"last": "Enevold"
},
{
"first": "Kordai MP",
"last": "Sowa"
},
{
"first": "Trine",
"last": "Staalsoe"
},
{
"first": "David E",
"last": "Arnot"
}
]
}
|
PMC517944
|
Background
==========
Malaria infections often consist of more than one parasite genotype \[[@B1]-[@B3]\]. Humans represent ecological niches for co-infecting malaria parasites, with shared predators (immune responses) and limited resources, so that competition between co-infecting malaria strains is likely to be intense \[[@B4]\]. Such competition could strongly affect the relative transmission of newly arisen drug-resistant strains, and thus the spread of drug resistance \[[@B5]\].
Resistant and sensitive strains will co-occur in the same host both when *de novo*mutations arise, and when hosts acquire resistant and sensitive strains from one mosquito bite simultaneously or from different mosquito bites. In the absence of drug treatment, the transmission success of the resistant strain will depend on its intrinsic fitness and competitive ability. However, if drug treatment does occur, the resistant strain has two potential fitness advantages. First, it will better survive the drug than the sensitive strain. Second, treatment can remove drug-sensitive competitors, thus freeing up ecological space for the resistant strains to occupy; this would increase the relative transmission of the drug-resistant strain. This second effect, well recognized in theory, has the potential to greatly enhance the rate of spread of drug resistance in a population \[[@B5]\]. However, there is no direct experimental evidence that removal of competitors by drug treatment does enhance the transmission of drug-resistant parasites. This paper reports the first direct experimental demonstration that competitive release of drug-resistant strains can occur following drug treatment.
Competition between drug-sensitive and -resistant malaria clones was studied using the rodent malaria *Plasmodium chabaudi*. This parasite is commonly used as a model for human malaria \[[@B6]\], and has been extensively used to study drug resistance \[[@B7]\]. In the absence of drugs, the drug-resistant clone is competitively suppressed by a drug-sensitive clone \[[@B8]\]. Here, competition between the two strains in drug-treated and untreated mice is compared.
Methods
=======
Two genetically distinct *Plasmodium chabaudi chabaudi*clones were used: an AS clone resistant to the antifolate drug pyrimethamine \[[@B9]\], and AJ, a sensitive clone. These clones will be referred to as R (for resistant) and S (for sensitive) from hereon. Hosts were eight weeks old CBA/Ca inbred female mice (Ann Walker, University of Edinburgh; Harlan, England). Two experiments were performed. In the first, two groups of five mice were infected with 10^6^R parasites, and two groups with 10^6^R + 10^6^S parasites, as described elsewhere \[[@B8]\]. One group from each of these two infection types was drug-treated within three hours of inoculation and again on days 1, 2 and 3 PI (post-infection), using an oral administration of 8 mg pyrimethamine per kg mouse body weight.
Asexual parasite densities and gametocyte densities -- the latter being the transmission stages to the mosquito -- were monitored using microscopic examination of thin blood smears and determination of red blood cell densities using flow cytometry (Beckman Coulter), as described elsewhere \[[@B8]\]. Real-time quantitative PCR was used to distinguish and quantify R and S parasites in mixed infections \[[@B8],[@B10]\]. This protocol cannot distinguish between asexual parasites and gametocytes, but real-time PCR data were used as estimates of asexual densities, because gametocyte densities were 2--3 orders of magnitude lower than asexual densities and thus a negligible component of overall parasite numbers. For each infection, two phases were distinguished: the acute phase, involving the first wave of parasites, and the chronic phase, beginning when parasite numbers began to recover after the collapse of that first wave around day 12. All parasites had disappeared below detectable levels after 50 days.
In the second experiment, two groups of nine mice were infected as above with either R parasites or R+S parasites. The subsequent transmission success of clone R was assayed by allowing batches of 30 starved *Anopheles stephensi*mosquitoes to feed on 3 mice from each group on each of days 7, 14, and 21 PI, as described elsewhere \[e.g. \[[@B11]\]\]. Eight days after the feeds, mosquitoes were dissected, and DNA extracted from midguts carrying oocysts. Real-time quantitative PCR was subsequently used to determine the prevalence of clone R in these mosquitoes.
All procedures were regulated and carried out under the British Home Office Animals (Scientific Procedures) Act 1986.
Results
=======
Two untreated mice infected with R+S parasites died on days 10 and 11 PI respectively, and were excluded from the analysis.
In untreated mice, there were far fewer R parasites during the acute phase in mixed infections with clone S than in R-only infections (Figures [1a,1c](#F1){ref-type="fig"}). However, in drug-treated mice, where S parasites were entirely removed by pyrimethamine (none of the PCR reactions performed were positive for clone S), there were as many R parasites in mixed infections as there were in R-only infections (Figures [1b,1c](#F1){ref-type="fig"}; Drug treatment × Alone/Mixed interaction: F~1,14~= 14.4, p = 0.002). Thus, R parasites were competitively suppressed in mixed infections in untreated mice, but this suppression was negated when mice were treated with pyrimethamine, which effectively removed S parasites.
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Log asexual parasite densities of the resistant clone R over time in untreated (a) and drug-treated (b) mice infected with R alone or a mixture of R+S clones, and total numbers of R parasites produced over the acute (c) and chronic phases (d). All data points (mean ± 1 s.e.m.) are based on 5 replicate mice, except for mixed infections in untreated mice in (a) (4 mice on day 11 and 3 mice from day 12 onwards) and (c) and (d) (3 mice). As the limit of detection was 100 parasites per μl blood, y-axes in (a) and (b) start at 2.
:::
:::
During the chronic phase, clone R was more numerous in untreated mice in mixed infections than in single-clone infections (due to the parasite peak around day 21; Figures [1a,1d](#F1){ref-type="fig"}). Thus, in untreated mice in the chronic phase, clone R did not suffer from competition, and actually benefited from the presence of clone S (facilitation). In drug-treated mice, however, R parasites were similarly numerous in mixed- and single- clone infections (Figures [1b,1d](#F1){ref-type="fig"}; Drug treatment × Alone/Mixed interaction: F~1,14~= 13.8, p = 0.002).
The large peak of R parasites in the chronic phase in the untreated mixed infections around day 21 (Figure [1a](#F1){ref-type="fig"}) coincided with a large peak of gametocytes, the transmissible stages of the parasite (Figure [2a](#F2){ref-type="fig"}). This was in contrast with single-clone infections of R in untreated mice, and infections in drug-treated mice, where gametocytes were mainly produced around day 14 (Figures [2a,2b](#F2){ref-type="fig"}). Overall, gametocyte numbers were the same for all four infection types (p \> 0.05 for both Drug treatment and Alone/Mixed). Whether clone R really suffered from competitive suppression by clone S in untreated mice thus depends on how many of the gametocytes around day 21 were of the R genotype, and on how transmissible they were.
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Log gametocyte densities over time (mean ± 1 s.e.m.) for untreated (a) and drug-treated (b) mice. In (a) gametocyte densities for mixed R+S infections reflect overall R+S gametocytes, as the PCR assay could not distinguish between these (see text); in (b) all gametocytes are produced by clone R, as clone S was cleared from mixed infections. All data points are based on 5 replicate mice, except for mixed infections in untreated mice in (a): 4 mice on day 11 and 3 mice from day 12 onwards. As the limit of detection was 100 gametocytes per μl blood, y-axes start at 2.
:::
:::
The second experiment assessed transmission to mosquitoes on days 7, 14 and 21 PI. It was found that the resistant clone R infected far fewer mosquitoes from mixed infections than from single infections (figure [3](#F3){ref-type="fig"}; Alone/Mixed: p = 0.002), indicating that transmissibility of gametocytes produced around day 21 was low, probably as a result of transmission-blocking immunity \[[@B12]\]. Thus, the competitive suppression of the resistant clone in untreated infections translated into reduced transmission success.
::: {#F3 .fig}
Figure 3
::: {.caption}
######
Proportions of mosquitoes infected with the resistant clone R (mean and 95% confidence interval); mosquitoes fed either on mice infected with clone R alone or mice infected with a mixture of clones R and S. Means are based on 9 mice (3 on day 7, 3 on day 14 and 3 on day 21 PI) from which totals of 205 (R alone) and 216 (mixed R+S) mosquitoes took a blood meal. Infection with clone R was assessed by real-time PCR.
:::
:::
Discussion
==========
These results show that drug treatment of malaria infections can severely affect ecological interactions between co-infecting strains. The drug-resistant clone was competitively suppressed by the drug-sensitive clone in untreated mice, in terms of both within-host growth and transmission to the mosquito vector. However, drug treatment removed that competitive suppression, and allowed the resistant clone to fill the ecological space emptied, giving it a substantial and additional fitness benefit in addition to the simple survival advantage conferred by resistance. Thus, under drug pressure, resistant strains can have two advantages: they survive better than sensitive strains and they can exploit the opportunities presented by the removal of their competitors, thereby increasing their relative transmission. Competition was studied between two unrelated clones, and thus did not reflect the situation in which a resistant clone arose *de novo*\[[@B13]\], but it seems likely that the competitive release following drug therapy would also apply there.
Competitive release following drug treatment will greatly enhance the spread of drug resistance \[[@B5]\]. Also, with only the resistant strain left in the host, the probability of outbreeding is reduced, thus reducing the chances of meiotic recombination destroying multi-locus resistance \[[@B14]\]. In combination, these two processes could enhance the spread of drug resistance, especially in areas with high numbers of strains per infection \[[@B5]\].
Of course, this is an argument for judicious use of drugs, not their non-use. Clearance of drug-sensitive strains from mixed infections might enhance the spread of drug resistance, but this has to be offset against the short-term public health benefits, such as reducing overall malaria prevalence. In these experiments, the drug-sensitive clone was also the more virulent clone \[[@B8]\], and when it was cleared from mixed infections by drug treatment, mice were less sick, in that they lost less weight and became less anaemic (results not shown).
In this experiment, mice were drug-treated before symptoms occurred, resulting in competitive release. This situation perhaps best mimics the case of prophylactic drug use, or what might occur to new co-infections in high transmission areas where drug use is common. A battery of more complex experiments will be necessary to determine if competitive release occurs when treatment follows symptoms, and when drugs are used to treat semi-immune individuals. The facilitation observed in chronic infections (Figures [1a,1d](#F1){ref-type="fig"}) suggests the situation might be very complex.
Within-host competition in *P. chabaudi*is now firmly established \[[@B8],[@B15],[@B16]\]. Evidence for competition between co-infecting genotypes in human malaria infections is necessarily indirect, but consistent with this \[[@B4]\]. In older children and adults, for example, parasite densities do not increase with increasing numbers of clones, thus indicating that parasite clones are not regulated independently \[[@B17]\]. Given this, and the high frequency of mixed infections in human malaria \[[@B1]-[@B3],[@B18]\] often consisting of both resistant and sensitive genotypes \[[@B19]\], and the fact that genetic diversity can be altered by antimalaria prophylaxis \[[@B20]\], it is highly likely that competitive release of drug resistance also occurs in human malaria. Indeed, a recent study has already implicated release of within-host competition as a key-factor in the spread of drug resistance in Uganda \[[@B21]\].
Authors\' contributions
=======================
JCdR and RC designed and performed the first experiment, while JCdR and ASB performed the second experiment. JCdR analysed the results and drafted the manuscript. ASB developed the real-time PCR assays for analysis of parasite populations inside mosquitoes. AFR assisted in designing both experiments and writing the manuscript. All authors read and approved of the final version of the manuscript.
Competing interests
===================
None declared.
Acknowledgements
================
D. Walliker is thanked for assistance with drug-treating mice, B. Chan for technical assistance, R. Carter and S. Cheesman for fruitful discussion and development of real-time PCR assays, M. Guinnee for comments on an earlier manuscript, and the staff of the March animal house for excellent husbandry. The study was funded by the Wellcome Trust and the BBSRC, and JCdR was supported by the Darwin Trust of Edinburgh.
|
PubMed Central
|
2024-06-05T03:55:47.878948
|
2004-9-14
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517944/",
"journal": "Malar J. 2004 Sep 14; 3:33",
"authors": [
{
"first": "Jacobus C",
"last": "de Roode"
},
{
"first": "Richard",
"last": "Culleton"
},
{
"first": "Andrew S",
"last": "Bell"
},
{
"first": "Andrew F",
"last": "Read"
}
]
}
|
PMC517945
|
Background
==========
Epidemiological evidence consistently shows a positive association between alcohol, even low to moderate intake, and breast cancer risk \[[@B1]\]. However, during the past two decades, it has become evident that moderate drinking is associated with longer life \[[@B2]\], reduced rates of heart disease \[[@B3]\] and stroke \[[@B4]\]. What does this mean for women when the epidemiologic data show an exposure is associated with both benefits and harms? Recommendations regarding the use or avoidance of moderate alcohol, must take into consideration both its potential benefit on cardiovascular disease, as well as its potential risk for breast cancer. To understand the biologic parameters potentially influenced by alcohol, there is a need for well-controlled mechanistic studies of dose and duration of use on markers of risk in the causal pathway of breast cancer.
A reanalysis of nine prospective studies shows that levels of endogenous sex hormones are strongly associated with breast cancer risk in postmenopausal women \[[@B5]\]. Clear evidence that moderate alcohol consumption increases levels of hormones associated with increased risk for breast cancer would provide support for a causal relationship. In a controlled study of acute alcohol ingestion, serum estrone levels were significantly elevated in postmenopausal women on hormone replacement therapy (HRT), but did not affect serum estrone levels in women not using HRT \[[@B6]\]. To better understand the effects of moderate long-term alcohol ingestion on sex hormones, we conducted a controlled feeding study in postmenopausal women not using HRT. As previously reported, there were significant elevations in both serum estrogen sulfate and dehydroepiandrosterone sulfate (DHEAS) after 8 weeks of supplementation \[[@B7]\]. Here, we evaluate the relationships between serum estrogen sulfate and DHEAS after 4 weeks of supplementation with moderate alcohol, and compare the results to the 8 week data to elucidate time-to-effect differences.
Methods
=======
Details of the Women\'s Alcohol Study (WAS) was previously published \[[@B7]\]. Briefly, a total of 51 postmenopausal women not on HRT completed the study and are included in the analysis. The WAS utilized a crossover design. Each participant rotated through three 8-weeks controlled dietary periods during which she consumed a beverage daily that contained no alcohol (placebo), 15 g alcohol, or 30 g alcohol in random order. Each of the three dietary periods was preceded by a 2- to 5-week washout period during which the women consumed no alcohol. Alcohol was supplied as 95% ethanol (Everclear™ Pharmaco Products, Inc., Brookfield, CN) in orange juice (12 ounces). All meals were prepared at the Beltsville Human Nutrition Research Center and the participants ate breakfast and supper at the Center and had carryout lunches on weekdays. On weekends, food and beverages were packaged for consumption at home. The calorie level for each subject was adjusted to maintain constant body weight.
Blood for hormone analyses was collected after an overnight fast at weeks 4 and 8. Serum was separated, and aliquots were frozen at -70°C. In the samples taken after 4 weeks of alcohol supplementation, we only measured serum estrone sulfate and DHEAS, as they were the only two hormones that were significantly elevated at 8 weeks \[[@B7]\].
Hormone concentrations were transformed using natural log. Changes in hormone concentrations from placebo to 15 g and 30 g of alcohol per day were estimated at 4 and 8 weeks using linear mixed models including a random intercept and alcohol levels as fixed effects treated as two indicator variables. Separate models used alcohol as a continuous variable to test for trend. Regressions to evaluate the effect of several baseline covariates on the precision of the parameter estimates for alcohol consumption included age, BMI, and years since menopause modeled as continuous fixed effects; assignment order, dietary period, hysterectomy, and race were modeled as indicator variables. Effect modification by race, assignment order, dietary period, age, BMI, and years since menopause were assessed by likelihood ratio tests of improvement in the model fit after addition of cross-product terms to models that included main effects for alcohol and the characteristic being evaluated. All tests of statistical significance were two-sided. Statistical analyses were performed using S-PLUS (S-PLUS version 6.1 for Windows. Seattle (WA): Insightful Corporation; 2002.)
Results and Discussions
=======================
Table [1](#T1){ref-type="table"} summarizes the mean hormone concentrations at four weeks and eight weeks in the participants when not consuming alcohol and the percent changes from no alcohol consumption when consuming 15 g or 30 g of alcohol per day, respectively. At 4 weeks of alcohol intake the inclusion of age, years since menopause, race, and baseline BMI in the models did not change the precision of parameter estimates for alcohol doses and thus results from simple models are presented. At week 4, compared to the no alcohol placebo, estrone sulfate increased an average 6.9% (P = 0.24) when women consumed 15 g of alcohol per day and 22.2% (P = 0.0006) when they consumed 30 g of alcohol per day. DHEAS concentrations also increased significantly by an average 8.0% (P \< 0.0001) on 15 g of alcohol per day and 9.2% (P \< 0.0001) when 30 g alcohol was consumed per day at week 4. Trend tests for both estrone sulfate (P = 0.0006) and DHEAS (P \< 0.0001) were highly significant.
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Geometric mean hormone levels (ng/dL) for participants on 0 g alcohol and % change (Δ) in hormone levels from 0 g to 15 g and 30 g alcohol per day at weeks 4 and 8
:::
Hormone 0 g/d, mean (95% C.I.) 15 g/d, Δ (95% C.I.)\* 30 g/d, Δ (95% C.I.)\* *P*-trend†
----------------- -------- ------------------------ ------------------------ ------------------------ ------------
Estrone Sulfate (4 wk) 47.5 (39.2--57.4) 6.9% (-4.2%--19.3%) 22.2% (9.4%--36.5%) 0.0006
(8 wk) 47.4 (40.5--55.6) 7.5% (-0.3%--15.9%) 10.7% (2.7%--19.3%) 0.009
DHEAS (4 wk) 55.3 (47.0--65.1) 8.0% (4.5%--11.6%) 9.2% (5.6%--12.8%) \<0.0001
(8 wk) 59.4 (50.5--70.0) 5.1% (1.4%--9.0%) 7.5% (3.7%--11.5%) 0.0001
\* Estimates of percent change are from linear mixed models, including participant as a random effect and alcohol levels as fixed effects treated as two indicator variables.
† *P*-trend values (two-sided) are from linear mixed models, including participant as a random effect and alcohol levels as a continuous fixed effect with values 0, 15, and 30.
:::
The effects of alcohol supplementation on serum estrone sulfate and DHEAS levels did not vary with age, BMI, race, or years since menopause. These hormone concentrations also did not differ among the three dietary periods, and the order of the assignment to the treatment regimens did not modify the associations with either of the two hormones.
At 8 weeks of alcohol intake, the 15 g dose versus the placebo increased serum estrone sulfate and DHEAS by 7.5% and 5.1% respectively, whereas the 30 g dose compared to the placebo, increased levels of estrone sulfate and DHEAS by 10.7% and 7.5% respectively. When comparisons using linear mixed models are made, after controlling for alcohol intake across all doses, there was no statistically significant difference between the absolute levels of serum estrone sulfate at week 4 versus 8 (P = 0.32). However, controlling for alcohol intake absolute DHEAS levels increased between weeks 4 and 8 (P \< 0.0001). The increase in DHEAS between weeks 4 and 8 did not occur in just the 15 or 30 g per day groups, however; the increase was similar in each of the three groups. In the 0 g per day group the geometric mean shifted from 55.3 ng/dL at 4 weeks to 59.4 ng/dL at 8 weeks. In the 15 g per day group the geometric mean shifted from 59.7 ng/dL to 62.5 ng/dL, and in the 30 g per day group the geometric mean shifted from 60.4 ng/dL to 63.9 ng/dL. The models did not suggest an interaction between measurement week and alcohol dose in serum estrone sulfate (P = 0.32) or DHEAS (P = 0.58).
In postmenopausal women moderate alcohol consumption for four weeks resulted in statistically significant increased levels of serum estrone sulfate, the most abundant circulating estrogen, and DHEAS, the steroid hormone with the highest concentration in the blood. Compared to the placebo, serum estrone sulfate levels increased 6.9% (P = 0.24) and 22.2% (P = 0.0006) respectively among women who consumed 15 g and 30 g alcohol per day for four weeks. Serum DHEAS concentrations also increased by 8.0% (P \< 0.0001) and 9.2% (P \< 0.0001) respectively among women who consumed 15 g or 30 g alcohol per day for four weeks. At week 8, serum estrone sulfate levels increased 7.5% and 10.7% respectively among women who consumed 15 g and 30 g alcohol per day whereas DHEAS concentrations increased 5.1% and 7.5% respectively among women who consumed 15 g or 30 g alcohol per day compared to the placebo \[[@B7]\]. The increased levels of serum estrone sulfate concentrations at week 4 were essentially the same as those seen at week 8. The % change in serum estrone sulfate levels from week 4 to week 8 is -0.1%, 0.5%, and -8.9% respectively in the 0 g, 15 g, and 30 g alcohol doses. Estrone sulfate does not show a consistent change over time across all alcohol doses and there is no statistical evidence of an interaction between time and alcohol (P = 0.32). Although there appears to be a difference when looking at the point estimates in the 30 g alcohol dose, variance in estrone sulfate is so large at both 4 weeks and 8 weeks the difference between the two point estimates is not statistically significant. The large variance in estrogen sulfate at the 30 g dose will require more people to accurately judge this possible interaction.
For DHEAS, the absolute levels were statistically (P \< 0.0001) higher at week 8 compared to week 4 in all the alcohol groups. This increase in DHEAS between weeks 4 and 8 did not differ regardless of 0 g, 15 g, or 30 g per day dose (P = 0.58). Biological reasons may explain the increase in the 15 g and 30 g per day alcohol dose, but the reasons behind the increases in DHEAS for the 0 g dose need further research. We did not find any evidence for an effect modification between measurement week and alcohol supplementation in serum estrone sulfate (P = 0.32) or DHEAS (P = 0.58).
These data indicate that the hormonal effects due to moderate consumption of alcohol equivalent to one or two drinks per day are seen early, within 4 weeks of initiation of ingestion. Importantly from a study design perspective, our study also demonstrates that it may be possible to utilize shorter study periods when assessing the effects of alcohol consumption on hormone levels, at least in postmenopausal women. To understand the earliest effects of moderate alcohol intake on hormone levels in postmenopausal women, future studies will have to be designed to assess serum levels earlier than 4 weeks or possibly later than 8 weeks.
Postmenopausal women with elevated levels of serum estrone sulfate \[[@B8],[@B9]\] and DHEAS \[[@B8]-[@B11]\] levels were reported to be at an increased risk of breast cancer in several prospective cohort studies. Results from our study showing statistically significant increased serum estrone sulfate and DHEAS concentrations after four weeks of supplementation with alcohol equivalent to one or two drinks per day, provide one possible mechanism by which moderate alcohol ingestion could increase breast cancer risk in postmenopausal women.
Alcohol has many physiologic effects and could influence breast cancer risk through non-hormonal mechanisms as well. Experimental evidence suggests that alcohol interferes with folate absorption, transport, and metabolism, potentially limiting folate stores in the tissues and may interfere with DNA methylation \[[@B12],[@B13]\]. Alcohol consumption and metabolism can result in increased production of several classes of DNA damaging molecules including reactive oxygen species \[[@B14]\] which can lead to increase DNA damage and the development of breast cancer \[[@B15]\].
Conclusions
===========
In conclusion, our results provide additional evidence for a mechanism by which moderate alcohol drinking could modify breast cancer risk, indicating that this effect occurs after a short time period (as early as four weeks), and thus provides further support for a causal association.
Competing interests
===================
None declared.
Acknowledgements
================
The present work was funded in part by interagency agreement Y1-SC-8012
|
PubMed Central
|
2024-06-05T03:55:47.880261
|
2004-9-7
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517945/",
"journal": "Nutr J. 2004 Sep 7; 3:11",
"authors": [
{
"first": "Somdat",
"last": "Mahabir"
},
{
"first": "David J",
"last": "Baer"
},
{
"first": "Laura L",
"last": "Johnson"
},
{
"first": "Joanne F",
"last": "Dorgan"
},
{
"first": "William",
"last": "Campbell"
},
{
"first": "Ellen",
"last": "Brown"
},
{
"first": "Terryl J",
"last": "Hartman"
},
{
"first": "Beverly",
"last": "Clevidence"
},
{
"first": "Demetrius",
"last": "Albanes"
},
{
"first": "Joseph T",
"last": "Judd"
},
{
"first": "Philip R",
"last": "Taylor"
}
]
}
|
PMC517946
|
Finding
=======
Single-cell based analysis methods have become more and more important for understanding the cell-group effects such as how information is controlled and recorded in a cell group or a network shape. Early tissue culture studies of cardiac myocyte cells demonstrated that a single beating cell can influence the rate of a neighbouring cell in close contact and that a group of heart cells in a culture, beating synchronously with a rapid rhythm, can act as pacemaker for a contiguous cell sheet \[[@B1]\]. Though the former results predicted that a rapidly beating region of tissue acts as pacemaker for a slower one and examined how the synchronization process of two isolated beating cardiac myocytes \[[@B2]\], the cell-to-cell connection could not be controlled completely without using microstructures on the cultivation plate. As means of attaining the spatial arrangement of cardiac myocytes, we have developed a new single-cell cultivation method and a system using agar microstructures, based on 1064-nm photo-thermal etching \[[@B3]-[@B6]\]. We have also developed the on-chip single-cell sorting method for cultivating particular cells chosen from clued mixture of cells \[[@B7]\], and have found the adaptation process of epigenetic memorization in cells by storing the information as the localization of proteins \[[@B8]\].
This paper reports the practical use of the agar chamber for screening the community size effect of the synchronization process of adjacent cardiac myocyte cells having independent oscillation.
Figure [1](#F1){ref-type="fig"} shows the schematic drawing of the agar microchambers on the chip. The microchambers and microchannels were constructed by localized melting of a portion of the 5-μm-thick agar layer using a 1064-nm the infrared focused laser beam, a process we have termed photo-thermal etching. The 1064-nm laser beam is not absorbed by either water or the agar, and selectively melts a portion of the agar just near the chromium thin layer as this layer absorbs the beam energy. Microstructures such as holes and channels can be easily produced using this non-contact etching within only a few minutes without the requirement of any cast moulding process. The melting of agar by laser occurred as follows: (a) the 1064-nm infrared laser beam was focused on the agar layer on the glass slide; (b) the agar at the focal point and on the light pathway started to melt; (c) when the focused beam was moved parallel to the chip surface, a portion of agar around the focal spot of laser melted and diffused into water; (d) after the heated spot had been moved, a channel was created at the bottom of the agar layer connecting the two adjacent holes. The microscope confirmed the melting had occurred, and then either the heating was continued until the spot size reached the desired size, or the heating position was shifted to achieve the desired shape. Cardiac myocytes were cultivated in each hole of the agar microchambers on the chip as shown in Fig. [1](#F1){ref-type="fig"}. Collagen-type I (Nitta gelatin, Osaka, Japan) was coated on the glass layer surface to improve the attachment of the cell to the bottom of the microchambers.
::: {#F1 .fig}
Figure 1
::: {.caption}
######
(A): Schematic drawing of the on-chip agar cultivation assay. (B): Optical micrograph of 24-h cultivation of two cardiac myocyte cells. (C): Time-course of oscillation of cardiac myocytes shown in Fig. (B). (D): Optical micrograph of 24-h cultivation of two sets of the synchronized pairs. (E): Time-course of oscillation of cardiac myocytes shown in Fig. (D).
:::
:::
Neonatal rat cardiac myocytes were isolated and purified as follows. First, the hearts of 1- to 3-day-old Wistar rats (Nippon Bio-supp. Center, Tokyo, Japan) were excised under ether anaesthesia. The ventricles were separated from the atria and then washed with phosphate buffered saline (PBS, 137 mM NaCl, 2.7 mM KCl, 8 mM Na~2~HPO~4~, 1.5 mM KH~2~PO~4~, pH 7.4) containing 0.9 mM CaCl~2~and 0.5 mM MgCl~2~. The ventricles were minced in PBS without CaCl~2~or MgCl~2~and then incubated in PBS containing 0.25% collagenase (Wako, Osaka, Japan) for 30 minutes at 37°C to digest the ventricular tissue. This procedure was repeated twice more and the cell suspension was then transferred to cell culture medium (DMEM \[Invitrogen Corp., Carlsbad, CA USA\] supplemented with 10% fetal bovine serum, 100 U/ml penicillin, and 100 μg/ml Streptomycin) at 4°C. The cells were filtered through a 40-μm nylon mesh and centrifuged at 180 g for 5 minutes at room temperature. The cell pellet was re-suspended in a HEPES buffer (20 mM HEPES, 110 mM NaCl, 1 mM NaH~2~PO~4~, 5 mM glucose, 5 mM KCl, and 1 mM MgSO~4~, pH 7.4). Cardiac myocytes present in the suspension were separated from other cells (i.e., fibroblasts and endothelial cells) by the density centrifugation method. The cell suspension was then layered onto 40.5% Percoll (Amersham Biosciences, Uppsala, Sweden) diluted in the HEPES buffer, which had previously been layered onto 58.5% Percoll diluted in the same buffer. The cell suspension was then centrifuged at 2200 g for 30 minutes at room temperature. Cardiac myocytes were retrieved from the interface of the 40.5% and 58.5% Percoll layers. Retrieved cells were then re-suspended in the cell culture medium. An aliquot (5- μl) of the suspension was diluted to achieve a final concentration of 3.0 × 10^5^cells/ml then plated into the chip. Individual cardiac myocytes were picked up by a micropipette and manually introduced into each chip microchamber and incubated on a cell-cultivation microscope system at 37°C in the presence of a humidified atmosphere of 95% air /5% CO~2~. It should be noted that because the microchamber sidewalls were made of agar, then the cells could not easily pass over the chambers.
Phase-contrast microscopy was used to measure the contraction rhythm of the cardiac myocytes and the network formation of cells in the two adjacent chambers that were connected by the focused beam.
The spontaneous contraction rhythm of cultured cardiac myocytes was evaluated by a video-image recording method. Images of beating cardiac myocytes were recorded with a CCD camera through the use of a phase contrast microscope. The sizes (cross-section of volume) of cardiac myocytes, which changed considerably with contraction, were also analyzed and recorded every 1/30 s by a personal computer with a video capture board.
Figure [1](#F1){ref-type="fig"} shows a micrograph image of two isolated, independently beating cardiac myocytes coming into contact through the microchannel. Ninety min after the physical contact, the two connected cells started to oscillate synchronously. The time course change of the heart beating was as shown in Fig. [1](#F1){ref-type="fig"}. As shown in the graph, the process of synchronization was accomplished only after one of the cells stopped beating and then synchronized its oscillation with other cell. Movie 1 (see [additional file 1 \"movie1.mpg\"](#S1){ref-type="supplementary-material"}) depicts the process of beating synchronization. Once the synchronized oscillation of the two cells was accomplished (arrowhead in Fig. [1](#F1){ref-type="fig"}), then the two cells maintained synchronization similar to that observed in whole tissue. A time interval of approximately 90 min was needed to form the gap junction between the two adjacent cells.
The same method was also used to make more complicated network patterns of cardiac myocytes. Figure [1](#F1){ref-type="fig"} shows a micrograph of a four-cell network. As shown in the graph (Fig. [1](#F1){ref-type="fig"}), two sets of the beating pairs synchronized without having to stop unlike that previously observed for the synchronization of isolated cells (see [additional file 2 \"movie2.mpg\"](#S1){ref-type="supplementary-material"}). This suggests that the synchronization dynamics and rhythm of the cell group is more stable than that of single cells.
In conclusion, we present a 1064-nm photo-thermal etching technology with which to create agarose microchambers for growing networks of cardiac myocyte cells. Using the system, we first observed the differences of the synchronization process of cardiac myocyte cells and their dependence on community size. This system has great potential for use in the biological/medical fields for cultivating the next stage of single-cell based networks and measuring their properties in laboratories.
Authors\' contributions
=======================
KK and TK carried out the microchamber design, cell preparation, single cell cultivation and observation, image analysis. Both authors contributed equally to this article. KY conceived of the study, and participated in its design and coordination. All authors read and approved the final manuscript.
Supplementary Material
======================
::: {.caption}
###### Additional File 1
two cells. synchronized oscillation of the two cells
:::
::: {.caption}
######
Click here for file
:::
::: {.caption}
###### Additional File 2
two sets of cells. synchronized oscillation of the two sets of cells
:::
::: {.caption}
######
Click here for file
:::
|
PubMed Central
|
2024-06-05T03:55:47.881489
|
2004-9-9
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517946/",
"journal": "J Nanobiotechnology. 2004 Sep 9; 2:9",
"authors": [
{
"first": "Kensuke",
"last": "Kojima"
},
{
"first": "Tomoyuki",
"last": "Kaneko"
},
{
"first": "Kenji",
"last": "Yasuda"
}
]
}
|
PMC517947
|
Background
==========
The intrinsically fluorescent protein from the jellyfish *Aequoria victoria*, termed green fluorescent protein (GFP), can be used to visualize dynamic processes in live cells in real time \[[@B1]\]. A fusion between a molecule of interest and GFP is supposed to localize fluorescence to the normal intracellular locale of the target protein. This technology has been used to study the intracellular location and dynamics of many different proteins in many different organisms. Included in this group are proteins that traffic to and ultimately are released from regulated secretory compartments \[[@B2]\]. In this report an attempt was made to use a GFP fusion protein strategy to study the regulated secretory compartment of cytotoxic lymphocytes.
Vertebrate organisms have developed a system of contact-dependent cytotoxicity in order to control tumors and infection. Specialized cytotoxic lymphocytes, T cells and natural killer (NK) cells, function as effector cells in this system \[[@B3]\]. Cell surface receptors on these cells recognize changes to cell surface molecules of transformed or infected cells. Signaling through these receptors initiates target cell destruction. A major method used by these cells to kill targets is the regulated exocytosis of cytolytic granules \[[@B4]\]. The active components of these organelles and mechanisms by which they lead to target cell death have been well studied. However, the underlying molecular mechanisms governing their biogenesis and release remain less well understood. Adaptation of GFP tagging technology to analyze these processes might therefore be of considerable value in elucidating the underlying molecular mechanisms. Thus, GFP was fused to granulysin, a small secreted protein that sorts to and accumulates in cytolytic granules \[[@B5],[@B6]\], and expressed in the functional human NK cell line YT \[[@B7]\]. The YT cell line was utilized in this study because it had previously been stably transfected with native granulysin and shown to properly produce and accumulate the processed product in its regulated secretory compartment \[[@B6]\].
Findings
========
Stable transfectant lines for native granulysin, GFP-tagged granulysin, and non-fused GFP were derived using G418 selection. The GFP proteins were first characterized by immunoblot analysis of lysates and cell supernatants probed with antisera to GFP (figure [1a](#F1){ref-type="fig"}). The cell line transfected with the granulysin-GFP expression construct produces a doublet of proteins in the correct molecular weight range for the fusion protein, with both the cell lysate and supernatant media containing immunoreactivity. No explanation presently exists as to the difference between the two proteins of the doublet. The cell line expressing non-fused GFP, which does not contain a signal sequence, displayed an immunoreactive protein only in the cell lysate and not in the extracellular media. Thus, the granulysin-GFP fusion construct correctly directs the biosynthesis of the chimeric molecule into the secretory pathway. A previous publication demonstrated that a native granulysin transfectant also expresses protein, detectable by anti-granulysin sera, in both lysate and extracellular media fractions \[[@B6]\]. Next, the intracellular localization of native granulysin and granulysin-GFP was analyzed by two color immunofluorescent confocal microscopy using a polyclonal antisera reactive to granulysin and a monoclonal antibody reactive to perforin, a well characterized constituent of cytolytic granules \[[@B4]\] (figure [1b](#F1){ref-type="fig"}). Significant overlap in the dual staining, as evidenced by the abundant yellow signal, demonstrates that transfected native granulysin co-localizes with perforin in granules. On the contrary, the granulysin-GFP fusion protein displays very little overlap in staining with perforin, indicating that the chimera is altered in its subcellular distribution in comparison to the native molecule. Conclusions to be drawn from these data regarding the mechanism(s) of sorting to cytolytic granules are limited but could suggest that altering the overall biophysical properties of granulysin by the addition of the relatively large GFP moiety negates the information necessary to gain entrance into the correct secretory pathway. However, of perhaps broader scientific significance, the data serve as a striking demonstration of an obvious but seldom published limitation of using GFP fusion proteins as substitutes for the native molecules.
::: {#F1 .fig}
Figure 1
::: {.caption}
######
**Granulysin-GFP fusion protein is expressed and secreted but doesn\'t colocalize with perforin.**a) Immunoblot analysis using anti-GFP sera was performed on cell lysate and cell media supernatant samples of YT cells expressing granulysin-GFP fusion protein (YT.granGFP) and native GFP (YT.GFP). b) Confocal immunofluorescence staining for granulysin (green) and perforin (red) was performed for YT expressing native granulysin (YT.granulysin) and granulysin-GFP fusion protein (YT.granGFP).
:::
:::
Materials and Methods
=====================
Cells
-----
The NK cell line YT was transfected via electroporation with the linearized expression construct plasmids of full-length native granulysin-pcDNA3.1, full-length granulysin (res. 1-145)-pGFP and control non-fused pGFP. Stable transfectants were selected and grown in RPMI 1640 + 10% fetal bovine serum containing 1 mg/ml G418.
Immunoblots
-----------
One ml liquid aliquots of log-phase cells were pelleted (supernatant saved), washed in PBS, and lysed in 100 μl of reducing sample buffer. The supernatant was diluted 1:1 (v:v) in 2X sample buffer containing DTT. Ten μl of lysate sample (10% of total) and 10 μl of supernatant sample (0.5% of total) were loaded into wells of a 10% PAGE-SDS gel. After electrophoretic separation, proteins in the gel were transferred to nitrocellulose using a semi-dry blot apparatus. Blots were probed with rabbit antisera specific for GFP followed by peroxidase-conjugated anti-rabbit antibodies. Reactive protein bands were revealed by chemiluminescent detection.
Confocal microscopy
-------------------
Log-phase cells were immobilized in wells of a poly-L-lysine coated printed glass slide. After fixation with 4% (w/v) paraformaldehyde in PBS, the cells were permeabilized for 30 minutes in staining buffer \[10% (v/v) normal goat serum, 1% (w/v) nonfat dry milk powder, 0.1% (w/v) saponin, in PBS\]. Next, samples were incubated for 30 minutes with primary antibodies to granulysin (rabbit antisera) and perforin (mouse mAb) diluted in staining buffer. After washing 3X with staining buffer, samples were incubated 30 minutes with species-specific fluorescent Alexa 488 goat anti-rabbit and Alexa 568 goat anti-mouse secondary antibodies (Molecular Probes). Cells were then washed 3X with staining buffer, then twice with PBS, and glass coverslips mounted using 50% (v/v) glycerol in PBS. Images were collected using a BioRad MRC 1024 confocal imaging system mounted on a Nikon Diaphot inverted microscope.
Authors\' contributions
=======================
DAH designed the study, carried out all experimental procedures, and drafted the manuscript. SFZ consulted on the experimental design, provided the resources that allowed the study to be conducted and edited the manuscript. Both authors read and approved the final manuscript.
|
PubMed Central
|
2024-06-05T03:55:47.882692
|
2004-9-10
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517947/",
"journal": "J Negat Results Biomed. 2004 Sep 10; 3:2",
"authors": [
{
"first": "Dennis A",
"last": "Hanson"
},
{
"first": "Steven F",
"last": "Ziegler"
}
]
}
|
PMC517948
|
Background
==========
During cell cycle progression different functional protein complexes associate with and dissociate from chromosomal DNA \[[@B1],[@B2]\]. We have taken a proteomic strategy to identify and then characterize proteins that are bound to chromatin at defined stages of the cell cycle in cell free extracts derived from *Xenopus*eggs. The combination of 2D gel electrophoresis (2DE) and Mass Spectroscopy (MS) are powerful tools for this analysis.
2DE is capable of resolving thousands of proteins in a single separation procedure \[[@B3]\]. Development of immobilised pH gradients (IPG) coupled with pre-cast gradient polyacrylamide gels and introduction of new sensitive fluorescent stains have considerably simplified and greatly improved the capacity, sensitivity and reproducibility of 2D gels. These recent technological advances do not however eliminate a number of difficulties associated with the separation of proteins by 2DE. One major problem is the solubilisation of protein mixtures during isoelectric focusing (IEF), (reviewed in \[[@B4]\]). In addition, reduction and alkylation of protein samples for 2DE has not yet been fully optimised \[[@B5],[@B6]\]. As a consequence, conventional approaches for protein solubilisation and modification do not reliably provide the best samples for electrophoresis.
Good solubilisation of protein samples is critical for high performance 2D electrophoresis and there is a wide range of protein solubilisation cocktails reported in the literature. However we have not found any systematic studies reporting optimal concentrations of critical ingredients, possibly because conventional approaches to optimisations are very time consuming: varying all the possible components in turn and in combination is quite laborious. There are, however, methods for reducing the complexity of multi-parametric matrices. The Taguchi method, has been widely used for several decades in the development of industrial processes and recently found its way to the area of life sciences \[[@B7]-[@B10]\]. The conventional optimisation experiments require independent testing of each variable in turn. For example, testing the effect and interaction of four different reaction components, each at three separate concentration levels, would require experiment with 81 (i.e. 3^4^) separate reactions. Using Taguchi approach the same task can be accomplished in the experiment with just nine reactions.
To find the optimal and most robust conditions for 2DE, we applied a modified Taguchi method \[[@B9]\] for the formulation of the rehydration buffer (RB) used to solubilise and run protein mixtures during IEF. We also optimised the sample reduction and alkylation procedure traditionally performed after IEF step. The resulting protocol, substantially improved the solubility and resolution of protein mixtures derived from a variety of sources on 2DE.
Results
=======
Choosing components for optimisation of RB
------------------------------------------
Rehydration buffers for IEF generally consist of chaotropes (urea, thiourea), detergent(s), reducing agent(s) and carrier ampholytes (reviewed in \[[@B11]\]). The standard formulation of RB (sRB) contains 8 M urea \[[@B12]\]. However the combination of chaotropes, 7 M urea and 2 M thiourea, was reported to produce better 2D images with an immobilised pH gradient (IPG) compared to 8 M urea alone \[[@B13]\] and this mix was chosen as the basis for all subsequent rehydration solutions.
During IEF, proteins must be maintained in a fully reduced state. Three reducing agents: DTT, TBP and TCEP were tested in identical conditions with the same protein sample using an RB containing 7 M urea, 2 M thiourea, 4% CHAPS, 0.5% ampholytes and either 20 mM DTT, 2 mM TBP or 10 mM TCEP. 50 μg pellets of *Xenopus*egg proteins were solubilised in each RB and separated by 2DE (Figure [1](#F1){ref-type="fig"}). Both TBP and TCEP reduced focusing in our gel system. The best focusing was achieved in the RB containing DTT, so this compound was selected for all successive optimization experiments.
::: {#F1 .fig}
Figure 1
::: {.caption}
######
The effect of different reducing agents on protein resolution in 2D gels. 50 μg aliquots of total *Xenopus*egg extract were dissolved in RB containing 7 M urea, 2 M thiourea, 4% CHAPS, 0.5% ampholytes and different reducing agents. 2DE separation was conducted as described in Materials and Methods. (A) 20 mM DTT, (B) 2 mM TBP, (C) 10 mM TCEP.
:::
:::
Detergents in RBs help to prevent protein interaction and aggregation, and their properties are critical for protein solubilisation. The increasing number of proteins detected in 2D gels was reported when different zwitterionic detergents were added to solubilisation cocktails \[[@B14]-[@B16]\]. We therefore decided to optimise the combination of two widely used detergents, CHAPS and ASB14 \[[@B17],[@B18]\].
The addition of carrier ampholytes enhances solubility of individual proteins as they approach their isoelectric points. They also produce an approximately uniform conductivity across a pH gradient without affecting its shape. For these reasons, we also optimised the concentration of carrier ampholytes within the solubilisation buffer.
The concentration ranges of components used in one representative optimisation experiment are presented in Table [1](#T1){ref-type="table"}. To accommodate increased carrier ampholyte concentrations, we increased the length of focusing time during electrophoresis. We found that a one step fast ramping gradient between 250--5500 V after the initial phase of 30 min at 250 V worked well for 7 cm IPG strips of different pH ranges (pH 3--10, pH 4--7, pH 6--11). The duration of the IEF step was dependent on both sample conductivity and protein loading, producing good results if performed for a total of more than 33000 volts-hours. The actual voltage was limited since the current was restricted to 50 μA/strip. This total value of volt-hours was enough to complete focusing in samples with the highest carrier ampholyte concentrations.
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Set up of the Taguchi optimisation experiment presented in Figure 2 with total number of spots detected in each gel.
:::
Buffer\* Ampholytes(%) CHAPS(%) ASB14(%) DTT(mM) Spot number\*\*
---------- --------------- ---------- ---------- --------- -----------------
1 0.5 0.5 0.4 20 **361**
2 0.5 1.0 0.8 40 **339**
3 0.5 2.0 1.6 80 **339**
4 1.0 0.5 0.8 80 **296**
5 1.0 1.0 1.6 20 **351**
6 1.0 2.0 0.4 40 **355**
7 2.0 0.5 1.6 40 **319**
8 2.0 1.0 0.4 80 **327**
9 2.0 2.0 0.8 20 **299**
\* -- all buffers contained 7 M urea, 2 M thiourea, 10 mM Tris
\*\* -- number of spots detected, using Phoretix 2D Pro imaging software
:::
After IEF, the focused gel is prepared for SDS-PAGE, usually by incubating consecutively in two equilibration buffers containing DTT or iodoacetamide (IAA) respectively. IAA serves to alkylate reduced cysteine residues and prevent their modification during and after SDS-PAGE. There is evidence that this protocol is not very efficient as the SDS in equilibration solution interferes with IAA alkylation. Variable alkylation can cause a substantial number of artefactual spots on 2D gels \[[@B6],[@B19]\]. One of the ways to overcome the problem is to alkylate protein mixtures in solubilisation buffer before the IEF. However, the presence of thiourea in the RB prevents effective protein alkylation by IAA \[[@B5]\]. Acrylamide is an alternative alkylating agent, and is used widely for protein modification in MS studies. To alkylate cysteines we adjusted acrylamide concentration in RB to 60 mM after solubilisation of protein pellets for 2 hours in the presence of the indicated amount of DTT. The acrylamide treatment was also repeated after IEF as part of the equilibration procedure (see Materials and Methods).
Taguchi optimisation of RB
--------------------------
Aliquots of total *Xenopus*egg extract containing 50 μg of protein were dissolved in rehydration buffers formulated according to the L9 orthogonal Taguchi array shown in Table [1](#T1){ref-type="table"} and then separated by 2DE. The resulting 2D gels exhibited different degrees of focusing and spot presentation especially in the high molecular weight region of the gels (Figure [2](#F2){ref-type="fig"}). The number of spots detected by commercial image analysing software in each individual gel was used to calculate the Taguchi\'s *SNR*values for each level of a given component. The signal-to-noise ratio (*SNR*) function is a statistical measure of performance and takes into account both the mean and variability. In its simplest form, the *SNR*is the ratio of the mean (signal) to the standard deviation (noise). While there are many different possible *SNR*s their simple interpretation is always the same: the larger the *SNR*the better. We used the Taguchi *SNR*function that is most applicable to the situation where the highest yield of optimised process is desirable (see Materials and Methods).
::: {#F2 .fig}
Figure 2
::: {.caption}
######
2D gel images from a representative optimisation experiment. Nine rehydration buffers were tested according to Table 1. Each buffer was used to solubilise 50 μg whole Xenopus egg extract and each sample was run on identical gels under identical conditions. (1--9) are images of high molecular weight regions of 9 gels with arrows pointing to some spots whose intensity and focusing pattern changed considerably between different RB compositions. Total numbers of detected spots in individual gels are presented in Table 1.
:::
:::
Figure [3](#F3){ref-type="fig"} demonstrates the *SNR*graphs from a representative optimization experiment. For two variables in this experiment, CHAPS and DTT, the *SNR*functions had a maximum within the analysed range and highest *SNR*s were achieved at 1.32% CHAPS and at 34 mM DTT (Figure [3A,3B](#F3){ref-type="fig"}). By contrast the highest *SNRs*were achieved with the lowest concentration of ampholytes and ASB14 (Figure [3C,3D](#F3){ref-type="fig"}).
::: {#F3 .fig}
Figure 3
::: {.caption}
######
Effects of reaction components on *SNR*functions in a representative experiment. The Taguchi calculations were carried out using total number of spots detected by imaging software in 2D gels (Table 1). The optimal concentration of each component corresponded to the highest value of the *SNR*function (a--d).
:::
:::
To analyse reproducibility of our approach we repeated experiments three times and determined optimal concentrations of RB components as (1.20 ± 0.18)% CHAPS, (43 ± 12) mM DTT, 0.25% ampholytes and 0.4% ASB14 (the last two are the lowest concentrations used in our optimisation experiments).
The *SNR*response for ASB14 suggests there may be two concentrations that increase the number of detected spots. While we chose detected spot number as a general reporter of RB performance, other factors such as spot circularity, streaking, spot intensity, etc are also critical. We noted that concentrations of ASB14 slightly higher than 2.0% induced significant streaking and spot shape changes leading to a reduced number of detectable spots (see [Additional file 1](#S1){ref-type="supplementary-material"}). This suggested that concentrations of ASBB14 near 2.0% could not perform robustly, i.e. small changes would have deleterious effect on 2DE.
Figure [3C](#F3){ref-type="fig"} and [3D](#F3){ref-type="fig"} suggest that low concentrations of ampholytes and ASB14 may improve detected spot number. To determine if we achieved optimal concentrations for these components, we assayed whether further reducing the amount of these components might increase detected spot number and further improve 2DE performance. Using concentrations of 0.1% -- 0.4% ASB14 and 0.05% -- 0.25% ampholytes we found no significant changes in detected spot number (see [Additional file 1](#S1){ref-type="supplementary-material"}). Thus, the chosen concentrations of ASB14 and ampholytes gave a robust performance and we therefore considered them to be optimised for our 2DE system.
To confirm that the correct choice was made for the optimal ASB14 concentration we compared 2D gels of total *Xenopus*eggs proteins separated with sRB (8 M urea, 4% CHAPS, 0.5% ampholytes, 20 mM DTT) and with oRB (7 M urea, 2 M thiourea, 1.2% CHAPS, 0.4% ASB14, 0.25% ampholytes) (Figure [4A,4B](#F4){ref-type="fig"}). We observed at least a 50% increase in detected spot number in oRB (659 spots) compared to the standard buffer composition (425 spots).
::: {#F4 .fig}
Figure 4
::: {.caption}
######
2DE of two different sets of proteins in sRB (A, C) and oRB (B, D). 50 μg of total *Xenopus*egg extract (A, B) or 25 μg of protein eluted from mitotic chromosomes assembled for 30 min in mitotic *Xenopus*egg extract (C, D) were dissolved in sRB (8 M urea, 4% CHAPS, 0.5% ampholytes, 20 mM DTT) and oRB (7 M urea, 2 M thiourea, 1.2% CHAPS, 0.4% ASB14, 0.25% ampholytes, 43 mM DTT, 30 mM Tris) and separated as described in Materials and Methods. Spots detected: (A) 425, (B) 659, (C) 112, (D) 350.
:::
:::
To extend our analysis we have evaluated the performance of oRB with a variety of different samples. Chromatin associated proteins are often enriched in lysine and arginine residues that mediate interactions with DNA. When we analysed a preparation of mitotic chromosome proteins \[[@B20]\] using sRB, we noted a distinct lack of basic and high molecular weight polypeptides detected on the gel (Figure [4C](#F4){ref-type="fig"}). 2DE of chromosome associated proteins with oRB revealed a large number of basic proteins, as well as many high molecular weight polypeptides, including known high molecular weight chromosome components like DNA topoisomerase II and condensin \[[@B21]\] (Figure [4D](#F4){ref-type="fig"}). Similar performance was noted with preparations of human nucleolar proteins, mouse and shrimp mitochondria (data will be presented elsewhere). We therefore concluded that our optimised 2DE methodology could be successfully applied to a wide variety of samples.
Analysis of post-translational modifications by 2DE
---------------------------------------------------
As a test of the use of an oRB, we characterised a series of well-known chromatin proteins whose function is regulated during the cell cycle. Our improved RB and revised alkylation procedure eliminated ambiguities in immunoblots of high molecular weigh proteins and revealed specific modifications that have not been described previously. XCAP-E (M.W. 140 kDa), a component of condensin, a protein complex involved in the assembly of mitotic chromosomes \[[@B21]\], was analysed in mitotic chromatin eluates. With sRB, 2D gels stained with SYPRO-Ruby or immunoblotted with an anti-XCAP-E antibody produced only a smear, suggestive of poor solubilisation or focusing (Figure [5A,5B](#F5){ref-type="fig"}). The same sample was resolved into 7 distinct spots by oRB and acrylamide alkylation (Figure [5C,5D](#F5){ref-type="fig"}).
::: {#F5 .fig}
Figure 5
::: {.caption}
######
Effect of different rehydration buffers on quality of western blotting analysis of 2D gels. 25 μg of mitotic chromosomes eluates were separated on pH6-11 IPG strips using sRB (A, B) or oRB (C, D) as in Figure 4. 2D gels were stained with SYPRO Ruby (A, C) or immunoblotted using anti-XCAP-E antibody (B, D). The protein spots seen on the top right of (A) were not reproducible and were perhaps due to poor alkylation. The spot pattern observed in (C) was reproducible.
:::
:::
Phosphorylation is one of the post-transcriptional modifications that can change the pI of proteins. Previous analysis has not detected significant phosphorylation in XCAP-E and treatment of these samples with phosphatase produced no change in the 2DE pattern (data not shown). We are currently exploring the nature of this apparently specific modification. Regardless, an optimised 2DE methodology can reveal multiple forms of proteins, even relatively large ones that are traditionally poorly resolved.
The 6 mini chromosome maintenance proteins MCM2-7, which are a central component of the replication licensing system, are bound to *Xenopus*chromatin from the end of mitosis and are released during S-phase \[[@B22],[@B23]\]. The six proteins (M.W. \~90--105 kDa) were identified by 2DE from replicating chromatin eluates using immunoblotting analysis and MALDI-TOF (data not shown). Figure [6](#F6){ref-type="fig"} shows 2DE images of MCM2, 3,4,6 and 7 eluted from replicating *Xenopus*chromatin at the beginning of S-phase in a control experiment (Figure [6A](#F6){ref-type="fig"}) and in extract treated with geminin, which prevents loading of MCM2-7 onto chromatin (Figure [6B](#F6){ref-type="fig"}) \[[@B24]-[@B26]\]. The treatment of chromatin eluates with λ-phosphatase changed the distribution of spots corresponding to MCM2, 3 and 4 whereas MCM6 and MCM7 spots remained mostly unchanged (Figure [6C](#F6){ref-type="fig"}). With the improved resolution of 2DE provided by oRB and sample treatment, the analysis of post-translational modifications of relatively large proteins is now possible.
::: {#F6 .fig}
Figure 6
::: {.caption}
######
Cell cycle dependent association of replication licensing complex with chromatin. Proteins eluted from chromatin assembled for 30 min in *Xenopus*egg extracts were separated on pH 3--10 2D gels and stained with SYPRO Ruby. In control assembly reaction MCM2,3,4,6 and 7, were detectable in eluates as multiple spot chains (A). In the presence of geminin, association of MCMs with chromatin was prevented (B). The treatment of control chromatin eluates with λ-phosphatase changes the MCMs presentation in the 2D gel (C).
:::
:::
Discussion
==========
In this study we successfully applied a modified Taguchi strategy \[[@B9]\] to optimise conditions for 2DE. An optimal formulation of the rehydration buffer used to dissolve proteins and run IPG strips in the first dimension was determined using the Taguchi experimental design based on an orthogonal L9 array (Table [1](#T1){ref-type="table"}).
We observed that the resolution of proteins over 100 kDa depended heavily on the composition of the RB and were able to define a recipe that provides significantly improved 2DE performance for many different samples.
Our data demonstrated that the combination of different detergents in the rehydration solution improved the solubility and resolution of proteins on 2D gels, though their optimal concentrations in the mix may be very different from the ones published for mono-detergent solutions. In addition, we found that the concentration of ampholytes has the biggest effect on *SNR*variation and that the minimal values of 0.25% produced the highest *SNR*. However, different regions of the 2D gel responded differently, with proteins \<30 kDa becoming less well resolved at low ampholyte concentrations. While further reduction of ampholyte concentration in RB may be beneficial for the resolution of high molecular weight proteins, this should be performed only when resolution of low molecular weight proteins is not necessary. Our results therefore suggest a method of significantly improving 2DE performance, although we cannot specify a single, universally applicable electrophoresis protocol.
To verify the applicability of our oRB for different protein samples we applied standard and optimal conditions for the separation of protein fractions which were eluted from chromosomes reconstituted in *Xenopus*egg extracts \[[@B27],[@B28]\], whole *Xenopus*egg extract, human nucleoli and mouse and shrimp mitochondria. The amount of protein generated in these experiments is limited and complete solubilisation of the samples is an important issue for 2DE and MS analysis. Use of our oRB has improved the resolution and detection of 2DE and increased the amount of protein we can provide for MS. To date, we have not observed any dependence of the composition of RB on the source of protein. Within our lab, where we use one type of gel and one gel analysis system, we now have a standard composition for RB that appears to work with all samples.
Our optimised composition of RB is determined by scoring the number of spots observed employing specific commercial IPG gel strips, pre-cast SDS-PAGE gels, and commercially available 2DE analysis software. It is likely that the optimal composition of RB depends on each of these parameters. For instance, a different 2DE spot finding algorithm might find a slightly different set of spots, especially in the extreme regions of the gel, and thus change the optimal composition of RB determined by the Taguchi method. Moreover, spot number does not reflect other spot characteristics, such as intensity, circularity, etc. The use of a single parameter for the performance evaluation is a basic tenet of the Taguchi approach and the choice of it defines the result of an optimisation experiment. We therefore used a single performance criterion as the prime determinant for oRB, and incorporated other characteristics to refine our choice of oRB constituents.
Therefore our most important findings are: (1) combinations of zwitterionic detergents, appropriately optimised, can provide improved solubilisation of proteins for 2DE; (2) the concentration of carrier ampholytes must be optimised; (3) the use of a technique like the Taguchi method can rapidly and relatively easily determine an optimal combination of RB components for 2DE. Whereas systematic evaluation of all possible combinations in a multi-component system is prohibitively costing and time consuming, the Taguchi method provides a systematic assessment of a systems behaviour that is reasonably straightforward to perform.
Our results also extend the power of 2DE in the analysis of post-translational modifications. For subsequent MS identification of proteins and characterisation of post-translational modifications, difficulties with differential solubility and focussing must be resolved. The oRB addressed these issues and substantially improved the resolution of protein isoforms, including those larger than 100 kDa.
Conclusions
===========
We have successfully applied the Taguchi method to optimise the complex composition of a rehydration buffer used in 2DE. The strategy greatly reduced the number of experiments required compared to classical designs, reduced cost, and has produced a substantially improved 2DE RB.
Materials and methods
=====================
Chemicals and equipment
-----------------------
Immobiline DryStrip 7 cm gels and carrier ampholytes of different pH ranges were purchased from Amersham Pharmacia Biotech UK Ltd. The Protean IEF cell from BioRad (Bio-Rad Laboratory Ltd., Hemel Hempsted, UK) was used to run the isoelectric focusing separation. For the second dimension, the focused IPG strips were loaded on precast Novex ZOOM gels (Invitrogen, Ltd, Paisley, UK) and run with NuPage MOPS SDS buffer as instructed by the manufacturer.
The zwitterionic detergent ASB14 was obtained from Calbiochem (Merck Biosciences, Ltd., Nottingham UK). Urea of AristaR grade and other general chemicals of AnalaR grade were purchased from BDH (Merck House, Poole, Dorset, UK). SYPRO Ruby (Molecular Probes, Leiden, The Netherlands) was used to stain 1D and 2D gels according to manufacture recommendations. The images of stained gels were acquired by a Fujiimager LAS1000 using the Dark Reader trans-illuminator (Clare Chemical Research, Inc., Dolores, USA). Spot detection, matching, quantification and analysis were carried out using Phoretix 2D Pro software (Nonlinear Dynamics Ltd, Newcastle, UK). The antibody against XCAP-E (R5-5) was kindly supplied by T. Hirano \[[@B21],[@B29]\].
Sample preparations
-------------------
*Xenopus*egg extract preparation, chromatin reconstitution, and elution of chromosomal proteins was carried out as previously described \[[@B27],[@B28],[@B20]\]. For IEF, methanol/chloroform precipitated samples containing 50 μg protein (or as otherwise stated) were solubilised either in the standard rehydration buffer (sRB: 8 M urea/4% CHAPS/0.5% ampholytes/20 mM DTT) or RBs prepared according to the Taguchi orthogonal array (Table [1](#T1){ref-type="table"}). The composition of optimised rehydration solution was as follows: 7 M urea/2 M thiourea/1.2% CHAPS/0.4%ASB14/0.25% ampholytes/43 mM DTT/30 mM Tris base). Solubilisation was carried out on a vibra-shaker for 2 hours at room temperature. To alkylate proteins before IEF, freshly prepared 9 M acrylamide in water was added to each sample to a final concentration of 60 mM and incubation continued for another 1.5 hours at room temperature. At the end of the incubation, samples were spun for 10 min at 16000 × *g*in a micro-centrifuge and transferred to rehydration chambers. The dry IPG strips were allowed to re-swell in RBs over night before IEF separation. For samples that were prepared in sRB solubilisation was continued for 2 hours without alkylation before starting the IPG re-swelling.
Electrophoresis and spot detection
----------------------------------
Isoelectric focusing was performed using a two phase protocol: (1) 250 V for 30 min and (2) 250 -- 5500 V fast ramping voltage gradient to accumulate 33000 total volt-hours. The focused IPG strips were subjected to additional reduction and alkylation treatment before the second dimension SDS-PAGE. The strips were equilibrated for 20 min in 25 mM DTT dissolved in 6 M Urea/2% SDS/30% glycerol/50 mM Tris HCl pH8.8 and then alkylated by incubating with 360 mM acrylamide for 20 min in the same buffer. Equilibrated IPG strips were applied to precast Novex 4--12% Zoom gels and run at room temperature for 1 hour at 200 V. SYPRO Ruby stained gels were imaged and the total number of spots in individual gels was determined by Phoretix 2D Pro imaging software. The resulting data were visually inspected to remove background artefacts. The number of spots identified in each individual gel was used in the Taguchi calculations.
Taguchi experimental design
---------------------------
In the Taguchi method, variables under optimisation are arranged into orthogonal array (Table [1](#T1){ref-type="table"}, L9 orthogonal array for the representative experiment). With 2DE, each column would correspond to individual buffer components, and each row would represent individual IEF rehydration buffer. Each component is taken at three defined concentration (A, B and C), covering the range where its effect can be determined. The number of spots detectable in 2D gels prepared with individual RB compositions (the yield of trials) is used to evaluate the effect of the components. This is done by calculating Taguchi\'s signal to noise ratios (*SNR*) for each component. The goal with 2DE is to maximise the numbers of detectable spots. For this aim G. Taguchi designed the following *SNR*function:
where *SNR*is signal to noise ratio, *n*is a number of trials with given concentration and *Y*~*i*~is the yield in correspondent trials \[[@B9],[@B30]\]. To calculate the *SNR*for 1% CHAPS, for example, we used total spot numbers in gels 2, 5 and 8 (*n*= 3), where CHAPS was present at 1% level (Table [1](#T1){ref-type="table"}). A second order polynomial fit was employed to calculate the concentration corresponding to the maximum of *SNR*if it was present on a graph.
Mass spectrometry
-----------------
The spots of interest were excised from 2D gels and were subjected to MALDI-TOF or LC/MS-MS analysis in the Post-Genomics and Molecular interactions Centre of University of Dundee.
List of abbreviations
=====================
RB -- rehydration buffer, sRB -- standard rehydration buffer, oRB -- optimised rehydration buffer, *SNR*-- signal to noise ratio, TBP -- tributylphosphine, TCEP -- tris(2-carboxyethyl)phosphine hydrochloride, DTT -- dithiothreitol, IAA -- iodoacetamide, IPG -- immobilised pH gradient, MCM -- mini-chromosome maintenance proteins, PTM -- post-translational modifications.
Competing interests
===================
None declared.
Authors\' contributions
=======================
GAK designed and carried out optimisation experiments, 2DE analysis of *Xenopus*licensing complex and human nucleolar proteins and drafted the manuscript. IMP carried out 2DE analysis of *Xenopus*condensin complex and mitochondrial extracts from mouse and shrimp cells. JJB participated in the design of the study and coordination. JRS conceived of the study, and participated in its design and coordination. All authors read and approved the final manuscript.
Supplementary Material
======================
::: {.caption}
###### Additional File 1
2DE response to variations of ASB14 and ampholytes concentrations. 50 μg aliquots of total *Xenopus*egg extract were dissolved in RBs containing 7 M urea, 2 M thiourea, 1.2% CHAPS, 43 DTT and variable amount of ASB14 and ampholytes as indicated on each picture. Spots detected: (A) 682, (B) 227, (C) 662, (D) 640.
:::
::: {.caption}
######
Click here for file
:::
Acknowledgements
================
The authors thank T. Hirano for the anti-XCAP-E antibody and members of the Swedlow and Blow laboratories for helpful discussions and criticism of this work. This work was supported by Cancer Research UK grants C303/A2666 and C303/A3135. MS data were obtained in The Post-Genomics and Molecular Interactions Centre, University of Dundee, funded by Wellcome Trust grant 60269. J. R. Swedlow is a Wellcome Trust Senior Research Fellow.
|
PubMed Central
|
2024-06-05T03:55:47.883518
|
2004-9-9
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517948/",
"journal": "Proteome Sci. 2004 Sep 9; 2:6",
"authors": [
{
"first": "Guennadi A",
"last": "Khoudoli"
},
{
"first": "Iain M",
"last": "Porter"
},
{
"first": "J Julian",
"last": "Blow"
},
{
"first": "Jason R",
"last": "Swedlow"
}
]
}
|
PMC517949
|
Background
==========
Dry eye is a common disorder of the ocular surface and tear film and is estimated to affect from 2% to over 15% of persons in surveyed populations, depending on the definition used \[[@B1]-[@B6]\]. Symptoms of dry eye are a major reason to seek ophthalmic care: a study by Nelson and co-workers found that 1.3% of Medicare patients had a primary diagnosis of keratoconjunctivitis sicca or dry eye \[[@B7]\]. Dry eye can range from mild to severe disease; although the majority of patients with dry eye experience ocular discomfort without serious vision-threatening sequelae, severe dry eye can compromise corneal integrity by causing epithelial defects, stromal infiltration, and ulceration, and can result in visually significant scarring \[[@B8]\]. Moderate to severe dry eye disease can adversely affect performance of visually demanding tasks due to pain and impaired vision \[[@B9]\]. In addition, corneal surface irregularity due to epithelial desiccation, quantified by using corneal topography, can decrease visual acuity \[[@B10]\].
Patient-reported measurements used to evaluate the specific impact of eye disease and vision on symptoms (discomfort), functioning (the ability to carry out activities in daily life), and perceptions (concern about one\'s health) are referred to as vision-targeted health-related quality of life (VT-HRQ) instruments. Valid and reliable measurements of VT-HRQ have become essential to the assessment of disease status and treatment effectiveness in ocular disease \[[@B11]\]. There are two general categories of VT-HRQ instruments: generic, which are designed to be used for a broad spectrum of visual disorders and ocular disease; and disease-specific, which are tailored toward particular aspects of a specific ocular disorder. In general, disease-specific instruments tend to be more sensitive than generic ones in detecting VT-HRQ impairments \[[@B12]\]; however, generic instruments allow comparisons across more diverse populations and diseases \[[@B13]\]. In addition, generic instruments may be able to capture additional aspects of systemic disease, related to the ocular disorder in question, providing a broader characterization of health-related quality of life \[[@B14],[@B15]\]. There is therefore no clear-cut basis in a given study or population for choosing a generic versus a disease-specific measure: if possible, both should be utilized to determine whether one or the other is more consistent with clinical indicators, or if one appears to obtain additional, relevant information on patient status \[[@B16]\]. However, it may be the case that weak-to-moderate associations between clinical indicators and quality-of-life measures indicates that the VT-HRQ measure is capturing elements of disease above and beyond those that can be measured clinically (for example, visual acuity may be good but a patient may have problems with functioning related to problems with contrast sensitivity or glare disability). Again, depending on the characterization of the disease desired and the goal of the study, a researcher might choose an instrument that either is or is not strongly correlated with clinical signs.
The measurement of the impact of dry eye on a patient\'s daily life, particularly symptoms of discomfort, is a critical aspect of characterizing the disease \[[@B17]\]. Despite the fact that most studies have found weak or no correlations between symptoms and signs of dry eye \[[@B18]-[@B20]\], symptoms are often the motivation for seeking eye care and are therefore a critical outcome measure when assessing treatment effect \[[@B7]\], and hence are increasingly used as a surrogate for ocular surface disease in many epidemiologic studies. Indeed, recent studies have focused on developing more robust ways of measuring patient-reported symptoms of dry eye \[[@B21]-[@B23]\]. The Ocular Surface Disease Index (OSDI)^©^\[[@B24]\] was developed to quantify the specific impact of dry eye on VT-HRQ.
Sjögren\'s Syndrome is an autoimmune systemic disease characterized by dry mouth and dry eye signs and symptoms \[[@B25],[@B26]\]. Its manifestations include fatigue, arthritis, neuropathy, and pulmonary and renal disease. Histopathologic evidence of salivary gland inflammation and the presence of serum autoantibodies SSA or SSB are important diagnostic features of the disease \[[@B27]\]. Sjögren\'s Syndrome has been stated to be the second most common autoimmune disease, ranking between rheumatoid arthritis and systemic lupus erythematosus \[[@B27]\]. In the U.S., it is estimated that between 1 and 4 million persons (approximately 1--2 in 200) have Sjögren\'s Syndrome \[[@B28]\]. Prevalence estimates for other countries range from 0.3 to 4.8% \[[@B29]\]. Female gender and older age are known risk factors for Sjögren\'s syndrome \[[@B30]\]. A wide range of studies have assessed the ocular manifestations of Sjögren\'s syndrome \[[@B31]-[@B33]\]; however, assessment of symptoms and quality of life have been limited and, in most cases, generic measures of well-being, psychological distress, and fatigue without ocular dimensions have been employed \[[@B34]-[@B40]\]. Further, while there are many published studies of VT-HRQ in mild to moderate dry eye, there are few publications on VT-HRQ in Sjögren\'s syndrome, which is characterized by dry eye causing significant ocular irritation as well as systemic disease factors that could have their own additional significant impact on VT-HRQ.
Our purpose in this study was to examine VT-HRQ in patients with primary Sjögren\'s syndrome, using a generic and a dry-eye-disease-specific instrument. We examined the associations of ocular surface parameters with the VT-HRQ scores, hypothesizing that the disease-specific instrument would be more closely related than the generic to the clinical markers of disease. We also examined the association of the generic and disease-specific VT-HRQ scores with each other.
Methods
=======
The study protocol was approved by the National Eye Institute Internal Review Board. All patients completed an informed consent prior to examination. Consecutive patients with diagnosed primary Sjögren\'s syndrome were recruited from the NIH Clinical Center, Bethesda, MD. The diagnosis of primary Sjögren\'s syndrome was based on European-American criteria, which requires at least four of the following six features: signs and symptoms of dry eye and of dry mouth, histopathologic evidence of inflammation on minor salivary gland biopsy, and positive anti-Ro or anti-La antibodies.
Before the clinical examination, a trained interviewer administered two questionnaires (described further below) to measure VT-HRQ to each patient. The subsequent clinical examination included a comprehensive anterior segment evaluation, including slit lamp biomicroscopy, evaluation of lid margin thickness and hyperemia, conjunctival erythema, chemosis, tear film debris and mucus, and extent of meibomian gland plugging. Tests of tear function and ocular surface status were performed as described below.
The OSDI \[[@B24]\] (provided by Allergan, Inc. Irvine, CA) was used to quantify the specific impact of dry eye on VT-HRQ. This disease-specific questionnaire includes three subscales: ocular discomfort (OSDI-symptoms), which includes symptoms such as gritty or painful eyes; functioning (OSDI-function), which measures limitation in performance of common activities such as reading and working on a computer; and environmental triggers (OSDI-triggers), which measures the impact of environmental triggers, such as wind or drafts, on dry eye symptoms. The questions are asked with reference to a one-week recall period. Possible responses refer to the frequency of the disturbance: none of the time, some of the time, half of the time, most of the time, or all of the time. Responses to the OSDI were scored using the methods described by the authors \[[@B24]\]. Subscale scores were computed for OSDI-symptoms, OSDI-function, and OSDI-triggers, as well as an overall averaged score. OSDI subscale scores can range from 0 to 100, with higher scores indicating more problems or symptoms. However, we subtracted the OSDI overall and subscale scores from 100, so that lower scores would indicate more problems or symptoms.
The 25-item NEI Visual Function Questionnaire (NEI-VFQ) \[[@B41],[@B42]\] is a non-disease-specific (i.e., \"generic\") instrument designed to measure the impact of ocular disorders on VT-HRQ. Depending on the item, responses to the NEI-VFQ pertain to either frequency or severity of a symptom or functioning problem. A recall period is not specified in the questionnaire. Responses to the NEI-VFQ were scored using the methods described by the authors \[[@B43]\]. Subscale scores for general vision, ocular pain, near vision, distance vision, social functioning, mental functioning, role functioning, dependency, driving, color vision, and peripheral vision, as well as an overall score, were computed. The NEI-VFQ scores can range from 0--100, with lower scores indicating more problems or symptoms.
Schirmer tests of tear production without and with anesthesia were performed by inserting a Schirmer tear test sterile strip (35 mm, Alcon Laboratories, Inc, Fort Worth, TX) into the inferior fornix, at the junction of the middle and lateral third of the lower eyelid margin, for 5 minutes with the eyes closed. The extent of wetting was measured by referring to the ruler provided by the manufacturer on the envelope containing the strips. Possible scores range from 0 to 35 mm, with lower scores indicating greater abnormality in tear production. This test was repeated after instillation of topical anesthetic, 0.5% proparacaine \[[@B44]\]. A Schirmer without anesthesia score of ≤ 5 mm in at least one eye is one required element of dry eye, as defined by the European-American Sjögren\'s syndrome diagnostic criteria \[[@B45]\].
The assessment of ocular surface damage was performed by a cornea specialist using vital dye staining with 2% unpreserved sodium fluorescein and then 5% lissamine green dye. The corneal, temporal, and nasal regions of the conjunctiva were scored individually from 0--5 (for fluorescein) and 0--5 (for lissamine green) using the Oxford grading scheme \[[@B46]\]. The Oxford score was derived by adding the scores for corneal fluorescein and nasal plus temporal conjunctival lissamine green staining. Total Oxford score could range from 0--15. The van Bijsterveld score \[[@B47]\] (VB) was assessed using lissamine green staining of the cornea (0--3) and conjunctiva (0--3). Total VB score could range from 0--9. For all staining tests, higher scores indicate worse ocular surface damage.
Tear film stability was assessed using fluorescein tear film breakup time (TBUT). Five microliters of 2% sodium fluorescein was instilled into the inferior fornix and the patient was asked to blink several times. Using the cobalt blue filter and slit lamp biomicroscopy, the duration of time required for the first area of tear film breakup after a complete blink was determined. If the TBUT was less than 10 seconds, the test was repeated for a total of 3 values and the average was calculated.
For analysis, for each individual, the maximum (worse) score for the two eyes was used for Oxford score and VB, and the minimum (worse) score for the two eyes was used for Schirmer with and without anesthesia and for TBUT. TBUT values greater than or equal to 10 seconds \[[@B48]\] were coded as 10 (normal) and \< 10 seconds was defined as abnormal. Schirmer without anesthesia score result of ≤ 5 mm or VB ≥ 4 were used as objective evidence of dry eye, following the European / American criteria for the diagnosis of dry eye for Sjogren\'s syndrome \[[@B49]\].
Hypotheses of specific associations were formulated based on the areas and domains assessed by the two VT-HRQ instruments. Scatterplots and Spearman\'s correlation coefficient (ρ) \[[@B50]\] were used to examine associations between pairs of variables. Multiple linear regression \[[@B51]\] was used to assess the strength of association between pairs of variables while adjusting for confounders (e.g., age).
Results
=======
Characteristics of participants
-------------------------------
A total of 42 patients, 40 female and 2 male, were included in this study. The average age was 55 years (range, 31--81 y). Most (81%) were of European descent. Visual acuity in the better eye was 20/20 or better for 68% of the patients; the remainder had 20/25 or better in the better eye, except for one patient who was 20/32 in both eyes. Ocular examination (Table [1](#T1){ref-type="table"}) showed that, on average, the participants suffered from moderate to severe dry eye: mean Oxford score was 7.2, mean VB score was 5.3. Average Schirmer without anesthesia score was 4.8 mm, with nearly all (79%) having scores less than 10 mm and the majority (59%) having scores less than 5 mm. Mean TBUT was 2.9 seconds, with nearly all (87%) having scores less than 5 seconds.
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Characteristics of participants (n = 42)
:::
Mean, sd \[range\] N (%)
------------------------------------ ------------------------ ----------
Age (y) 54.9 (12.7) \[31--81\]
Ethnicity
European-derived 34 (81%)
African-derived 3 (7%)
Other 5 (12%)
Gender
Female 40 (95%)
Male 2 (5%)
Visual acuity\*
20/20 + OU 18 (44%)
20/20+, better eye 10 (24%)
20/25+, better eye 12 (29%)
\<20/25, better eye 1 (2%)
Vital dye staining
Oxford score 7.2 (3.4) \[1--14\] \--
5+ \-- 34 (81%)
Van Bijsterveld score\*\* 5.3 (2.7) \[0--9\] \--
4+ \-- 28 (74%)
Tear production
Tear film break-up time (s)\*\* 2.9 (1.7) \[1--8\] \--
\< 5 sec \-- 33 (87%)
Schirmer without anesthesia (mm) 4.9 (5.4) \[0--20\] \--
0--5 \-- 25 (60%)
5-\<10 \-- 8 (19%)
10+ \-- 9 (21%)
Meibomian gland disease\*\*
None \-- 10 (26%)
1 \-- 8 (21%)
2+ \-- 20 (53%)
European-American dry eye criteria \-- 37 (90%)
\*One person had missing visual acuity information; \*\*Four persons had missing information for some components of the clinical examination
:::
Association of OSDI^©^with ocular surface parameters
----------------------------------------------------
OSDI scores (all subtracted from 100) indicated moderate problems with symptoms, functioning, and adverse environmental conditions. Mean OSDI-symptoms score was 62.5, mean OSDI-function score was 78.2, and mean OSDI-triggers score was 60.2. However, some patients had no problems with these areas: 12% reported no problems with irritation symptoms, 21% reported no problems with functioning, and 24% had no problems with environmental triggers. Associations of the OSDI subscale and overall scores with ocular surface parameters (Oxford score, VB, TBUT, and Schirmer score with and without anesthesia) are shown in [2](#T2){ref-type="table"}. In general, no substantive associations were found, except for visual functioning with TBUT (r = 0.22), and none of the observed associations reached statistical significance. Median scores on OSDI were compared between normal/abnormal categories of ocular surface variables (Schirmer without anesthesia score \< 5, 5-\<10, versus 10+; TFB \< 5 versus \> = 5; VB \< 4 versus 4+, Oxford score \< 5 versus 5+; European-American criteria, yes versus no). Considerable overlap in the distributions between categories was observed for all subscales, with no significant differences in median values (data not shown).
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Association of OSDI (scores subtracted from 100) with ocular surface parameters (Spearman ρ)
:::
**Oxford score** **van Bijsterveld score** **Tear film breakup time** **Schirmer without anesthesia score** **Schirmer with anesthesia score**
------------------------ -------------------- ------------------ --------------------------- ---------------------------- --------------------------------------- ------------------------------------
**OSDI** Mean (sd); % floor
Symptoms 62.5 (25.7); 12% 0.02 0.16 -0.10 -0.04 0.02
Visual function 78.2 (21.4); 21% 0.15 0.17 0.22 0.12 0.05
Environmental triggers 60.2 (34.3); 24% -0.01 0.13 -0.02 0.04 0.12
Overall 70.0 (20.2); 10% 0.07 0.19 0.06 0.04 0.08
:::
Association of NEI-VFQ with ocular surface parameters
-----------------------------------------------------
Overall, scores on the NEI-VFQ subscales tended to be high. Average scores for near and distance vision, social and mental functioning, dependency, driving, and peripheral vision were over 80, and a substantial percentage reported no problems at all with any of the items on the subscale: 26% for near vision, 24% for distance vision, 83% for social functioning, 17% for mental functioning, 74% for dependency, 38% for driving, and 79% for peripheral vision. The subscale indicating the most impairment was the ocular pain subscale, with a mean score of 66.7. Associations of the NEI-VFQ subscale and overall scores with ocular surface parameters (Oxford score, VB, TBUT, and Schirmer score with and without anesthesia) are shown in Table [3](#T3){ref-type="table"}. Overall, associations were weak to moderate, and none attained statistical significance. General vision showed moderate correlations with Oxford score, VB, and TBUT scores (r values from 0.20--0.27). Ocular pain showed a moderate correlation with TBUT (r = 0.23) and Schirmer with anesthesia score (r = 0.22). Near vision was associated with VB (r = .20) and to a greater extent with TBUT (r = 0.32). Distance vision showed moderate associations with Oxford score, TBUT, and Schirmer with anesthesia score (r values from 0.21 -- 0.26) and a stronger association with VB (r = 0.33). Social functioning was moderately associated with VB (r = .24). Role functioning was associated with Schirmer scores both with and without anesthesia, more strongly so with Schirmer with anesthesia score (r = 0.31). Dependency was associated with TBUT (r = .29) and Schirmer with anesthesia score (r = .21). An anomalous finding was that peripheral vision showed moderate association with VB score (r = .29). Mental functioning and driving showed no associations with any of the ocular surface parameters. Median scores on NEI-VFQ scales were compared between normal/abnormal categories of ocular surface variables (Schirmer without anesthesia score \< 5, versus 10+; TFB \< 5 versus \> = 5; VB \< 4 versus 4+, Oxford score \< 5 versus 5+; European-American criteria, yes versus no). Considerable overlap in the distributions between categories was observed for all subscales, with no significant differences in median values (data not shown), with the exception of the European-American criteria, where, counterintuitively, scores were higher (better) for near vision for those with dry eye (45.8) than for those without (83.7; p = .03). However, only 4 patients were in the \"no dry eye\" category, so this result may be the consequence of unstable small sample size.
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Association of NEI-VFQ with ocular surface parameters (Spearman ρ)
:::
**Oxford score** **van Bijsterveld score** **Tear film breakup time** **Schirmer without anesthesia score** **Schirmer with anesthesia score**
------------------- -------------------- ------------------ --------------------------- ---------------------------- --------------------------------------- ------------------------------------
**NEI-VFQ** Mean (sd); % floor
General vision 78.6 (12.8); 14% 0.22 0.20 0.27 -0.04 0.08
Ocular pain 66.7 (22.2); 12% 0.06 0.06 0.23 -0.06 0.22
Near vision 80.4 (19.4); 26% 0.18 0.20 0.32 -0.02 0.16
Distance vision 80.2 (18.4); 24% 0.25 0.33 0.26 -0.04 0.21
Social function 96.1 (11.2); 83% 0.14 0.24 0.15 -0.07 -0.09
Mental function 83.1 (17.5); 17% 0.15 0.18 0.19 -0.10 0.17
Role function 73.2 (25.4); 29% 0.07 -0.02 0.16 0.22 0.31
Dependency 94.4 (10.5); 74% -0.09 -0.04 0.29 0.03 0.21
Driving 84.9 (15.5); 38% -0.02 0.04 0.19 -0.07 -0.06
Peripheral vision 91.7 (19.6); 79% 0.11 0.29 0.15 -0.15 -0.13
Overall 83.6 (12.8); 2% 0.19 0.20 0.24 -0.04 0.19
:::
Association of OSDI^©^with NEI-VFQ subscales
--------------------------------------------
In general, stronger associations were observed between subscales of the OSDI and NEI-VFQ (Table [4](#T4){ref-type="table"}) than between ocular surface parameters and either the OSDI or the NEI-VFQ. Because of the large number of potential comparisons, we restrict discussion to associations that were hypothesized based on clinical plausibility. To test whether the overall (i.e., combined) OSDI and NEI-VFQ scales were related, we examined their linear relationship (Figure [1](#F1){ref-type="fig"}). Indeed, the association of these scales was strong (r = 0.61) and remained statistically significant after age adjustment. We hypothesized that the OSDI-symptoms subscale and the NEI-VFQ ocular pain subscale should show strong association, and in fact this was observed (r = 0.60, p \< .001 after adjustment for age). A scatterplot of the data is shown in Figure [2](#F2){ref-type="fig"}. We also hypothesized that the OSDI-triggers measure should be associated with the NEI-VFQ ocular pain subscale. This association was moderate (r = 0.46, Figure [3](#F3){ref-type="fig"}) and did not remain statistically significant after age adjustment. The OSDI-function subscale measures a domain that has theoretical overlap with the NEI-VFQ subscales for general, near, and distance vision, as well as driving, so we hypothesized that these correlations should also be relatively strong. This was true in particular for general vision (r = 0.60, Figure [4](#F4){ref-type="fig"}) and driving (r = 0.57, Figure [7](#F7){ref-type="fig"}), both of which remained highly statistically significant after adjustment for age (p \< .001). The correlations of OSDI-function with NEI-VFQ near and distance vision were not as strong (0.45, Figures [5](#F5){ref-type="fig"} and [6](#F6){ref-type="fig"}) and were not statistically significant after adjusting for age.
::: {#T4 .table-wrap}
Table 4
::: {.caption}
######
Associations of OSDI^©^subscales (subtracted from 100) with NEI-VFQ subscales (Spearman ρ).
:::
**OSDI**Symptoms **OSDI**Visual function **OSDI**Environmental triggers **OSDI**Overall
------------------- ------------------ ------------------------- -------------------------------- -----------------
**NEI-VFQ**
General vision 0.34 0.60\*† 0.28 0.51\*
Ocular pain 0.60\*† 0.50\* 0.46† 0.62\*
Near vision 0.08 0.46† 0.23 0.33
Distance vision 0.37 0.45† 0.27 0.46
Social function 0.16 0.26 0.17 0.22
Mental function 0.45\* 0.61\* 0.20 0.53\*
Role function 0.19 0.64\* 0.33 0.48\*
Dependency 0.17 0.42\* 0.17 0.33
Driving 0.28 0.57\*† 0.33 0.48\*
Peripheral vision 0.18 0.02 0.04 0.14
Overall 0.43 0.67\* 0.37 0.61\*†
†Associations hypothesized at the start of the study; \*statistically significant after age adjustment (p \< 0.001)
:::
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Association between OSDI (scores subtracted from 100) and NEI-VFQ overall scales. Spearman ρ: 0.61\*.
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Association between OSDI ocular discomfort subscale (scores subtracted from 100) and NEI-VFQ ocular pain subscale. Spearman ρ: 0.60\*
:::
:::
::: {#F3 .fig}
Figure 3
::: {.caption}
######
Association between OSDI environmental triggers subscale (scores subtracted from 100) and NEI-VFQ ocular pain subscale. Spearman ρ: 0.46.
:::
:::
::: {#F4 .fig}
Figure 4
::: {.caption}
######
Association between OSDI visual function subscale (scores subtracted from 100) and NEI-VFQ general vision subscale. Spearman ρ: 0.61.
:::
:::
::: {#F7 .fig}
Figure 7
::: {.caption}
######
Association between OSDI visual function subscale (scores subtracted from 100) and NEI-VFQ driving subscale. Spearman ρ: 0.57.
:::
:::
::: {#F5 .fig}
Figure 5
::: {.caption}
######
Association between OSDI visual function subscale (scores subtracted from 100) and NEI-VFQ near vision subscale. Spearman ρ: 0.46.
:::
:::
::: {#F6 .fig}
Figure 6
::: {.caption}
######
Association between OSDI visual function subscale (scores subtracted from 100) and NEI-VFQ distance vision subscale. Spearman ρ: 0.45.
:::
:::
Table [4](#T4){ref-type="table"} shows that, in fact, several other significant associations not conjectured in our original hypotheses were observed. In particular, the OSDI-function subscale, in addition to the associations hypothesized above, showed substantial and statistically significant associations with ocular pain (r = 0.50), mental function (r = 0.61), role function (r = 0.64), and dependency (r = 0.42). The OSDI-symptoms subscale showed a moderate and statistically significant association with NEI-VFQ mental health (r = 0.45). The overall OSDI scale showed significant associations with NEI-VFQ general vision (r = 0.51, ocular pain (r = 0.62), mental and role functioning (r = 0.53 and 0.48, respectively), and driving (r = 0.61).
Discussion
==========
We compared subscale scores for an ocular surface *disease-specific*instrument (OSDI) with a *generic*VT-HRQ instrument (NEI-VFQ-25) in patients with a systemic autoimmune disease associated with moderate to severe dry eye. We found that patients with primary Sjögren\'s syndrome had OSDI scores (mean, 30, before subtraction from 100) similar to those previously published \[[@B24]\] for moderate to severe dry eye patients (mean score was 36 for severe cases). Despite the fact that all of our patients had Sjögren\'s syndrome, with moderate to severe dry eye, we found that correlations of ocular surface parameters with VT-HRQ (i.e., patient-reported) parameters tended to be weak or nonexistent, consistent with several other studies demonstrating poor correlations between signs and symptoms of dry eye \[[@B18]-[@B20]\]. Indeed, contrary to our expectations, NEI-VFQ correlations with objective ocular surface parameters tended to be higher than those of OSDI, although all were relatively modest (all \< 0.35) and none reached statistical significance.
One explanation could be that the nature of the items for each of these instruments is quite different. The OSDI queries the frequency of a symptom or difficulty with an activity, over a one week recall period. The NEI-VFQ incorporates questions both the frequency and intensity of symptoms and their impact on activities, with no specified recall period. Perhaps this added element of capturing both the frequency and intensity of a symptom or impact accounts for some of the differences we found. For subscales that are similar, agreement was higher but still moderate, possibly due to differences in the nature of the questions or response options. The OSDI is targeted to assess how much the symptoms of dry eye affect the patient\'s current status (i.e., in the past week), whereas the NEI-VFQ may be more suited to capturing the overall impact of a chronic ocular disease on VT-HRQ.
In this group of primary Sjögren\'s syndrome patients, associations between subscales of the NEI-VFQ and OSDI were moderate to strong (\< 0.70) and in hypothesized directions. Significant associations were seen between OSDI and NEI-VFQ overall scales; OSDI-symptoms and NEI-VFQ ocular pain; and OSDI-function and NEI-VFQ general vision and driving. This suggests that both instruments are capturing important aspects of VT-HRQ. It is not surprising that the highest correlations were observed between subscales with similar domains, which serves to validate the use of alternate methodologies. On the other hand, it is counter-intuitive that the generic and disease-specific instruments appeared similar (or that the generic seemed to do a little better) with respect to their association with objectively measured clinical signs of dry eye, as the NEI-VFQ was designed to capture broader aspects of VT-HRQ. For the NEI-VFQ, we found moderate correlations (greater than 0.3) of distance vision with VB and near vision with TBUT. This was surprising, as one may have expected that subscales measuring ocular discomfort or pain (i.e., more disease-specific for dry eye) would have the strongest correlations with clinical measures of dry eye. Clinical signs of dry eye include measures of tear production, ocular surface staining, and tear film break-up; visual acuity and other aspects of visual function are not generally as widely used. However, some investigators have reported that visual acuity in dry eye patients is correlated with decreased spatial contrast sensitivity \[[@B52]\] and is functionally reduced with sustained eye opening due to increased surface irregularity which can be detected with corneal topography \[[@B53],[@B10]\], which could explain our finding of moderate associations of ocular surface measures with near and distance vision. It has been proposed \[[@B10]\] that \"subtle visual disturbance\" is an important reason for dry eye patients to seek care. Indeed, improvement in blurred vision symptoms was one of the most frequently reported benefits of topical cyclosporine treatment for dry eye in a large, multicenter clinical trial \[[@B54]\]. The impact of the quality of vision or functional visual acuity on VT-HRQ has not been a focus of studies of the subjective aspects of dry eye. Our data indicate that the impact of dry eye on VT-HRQ is only partially accounted for by ocular pain in patients with severe dry eye, such as in Sjogren\'s syndrome.
Would we expect the associations to be different in Sjögren\'s patients? Sjögren\'s syndrome is an autoimmune exocrinopathy and effects of its systemic nature and chronicity on dry eye may have been more readily captured by the NEI-VFQ\'s ability to measure both frequency and intensity of problems with VT-HRQ. In contrast, although the OSDI includes items to measure function, responses are limited to the frequency of problems. Because the type of dry eye in Sjögren\'s syndrome is more likely to be severe, and all patients in our study had Sjögren\'s-related dry eye, we speculated that somewhat stronger associations between signs and symptoms might be observed. On the other hand, ocular surface inflammation and decreased corneal sensation are features of severe dry eye which might alter a patient\'s perception of symptoms of ocular irritation and might be the cause of weaker correlations between signs and symptoms \[[@B48],[@B55]\]. Indeed, reduced corneal sensation could provide inadequate feedback through the ophthalmic nerve to the central nervous system, resulting in less efferent stimulation to the lacrimal gland with reduced tear production and promotion of a vicious cycle. In addition, meibomian gland dysfunction plays a key role in dry eye in Sjögren\'s syndrome \[[@B56]\]. Therefore, aqueous and evaporative tear deficiency may combine to produce a particularly diseased ocular surface.
Conclusions
===========
In addition to clinical signs, it is important to include assessments of VT-HRQ and visual function to fully characterize the impact of dry eye on health status. The correlation between signs and VT-HRQ are modest at best, indicating that VT-HRQ is capturing an additional component of disease that is not captured by the clinical assessment. This does not necessarily mean that the measures of VT-HRQ or the methods of detecting clinical signs are deficient, but rather that VT-HRQ is an additional element of the overall impact of this disease process on affected individuals. Furthermore, in diseases with systemic manifestations, such as Sjögren\'s syndrome, that may have an influence on quality of life independent of dry eye symptoms, appropriate tests of VT-HRQ are critical to completely characterize quality of life in these patients. It may also be valuable to explore possible differences in associations of clinical signs with VT-HRQ in patient populations with different manifestations or causes of dry eye.
List of abbreviations
=====================
VT-HRQ: Vision-targeted health-related quality of life; TBUT: Tearfilm breakup time; OSDI: Ocular Surface Disease Index; NEI-VFQ: National Eye Institute Visual Function Questionnaire; VB: van Bijsterveld
Authors\' contributions
=======================
SV helped to design the study and performed all analyses and took the lead in writing the manuscript. LG performed the patient interviews and assisted with data analyses. GFR provided advice on statistical methods and presentation of the results. JA conceived and helped to design the study and assisted with writing the manuscript.
Acknowledgments
===============
We thank Shirley Greishaber, RN, for her assistance with interviewing the participants, and the staff of the NIH Sjogren\'s Syndrome Clinic, including Rose Anne Leakan, RN, Vidya Sankar, DDS, and Stanley Pillemer, MD, for evaluating and referring participants to the study.
|
PubMed Central
|
2024-06-05T03:55:47.886224
|
2004-9-1
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517949/",
"journal": "Health Qual Life Outcomes. 2004 Sep 1; 2:44",
"authors": [
{
"first": "Susan",
"last": "Vitale"
},
{
"first": "Linda A",
"last": "Goodman"
},
{
"first": "George F",
"last": "Reed"
},
{
"first": "Janine A",
"last": "Smith"
}
]
}
|
PMC517950
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Background
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Carcinoma of prostate is the most common cancer in males in America, ranking as the second most common leading cause of cancer-related deaths, just after carcinoma of the lung. In addition, the incidence and mortality of carcinoma of prostate are increasing in China. Although surgery and radiation therapy remain the primary choice for localized stage of carcinoma of prostate, there is no effective treatment for patients who develop recurrences or those who have metastatic disease at the time of diagnosis. Therefore, there is an urgent need for new types of treatment.
Strategies that stimulate the ability of the immune system to recognize and destroy cancer cells via selective killing mechanisms have shown promise in the treatment of cancer. DNA vaccines offer several potential advantages for the immunotherapy of cancer. Proteins encoded by DNA vaccines are expressed in the cytoplasm and presented through the endogenous processing pathway associated with MHC Class I molecules, thereafter leading to the activation of CD8 + cytotoxic T lymphocytes (CTL) \[[@B1],[@B2]\], which act as effectors in the anti-tumor immune response. DNA vaccines are cost-effective since DNA is relatively simple to purify in a large quantities. Another intrinsic advantage consists in the presence in the plasmid itself of un-methylated CpG motifs (immunostimulatory sequences) that may act as a potent immunological adjuvant \[[@B3]\]. Thus, there is a good rationale for further development of DNA vaccines to immunize against antigens present on cancer cells.
Prostate specific membrane antigen (PSMA), a well-established prostate specific tumor associated antigen (TAA), is 100 kD type II transmembrane glucoprotein. It is predominantly expressed in the prostate gland, minimal levels of expression in brain tissue, jejunum and proximal kidney tubules \[[@B4],[@B5]\]. Its expression is significantly elevated in carcinoma of prostate, particularly in metastastic disease and recurrent disease after hormone therapy fails \[[@B6],[@B7]\]. These properties of PSMA propose it as an ideal target of anti-cancer vaccines.
A number of strategies are under evaluation to enhance the potency of DNA vaccines, some of which involves broad stimulation of the immune system using immunomodulatory agents. Synthetic CpG oligodeoxynucleotides have immunological effects similar to those seen with bacterial DNA and represent promising vaccine adjuvants, which promote T helper1 (Th1)-type immune responses \[[@B8]\]. Unmethylated CpG motifs are present at a much higher frequency in the genome of prokaryotes than eukaryotes. The release of unmethylated CpG DNA during an infection provides a \'danger signal\' to the innate immune system, triggering a protective immune response that improves the ability of the host to eliminate the pathogen \[[@B9]\]. CpG oligodeoxynucleotides up-taken by B cells and plasmacytoid dentritic cells (pDCs), which express Toll-like receptror 9 (TLR9) \[[@B10],[@B11]\] initiate an immune stimulatory cascade that culminates in the indirect maturation, differentiation and proliferation of T cells and natural killer (NK) cells\[[@B12],[@B13]\]. Together, these cells secrete cytokines and chemokines that create a pro-inflammatory (IL-1, IL-6, IL-18 and tumor necrosis factor-α) and Th1-polarized (interferon-γ, and IL-12) immune *milieu*\[[@B14]\], which further facilitates the development of antigen-specific CTLs \[[@B15]-[@B17]\]. These effects indicate that CpG oligodeoxynucleotides could act as vaccine adjuvant. The present study was designed to test the therapeutic efficacy of a PSMA-based DNA vaccine in a mouse model of tumor cell implants expressing PSMA. In addition, the adjuvant role of CpG oligodeoxynucleotides to augment the potency of the constructed DNA vaccine was tested.
Methods
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Mice and Cell lines
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C57BL/6 mice (H-2b) were bred and kept under pathogen-free conditions. Male mice were used at 12 to 16 weeks of age. All animal experiments were performed in an approved protocol and in accordance with recommendations for the proper care and use of laboratory animals.
The murine melanoma B16 cell was purchased from the Type Culture Collection of the Chinese Academy of Sciences and cultured in RPMI-1640 medium (Life Technologies, Gaithersburg, MD) supplemented with 10% (v/v) heat-inactivated fetal bovine serum (Hyclone, Logan, UT), penicillin G (100 U/ml), and streptomycin (100 μg/ml).
The COS-7 cell line was cultured in DMEM medium (Life Technologies) supplemented with 10% (v/v) heat-inactivated fetal bovine serum, sodium pyruvate (1 mM), penicillin (100 U/ml) and streptomycin (100 μg/ml).
Antibodies and reagents
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The monoclonal antibody 4A12 specific for an extra-cellular epitope of PSMA was previously described \[[@B18]\]. The β-actin-specific monoclonal antibody was purchased from Sigma Chemical Co (St. Louis, MO). FITC-labeled goat anti-mouse IgG was purchased from Santa Cruz Biotech (Santa Cruz, CA). Recombinant murine IL-2 was purchased from PeproTech (Rocky Hill, NJ). ConA and mitomycin C were purchased from Sigma Chemical Co.
CpG oligodeoxynucleotides 1826 chosen according to published data \[[@B19]-[@B21]\] had the following sequence TTCAT[GACGTT]{.underline}CCT[GACGTT]{.underline} (CpG motifs were shown underlined) with the backbone phosphorothioate stabilized. CpG oligodeoxynucleotides were synthesized by Sangon (Shanghai, China), reconstituted in sterile pyrogen-free water and diluted in phosphate buffered saline for in vivo injections.
Transient transfection of COS7 cells
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The eukaryotic expression plasmid pCDNA3.1-*PSMA*encoding full-length PSMA was constructed by cloning the BamH I /Xho I fragment of pBluescipt-*PSMA*as described previously \[[@B18]\] into the pCDNA3.1 vector (Invitrogen Corp, Carlsbad, CA) cut with identical endonuclease.
COS-7 cells were transfected with pCDNA3.1-*PSMA*or an empty (mock) vector by the mediation of liposome Tfx-20™ (Promega, Madison, WI) according to the manufacturer\'s instructions. Briefly, COS-7 cells were cultured in six-well tissue culture plates with a coverslip in each well and grown to 50--70% confluence. 1.5 μg plasmid DNA was mixed with 4.5 μl Tfx-20™ and diluted in 1000 μl serum-free DMEM medium before addition to cells. After 20 minutes of incubation, DNA-liposome complex was added to the cells and incubated for 6 hours at 5% CO2, 37°C. Complete DMEM medium containing 10% fetal bovine serum was added to the cells and incubated overnight, and then the medium was replaced with complete DMEM medium. After 2 days, the cells were fixed in cold acetone for 10 minutes at 4°C followed by extensive washing with phosphate buffered saline. The cells were incubated with anti-PSMA monoclonal antibody 4A12 for 1 hour at 37°C, subsequently incubated with FITC-labeled goat anti-mouse IgG (1:40) for 1 hour at 37°C. After thorough washing, the coverslips were mounted and observed with a fluorescence microscope.
Stable transfection of B16 melanoma cells with *PSMA*plasmid
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The B16 murine melanoma cells were transfected with 2 μg of pCDNA3.1-*PSMA*or empty vector by the mediation of 6 μl liposome Tfx-20™ as above. After 2 days of culture, the cells were reseeded into a 10 cm-dish and cultured for other 2 days, complete RPMI-1640 medium containing 1000 μg/ml G418 (Life Technologies) was added to the culture. After 20 days of selection, all non-transfected cells died and discrete clones were visible in transfected cells. These clones were expanded in the presence of 400 μg/ml G418, positive cells expressing PSMA were identified as follows.
Detection of *PSMA*mRNA by Reverse Transcriptase-PCR
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Total RNA was extracted from mock-transfected or transfected B16 cells using Trizol (Life Technologies) and dissolved in RNase free water. 2 μg of total RNA was transcribed into cDNA using AMV reverse transcriptase (Promega). Briefly, the total RNA was mixed with 1 μl oligo (dT) primers (0.1 μg/ μl), 4 μl RT Buffer (5×), 2 μl dNTPs (10 mM), 1 μl AMV reverse transcriptase and diethypyrocarbonate-treated water to a final volume of 20 μl. The cDNA synthesis was performed using the following PCR parameters: 37°C for 1 hour then 10 minutes at 95°C. Synthesized cDNA was used as template for PCR. The sequence of the primers used were 5\'- CGAGGAGGG ATGGTG TT-3\' (forward) and 5\'-TGTTGTGGCTGCTTGAG-3\' (reverse). PCR was carried out in a 10 μl aliquot containing 0.5 μl cDNA, 0.5 μl each primer (10 μM), 1 μl dNTPs (2 mM), 1 μl Taq buffer (10×), 0.8 μl MgCl~2~(25 mM), 1 unit of Taq. The PCR reaction conditions included 5 minutes of initial denaturation at 94°C followed by 30 cycles of 30 seconds at 94°C, 1 minute at 62°C, 1 minute at 72°C and 10 minutes of final extension at 72°C. The 358 bp fragment was resolved on 2% agarose gel. GAPDH was also detected as internal reference.
Detection of PSMA protein by Western Blot
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The transfected and mock-transfected B16 cells were harvested and lysed with lysis buffer (50 mM NaCl, 0.01 M Tris-Cl (pH8.0), 5 mM EDTA, 0.5% NP-40, 1 mM phenylmethylsulfonyl fluoride, 1 μg/mL aprotinin, 1 μg/mL leupeptin) for 30 min at 4°C, cell debris were removed by centrifugation. Cell lysates were heated at 100°C for 3 minutes, the samples were loaded on 6% SDS-PAGE for electrophoresis. After electrophoresis, the proteins were transferred to polyvinylidene difluoride membranes (Amersham Pharmacia Biotech, Piscataway, NJ) using semi-humid transferring system (Bio-Rad, Hercules, CA). The polyvinylidene difluoride membranes were blocked with Tris-buffered solution containing 5% (w/v) non-fat milk for 1 hour at room temperature. For detection of protein, the polyvinylidene difluoride membranes were probed with anti-PSMA monoclonal antibody 4A12 and monoclonal antibody to β-actin (1:50) respectively for 1 hour at room temperature then overnight at 4°C, after then the membranes were incubated with horse anti-mouse IgG-HRP conjugate (1:500, Vector, Burlingame, CA) for 1 hour at 37°C, ABC complex (1:500, Vector) for 1 hour at 37°C subsequently. The bands were visualized with 3,3\'-diaminobenzidine substrate solution (5 mg diaminobenzidine dissolved in 10 ml Tris-buffered solution, 10 μl 30% hydrogen peroxide).
DNA vaccination of C57BL/6 mice
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Plasmids pCDNA3.1-*PSMA*and pCDNA3.1 were purified with EndoFree plasmid Maxi Kit (Qiagen, Valencia, CA). Three groups including 6 mice each were immunized: DNA vaccination group, CpG oligodeoxynucleotides and DNA vaccine co-administration group (hereafter referred to as CpG+DNA vaccination) and control group receiving empty plasmid. All mice were injected with 0.25% lidocaine in the quadriceps femoris muscle 3 days before vaccination in order to improve the uptaking of plasmids by muscles. The mice then received bilateral intramuscular injection with 50 μg of plasmid in the regenerating muscles. Mice in the DNA vaccination group were immunized with endotoxin-free pCDNA3.1*-PSMA*, mice in CpG+DNA vaccination group were further immunized with 25 μg of CpG oligodeoxynucleotides in the same location 3 days after DNA plasmid immunization, as control, mice were injected with pCDNA3.1 plasmid. All mice were boosted every 4 weeks for 3 times.
Measurement of PSMA specific serum antibodies
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Two weeks after the last immunization, the mice were bled and serum antibodies were measured by solid phase enzyme-linked immunosorbent assay (ELISA). Briefly, bacterially expressed fusion protein containing PSMA-derived fragment was coated on 96-well plates. The plates were blocked with 5% bovine serum albumin in phosphate buffered saline overnight at 4°C. The sera from C57BL/6 mice were serially diluted in phosphate buffered saline with 5% bovine serum albumin and then 100 μl of diluted serum was added into each well. The plates were incubated at 37°C for 1 hour, 100 μl of a 1:3000 dilution of goat anti-mouse IgG-HRP conjugate (Jackson ImmunoResearch, West Grove, PE) was added into each well and incubated for 1 hour at 37°C, then 100 μl tetramethyl benzidine (TMB) chromagen/substrate solution (0.1 mg/ml TMB, 0.1 M citric acid buffer pH6.0, 4 μl 30% hydrogen peroxide per 10 ml) was added to each well. The plates were read and the absorbance at 450 nm (A450) was measured by microplate reader.
Cytotoxic T Lymphocyte (CTL) Assay
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Two weeks after the last immunization, mice were sacrificed. Their spleens were removed and teased apart in serum-free RPMI-1640 media, the lymphocytes were collected and cultured in RPMI-1640 medium supplemented with 10% heat-inactivated fetal bovine serum, 50 IU/ml recombinant murine IL-2 and 2 μg/ml ConA for 2 days. B16 stimulator cells expressing PSMA (B16-PSMA) were prepared in complete RPMI-1640 medium containing 50 μg/ml mitomycin C for 1 hour at 37°C. Two × 10^7^lymphocytes (responders) were incubated in 6-well plates with 2 × 10^6^stimulator cells in the presence of 50 IU/ml recombinant murine IL-2 and 2 μg/ml ConA. After 6 days of culture, the re-stimulated cells were harvested and separated from the dead cells. Target cells (B16-PSMA) and re-stimulated lymphocytes (effector cells) were resuspended in phenol red-free RPMI-1640 medium supplemented with 5% new born calf serum, 5 × 10^3^target cells and various number of effector cells were added into individual flat-bottom wells in 96-well plates. The cells were incubated at 37°C overnight. 50 μl per well of supernatant was transferred to fresh 96-well plates. CTL reactivity was assessed by measuring lactate dehydrogenase (LDH) release using a Cytotox 96 assay kit (Promega). Controls were setup on each plate for spontaneous LDH release by target and effector cells. A parallel experiment using B16 cells transfected with pCDNA3.1 as target cells was also performed to test the specificity of lysis. All experiments were performed in triplicate. Percent lysis was calculated according to manufacturer\'s instructions.
Subcutaneous transplantation of tumor cells
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C57BL/6 mice were divided into 3 groups and immunized as above. B16-PSMA cells were trypsinized and resuspended in phosphate buffered saline, 2 × 10^5^cells were subcutaneously injected into the left lateral flank of mice. The time to the development of tumor was recorded. After tumors became detectable, their volume was measured two-dimensionally with a caliper along the longest axis (x) and the axis perpendicular to the longest axis (y) every second days. The volume of tumors was estimated by the following formula:
Volume = π/6 × x × y^2^
After 26 days, when tumor reached 20 mm in their largest axis, the mice bearing tumors were sacrificed. Tumors were removed and weighed.
Data Analysis
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The data from ELISA and CTL assays are expressed as means ± SD and are representative of at least three different experiments. Comparisons between individual data points were made using ANOVA or student\'s t-test. In the tumor challenge experiment, the primary endpoint was time of tumor appearance. Tumor-free survival time was compared by the Kaplan-Meier method and log-rank statistic. *P*\< 0.05 were considered significant.
Results
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Expression of plasmid *pCDNA3.1-PSMA*in COS7 cells
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To confirm the expression of PSMA in mammalian cells, plasmid pCDNA3.1*-PSMA*was introduced into COS7 cells. The cells were the incubated with anti-PSMA monoclonal antibody and goat anti-mouse IgG-FITC conjugate. The immunofluorescence assay demonstrated that the reactivity was present in the cytoplasm of COS7 cells transfected with pCDNA3.1-*PSMA*but not in mock-transfected cells, thus indicating that pCDNA3.1*-PSMA*could express protein in mammalian cells (Figure [1](#F1){ref-type="fig"}). We considered that plasmid pCDNA3.1 containing the Simian virus 40 (SV40) origin of replication were rapidly amplified in COS7 cells, which constitutively express SV40 large T antigen (T-Ag), so pCDNA3.1-*PSMA*underwent multiple rounds of duplication within one cell generation. A large amount of protein therefore was expressed and could not be delivered completely through the transporting machinery to cytomembrane, this may explain why the reactivity was found in cytoplasm.
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Figure 1
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**Immunofluorescence staining of COS7 cells.**The COS7 cells were transfected with either pCDNA3.1-*PSMA*or empty pCDNA3.1 and fixed with cold aceton. Fixed cells were incubated with a anti-PSMA monoclonal antibody 4A12, stained with a goat anti-mouse immunoglobulin-FITC conjugate, PSMA immunoreactive cells were visualized with a fluorescent microscope (×40). Cytoplasmatic reactivity was found in COS7 cells transfected with pCDNA3.1-*PSMA*(A) but not in COS7 cells transfected with pCDNA3.1 (B).
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Detection of *PSMA*mRNA
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The transfected and mock-transfected B16 murine melanoma cells were selected by G418 and, after 3 weeks of selection, clones resistant to G418 were obtained. Total RNA was extracted and reverse-transcribed into cDNA to be used as template for PCR detection of *PSMA*mRNA. A 358 bp band was present in 3 B16 clones transfected with pCDNA3.1-*PSMA*but not in clones transfected with pcDNA3.1 (Figure [2](#F2){ref-type="fig"}). GAPDH were detected in all samples (data not shown).
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Figure 2
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**Detection of *PSMA*mRNA by RT-PCR.**The murine melanoma B16 cells were transfected with either pCDNA3.1-*PSMA*or empty pCDNA3.1 and selected by G418. After 20 days of selection, clones resistant to G418 were acquired. Total RNA was extracted, and *PSMA*mRNA was detected by RT-PCR. 3 clones of B16 cells transfected with pCDNA3.1-*PSMA*were positive for *PSMA*mRNA, while B16 cells transfected with pCDNA3.1 were negative. Lanes 1, 2 and 3, B16 clones transfected with pCDNA3.1-*PSMA*; lane 4, B16 clones transfected with pCDNA3.1.
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Detection of PSMA protein
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The lysates from 3 clones with detectable *PSMA*mRNA were resolved by 6% SDS-PAGE followed by immunoblotting. A predicted 100 kD band was identified in the 3 clones but not in mock-transfected B16 cells (Figure [3](#F3){ref-type="fig"}). One of the clones was designated as B16-PSMA and used as target cells for cytotoxic T lymphocytes (CTL) assay or in tumor challenge experiment. A B16 cell line transfected with pCDNA3.1 (referred to as B16-pCDNA) was also obtained and used as negative control in CTL analysis.
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Figure 3
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**Detection of PSMA protein by Western Blot.**Total cell lysates were harvested and presence of PSMA protein was detected by anti-PSMA monoclonal antibody 4A12. A 100 kD band was identified in 3 clones with detectable *PSMA*mRNA but not in B16 cells transfected with empty vector (A). Lane1, 2 and 3, B16 cells transfected with pCDNA3.1-*PSMA*. Lane 4 B16 cells transfected with pCDNA3.1. β-actin was used as reference (B).
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Measurement of PSMA specific serum antibodies
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ELISA was used to measure PSMA specific serum antibodies in C57BL/6 mice. All mice immunized with pCDNA3.1-*PSMA*generated low titers of antibodies, while PSMA specific antibodies were not detected in control group. When sera were diluted at 1:10, 1:20,1:40,1:80,1:160, the differences between control group and other two groups were all statistically significant (*P*\< 0.001). However, titers were similar between the DNA vaccine and the CpG+DNA vaccination groups (*P*\> 0.05), suggesting that CpG oligodeoxynucleotides did not augment the antigen-specific humoral immunity (Figure [4](#F4){ref-type="fig"}). The experiment was repeated 3 times with sera from independently immunized mice yielding comparable results.
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Figure 4
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**Measurement of PSMA specific serum antibodies.**Mice were immunized 4 times at 4 weeks intervals by intramuscular injection with pCDNA3.1-*PSMA*or pCDNA3.1, antibody titers were measured by ELISA. Sera were serially diluted and measured individually. The experiment was performed in triplicate. Shown is the average antibody titer (n = 6) with standard errors. *P*valure was calculated by ANOVA. Antibody titer was similar in DNA vaccination group and CpG + DNA vaccination group, no antibody was detected in control group. \* indicated the difference between control group with other two groups was statistically significant (*P*\< 0.05).
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Cytotoxic T Lymphocyte (CTL) Assay
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Splenocytes from C57BL/6 mice were re-stimulated for 6 days with mitomycin C-treated B16-PSMA cells. Cytotoxicity was measured by LDH release from attacked B16-PSMA cells or B16-pCDNA cells. Splenocytes from mice in the DNA vaccination group exhibited specific lysis against B16-PSMA, whereas those from mice in the control group did not acquire killing activity. The differences between control group and the other two groups were statistically significant at E:T ratios of 40:1, 20:1, 10:1 (*P*\< 0.01). More importantly, CTL reactivity was significantly enhanced in mice treated with CpG oligodeoxynucleotides compared with DNA vaccine alone at E:T ratios of 40:1, 20:1 (t = 9.737, *P*\< 0.001; t = 2.14,*P*= 0.021 respectively) (Figure [5A](#F5){ref-type="fig"}). However, specific lysis was not observed in all groups when B16-pCDNA cells were used as target cells (Figure [5B](#F5){ref-type="fig"}).
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Figure 5
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**Cytotoxic T Lymphocyte (CTL) Assay.**Splenocytes from C57BL/6 mice were re-stimulated for 6 days with mitomycin C-treated B16-PSMA cells. Cytotoxicity was measured by LDH release assay. The experiment was carried out in triplicate. Shown is the average CTL (n = 6) with standard errors. When B16-PSMA cells were used as target cells, specific lysis was found in DNA vaccination group but not in control group. The CTL reaction was enhanced by CpG oligodeoxynucleotides(Fig. 5A). However, when the mock-transfected B16-pCDNA cells were used as target cells, specific lysis was not observed in all groups (Fig. 5B). \* indicated the difference between control group with other two groups was statistically significant (*P*\< 0.05); △ indicated the difference between DNA vaccination group and CpG + DNA vaccination group was statistically significant (*P*\< 0.05).
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Suppression of Tumor Growth in Tumor-bearing Mice by pCDNA3.1-*PSMA*
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C57BL/6 mice (n= 6/group) were vaccinated with pCDNA3.1-*PSMA*or empty vector, and then challenged with B16-PSMA cells. Protection was observed in pCDNA3.1-*PSMA*vaccinated mice with decrease of tumor incidence. After 26 days, all mice in the control group developed tumors while 2 (2/6) and 3 tumor-free mice (3/6) were observed in the DNA and in the CpG + DNA vaccination groups respectively. Kaplan-Meier curves showed that the tumor-free survival interval was 19.67 ± 2.24 days in the DNA vaccination group, 22.33 ± 1.61 days in the CpG +DNA vaccination group and 13.17 ± 1.01 in the control group (Fig. [6A](#F6){ref-type="fig"}). The difference between DNA vaccination group and control group was statistically significant (*P*= 0.0161), so was the difference between CpG+DNA vaccination group and control group (*P*= 0.0016). Tumor-free survival time was longer in CpG+DNA vaccination group than DNA vaccination group, but the difference was of no statistical significance (*P*= 0.49). This observation may be associated with the small number in each group.
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Figure 6
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**Suppressive Effects of DNA vaccine to Tumor Growth.**C57BL/6 mice (n= 6/group) were vaccinated with pCDNA3.1-*PSMA*or empty vector, and then challenged with B16-PSMA cells. Kaplan-Meier curves showed the tumor-free survival time of mice was 19.67 ± 2.24 days in DNA vaccine group, 22.33 ± 1.61 days in CpG + DNA and 13.17 ± 1.01 days in control group respectively (Fig. 6A). Some mice still developed tumors after pCDNA3.1-*PSMA*and CpG oligodeoxynucleotides vaccination, but the individual tumors grew much more slowly than those in control group (Fig. 6B). Two mice in control group died before the termination of the experiment, all mice bearing tumor were sacrificed and tumor tissues were removed, the volumes of tumors in control group were larger than those in other two groups (Fig. 6C).
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Although mice developed tumors after pCDNA3.1-*PSMA*vaccination, the individual tumors were consistently smaller than those in the control group and the analysis of tumor growth kinetics indicated that the tumor growth was significantly slower in the CpG +DNA vaccination group compared to the other two groups (Fig. [6B](#F6){ref-type="fig"}).
The volume of the tumors in the control group was consistently larger than in other two groups (Fig. [6C](#F6){ref-type="fig"}) and the average tumor weight was 2.28 ± 0.51 g in the DNA vaccine group, 1.10 ± 0.70 g in CpG + DNA group and 4.75 ± 0.66 g in the control group. The differences between control group and DNA vaccination group, CpG +DNA vaccination group were statistically significant (t = 5.92, *P*= 0.001; t = 7.062, *P*= 0.001 respectively). Moreover, the difference between DNA vaccination group and CpG +DNA vaccination group was statistically significant (t = 2.588, *P*= 0.049).
Discussion
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Although treatments are available for organ-confined carcinoma of prostate, there is no effective approach to treat recurrent disease after androgen deprivation therapy fails. New approaches are required to treat this incurable disease. DNA vaccination enables maintenance of tumor antigen expression at the vaccination site and results in immune responses in the host, therefore, shedding light on the treatment of cancer. It has been reported that tumor growth is suppressed when tumor cells are implanted in mice previously immunized with DNA vaccines encoding tumor antigens \[[@B22]-[@B25]\].
PSMA is a well-defined prostate-restricted tumor associated antigen whose expression is significantly elevated in carcinoma of prostate, especially in advanced stages. The expression of PSMA is down-regulated by androgen, after androgen deprivation therapy, its expression is strongly elevated\[[@B6],[@B26]-[@B28]\], Thus, PSMA is a potential target for the immunotherapy to carcinoma of prostate. Several PSMA-based vaccines had been developed and it has been observed in a phase II trial utilizing MHC Class I-restricted peptides that PSMA can induce immune responses in patients with advanced carcinoma of prostate and alleviate the disease \[[@B29]-[@B31]\]. This observation suggests PSMA as an appropriate target of active-specific immunization against carcinoma of prostate. However, standard methods of protein/epitope preparations often coupled to the adoptive transfer of antigen presenting cells are labor-intensive decreasing the widespread use of vaccines in the general cancer patient population.
The purpose of our work was to delineate new ways to induce immune responses by DNA vaccination. In this study, all mice immunized with DNA vaccine expressing PSMA generated PSMA specific antibodies at a low level, which may result from the small amount of antigen expressed by plasmid in vivo. What is noteworthy is that all immunized mice developed CTL reactivity to B16-PSMA which led to suppression of tumor growth. In addition, although some tumors developed in some treated mice, they were consistently smaller in the control group. These findings suggest that DNA vaccines expressing PSMA could elicit immune response against tumor cells expressing the target molecule.
Although DNA vaccines provide a convenient and effective approach to elicit cellular immunity, clinical outcomes have not been satisfactory, mainly because tumor-specific CTL elicited by the vaccines are insufficient to suppress cancer progression. CD8+ CTLs constitute one of the most important arms of the immune system, exhibiting the capacity of recognizing and destroying cancerous cells\[[@B32],[@B33]\]. A variety of approaches are under evaluation to activate CD8+ CTLs, to that end, vaccines need to be administered in combination with adjuvants of which the most commonly used in experimental models is incomplete Freud\'s adjuvant (IFA). However, this adjuvant is not widely used in human vaccination protocols due to its undesirable side effects, such as erythema and induration at the injection site, in addition, IFA functions mainly to promote humoral immunity. For these reasons, alternative potent and safe adjuvants need to be identified to enhance cellular immune response against cancer \[[@B34],[@B35]\].
Synthetic CpG oligodeoxynucleotides represent a promising adjuvant. The predominant effect of CpG oligodeoxynucleotides exposure is the promotion of Th1-type immune responses. Professional antigen presenting uptake CpG oligodeoxynucleotides and become activated with increased expression of MHC and co-stimulatory molecules \[[@B36]-[@B38]\] that promote antigen presentation to naïve T cells. In addition, dentritic cells are stimulated to secret Th1-biased cytokines, such as interferon-γ and IL-12 particularly desirable in cancer immunotherapy \[[@B39],[@B40]\]. Therefore, CpG oligodeoxynucleotides may be useful vaccine adjuvants.
CpG oligodeoxynucleotides 1826 is a potent enhancer of Th1-type immune responses and may benefit anti-cancer therapy \[[@B41]-[@B43]\]. We, therefore, hypothesized that the administration of these CpG oligodeoxynucleotides should enhance the cellular immunity elicited by DNA vaccines. However, co-adminstration of CpG oligodeoxynucleotides and DNA vaccines inhibit each other activity because CpG oligodeoxynucleotides may compete with plasmid uptake by antigen presenting cells. Furthermore, IFN-γinduced by CpG oligodeoxynucleotides could inhibit the activity of the CMV promoter utilized by eukaryotic expression vector, thus decreasing antigen expression. To examine the efficacy of CpG oligodeoxynucleotides as vaccine adjuvants, we injected them at the DNA injection site 3 days after vaccination rather than simultaneously. This strategy was based on a previous observation that transfected cells reach maximum yield of antigen expression between day 2 and 3 after vaccination. In this context, delivering the CpG oligodeoxynucleotides at the time of maximal antigen expression may be crucial to optimize the immunogenic boost \[[@B44],[@B45]\].
Consistent with previous reports, this study suggests that CpG oligodeoxynucleotides enhance cellular immunity. The activity of CTL against PSMA expressing cells in the CpG +DNA vaccination group was significantly higher than in the DNA vaccination group. Furthermore, tumor challenge experiments demonstrated a potentiation of the suppressive effects on the growth of tumor cells expressing PSMA. These findings indicate that CpG oligodeoxynucleotides should be a powerful adjuvant in the context of DNA-based vaccination.
Conclusions
===========
In this study, we designed a DNA vaccine expressing prostate specific membrane antigen (PSMA) and utilized CpG oligodeoxynucleotides to promote Th1-type immune response. We discovered that the constructed vaccine generated anti-tumor reactivity against malignant cells expressing PSMA that was enhanced by CpG oligodeoxynucleotides co-administration. This strategy may provide a new venue for the treatment of carcinoma of prostate, particularly for recurrent disease after hormone therapy fails.
Competing interests
===================
None declared.
Authors\' contributions
=======================
R.J.Q participated in the design of the study and carried out plasmid DNA transfection, RT-PCR, immunofluorescence assay, DNA vaccination, lymphocyte stimulations, cytotoxicity assays, and completed the preparation of the manuscript. Z.L participated in the design of the study and carried out the construction of the expression plasmid, western blotting, and histological analysis and assisted in the preparation of the manuscript. C.Q carried out cell culture, L.H carried out RNA extraction, Z.L carried out ELISA. Z.H.G conceived of the study, participated in its design and coordination, and helped draft the manuscript. All authors read and approved the final manuscript.
Acknowledgements
================
The authors thank Ms. Xiurong Zhang, Mr. Zhonghua Zhao and Hui Xu for their technical assistance thank Mr Huakang Cao for animal breeding, and we also thank Dr Jinsheng Zhang for helpful comments and criticism.
|
PubMed Central
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2024-06-05T03:55:47.889598
|
2004-9-9
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517950/",
"journal": "J Transl Med. 2004 Sep 9; 2:29",
"authors": [
{
"first": "Jiaqiang",
"last": "Ren"
},
{
"first": "Li",
"last": "Zheng"
},
{
"first": "Qi",
"last": "Chen"
},
{
"first": "Hua",
"last": "Li"
},
{
"first": "Lin",
"last": "Zhang"
},
{
"first": "Hongguang",
"last": "Zhu"
}
]
}
|
PMC517951
|
Introduction
============
The precise identification of HLA Class I and Class II alleles is critical for successful hematopoietic progenitor transplants, the development of peptide based viral and cancer vaccines, and investigating immune response \[[@B1],[@B2]\]. DNA sequencing is one of the most comprehensive methods available for HLA typing. Sequence-based typing (SBT) involves PCR amplification of specific coding regions of HLA genes and sequencing of the amplicons \[[@B3],[@B4]\]. SBT allows for a detailed interpretation of HLA alleles by comparing nucleotide sequences of the polymorphic, and sometimes conserved, regions of the HLA gene to a database of possible allelic combinations. While SBT permits the highest resolution of genotypes, like all typing methods, it has limitations. One of the inherent problems when using SBT is the interpretation of ambiguous allele combinations which can occur for several reasons \[[@B5]-[@B7]\].
There exist two main types of ambiguous typing results obtained with SBT. The first is when a heterozygous sequence can be explained by more than one possible pair of alleles within the region analyzed. The second exists when alleles are defined by a polymorphism outside the region analyzed. In addition to these two situations, a third type of ambiguity arises when an allele has an incomplete sequence in the region analyzed.
The prevalence of ambiguities in HLA typing relates to the nature of polymorphisms which exists in the sequence of the major histocompatibility complex (MHC) Class I and Class II genes. The majority of polymorphisms that distinguish one MHC allele from another are oftentimes due to gene conversion, recombination and exon shuffling events. Due to this, polymorphic motifs at given positions are generally shared among several alleles.
Sequence-based typing involves PCR amplification and sequencing of specific HLA exons, which are known to be polymorphic, from genomic DNA. For each HLA locus both alleles are amplified and sequenced; therefore, it is not always possible to determine exactly which two alleles were responsible for sequence results. For example two or more different allele combinations can combine to produce identical sequences due to the heterozygous base pair combinations, the first type of ambiguity. More specifically, in the Class I region, HLA-B\*070201, 3503 would have the same nucleotide sequence as HLA-B\*0724, 3533 in positions 559 and 560 (Figure [1](#F1){ref-type="fig"}). In this example, the SBT produces a heterozygous base pair combination at positions 559 and 560 with an international union of biochemists (IUB) designation of K(G+C)W(A+T). Therefore, the interpretation to the high resolution level can not be made because it is not known which allele combination is correct.
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Two different HLA-B allele combinations that yield identical sequence based-typing results. The amplification and sequencing of exon 3 of HLA Class I from a HLA-B\*070201/B\*0724 subject and a HLA-B\*3503/3533 subject produce the same results. Both G and C are detected at nucleotide 559 and both A and T at nucleotide 560.
:::
:::
The second type of ambiguity relates to defining a polymorphism outside the region analyzed. For example, many HLA-A alleles are defined by a polymorphism located in Exon 4 (Table [3](#T3){ref-type="table"}). Traditionally, for Class I typing most laboratories only sequence Exon 2 and Exon 3; for Class II typing most laboratories only sequence Exon 2. This approach has been the standard due to the functional relevance of this region which defines the peptide groove of Class I and Class II molecules, respectively. However, some Class I alleles have identical sequences across Exons 2 and 3. To resolve these alleles it is necessary to analyze the gene at the region where they differ. As DNA sequencing has become easier and more widely applied to defining HLA alleles, additional polymorphisms have been found in other exons, and also in the introns.
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Specific A locus sequence-based typing ambiguities discovered during this study and the reason that the ambiguity occurs.
:::
---- ------------------------------------------------------------------ ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
1 A\*010101/04N 0104N is resolved as a C insertion at bp 628 in exon 4.
2 A\*2402/09N/11N 24020101 is unresolvable from 24020102L. 2409N is resolved in exon 4 at bp 742 by a T substitution. The base change responsible for 2409N creates a premature termination on exon 4. 2411N is the result of the same insertion at 0104N.
3 A\*010101/04N, 0201/09/43N or 0236, 3604 0209 is resolved as an A substitution in exon 4 at bp 779. 0243N is resolved as a C insertion at bp 780. 0236 and 3604 are not defined in exon 4.
4 A\*020101/43N, 030101 or 0226, 0307 or 0234, 0308 0226 and 0308 are not defined in exon 4. As a result resolution can not be determined.
5 A\*0201/09/43N, 2301/07N or 0236, 2304 The 02 alleles are resolved in exon 4 as described above. 2307 N is resolved by a C insert at bp 628 in exon 4. Neither 0236 nor 2304 are defined in exon 4.
6 A\*020101/09/43N, 240201/09N/11N or 0212, 2413 or 0236, 24031/33 The 02 and 24 alleles are resolved in exon 4 as described above. Alleles 2413 and 0236 are not defined in exon 4.
7 A\*0201/09, 2501 or 0206, 2503 The 02 alleles are resolved in exon 4 as described above. 2503 is not defined in exon 2.
8 A\*030101, 240201/09N/11N or 0308, 2407 The 24 alleles are resolved in exon 4 as described above. 0308 is not defined in exon 4.
9 A\*030101/2501 or 0308/2502 or 3204/6601 0308, 2502, and 3204 are not defined in exon 4.
10 A\*A\*030101, 2601 or 0308, 2613 0308 and 2613 are not defined in exon 4.
11 A\*240201/09N/11N, 2601 or 2406, 2608 The 24 alleles are resolved in exon 4 as described above. 2406 is undefined in exon 4.
12 A\*240201/09N/11N, 2902 or 24031, 2903 The 24 alleles are resolved in exon 4 as described above. 24020101, 2902 and 240301, 2903 are unresolved.
13 A\*020101/09/20/43N, 310102/3102 3102 is not defined in exon 4.
14 A\*240201/09N/11N, 3201 or 2432, 3203 Both 2432 and 3203 are not defined in exon 4.
15 A\*240201/09N/11N, 680102/11N or 2406, 6809 or 2407, 680301 680102 and 6811N are not resolvable. 2406 and 6809 are not defined in exon 4. Exon 4 would resolve 24020101 from 2409N and 2411N. 24020101, 680102/11N is unresolvable from 2407, 680301.
16 A\*2502, 7401 or 2502, 7402 or 3201, 6601 7402 is not defined in exon 4. 2502, 7401 is unresolvable from 3201, 6601.
---- ------------------------------------------------------------------ ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
:::
Finally, an ambiguity may be due to incomplete sequence information, because not all alleles have been sequenced for the same exons. For some alleles the entire sequence is not known in the region that is amplified. For example, A\*010101 has been sequenced from Exon 1 through Exon 8, but A\*010102 has been sequenced only in Exon 2 and Exon 3. Numerous ambiguities arise due to an incomplete sequence in Exon 4. The minimum requirements for submission of new sequences into reference databases of HLA sequences are the sequencing of Exon 2 and Exon 3 for Class I and Exon 2 for Class II.
The relevance of completely identifying the polymorphisms found by SBT needs consideration. In clinical respects, it may not always be necessary to resolve ambiguities that involve a silent non-coding polymorphism and/or an intron polymorphism. Exceptions will exist to this situation where the polymorphism negates or impairs expression (e.g. A\*24020102L or B\*15010102N -- both are due to an intron polymorphism). However, for investigations of genetic inheritance or disease association, the definition of all polymorphisms may be significant.
The purpose of this study was to summarize the incidence, nature, and cause of ambiguous HLA SBT results. This represents an important step toward developing strategies to reduce or eliminate this problem.
Methods
=======
DNA Isolation
-------------
Genomic DNA was isolated from peripheral blood using the Gentra PUREGENE^®^isolation kit (Gentra Systems, Minneapolis, MN, U.S.A). The DNA was resuspended in Tris HCl buffer (pH 8.5) and the concentration was measured using a Pharmacia Gene Quant II Spectrophotometer. The DNA was then stored at -70°C until testing.
Sequence-Based Typing
---------------------
The primary PCR amplification reaction consists of a 1.5 kb reaction encompassing exon 1 through intron 3 of the HLA region. All reagents necessary for primary amplification and sequencing are supplied in the HLA-A or HLA-B AlleleSEQR Sequenced Based Typing Kits (Forensic Analytical, Hayward, CA, U.S.A.). The primary amplification PCR products were purified from excess primers, dNTPs, and genomic DNA using ExoSAP-IT (Amersham Life Science, Cleveland, OH, U.S.A.) Each template was sequenced in the forward and reverse sequence orientation for exon 2 and Exon 3 according to protocols supplied with the SBT kit. Excess dye terminators were removed from the sequencing products utilizing an ethanol precipitation method with absolute ethanol. The reaction products were reconstituted with 15 μl of Hi-Di™ Formamide (PE Applied Biosystems/Perkin-Elmer, Foster City, CA, U.S.A.) and analyzed on the ABI Prism^®^3700 DNA Analyzer with Dye Set file: Z and mobility file: DT3700POP6 {ET}.
Results
=======
Sequence based typing analysis of HLA-A and B alleles was performed on a population of 676 normal donors. The racial distribution of the subjects studied was: 615 Caucasian, 13 Asian, 23 African American, 17 Hispanic and 8 Unknown. 672 of the 676 subjects were analyzed for the presence of HLA-A locus ambiguities and 666 were analyzed for HLA-B locus ambiguities. Each allele was counted separately in this analysis in order to determine the total percentage of ambiguous allele combinations. Four new potential alleles were found.
At the HLA-A locus a total of 548 ambiguous allele combinations were found. This represented 41% of all HLA-A alleles (548 of 1344) (Table [1](#T1){ref-type="table"}). Approximately half, 51% (278 of 548) of these ambiguities were due to the fact that Exon 4 analysis was not performed (Table [2](#T2){ref-type="table"} and Table [3](#T3){ref-type="table"}). HLA-A\*01 and HLA-A\*24 are very prevalent alleles and most ambiguities involving these alleles could be resolved by performing Exon 4 analysis. For example the ambiguity most prevalent for HLA-A\*01 in this study was HLA-A\*0101/0104N. The sequences of these two alleles are identical across Exons 2 and 3; the difference between these two alleles occurs at position 627insC, which is located in Exon 4.
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Prevalence of ambiguous sequence-based typing allele combinations among 672 people analyzed at the HLA-A locus and 666 analyzed at the HLA-B locus
:::
**Allele** **Occurrence** **Allele** **Occurrence**
------------ ---------------- ------------ ----------------
A\*01 174 B\*07 51
A\*02 162 B\*08 56
A\*03 43 B\*13 2
A\*23 2 B\*14 3
A\*24 104 B\*15 26
A\*25 5 B\*18 17
A\*26 26 B\*27 37
A\*29 3 B\*35 34
A\*31 4 B\*39 3
A\*32 5 B\*40 31
A\*66 1 B\*44 44
A\*68 16 B\*51 14
A\*74 3 B\*52 1
B\*55 2
B\*58 1
**TOTAL** **548** **TOTAL** **322**
:::
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Nature and Resolution of HLA-A and -B Allele Ambiguities
:::
**HLA-A Locus** **HLA-B Locus**
------------------------------------- ------------------------- -------------------------
Portion of alleles with ambiguities 41% 24%
Most frequently involved alleles A\*01, 02, and 24 B\*7, 8, 15, 35, and 44
Methods used to resolve ambiguities Exon 4 sequencing (51%) Many different methods
A\*02 subtyping (30%)
:::
A large portion of HLA-A locus sequence-based typing ambiguities involved HLA-A\*02, 30% or 162 of 548. Some of the HLA-A\*02 ambiguities can also be resolved via Exon 4 sequencing and most of the other HLA-A\*02 ambiguities can be resolved with traditional A\*02 molecular subtyping methodologies using sequence specific primers or sequence specific probes.
Not all HLA-A ambiguous allele combinations can be resolved as simply as those involving A\*01, A\*024 and A\*02. Most of the remaining 19% (108 of 548) of the HLA-A ambiguities cannot be resolved with Exon 4 analysis (Table [3](#T3){ref-type="table"}).
Review of the HLA-B locus results revealed 322 ambiguous allele combinations among the 1332 total HLA-B alleles (24%). Antigens HLA-B\*07/08/15/27/35/44, common in Caucasians, produced the largest portion of the ambiguities (279 of 322 or 87%). Each of these ambiguities had an independent reason for occurring. Table [4](#T4){ref-type="table"} lists some of the more common B locus ambiguities seen in this study. The reason for each ambiguity is variable; however a large portion of the ambiguities are related to cis/trans allele combinations.
::: {#T4 .table-wrap}
Table 4
::: {.caption}
######
Comparison of B locus ambiguities seen with the standard single tube amplification sequence-based typing method utilized in this study and those expected to be seen when utilizing a new two tube sequence-based typing method.
:::
------------------------------------------------------------------------
**Ambiguities using a single tube amplification**
B\*270502 or 270502/13 or 2713
B\*070201, 0801 or 0705/06, 0807
B\*070201, 1402 or 0726, 1403
B\*0702, 150101 or 0707, 1507 or 0709, 1563
B\*070201, 180101/17N or 0707, 1814 or 0726, 1813
B\*07021, 400101/0102 or 0705/06, 4033
B\*070201, 440201/19N/27 or 0720, 4416 or 0724, 4421
B\*0801, 180101/17N or 0804, 1807 or 0812, 1814
B\*0801, 400101/0102 or 0804, 4007
B\*0801, 440201/19N/27 or 0802, 4409
B\*150101/15, 3503/13
B\*1503, 3501 or 1529, 3528
B\*3501, 400101/0102 or 3520, 4007
B\*350101/40N/42, 4402/19N/27 or 3510, 4412
B\*400101, 4402 or 400102, 4402 or 4042, 4414
B\*4001, 510101 or 4007, 5107
**Ambiguities reduced by 56% if Two Tube Group Amplification is Used**
Remaining ambiguities:
B\*070201, 180101/17N or 0707, 1814 or 0726, 1813
B\*070201, 440201/19N/27 or 0720, 4416 or 0724, 4421
B\*0801, 180101/17N or 0804, 1807 or 0812, 1814
B\*0801, 440201/19N/27 or 0802, 4409
B\*150101/15, 3503/13
B\*1503, 3501 or 1529, 3528
B\*3501, 400101/0102 or 3520, 4007
B\*400101, 4402 or 400102, 4402 or 4042, 4414
B\*4001, 510101 or 4007, 5107
------------------------------------------------------------------------
:::
Discussion
==========
While SBT provides the best available typing of HLA-A and B antigens, it is limited by sequence results that don\'t allow the precise identification of alleles. We found that 41% of HLA-A alleles and 24% of HLA-B alleles were ambiguously typed. The ambiguities involve some of the most frequent HLA-A and HLA-B antigens: A\*01, A\*02, A\*24, B\*07, B\*08, B\*15, B\*27, B\*35, and B\*44. However, ambiguous allele combinations occur in all loci tested in HLA. The IMGT/HLA Sequence Database <http://www.ebi.ac.uk/imgt/hla/> maintains an updated listing of all ambiguous possibilities <http://www.ebi.ac.uk/imgt/hla/ambig.html>\[[@B5],[@B8]\].
The need to initiate additional testing to clarify ambiguous allele combinations must consider whether it is practical to obtain the information and if the information is useful and valuable. The clinical need for the highest resolution HLA typing possible is an important variable that must be considered. When typing is performed for cancer and viral vaccine development studies, high resolution allele data may be necessary to determine if a subject has an HLA type that is appropriate for a study. Utilization of high resolution data may also have implications for hematopoietic progenitor cell transplantation. Transplants involving partially mismatched or unrelated donor-recipient pairs require a higher resolution typing, but those involving HLA identical siblings may not.
If it is necessary to resolve an ambiguous typing, a variety of different methods can be used. If the ambiguity is due to an allele that has not been completely sequenced or because the ambiguity is outside the region amplified by the SBT assay, the resolution is dependent on the nature and complexity of the ambiguity. Traditionally, for Class I sequencing purposes most laboratories have performed Exon 2 and Exon 3 analysis alone and for Class II sequencing only Exon 2 analysis. Many of the ambiguities can be resolved by sequencing Exon 4. In fact, in this study the largest portion of the typing ambiguities can be resolved by sequencing exon 4. However, many polymorphisms in exon 4 have no functional significance, so it may not be worthwhile resolving most ambiguities involving exon 4. The requirement for the analysis of Exon 4 to reduce the incidence of typing ambiguity has now been realized by commercial kit manufacturers. Both Celera Diagnostics (Alameda, CA) and Forensic Analytical/Atria Genetics (South San Francisco, CA) now include reagents for analysis of exon 4 in the HLA-A and -B kits. As the use of SBT increases, more data may become available from non-traditional exons in addition to those that have been traditionally sequenced and the number of ambiguities due to unknown sequences will decrease.
If the ambiguity is due to an identical heterozygote sequence, as shown in figure [1](#F1){ref-type="fig"}, the ambiguous allele combinations can sometimes be addressed by utilizing a group-specific primary amplification approach. In this approach each allele is amplified separately by using group specific primers for the alleles in question. A homologous sequence for each separate allele can then be obtained by sequencing the product of the group specific amplifications. Currently, there are commercially available kits (Forensic Analytical, Hayward, CA) for group specific amplification of the B locus. These kits allow the primary amplification of a specific group. Upon discovery of a particular ambiguity, a group specific amplification is done to separate out the allele pair. The resultant sequence will be homozygous for each allele in question. Another method, which will reduce the number of ambiguities in the B locus, is the utilization of a two tube group amplification approach (DYNAL Biotech, Brown Deer, WI). This method allows for resolution of ambiguities by taking into account the cis/trans allele combinations which result from simultaneous nucleotide incorporation for DNA templates being sequenced. This method allows for separation of ambiguities when the ambiguity has arisen due to a cis/trans situation. Ambiguities utilizing this method are reduced by 56%. (Table [4](#T4){ref-type="table"}) Another method for separation of alleles is Haploprep™. (Genovision, Philadelphia, PA). Haploprep™ physically separates a diploid sample into its haploid components. Once the haplotypes are separated, routine HLA typing methods can be performed to determine the alleles. This laboratory is currently conducting studies to determine the efficacy of this product. Several of the remaining HLA loci ambiguities can be managed utilizing in-house custom group specific primary amplification mixes.
Other methods which have been utilized to produce a homologous sequence include cloning, reference strand conformational analysis (RSCA), Pyrosequencing™ and denaturing high-performance liquid chromatography (DHPLC) \[[@B9]-[@B11]\]. Pyrosequencing™ is being explored by this laboratory and results at this time are preliminary. This method relies on the identification of a correct dispensation order of nucleotides during the Pyrosequencing™ process. Each ambiguity would require a separate dispensation order to be determined due to the unique nature of each ambiguity. The initial setup of this technology may be cumbersome; however, once established it may become very streamlined due to the availability of data on different ambiguous allele combinations. Each one of these methods has advantages and concerns which must be thoroughly investigated by the laboratory. Some, not all, ambiguous allele combinations produced by having identical heterozygote combinations can be resolved utilizing traditional sequence specific primers (SSP) or sequence specific oligonucleotide probes (SSOP). This may be a more viable approach for laboratories if they are already performing one of these technologies.
In conclusion, although the prevalence of ambiguous allele combinations is high, methods exist to compensate for this problem. As the HLA field continues the discovery of new alleles, alternative approaches to discerning ambiguous allele combinations will need to be investigated in order to reduce the ever-growing number of ambiguities.
|
PubMed Central
|
2024-06-05T03:55:47.891915
|
2004-9-13
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517951/",
"journal": "J Transl Med. 2004 Sep 13; 2:30",
"authors": [
{
"first": "Sharon D",
"last": "Adams"
},
{
"first": "Kathleen C",
"last": "Barracchini"
},
{
"first": "Deborah",
"last": "Chen"
},
{
"first": "FuMeei",
"last": "Robbins"
},
{
"first": "Lu",
"last": "Wang"
},
{
"first": "Paula",
"last": "Larsen"
},
{
"first": "Robert",
"last": "Luhm"
},
{
"first": "David F",
"last": "Stroncek"
}
]
}
|
PMC517952
|
1. Background
=============
The currently favoured explanation for the origin of Mendel\'s dominant and recessive traits is untenable \[[@B1]\]. The primary error in this current attempted explanation is the assumption that there is a direct, proportional, relationship in a diploid cell between a series of allegedly dominant and recessive alleles written as (*AA*+ 2*Aa*+ *aa*) and the dominant, hybrid and recessive traits written as (*AA*+ 2*Aa*+ *aa*). This assumption (Figure [2](#F2){ref-type="fig"}, in reference \[[@B1]\]) incorporates four fundamental faults:
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Accounting for Mendel\'s observation of a 3(dominant):1(recessive) trait ratio in his F2 populations of plants. Mendel\'s notations for a dominant trait, a hybrid and a recessive trait were (*A*), (*Aa*) and (*a*) respectively. For reasons given in the preceding paper \[1\], a hybrid trait is represented in Figure 2 by (*H*). The molecular components of all traits are synthesised by a metabolic pathway. When the activity of any one enzyme in a metabolic pathway is changed in discrete steps, the flux to a trait component responds in non-linear (non-additive) fashion \[3\]. If the flux response is quasi-hyperbolic, as shown here, the hybrid trait (*H*) will be indistinguishable from the trait (*A*) expressed in the wild-type cell or organism, even when the enzyme activity in the hybrid (*H*) has been reduced to 50% of the wild-type activity. Trait (*a*), will be distinguishable from both traits (*A*) and (*H*) only if the enzyme activity is further reduced to a sufficient extent. Under these circumstances the trait series (*A*+ 2*H*+ *a*) becomes (3*A*+ *a*); Mendel\'s 3(dominant):1(recessive) trait ratio is accounted for without introducing arbitrary and inconsistent arguments \[1\].
:::
:::
\(i) A failure to distinguish between the parameters and the variables of any system of interacting components, specifically between the determinants (alleles in modern terminology) and what is determined (the form of the trait or characteristic expressed in a cell or organism). Thus, because Mendel defined the terms dominant and recessive for *traits*or *characters*, it was illegitimate (and illogical) to call alleles dominant or recessive, and to represent them by the same letters used by Mendel to represent traits \[[@B1]\].
\(ii) A trait series written as (*AA*+ 2*Aa*+ *aa*) suggests, incorrectly, that dominant and recessive traits comprise two aliquots, (*A + A*) or (*a*+ *a*), of dominance or recessivity.
\(iii) A failure to take account of the long established fact that the first non-nucleotide product of the expression of an allele is a polypeptide and that most polypeptides are enzymes or membrane-located translocators.
\(iv) A failure to note that the components of all tangible traits comprised the molecular products of metabolic pathways, i.e., the products of sequences of enzyme-catalysed reactions.
Correction of the first two of these four faults has already been achieved (section 4 in reference \[[@B1]\]) by writing an allele series as (*UU*+ 2*Uu*+ *uu*) and the corresponding trait series as (*A*+ 2*H*+ *a*). In these statements (*U*) and (*u*) are normal and mutant (not dominant and recessive) alleles respectively. Mendel\'s notation (*A*) and (*a*) is used to represent dominant and recessive traits but (*H*) replaces Mendel\'s implausible notation (*Aa*) for a hybrid class of trait \[[@B1]\]. Mutations at another gene locus, in the same or a different cell, will be written as (*WW*+ *Ww*+ *ww*); the corresponding trait series will appear as (*B*+ 2*H*+ *b*). Mendel\'s notation (*Aa*) for a hybrid trait will be used in this article only when referring directly to Mendel\'s paper \[[@B2]\].
2. A rational explanation of Mendel\'s observations
===================================================
Our stated task was to explain logically how an allele series (*UU*+ 2*Uu*+ *uu*) is expressed as a series of qualitatively distinguishable F2 traits (*A*+ 2*H*+ *a*) when F1 hybrids (*H*) are allowed to self-fertilise \[[@B1]\]. This is very simply achieved by correcting faults (iii) and (iv) in four successive steps (sections 2.1--2.4) based on a paper published 23 years ago \[[@B3]\]. A fifth step (section 2.5) allows us to go beyond that paper to explain how the trait ratio 3(dominant):1(recessive) sometimes occurs and sometimes does not. A sixth step (section 2.6), consistent with the earlier ones, explains why dominance and recessivity are not always observed. Section 2.7 validates an earlier section. Section 2.8 accounts for some aspects not dealt with in textbooks and reviews of genetics.
The treatment in this section 2 is extended in section 3 to account for quantitatively different traits, in section 4 to illustrate some implications of the present treatment, and in section 5 to account for pleiotropy and epistasis. Section 6 defines the conditions that must be met if a rational account is to be given for the occurrence of dominant and recessive traits.
2.1. A generalised metabolic system
-----------------------------------
If: the first non-nucleotide product of expression of an allele is a polypeptide and most polypeptides are enzymes \[[@B3],[@B4]\], it follows that most mutations at *any one*gene locus will result in the formation of a mutant enzyme at a catalytic locus in a metabolic pathway. This is true even if the functioning enzyme is composed of more than one polypeptide, each specified by different genes. It then follows that we need to ask how the concentration of a normal molecular component of a trait will be affected by a mutation of *any one*enzyme *within a metabolic system*. In short, a systemic approach, outlined below, is obligatory.
This is the key to an understanding of the origin of dominant and recessive traits, as first pointed out in the following two sentences: \"When as geneticists, we consider substitutions of alleles at a locus, as biochemists, we consider alterations in catalytic parameters at an enzyme step. - -. The effect on the phenotype of altering the genetic specification of a single enzyme - - - is unpredictable from a knowledge of events at that step alone and must involve the response of the system to alterations of single enzymes *when they are embedded in the matrix of all other enzymes*.\" (\[[@B3]\]; p.641).
2.2 Metabolic systems and steady states
---------------------------------------
Metabolic processes are facilitated by a succession of catalysed steps; i.e. by enzyme-catalysed transformations of substrates to products or by carrier-catalysed translocation of metabolites across membranes. Because enzymes and membrane-located carriers (or porters) are saturable catalysts that exhibit similar kinetics it is convenient in this article to refer only to enzymes and to represent both kinds of catalysts by the letter *E*. Any segment of a sequence of enzyme-catalysed reactions can then be written as shown in Figure [1](#F1){ref-type="fig"}.
::: {#F1 .fig}
Figure 1
::: {.caption}
######
A segment of a model metabolic pathway. This diagram shows those features, discussed in the text, that permit a systemic analysis of the response of any variable of a metabolic system (e.g. a flux *J*or the concentration of any intracellular metabolite S) to changes in any one parameter of the system (e.g. an enzyme activity). Each *S*is an intracellular metabolite; each *X*is an extracellular metabolite. In a diploid cell, every *E*stands for a pair of enzymes (allozymes), each specified by one of the two alleles at a gene locus. Each *E*is then a locus of catalytic activity within a system of enzymes; each *v*stands for the individual reaction rates catalysed jointly by a pair of allozymes in a diploid cell. Either or both allozymes at such a locus may be mutated.
:::
:::
There are ten important features of any such system.
\(1) Each enzyme, *E*~1~to *E*~6~, is embedded within a metabolic pathway, i.e. within a system of enzymes.
\(2) All components of this system except the *external*metabolites *X*~0~and *X*~6~are enclosed by a membrane.
\(3) *E*~1~and *E*~6~may then represent membrane-located enzymes or translocators.
(4)*X*~0~and *X*~6~interact with only one enzyme, whereas each internal metabolite (*S*~1~, *S*~2~, *S*~3~, *S*~4~, *S*~5~) interacts with two flanking enzymes.
\(5) In a haploid cell there will be one specimen of an enzyme molecule (*E*) at each catalytic locus. In a diploid cell there will be two specimens of enzyme molecules (two allozymes) at each catalytic locus: one specified by the maternal allele, the other by the paternal allele, at the corresponding gene locus or loci. The effective catalytic activity at each metabolic locus in a diploid will be, in the simplest case, the sum of the two individual activities. It is the single effective enzyme activity (*v*) at each catalytic locus that concerns us here, irrespective of whether the cell is haploid, diploid or polyploid.
\(6) The catalytic activity (*v*) at any one metabolic locus can be left at its current value or changed to and *maintained at*a new value by the experimentalist, e.g. by suitable genetic manipulation of an allele. Each allele in these circumstances is therefore an *internal parameter*of the system; it is accessible to modification by the direct and sole intervention of the experimentalist \[[@B1]\].
\(7) Because *X*~0~and *X*~6~are external to the system in Figure [1](#F1){ref-type="fig"}, their concentrations can be fixed, and maintained at a chosen value, by the direct intervention of the experimentalist; they are *external parameters*of the metabolic system.
\(8) In contrast to *X*~0~and *X*~6~, the concentrations of metabolites *S*~1~to *S*~5~within the system cannot be fixed and maintained at any desired value solely by the direct intervention of the experimentalist. The concentrations of *S*~1~to *S*~5~are *internal variables*of the system. (If a fixed amount of any one of these metabolites were to be injected through the membrane into the system, continued metabolism would ensure that the new intracellular metabolite concentration could not be maintained).
\(9) By the same arguments, each reaction rate (*v*) and the flux (*J*) through the system are also variables of the system.
\(10) The magnitude of each variable of the system is determined at all times by the magnitudes of all the parameters of the system and of its immediate environment. The variables comprise the *concentrations*(*s*~1~, *s*~2~, *s*~3~, *s*~4~,*s*~5~) of the intracellular metabolites shown in Figure [1](#F1){ref-type="fig"} and any other intracellular metabolites; the individual reaction rates *v*~1~, *v*~2~, *v*~3~, *v*~4~, *v*~5~, *v*~6~; and the flux *J*through this system of enzyme-catalysed steps.
It follows that, provided we maintain the concentrations of *X*~0~and *X*~6~constant, the system depicted (Figure [1](#F1){ref-type="fig"}) will, in time, come to a steady state such that:
*v*~1~= *v*~2~= *v*~3~= *v*~4~= *v*~5~= *v*~6~= *J*(the flux through this system).
At the same time the concentration of each intracellular metabolite *S*~1~to *S*~5~will settle to an *individual*steady value.
2.3. The response of the system variables to a change in any one system parameter
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In a metabolic system, the product of any one enzyme-catalysed reaction is the substrate for the immediately adjacent downstream enzyme (Figure [1](#F1){ref-type="fig"}). If, for any reason, the concentration of the common intermediate metabolite of two adjacent enzymes is changed (for example by mutation of one of the two adjacent enzymes), the concentration of the other adjacent enzyme will not change but its activity will change in accordance with the known response of an enzyme activity (at constant enzyme concentration) to a change in the concentration of its substrate or product. In other words, no matter how complicated that system may be, the *activity*of any one enzyme depends, at all times, on the activity of the adjacent enzyme; and this is true for every pair of adjacent enzymes throughout the system (up to the point in the system where a terminal product is formed).
\[This last statement is obviously still true for the system in Figure [1](#F1){ref-type="fig"} if we omit the words in parentheses but only because the extracellular product *X*~6~is a terminal product. *X*~6~is not an intermediate metabolite, flanked by *two*adjacent enzymes; it is not a substrate that is further metabolised by the system depicted. There are instances where an intracellular terminal product is formed. We must therefore add the words in parentheses if the statement is to apply generally\].
A finite change (by mutation) in any one allele at a locus will change the activity (*v*) of one enzyme at the corresponding metabolic locus; but, for reasons just stated in the first paragraph of this section 2.3, the activity (*v*) of each of the other enzymes will alter, the flux (*J*) will change, and the *concentrations*of all the metabolites (*S*~1~-*S*~5~) will also change, some more than others, until the system settles to a new steady state.
Thus, finite changes in the magnitude of *any one*of the internal or external *parameters*of the system will shift the original values of *all*the *variables*of the system to a new set of steady-state values. But, providing the external parameters *X*~0~and *X*~6~are kept constant, we can be sure that a change in any one selected internal parameter (an allele or an enzyme) would be the sole cause of any changes in the system variables. In short, we are obliged to adopt a whole-system (a systemic) approach if we want to understand how the flux to a trait component responds to a change in any one internal or external parameter of the system, no matter how that change in a parameter value is brought about. We are here concerned with changes in any one *internal*parameter such as a *mutation*in one or both alleles of a diploid cell.
Suppose the activity of any one of the enzymes *E*~1~to *E*~6~in Figure [1](#F1){ref-type="fig"} were to be changed stepwise (e.g. by a series of mutations of one or both alleles at a locus in a diploid) so that the residual activity of the enzyme was decreased in successive steps to, say, 75%, 60%, 45%, 25%, 0% of its initial activity. How would the flux (flow) through the whole series of enzymes vary; i.e. how would the flux (to a trait component) respond, and how would the concentration of that molecular component of a trait respond, when any one enzyme activity was changed by mutation in a series of finite steps?
It was shown, by experiment, that graded changes in the activity of any one of four different enzymes in the arginine pathway resulted in a non-linear (quasi-hyperbolic) response of the flux to arginine in constructed heterokaryons of *Neurospora crassa*(\[[@B3]\], Figures [1a,1b,1c,1d](#F1){ref-type="fig"}). Similar non-linear (non-additive) flux responses were observed when a series of mutations occurred in a single enzyme in four other metabolic pathways in four different diploid or polyploid systems (\[[@B3]\], Figures [1e,1f,1g,1h](#F1){ref-type="fig"}). Similar flux responses were observed during genetic down-modulation of any one of five enzymes involved in tryptophan synthesis in *Saccharomyces cerevisiae*\[[@B5]\]. The same quasi-hyperbolic response of a defined flux to a series of graded changes in one enzyme activity was observed in a haploid cell \[[@B6]\]. We can therefore dismiss the possibility that these non-linear responses (of a flux-to-a-trait-component) were restricted to the systems investigated by Kacser and Burns \[[@B3]\] or were in some way related to the ploidy of the cells and organisms they studied.
On the contrary, the various flux responses are a fundamental *biochemical property*of the fluxing metabolic system. It does not matter how the graded changes in activity of any one enzyme are brought about. Mutation is one way but not the only one. Graded replacement of a defective gene that expressed the chloride translocator in the cystic fibrosis mouse produced continuously non-additive responses of various functions associated with chloride transport, including the duration of the survival of the mouse \[[@B7]\]. Induced synthesis of graded concentrations of a single membrane-located enzyme resulted in continuously non-linear changes in growth rate, glucose oxidation, the uptake and phosphorylation of α-methyl glucose by *Escherichia coli*cells \[[@B8]\].
Stepwise decreases in cytochrome c oxidase activity (by titrating rat muscle mitochondria with an enzyme-specific inhibitor) had little effect on respiration until the enzyme activity was decreased to about 25% of normal; further decreases in this one enzyme activity caused a precipitous, continuously non-linear, decrease in mitochondrial respiration \[[@B9]\]. Other examples of non-linear (non-additive) responses of a defined flux to a change in activity of one enzyme in a metabolising system have been recorded \[[@B10]\], \[\[[@B11]\], Figures [6.2,6.3,6.4,6.6.6.7,6.8](#F6){ref-type="fig"}\]. The results of these various \"genetic\" and \"biochemical\" experiments illustrate the generality of the statement by Kacser and Burns \[[@B3]\] quoted in section 2.1 of this article.
::: {#F6 .fig}
Figure 6
::: {.caption}
######
Biochemistry and genetics merged thirty years ago. The symbol  indicates the catalysed translocation of an extracellular substrate or substrates (*X*~3~) and the subsequent intracellular catalysed transformations, including scavenging pathways, that form nucleoside triphosphate (NTP) precursors for the transcription process. Similarly,  indicates the catalysed translocation of the extracellular substrates (*X*~2~) and the subsequent synthesis from (*X*~2~), and other intracellular substrates, of the amino acid (AA) precursors for the translation process. The enzymes subsumed as *E*~Ts~and *E*~Tl~are involved in the final stages of the expression (transcription and translation) of genes g1, g2, g3, g4 - - etc as polypeptides (P~1~, P~2~, P~3~, P~4~- - etc). In diploid cells a pair of proteins will be synthesised from each pair of alleles at a gene locus. Those pairs of polypeptides (proteins) that are catalytically active in a diploid cell are represented by the single symbols *E*~1~, *E*~2~, *E*~3~, *E*~4~- - - etc in this Figure 6. Further details are given in Section 5.5.
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2.4. A rational explanation for the origin of dominant and recessive traits
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How did the observations of non-linear responses of individual fluxes to graded changes in any one enzyme activity lead to a rational explanation for the origin of Mendel\'s dominant and recessive trait classes \[[@B2]\]? For reasons already given, we cannot arrive at the answers to this question by relying on the illogical and illegitimate idea that alleles are themselves dominant or recessive. Such entities have never existed and do not now exist. Alleles can only be normal or abnormal (i.e. normal or mutant). If the ploidy of the cell cannot explain the non-additive response of a flux to mutations in an allele, it is equally certain that naming alleles as dominant or recessive will not provide the explanation \[[@B1]\]. We need to focus attention on the universally observed non-linear (often quasi-hyperbolic) responses of the flux-to-a-trait-component (and the concomitant change in concentration of that component) when the activity of any one enzyme, within a metabolic system of enzymes, is changed (decreased or increased), in stages, by any means available (including down-modulation by mutation and up-modulation by increasing the gene dose).
In this Section 2.4, and in Sections 2.5--2.7, consideration of the role of allele pairs (*uu*,*uU*,*UU*) in determining the outcome of mutations or changes in gene dose is set aside; this role will be considered in Section 2.8. For the moment, attention is focussed on what can be learned from the non-linear response of a flux -- to the molecular component(s) of a trait -- when the activity of one enzyme in a metabolic system is changed in graded steps by mutation or by changes in gene dose. Figures [1a,1b,1c,1d](#F1){ref-type="fig"} in Reference \[[@B3]\] showed that the flux to the normal trait component (arginine), and thus the concentration of arginine, was not significantly diminished before any one of four enzyme activities was decreased by more than 50%. In Figures [1b,1d](#F1){ref-type="fig"} the enzyme activity was decreased to about 15% of normal activity in *Neurospora crassa*before any significant diminution in the flux to arginine (and in the concentration of arginine) was detectable \[[@B3]\]; any further diminution of either enzyme activity caused a continuous but precipitous fall in the production of this trait component. Similar characteristics were displayed by a diploid (Figure [1h](#F1){ref-type="fig"} in Reference \[[@B3]\]). Figure [2](#F2){ref-type="fig"} represents these observations. Flux response plots with these characteristics are quasi-hyperbolic and asymmetric in the sense that, over low ranges of enzyme activity, the flux (and the metabolite concentrations in that fluxing pathway) respond markedly to small increases or decreases in enzyme activity; on the other hand, over high ranges of enzyme activity, substantial changes in activity have a small, if any, effect on the flux to a trait component and on the concentrations of the molecular components of a defined trait. A change in any \"Flux-to-trait-component\" implies a change in the concentrations of those metabolic products that typify a defined trait.
It was shown that a dominant trait (*A*) corresponded to the normal (100%) activity of the enzyme that was subsequently mutated to give lower activities \[[@B3]\]; i.e., the plotting co-ordinate (wild-type enzyme activity *versus*trait *A*) defined the terminus of the asymptote of the flux response plot depicted in Figure [2](#F2){ref-type="fig"}. A hybrid (*H*) must then correspond to *any*point on the asymptote of Figure [2](#F2){ref-type="fig"} that would not allow us (and would not have allowed Mendel) to distinguish a F1 hybrid (*H*) from its parent that displayed a dominant trait (*A*). A recessive (*a*) must then correspond to *any*point on the steeply falling part of the flux-response plot (Figure [2](#F2){ref-type="fig"}) that would allow us (or would have allowed Mendel) to *distinguish*the dominant trait (*A*) and the hybrid (*H*) from the recessive trait (*a*), e.g. dominant trait red flowers and hybrid red flowers from the recessive trait white flowers \[[@B1]\]. Note especially that a recessive trait would not *necessarily*correspond to zero flux (a complete metabolic block and a complete absence of the normal, downstream, metabolic products) in Figure [2](#F2){ref-type="fig"}.
The paper by Kacser and Burns \[[@B3]\] thus explains, for the first time in 115 years, how recessive *traits*arise from a sufficient decrease, by mutation, in one enzyme activity when that enzyme is embedded in a metabolic system. The explanation depends on recognising that when graded changes occur by mutation (in one, both or all of the allozymes at *any one*metabolic locus in biochemical pathways) there will be a non-linear response of the flux to the molecular component(s) of a defined trait; and concurrently a non-linear response of the concentrations of the normal molecular components of a trait (section 2.3).
Section 2.9 in reference \[[@B1]\] showed that it was difficult to understand how Mendel\'s recessive traits (*a*) were displayed in 1/4 of his F2 population of plants (*A*+ 2*Aa*+ *a*) when these same recessive traits were not displayed in Mendel\'s hybrids (*Aa*). We have replaced Mendel\'s implausible idea that his F1 hybrids (*Aa*) displayed only trait (*A*). We have substituted the plausible idea -- based on experimental evidence \[[@B3]\] -- that, under certain conditions, the F1 hybrid trait (*H*) is *indistinguishable*from trait (*A*). In the treatment advocated here, there is no problem in understanding how 1/4 of the individual plants in the F2 population of genetically related plants (*A*+ 2*H*+ *a*) displayed the recessive trait (*a*). We can now also see why Mendel emphasised the need to study crosses between parental plants that displayed readily distinguishable trait forms, e.g. red flowers (*A*) in one parent and white flowers (*a*) in the other \[[@B1]\]. Figure [2](#F2){ref-type="fig"} shows that this distinction would be possible only if the activity of one enzyme in the dominant trait plant was sufficiently diminished in the recessive trait plant.
Note too that *trait*dominance and *trait*recessivity are not independent phenomena (nor are they opposite, one to the other). We cannot define a dominant trait except as an alternative to a recessive trait; both traits must be observable before we can identify either of them. The statements in these last two sentences were obvious in Mendel\'s original paper \[[@B2]\] but they have been inexplicably overlooked by many later authors.
2.5. Mendel\'s 3(dominant):1(recessive) trait ratio occurs sometimes, not always
--------------------------------------------------------------------------------
Does this explanation for the *origin*of dominant and recessive traits also account for the occurrence of Mendel\'s 3(dominant):1(recessive) trait ratio? The answer is yes. Does it also explain why this ratio is not always observed? The answer is again, yes (although the original authors \[[@B3]\] did not pose or answer these two questions).
If the flux response plot is *sufficiently asymmetric*(approaches a hyperbolic plot, as in Figure [2](#F2){ref-type="fig"}), the concentration of molecular components of a defined trait will not be measurably different (when the activity of one enzyme is decreased by, say, 50%) from the concentrations of those same molecular components when the enzyme activity was 100%.
If the trait displayed by the hybrid (*H*) is indistinguishable from the trait (*A*), as in Figure [2](#F2){ref-type="fig"}, the trait distribution in the F2 population (*A*+ 2*H*+ *a*) becomes 3(*A*) + (*a*); i.e. the trait ratio in this population will be 3(dominant):1(recessive). This explanation for the occurrence of the 3:1 trait ratio in Mendel\'s, or any other F2 population of cells or organisms, depends entirely on an experimentally observed, sufficiently asymmetric, response of the flux (to the molecular components of defined trait) when changes occur in enzyme activity at any one metabolic locus in a fluxing biochemical pathway (Figure [1](#F1){ref-type="fig"}). It does not depend on the naïve and illegitimate assumption that alleles are either dominant or recessive (Sections 3.2, 3.3, 4 in Reference \[[@B1]\]).
Figure [2](#F2){ref-type="fig"} illustrates one of a family of regularly non-linear (non-additive) response plots which exhibit various degrees of asymmetry \[[@B3]\]. Is the flux response always sufficiently asymmetric for the 3:1 trait ratio to be observed? It is not. A flux response was observed in one particular (diploid) metabolic system (Reference \[[@B3]\], Figure [1f](#F1){ref-type="fig"}) that was still clearly non-linear (non-additive) but not as asymmetric as that shown in Figure [2](#F2){ref-type="fig"}. As in Figure [2](#F2){ref-type="fig"}, so in Figure [3](#F3){ref-type="fig"}, a recessive trait (*b*) can be clearly distinguished from the dominant trait (*B*) because the concentrations of the molecular components of this trait were sufficiently different when one enzyme activity in the metabolic system is decreased to a sufficient extent. The trait displayed by the hybrid (*H*) is now *distinguishable*(rather than indistinguishable) from the dominant trait (*B*) expressed in a genetically related normal cell or organism when, as in Figure [2](#F2){ref-type="fig"}, the enzyme activity is decreased to an arbitrarily chosen 50% of the normal activity. The 3(dominant):1(recessive) trait ratio will not then be observed (Figure [2](#F2){ref-type="fig"}). A blend of traits (*B*) and (*b*) is possible in the hybrid (*H*), for example when traits (*B*) and (*b*) are distinguished by colour differences.
::: {#F3 .fig}
Figure 3
::: {.caption}
######
Mendel\'s 3(dominant):1(recessive) trait ratio does not always occur. Mendel\'s notation for a dominant trait, a hybrid and a recessive trait were (*B*), (*Bb*) and (*b*) respectively. For reasons given in the preceding paper \[1\], the hybrid is represented in Figure 3 by (*H*). When graded changes are made in any one enzyme in a metabolic pathway the response of the flux through that pathway is always non-linear (non-additive) but not always quasi-hyperbolic (Figure 2). Consequently when the enzyme activity at one metabolic locus is decreased in the heterozygote to (say) 50% of wild-type, the trait displayed by the hybrid (*H*) is now distinguishable from the trait (*B*) displayed by the wild type cell or organism and from the trait (*b*) displayed by the homozygously mutant cell or organism. Mendel\'s 3(dominant):1(recessive trait ratio will not be observed. The explanation is consistent with the explanation for the observation of the 3:1 trait ratio in Figure 2 and achieves what the currently favoured explanation of Mendel\'s observations cannot achieve \[1\].
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2.6. Dominant and recessive traits are not always observed
----------------------------------------------------------
It is well known that dominance and recessivity are not universally observed. Are they therefore of no significance? Some authors have been tempted to think so. Their view is understandable because, before the work of Kacser and Burns \[[@B3]\], we lacked any credible explanation for the occurrence of dominant and recessive traits.
Can we now see why dominance and recessivity are not always observed? The answer is again, yes. Examination of Figure [2](#F2){ref-type="fig"} and Figure [3](#F3){ref-type="fig"} shows that it will be possible to observe dominant *and*recessive traits in genetically related organisms only when the enzyme activity at a metabolic locus is decreased from 100% to an activity approaching, but not necessarily reaching, 0% activity.
When the response plot is of the kind shown in Figure [2](#F2){ref-type="fig"}, it would be possible to decrease the expressed enzyme activity at a metabolic locus by at least 75%, perhaps by 85%, without eliciting any detectable change in trait from that displayed by the wild-type or normal organism. In other words some mutations will not, apparently, display Mendelian dominance and recessivity (dominant and recessive *traits*).
Only if the effective enzyme activity is decreased by at least 95% in this instance (Figure [2](#F2){ref-type="fig"}), would clear dominance and recessivity be noted. This is an extreme case; Figure [3](#F3){ref-type="fig"} illustrates the other extreme. Between these extremes, various degrees of asymmetry of flux response plots may be observed (Figure [1](#F1){ref-type="fig"} in Reference \[[@B3]\]). Nevertheless, unless: (i) the change in enzyme activity is measured, (ii) it is realised that there is a non-additive relationship between a change in any one enzyme activity at a metabolic locus and a change in expressed trait, and (iii) the shape of the flux response plot (Figure [2](#F2){ref-type="fig"}, Figure [3](#F3){ref-type="fig"}) is revealed by plotting, it is simply not possible to state that the system under investigation does or does not display Mendelian dominance and recessivity. Terms such as semi-dominance merely indicate that the flux response plot is not quite asymmetric enough to be sure that a 50% reduction in enzyme activity produces a trait that is indistinguishable from the dominant trait.
2.7. Is the Kacser & Burns treatment universally applicable?
------------------------------------------------------------
The change in the *concentrations*a normal metabolites has been treated in the present article as the source of a change in trait. This accords with the treatment in Figure [1](#F1){ref-type="fig"} of reference \[[@B3]\]. Allowance should, however, be made for the possibility that the change in concentration of a metabolite is, in reality, a change in the concentration of a \"signalling\" metabolite (e.g. an allosteric activator or inhibitor of another enzyme in the pathway that generated the \"signalling\" metabolite, or in another pathway). Such mechanisms merely shift the cause of the change in metabolite concentration to another part of the matrix of intracellular metabolic pathways. In other words, the Kacser and Burns approach remains a valid explanation for the origin of dominant and recessive traits.
2.8. Accounting for all the plotting points in Figures [2](#F2){ref-type="fig"} and [3](#F3){ref-type="fig"}
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In Figure [2](#F2){ref-type="fig"}, the relative enzyme activities (100, 50, 0) would be expressed from the series of allele pairs *UU*, *Uu*, *uu*in a diploid cell (Section 1) only if the mutant allele (*u*) was expressed as a catalytically inactive polypeptide. The same considerations apply to the relative enzyme activities expressed from the allele pairs *WW*, *Ww*, *ww*in Figure [3](#F3){ref-type="fig"}.
It is obvious that the continuously non-linear response plots (Figures [2](#F2){ref-type="fig"}, [3](#F3){ref-type="fig"}; and References \[[@B3]-[@B10]\]\]) could not be constructed if these three allele pairs were the only ones available to express a corresponding series of enzyme activities. Figure [1](#F1){ref-type="fig"} in Reference \[[@B3]\] showed that more than three distinct enzyme activities were observed in experimental practice in any one system. It is easy to see how relative enzyme activities other than 0, 50, 100 could be observed in a polyploid or heterokaryon (Figure [1a,1b,1c,1d,1e](#F1){ref-type="fig"} in Reference \[[@B3]\]). To account for the occurrence in a diploid of relative enzyme activities in addition to those taking values of 0, 50, 100 (in Figures [2](#F2){ref-type="fig"} and [3](#F3){ref-type="fig"}, and in Figures [1f,1g,1h](#F1){ref-type="fig"} of Reference \[[@B3]\]), we need to allow for allele pairs in addition to the three (*UU*, *Uu*, *uu*or *WW*, *Ww*, *ww*) in which the mutant alleles (*u*or *w*) express a catalytically inactive polypeptide.
The restriction to just three allele pairs in a diploid may be traced to Sutton \[[@B1]\]. He wrote Mendel\'s F2 trait series (*A*+ 2*Aa*+ *a*), incorrectly, as (*AA*+ 2*Aa*+ *aa*) and the number of distinguishable chromosome pairs as (*AA*+ 2*Aa*+ *aa*), so establishing a false one-for-one relationship between pairs of chromosomes (*AA*or *aa*) and dominant or recessive traits (*AA*or *aa*). Sutton\'s notation for chromosome pairs was later transferred to allele pairs. In this article, dominant and recessive traits are represented, as Mendel did, by (*A*) and (*a*) respectively; alleles have been represented by different letters (e.g. *UU*, *Uu*, *uu*) in order to distinguish alleles (parameters) from traits (variables). We should allow for the situation where (*U*^†^) is a mutant of (*U*) that would express an allozyme activity lower than that expressed from (*U*) but not so low as that expressed from (*u*); and where (*u*\*) would be a mutant of (*U*) that expresses an allozyme activity greater than that expressed by (*u*) = 0 in the traditional treatment but not so great as to merit the notation (*U*). The outcome of different hypothetical crosses that involve different mutations of one both alleles at a given locus in genetically related diploid parents would then be as follows:
\(1) Repeated crosses (*Uu*× *Uu*) would give, on average, the allele series (*UU*+ 2*Uu*+ *uu*) thus permitting expression of no more than three distinctive enzyme activities at the corresponding metabolic locus.
\(2) The cross (*Uu*\* × *Uu*) would give the allele series (*UU*+ *Uu*+ *Uu*\* + *uu*\*) in which two of the allele pairs differ from those in the progeny of the first cross; and in which three different heterozygotes are formed.
\(3) The cross (*U*^†^*u*× *Uu*) would give the allele series (*UU*^†^+ *Uu*+ *U*^†^*u*+ *uu*) in which only one allele pair in the progeny populations is identical with one of the allele pairs in the progeny from the second cross.
\(4) The cross (*UU*^†^× *Uu*) would give, on average, the allele series (*UU*^†^+ *UU*+ *Uu*+ *U*^†^*u*) which has only two allele pairs in common with the progeny of the third of these crosses of genetically related parents.
\(5) The cross (*U*^†^*u*× *Uu*\*) would give, on average, the allele series *(UU*^†^*+ U*^†^*u\* + Uu + uu\*)*.
In the second and fourth crosses it was assumed that the two heterozygous parents did possess exactly the same normal allele (*U*) at this particular locus so, among their progeny, the allele pair (*UU*) occurred. Analogously, among the progeny from the third cross, the allele pair (*uu*) occurred. But, importantly, in each of crosses (2), (3) and (4) three different heterozygotes occurred in each progeny population (a heterozygote is defined in a diploid by the occurrence of allele pairs other than those represented here by *UU*or *uu*). The allele pairs in the heterozygotes in any one progeny population of these crosses (2), (3) and (4) are not all identical with those in the progeny of another of these crosses. The parents in the fifth cross did not share an identical allele; no two alleles of a pair are then identical in the progeny. The allele pair (*Uu*) occurs in all of the progeny of these five crosses but only because one of two parents carried this allele pair or because one parent carried allele (*U*) and the other carried allele (*u*).
Cross (1) typifies events in self-fertilising organisms but is not typical of sexual reproduction in other organisms (cf Figure [2](#F2){ref-type="fig"} in reference \[[@B1]\]). Male and female parents that are *identically*heterozygous at any locus must be rare. Crosses (2)-(5) between two heterozygous parents will produce, under the circumstances noted above, truly homozygous allele pairs (such as *UU*and *uu*) but they will also produce, on average, three different heterozygotes among their progeny (four heterozygotes in the fifth cross).
The consequences are then as follows: From each locus in a diploid cell that expresses catalytic polypeptides, allozymes (pairs of enzymes) will be expressed; one from the gamete donated by the male parent the other from the gamete donated by the female parent. For simplicity, it will be assumed here that the combined allozyme activity at each catalytic locus in the metabolic pathways of the cell is the sum of the activities the two allozymes at each such locus.
The traditional allele series (*UU*+ 2*Uu*+ *uu*) in a diploid will then generate the enzyme series (*EE*+ 2*Ee*+ *ee*) at one metabolic locus in different, genetically related, individuals. This enzyme series provides two extreme combined allozyme activities, namely 100% (*EE*) and 0% (*ee*). There are no allele pairs at this locus that could provide \<0% or \>100% enzyme activity. All other allele pairs, e.g. (*UU*^†^), (*U*^†^*u*), (*U*^†^*u\**), (*Uu\**), (*uu\**), would provide combined allozyme activities that lie between the 100% and 0% values just described. Only if *(u)*happens to be a null mutant, will the heterozyote (*Uu*) express a single enzyme activity (*v*) equal to 50% of the maximum available from (*UU*). Only in this circumstance will the allele pair (*uu*) express two inactive polypeptides; the enzyme activity will then be zero at a metabolic locus and a \"metabolic block\" will occur at that locus.
Assembling the data from, for example, the second and third of the three hypothetical crosses between the genetically related parents described above gives an allele series (*UU*, *UU*^†^, *U*^†^*u*, *Uu*, *Uu*\*, *uu\*, uu*). They would contribute seven different allozyme pairs (*EE*, *EE*^†^, *E*^†^*e*, *Ee*, *Ee\**, *ee*\*, *ee*) at one metabolic locus and seven different, single, enzyme activities (*v*), one from each pair of allozymes. Given a range of enzyme activities in excess of the traditional three, a sufficient number of co-ordinates will be available to establish a continuously non-additive plot of the response of one defined flux (*J*) against changes in enzyme activity (*v*) at one metabolic locus in genetically related cells or organisms (Figures [2](#F2){ref-type="fig"}, [3](#F3){ref-type="fig"}). There is no guarantee that all of these mutants will be generated in every case but since (*U*^†^) and (*u\**) each represent only one of several possible mutations of allele (*U*), we may be reasonably confident of observing traits expressed from allele pairs in addition to, or instead of, those expressed from the two traditional mutant pairs (*Uu*) and (*uu*). Assembling sets of enzyme activity and flux (or metabolite concentration) data from the progeny of different but genetically related parents then creates the non-linear flux response plots illustrated in Figures [2](#F2){ref-type="fig"} and [3](#F3){ref-type="fig"}. All plotting points in the idealised Figures [2](#F2){ref-type="fig"} and [3](#F3){ref-type="fig"} should be regarded as tokens for the experimental plots published earlier \[[@B3]\].
This simple explanation for the occurrence of more than three co-ordinates for a plot of flux response against changes in enzyme activity (or gene dose) means that it is no longer acceptable to base arguments and conclusions on the assumed presence of only one heterozgote (*Uu*) in a diploid allele series at a locus, and on only one corresponding hybrid trait. Furthermore, statements that all heterozygotes express 50% (and only 50%) of the phenotype expressed from the homozygous wild-type are based on the false idea that the mutant allele (*u*) always produces a totally inactive enzyme. Figures [1a,1b,1c,1d,1e,1f,1g,1h](#F1){ref-type="fig"} of Reference \[[@B3]\] depended upon the availability of 5, 6 or 7 plotting points relating the flux response to experimentally determined changes in enzyme activity (effectively to changes in allele constitution at a locus). In addition to the traditional heterozygote (*Uu*), there must be a number of heterozygotes (e.g. *UU*^†^, *U*^†^*u*, *Uu*\*, *uu\**), and a corresponding a range of enzyme activities (*v*), that account for the response of a flux (*J*) to a change in enzyme activity at one metabolic locus (Figures [1](#F1){ref-type="fig"}, [2](#F2){ref-type="fig"}, [3](#F3){ref-type="fig"}). In Figure [2](#F2){ref-type="fig"}, some of these additional heterozygotes will establish the asymptote of the flux response plot. The trait expressed from any such heterozygote would be indistinguishable from the trait expressed from the normal allele pair (*UU*); they could have accounted for the occurrence of Mendel\'s hybrids (*Aa*) which appeared to display only the dominant trait (*A*). This is further evidence that the traditional treatment of elementary Mendelian genetics is inadequate and misleading \[[@B1]\].
3. Quantifiable differences between any two forms of a trait
============================================================
Differences in traits are generally and usefully described by qualitative terms:
hirsute/bald; red flowers/white flowers; lithe/obese; muscular/\"skinny\"; slow/fleet; albino/black. Such descriptive terms do, however, disguise the obvious fact these apparently qualitative differences in outward appearance are based on quantitative differences in the concentrations of molecular products that contribute to the outward appearance or function of a cell or organism.
These comments apply to the apparently qualitative differences examined by Mendel (Table 1 in reference \[[@B1]\]) and to those traits forms typified by a trait series (*A*+ 2*H*+ *a*) where (*A*) indicates the dominant trait form, (*a*) the recessive trait form and (*H*) a hybrid trait that may be indistinguishable (Figure [2](#F2){ref-type="fig"}) from the dominant traits (*A*) or distinguishable (Figure [3](#F3){ref-type="fig"}) from the dominant trait (*B*).
It should not therefore be supposed that the paper by Kacser and Burns \[[@B3]\] provided an explanation only for the occurrence of qualitative differences between any two traits. On the contrary, a continuously variable response of each of several defined fluxes was brought about when mutations of alleles at one locus changed the activity of one enzyme in a metabolic pathway (or when changes in gene dose changed the concentration and thus the activity of one enzyme in a metabolic pathway).
The flux responses were labelled \"Flux to arginine\", \"Flux to biomass\", \"Flux to melanin\", \"Flux to products\", \"Flux to DNA repair\" (Figure [1](#F1){ref-type="fig"} in reference \[[@B3]\]). The molecular *compositions*of \"arginine\", \"biomass\", \"melanin\", and \"products\" (of ethanol metabolism) were not changed. Their *concentrations*were changed as graded mutations at a gene locus caused graded changes in one enzyme activity in those pathways that created arginine, biomass, melanin, or the products (of ethanol metabolism). Similarly, a change in the \"flux to DNA repair\" was achieved by graded increases in the dose of the gene specifying the synthesis of the \"repair enzyme\" that excises covalently-linked adjacent thymines in DNA and allows incorporation of thymidine in place of the excised pyrimidines. This \"repair enzyme\" activity is absent in *Xeroderma pigmentosum*patients.
Additional examples of quantitative changes in the concentration of molecular components of a trait will be found in other publications \[[@B5]-[@B11]\]. None of these changes provide any justification for representing a trait by twinned letters, e.g. (*AA*) or (*aa*). The single letters (*A*) and (*a*) stood for qualitative differences in trait form in Mendel\'s work; they stand equally well for quantitative changes in a trait in modern work. The non-linear response plots of Kacser and Burns \[[@B3]\] apply to quantitative and to apparently qualitative changes in the phenotype that arise from mutations of any one enzyme at a metabolic locus in a biochemical pathway.
4. Implications of the systemic approach of Kacser and Burns \[[@B3]\]
======================================================================
Figure [2](#F2){ref-type="fig"} shows the response of the phenotype to changes in enzyme activity at a metabolic locus or to changes in gene dose at the corresponding gene locus. It follows, if the response plot takes this form, that *increasing*the dose of this particular gene in a wild-type haploid cell (or the dose of the normal homozygous alleles in a wild-type diploid or polyploid cell) is unlikely to produce a detectable change in the phenotype (e.g. an increase in the concentration of the trait component produced by a metabolic pathway; or a change in cell function associated with that pathway). It was demonstrated that it was necessary, under these circumstances, to increase concurrently the gene dose at each of no fewer than five loci if significant increases in the flux (and in the concentration of metabolic product) was to be achieved \[[@B5]\]. The systemic approach to a rational explanation of the origins of dominant and recessive traits \[[@B3]\] has obvious implications for biotechnologists.
Figure [2](#F2){ref-type="fig"} (representing several plots in Reference \[[@B3]\]) also suggests that somatic recessive conditions (in contrast to so-called dominant conditions) could be ameliorated by partial gene replacement therapy. Experiments in the cystic fibrosis mouse model support this suggestion \[[@B7]\]; they show that the systemic approach to the origins of dominant and recessive traits has implications for medical genetics.
It was pointed out (section 2.6) that substantial *decreases*in the dose of normal alleles at any one locus (or in the enzyme activity at the corresponding metabolic locus) may not elicit detectable changes in the trait(s) of the cell. In other words, given a response plot approximating to that shown in Figure [2](#F2){ref-type="fig"}, traits -- including associated cell functions -- are inherently buffered against substantial increases or decreases in the dose of any one gene, or against substantial changes in enzyme activity at the corresponding metabolic locus. This appears to be the probable origin of the so-called \"robustness\" or buffering of chemotaxis against changes in enzyme kinetic constants \[[@B12]-[@B15]\].
This proposed explanation for metabolic buffering is quite general; it does not depend on the particular kinetic mechanisms that have been suggested to account for this buffering \[[@B12]\]; it also suggests that there is no need to postulate the presence of diagnostic \"biological circuits\" as the source of this buffering of the phenotype against mutations at a single locus.
Attempts to improve the concentration of metabolic products by increasing the gene dose at one locus above that available in the wild-type or normal cell could be successful, at least to some self-limiting extent, if a response plot like Figure [3](#F3){ref-type="fig"} applies. Induced synthesis of one membrane-located enzyme activity to between 20% and 600% of wild-type activity illustrates the possibility \[[@B8]\]. In this instance, plots like Figure [3](#F3){ref-type="fig"} applied only to changes in the uptake and phosphorylation of α-methyl glucoside; changes in growth rates and glucose oxidation gave response plots like Figure [2](#F2){ref-type="fig"}. The explanation for the difference may lie in the suggestion \[[@B3]\] that shorter pathways will yield response plots like Figure [3](#F3){ref-type="fig"}, while the longer the pathway, the more likely is it that markedly asymmetric plots like Figure [2](#F2){ref-type="fig"} will be observed.
5. Expansions of the present treatment
======================================
5.1. Why mutating one enzyme in a metabolic pathway may alter more than one trait; and mutating more than one enzyme may annul these changes in more than one trait
-------------------------------------------------------------------------------------------------------------------------------------------------------------------
If the explanation for the origin of dominant and recessive traits depends on realising that fluxing metabolic pathways generate the molecular components of all traits, and that mutating any one enzyme in these pathways alters the flux and the concentrations of those normal metabolic products that are molecular components of a trait, other genetic phenomena could perhaps also be explained. Only two of the thirteen texts surveyed \[[@B1]\] gave a definition, in their glossaries, of pleiotropy and epistasis. Both agreed that pleiotropy was a phenomenon where a change at one gene locus brought about a change in more than one trait. Both attributed epistasis to an interaction between genes or their alleles. Neither of these descriptions of pleiotropy and epistasis is particularly revealing.
The following account, like those preceding it, does not depend on the fiction that all mutations generate inactive enzymes. Figure [1](#F1){ref-type="fig"} is elaborated as shown in Figure [4](#F4){ref-type="fig"}. One pathway, like that shown in Figure [1](#F1){ref-type="fig"}, is now coupled to another analogous pathway by the conserved metabolite pair (*p*, *q*). The sum of the concentrations of (*p*) and (*q*) is constant (is conserved) but the ratio of the two concentrations (*p*/*q*) is a free variable. All the characteristics of the metabolic system in Figure [1](#F1){ref-type="fig"} (Section 2), apply to each of the two fluxing pathways in Figure [4](#F4){ref-type="fig"}. Claims in the biochemical literature in the past that changes in the ratio (*p/q*) controlled metabolic fluxes were and remain untenable; one variable of a system cannot be said to control another variable of the system.
::: {#F4 .fig}
Figure 4
::: {.caption}
######
Accounting for the occurrence of pleiotropy. One unbranched pathway is coupled to another by a conserved metabolite pair *p*and *q*. Such coupling is not uncommon in cellular systems and is one source of pleiotropy. Mutation of any one enzyme in one pathway will affect both fluxes (*J*~a~and *J*~b~) to a trait component and the concentrations of those trait components. See also Figure 5. Figure 4, like Figure 1, illustrates the need to adopt a systemic approach in attempts to understand the responses of a metabolising system to changes in any enzyme activity brought about by mutation.
:::
:::
Figure [1](#F1){ref-type="fig"} may also be elaborated as shown in Figure [5](#F5){ref-type="fig"}. An input flux from *X*~1~to *S*~4~divides into two output fluxes \[[@B16]\]. Of the input flux, a proportion (α) enters one of the two output fluxes (*J*~a~) and a proportion (1-α) enters the other output flux (*J*~b~). The magnitude of (α) is determined by the magnitudes of the activities of all the enzymes of the metabolic system; (α) is a systemic characteristic \[[@B17]\]. Again, all the characteristics of the model metabolic system in Figure [1](#F1){ref-type="fig"} (Section 2), apply to each of the two pathways that generate fluxes *J*~a~and *J*~b~shown in Figure [5](#F5){ref-type="fig"}.
::: {#F5 .fig}
Figure 5
::: {.caption}
######
Accounting for the occurrence of pleiotropy and epistasis. Mutation of any one of enzymes *E*~2~, *E*~3~, *E*~4~would affect both fluxes *J*~a~and *J*~b~to separate trait components. Mutation of any one of enzymes *E*~5a~, *E*~6a~, etc would decrease flux *J*~a~to a trait component but increase *J*~b~to another trait component; the concentrations of trait components in pathway *J*~a~would decrease, those in pathway *J*~b~would increase. Epistasis would occur if a subsequent mutation occurred in any one of enzymes *E*~5b~, *E*~6b~etc. A branched metabolic pathway is thus a potential source of pleiotropy and epistasis; see the text for further discussion. This diagram, like that in Figure 4, emphasises the importance of adopting a systemic approach in understanding the potential effect, on a trait or traits, of a mutation in any one enzyme in enzyme-catalysed systems.
:::
:::
5.2. The origin of pleiotropy explained
---------------------------------------
It will be obvious that a mutation of any one enzyme in either of the two pathways of Figure [4](#F4){ref-type="fig"} will cause changes in the fluxes through both of the coupled pathways (and the concentrations of metabolites in both pathways). Similarly, a mutation in any one enzyme of the input flux of Figure [5](#F5){ref-type="fig"} will affect the concentrations of metabolites in both output fluxes *J*~a~and *J*~b~. Pleiotropy (a change in more than one trait as a consequence of a single mutation), when it is detected, is thus seen to depend on mutating an enzyme within a metabolic pathway, on the consequential changes in metabolite concentrations, and on the structure and interdependence of biochemical pathways. Only if one of the enzymes in the input pathway shows zero activity will both output fluxes (*J*~a~and *J*~b~) cease (Figure [5](#F5){ref-type="fig"}).
5.3. The origin of epistasis explained
--------------------------------------
Given a steady input flux from *X*~1~to *S*~4~(Figure [5](#F5){ref-type="fig"}), a mutation of one of the enzymes (*E*~5a~, *E*~6a~or any other enzyme in this output limb) would decrease flux *J*~a~and increase flux *J*~b~. The concentrations of metabolites in pathway *J*~a~would decrease and those in pathway *J*~b~would increase, a further example of a pleiotropic response to a single mutation. But suppose that, following the mutation of *E*~5a~, a mutation occurred in *E*~6b~or any other enzyme in this alternative output limb. Clearly, the effect of the first mutation on the cell characteristics would be at least partly nullified by the second mutation -- a phenomenon known as epistasis and sometimes attributed in genetic texts to an interaction between genes but shown here to depend on mutations of one or more enzymes, and on the structure and interdependence of metabolic pathways. Only if the activity of one of the enzymes in one of the two output pathways is diminished to zero by mutation, will the products of that output limb downstream from the mutation be lost.
If the fluxes proceeded in the opposite direction to that shown in Figure [5](#F5){ref-type="fig"} (so that two pathways merged into one), mutation of an enzyme in one of the input fluxes followed by a mutation of an enzyme in the other input pathway could again elicit epistatic responses in the system.
5.4. Are pleiotropy and epistasis always detectable?
----------------------------------------------------
Particular but common metabolic structures (Figures [4](#F4){ref-type="fig"}, [5](#F5){ref-type="fig"}) provide the potential for pleiotropy and epistasis; i.e. changes in concentrations of normal metabolites when an enzyme is mutated within a metabolic pathway. Whether pleiotropy or epistasis is detected, or not, will depend on the severity of the mutation and on the nature of the flux response plots (Figures [2](#F2){ref-type="fig"}, [3](#F3){ref-type="fig"}) as demonstrated in section 2.
5.5. Biochemistry and genetics are not separable topics
-------------------------------------------------------
Beadle and Tatum \[[@B18]\] isolated a series of mutants of *Neurospora crassa*and tested their ability to grow on basal medium or on basal medium supplemented with different metabolites or cofactors. Wild-type *Neurospora crassa*grew on basal medium. Different isolated mutants would grow only if the basal medium was supplemented with the specific product of an enzyme rendered partially or fully inactive in one of the mutants. These brilliant observations led to the paradigm \"one gene, one function\" \[[@B19],[@B20]\], later to \"one gene, one enzyme\". These observations \[[@B18]\] made explicit what was implied by the observations of Garrod \[[@B21]-[@B24]\]\] on inborn errors of metabolism namely: metabolism is catalysed by a sequence (or system) of different enzymes; and a sufficient decrease (by mutation) in the activity of any one enzyme may cause a change in the trait(s) or characteristic(s) of the system (e.g. the ability to grow, to accumulate cell mass \[[@B18]\]).
Beadle \[[@B20]\] expressed surprise that Garrod\'s work had received so little attention. He wrote: \"It is a fact both of interest and historical importance that for many years Garrod\'s book had little influence on genetics. It was widely known and cited by biochemists, and many geneticists in the first two decades of the century knew of it and the cases so beautifully described in it. Yet in the standard textbooks written in the twenties and thirties - - - - few mention its cases or even give a reference to it. I have often wondered why this was so. I suppose most geneticists were not yet inclined to think of hereditary traits in chemical terms. Certainly, biochemists with a few notable exceptions such as the Onslows, Gortner and Haldane were not keenly aware of the intimate way in which genes direct the reactions of living systems that were the subject of their science.\"
This lack of attention to the implications of Garrod\'s work is all the more surprising when it is recalled that Bateson \[\[[@B25]\], p.133\] pointed out that alkaptonuria (a change in concentration of the normal metabolite, homogentisic acid, and one of Garrod\'s inborn errors of metabolism) was an example of a Mendelian recessive trait or character; see also \[\[[@B26]\], p.19\]. In other words, some important aspects of genetics depended on recognising the role of changes in an enzyme activity, within a metabolic system, in effecting a change in a trait.
The aphorism \"one gene, one enzyme\" was refined to \"one allele, one polypeptide\" after the elucidation of the structure of DNA \[[@B27],[@B28]\] and the rapid advances made in the next 10 or 15 years in elucidating the mechanisms of expression of diploid alleles as pairs of polypeptides or proteins \[[@B29]-[@B32]\]\] most of which are enzymes \[[@B3],[@B4]\]. These more recent discoveries (Figure [6](#F6){ref-type="fig"}) emphasise what was implied by the work of Beadle and Tatum \[[@B18]\]: the molecular components of dominant and recessive traits or characteristics, in all biological forms, are generated by fluxing metabolic pathways catalysed by sequences or systems of enzymes. Dominant and recessive traits are not the direct product of the expression of alleles as suggested by the currently favoured explanation of Mendel\'s observations (Figure [2](#F2){ref-type="fig"} in Reference \[[@B1]\]); they are produced *indirectly*by a system of enzymes (Figures [1](#F1){ref-type="fig"}, [4](#F4){ref-type="fig"}, [5](#F5){ref-type="fig"}, [6](#F6){ref-type="fig"}).
Figure [6](#F6){ref-type="fig"} depicts the direct relationship between any one gene (g1, g2, g3, g4) and the synthesis of individual polypeptides (P~1~, P~2~, P~3~, P~4~) most of which, but not all, are enzymes (*E*~1~, *E*~2~, *E*~3~, *E*~4~). All polypeptides, catalytic and non-catalytic, are synthesised in this way.
*X*~1~, *X*~2~and *X*~3~in Figure [6](#F6){ref-type="fig"} are immediately identified as extracellular parameters of a cell system. *X*~3~stands for those substrates that lead, through a series of enzyme-catalysed reactions, to the synthesis of nucleoside triphosphates (NTPs) and their subsequent incorporation into mRNA. Note that mRNA is a terminal product of this pathway. It is a coding entity, a proxy for DNA. Each mRNA specifies the order of incorporation of individual amino acids into a polypeptide, but no individual mRNA molecule participates as a substrate in the subsequent steps of the catalysed formation of a polypeptide. The control of the overall expression of a gene as a polypeptide is therefore necessarily treated in Metabolic Control Analysis as a cascade of two fluxing metabolic pathways, one that starts at *X*~3~, the other that starts at *X*~2~\[[@B33]\].
*X*~2~stands for those extracellular substrates that lead, through a series of enzyme-catalysed reactions, to the synthesis *de novo*of amino acids (AAs) and their subsequent incorporation, along with any existing amino acids, into a polypeptide (P). In a haploid cell, one polypeptide is synthesised from each gene locus. In a diploid, one polypeptide is synthesised from each of two alleles at a gene locus. If these pairs of polypeptides are catalytically active, each enzyme in a diploid cell (*E*~1~, *E*~2~, *E*~3~, etc) consists of a pair of allozymes, one of each pair specified by the allele derived from the male parent, the other specified by allele derived from the female parent. Each pair of allozymes, whether normal or mutated, exhibits only one measurable activity (*v*) at a catalytic locus in a metabolic pathway. If the pairs of polypeptides (P) synthesised by a diploid cell are *not*catalytically active they will not, of course, play a direct role in catalysing a metabolic pathway. They may have other important functions (e.g. as hormones) and may be components of traits.
*X*~1~stands for all those initial extracellular substrates feeding the matrix of inter-dependent biochemical pathways that typify all functioning cells. It is these pathways that generate the non-protein, non-polyribonucleotide, molecular products of all cell traits.
Each of these three major fluxing pathways (Figure [6](#F6){ref-type="fig"}) is catalysed by a succession of enzyme-catalysed reactions as shown in Figure [1](#F1){ref-type="fig"}. The flux through any one of these pathways will respond to a mutation of any one enzyme in the pathway as shown in Figures [2](#F2){ref-type="fig"}, [3](#F3){ref-type="fig"}; any change in these fluxes could change the concentrations of the intermediate metabolites or the final product (section 2.3); but, provided mutations do not alter the specificity of an enzyme, they will not change the existing molecular structure or composition of these metabolites.
Most attention is concentrated on the pathway initiated by *X*~1~for the simple reason that this pathway stands for all the matrix of interdependent biochemical fluxes that generate such a wide range of the non-protein (and non-polyribonucleotide) molecular components of cell traits (e.g. skin pigments, membrane lipids, chlorophyll, xanthocyanins, non-peptide hormones, neural transmitters, chitin, serum cholesterol, peptidoglycans, etc, etc).
If any one of the three major pathways shown in Figure [6](#F6){ref-type="fig"} is coupled to another pathway (Figure [4](#F4){ref-type="fig"}) or contains a branch (Figure [5](#F5){ref-type="fig"}) there will be, potentially detectable, pleiotropic and epistatic responses to mutations of any of the pathway enzymes (section 5.3). Such pathway coupling and branching is a common feature of the pathways that start with one of the extracellular substrates typified by *X*~1~.
If the implications of the work of Beadle and Tatum \[[@B18]\] were not fully realised at the time, Figure [6](#F6){ref-type="fig"} might have suggested that a fresh approach to an understanding of the origins of dominant and recessive traits was needed. The currently favoured explanation for Mendel\'s findings (\[[@B1]\], Figure [2](#F2){ref-type="fig"}) does not take account of the biochemical pathways of the synthesis of enzymes (Figure [6](#F6){ref-type="fig"}) established 30--40 years ago, does not acknowledge that the molecular components of all traits are synthesised by systems of enzymes, does not take account of the change in concentration of molecular components of traits when any one enzyme is mutated, and fails to distinguish the system parameters (alleles) from the system variables (traits).
Note that changes in the concentrations of external metabolites (whether they are substrates like *X*~1~, *X*~2~, *X*~3~in Figure [6](#F6){ref-type="fig"}, or extracellular inhibitors or activators of intracellular enzymes) may effect changes in intracellular metabolism and consequently modify the effects of a mutation. This topic is not immediately relevant in the present article but is a notable feature of Metabolic Control Analysis. Descriptions of the role of the Combined Response Coefficient (*R*) in permitting extracellular effectors to modulate intracellular metabolism (and thus the effects of a mutation) will be found elsewhere \[[@B11],[@B34]-[@B36]\].
If pleiotropic and epistatic responses to a mutation are as common as is suggested (sections 5.1--5.4), the question then arises: how do we account for Mendelian segregation of traits during sexual reproduction? The answer lies in the fact that a mutation at a biochemical locus, within the matrix of interdependent pathways, has its most obvious effect on the most closely associated pathways. Distant pathways (on the scale of cellular dimensions) will be less obviously affected. Kacser and Burns (Reference \[[@B3]\], p.649) pointed out that \"This apparent independence of most characters makes simple Mendelian genetics possible, but conceals the fact that there is universal pleiotropy. All characters should be viewed as \'quantitative\' since, in principle, variation anywhere in the genome affects every character.\" Section 3 in the present article emphasised the importance of quantitative changes in cell traits. The considerations in this paragraph are germane to the apparent absence of a detectable change of phenotype in some so-called \'knock-out\' experiments.
6. Conditions that must be met to explain dominance and recessivity
===================================================================
The explanation advocated in this article for the origins of dominant and recessive traits from normal and mutant alleles in a diploid is based on:
\(i) An obligatory distinction, by notation and nomenclature, between the variables (traits) and the parameters (alleles and enzymes) of genetic/biochemical systems.
\(ii) The contention that the molecular components of all traits are the products of fluxing metabolic systems (Figures [1](#F1){ref-type="fig"}, [4](#F4){ref-type="fig"}, [5](#F5){ref-type="fig"}, [6](#F6){ref-type="fig"}).
\(iii) Experimental evidence for an inevitable non-linear response of a flux (through a metabolic system of enzymes) to graded changes in the activity of any one of those enzymes \[[@B3]\], evidence that is supported by a number of independent observations \[[@B5]-[@B11]\].
\(iv) A demonstration that dominant and recessive traits arise from changes in the concentration of the normal molecular components of a defined trait.
\(v) The argument that changes in concentration of a trait component may nevertheless be revealed as a qualitative change in that trait.
\(vi) A demonstration that both alleles (normal or mutant) at a locus in a diploid are generally expressed. If the normal allele expresses a catalytically active polypeptide, many mutants of this allele will express an enzyme with lower activity; a mutated enzyme with zero activity is an extreme case.
\(vii) The demonstration that an explanation of Mendel\'s observations cannot be based on an allele series containing only three terms (e.g. *uu*, 2*uU*, *UU*) one of which is a unique heterozygote (*uU*).
\(viii) A demonstration that dominant and recessive traits cannot be generated by those polypeptides that are not enzymes embedded in a system of enzymes.
\(ix) Rejection of the unjustified traditional claim that a hybrid (*H*) expresses a dominant trait (*A*) because the (allegedly) recessive allele (*u*) in a heterozygote (*Uu*) is always completely ineffective or because the allegedly dominant allele (*U*) suppresses the allegedly recessive allele (*u*) in the heterozygote \[[@B1]\].
\(x) Rejection of the traditional, unsubstantiated and implausible claim that one so-called dominant allele in a heterozygote is as effective as two such alleles in the wild-type cell \[[@B1]\].
It was also shown that pleiotropy and epistasis can be explained by taking a similar system approach to that used in explaining the origin of dominant and recessive traits.
It is then apparent that, to account rationally for Mendel\'s observations of dominant and recessive traits, a minimum of four conditions must be met.
\(i) Alleles must be distinguished by notation, nomenclature and concept from traits; functions of components of the genotype must be distinguished from properties of components of the phenotype. Traits alone may be dominant or recessive.
\(ii) Alleles cannot be called \"dominant\" or \"recessive\". (When alleles are so called, the flaws present in the current attempts to explain Mendel\'s observations will inevitably re-appear \[[@B1]\]).
\(iii) It must be shown how dominant traits become distinguishable from recessive traits in the same cell or organism (Figure [2](#F2){ref-type="fig"}, [3](#F3){ref-type="fig"}).
\(iv) It must be shown how a hybrid trait sometimes becomes indistinguishable from the dominant trait and sometimes does not (Figures [2](#F2){ref-type="fig"}, [3](#F3){ref-type="fig"}). The first circumstance will account for Mendel\'s 3(dominant):1(recessive) trait ratio; the second for exceptions to this ratio.
If all four conditions are be met; the first two conditions must first be met. The treatment given in sections 2--5 meets each of these requirements.
7. Conclusions
==============
Kacser and Burns \[[@B3]\] provided the basis for a rational explanation for the *origin*of dominant and recessive traits that arose from mutations of alleles at any one gene locus in a diploid or polyploid cell (sections 2.3, 2.4). Inherent in this explanation, as set out above (sections 2.5, 2.6), are further explanations for the occurrence of the 3(dominant):1(recessive) trait ratio in some situations in a diploid (Figure [2](#F2){ref-type="fig"}), for the absence of this trait ratio from other situations (Figure [3](#F3){ref-type="fig"}), for the absence of dominant and recessive traits in yet others and for the appearance of a blend of parental traits in some heterozygotes. These five demonstrations are internally consistent. In contrast to the currently favoured attempt to explain Mendel\'s results \[[@B1]\], no arbitrary assumptions are introduced (section 2.8) to explain how heterozygous allele pairs (e.g. *UU*^†^, *U*^†^*u*, *Uu*\*, *uu\**) may produce a trait that is indistinguishable from the trait expressed from the \"homozygous\" allele pairs (*UU*).
In other words, provided:
\(a) all current misrepresentations of Mendel\'s paper \[[@B1]\] are first discarded,
\(b) alleles are distinguished by notation and nomenclature from the traits they specify,
\(c) alleles are regarded as normal or mutant (but not dominant or recessive), it is possible to provide a rational and internally consistent explanation for the origin of Mendel\'s dominant and recessive traits, for the occurrence of his 3:1 trait ratio, and for exceptions to these observations noted by later investigators. The same systemic approach is applicable to current problems in biotechnology and medical genetics (section 4). It also explains the origins of pleiotropy and epistasis (section 5); and challenges the assumption that a mutation in a non-catalytic protein provides an example of Mendel\'s dominant and recessive traits \[[@B1]\].
Mendel found, by experiment, that the proportions of plant forms in each of his F2 populations was represented by (*A*+ 2*Aa*+ *a*). In the present paper these proportions have been written as (*A*+ 2*H*+ *a*). If the symbol (*H*) for a hybrid in Figure [2](#F2){ref-type="fig"} is replaced mentally and temporarily by (*Aa*), it will be clear why Mendel postulated that his hybrids (*Aa*) displayed trait (*A*) and not trait (*a*). If the same exercise is repeated in Figure [3](#F3){ref-type="fig"} by replacing (*H*) temporarily by (*Bb*), it will be clear why Mendel observed an anomalous blending of flower colours in the hybrids when he crossed parental bean plants bearing different flower colours.
The treatment of elementary Mendelian genetics advocated here is based on the work of Kacser and Burns \[[@B3]\]. So far as the present author is aware, that paper has not been described by any student textbook of \"classical\" or \"molecular\" genetics published in the intervening 23 years. Orr \[[@B37]\] did not see the full significance of the Kacser and Burns paper \[[@B3]\]. Darden \[\[[@B38]\], p. 72\] declared that \"(trying) to unravel the complex relations between mutant alleles and enzymes (Kacser and Burns, 1981) - - - is not a major research topic in genetics.\"
Several possible reasons for this failure to see the merits of the Kacser and Burns paper \[[@B3]\] may be worth consideration. They include:
\(1) Persistent misrepresentations of Mendel\'s paper, and incorporation of these distortions into currently favoured explanations of Mendel\'s observations \[[@B1]\].
\(2) A failure to recognise the consequences of not distinguishing between the function of the alleles and the properties of traits in attempting to explain Mendel\'s results. Normal and mutant alleles *specify*the kind (and order of incorporation) of amino acids into polypeptides (most but not all are enzymes). Dominance and recessivity are a reflection of changes in the *concentration(s)*of the molecular component(s) of a trait when an enzyme is mutated within a fluxing metabolic pathway.
\(3) Tardy recognition of the need to adopt the systemic approach of Metabolic Control Analysis in explaining the response of the *variables*of a biological system to perturbations of the magnitude any one system *parameter*.
\(4) A reluctance to accept a change in concepts even when currently accepted representations of Mendel\'s results are demonstrably untenable.
\(5) Elucidation of the double helical structure of DNA (Figure [6](#F6){ref-type="fig"}) and all that followed in the next 10--15 years imposed profound changes on genetics but was not perhaps always taken into account.
\(6) A determination in some quarters to regard genetics as an autonomous subject. It has been obvious at least since the work of Beadle and Tatum \[[@B18]\] that such claims cannot be sustained. Genetics is intimately related to, and in some respects dependent upon, biochemistry. The converse is equally true. Genetics and biochemistry are not separable topics in biology.
It is significant that Kacser & Burns were also one of two sets of authors who initiated the systemic approach to the control of metabolite concentrations and fluxes \[[@B39],[@B40]\]. This approach was elaborated by the original authors and many others. For some accounts and reviews, see \[[@B11],[@B36],[@B41]-[@B44]\].
8. A correction
===============
In an earlier paper \[[@B45]\] it was stated that Mendel had inferred the presence of segregating particles. These particulate determinants were then represented by (*A*) and (*a*). These statements are here formally withdrawn. They were consistent with textbook treatments of Mendelian genetics \[[@B1]\] but a subsequent reading of Mendel\'s original paper revealed that these statements, and others that occur frequently in the recent reviews of Mendel\'s paper and in current textbooks, were incorrect and misleading. A history of the misunderstandings and misrepresentations that have sustained the currently favoured depiction of Mendelian genetics \[[@B1]\] will be presented elsewhere. A paper setting out the concepts of parameters and variables will also be submitted.
Acknowledgements
================
I thank Dr Colin Pearson for his support during the preparation of this and the preceding paper, Dr Denys Wheatley for temporary accommodation during a logistic exercise and Dr Paul Agutter for valuable suggested modifications to the drafts of these two papers.
|
PubMed Central
|
2024-06-05T03:55:47.894170
|
2004-8-31
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517952/",
"journal": "Theor Biol Med Model. 2004 Aug 31; 1:6",
"authors": [
{
"first": "John W",
"last": "Porteous"
}
]
}
|
PMC517953
|
Background
==========
Transthyretin (TTR, formerly called prealbumin) belongs to a group of proteins including thyroxine-binding globulin and albumin which bind and transport thyroid hormones in the blood. It is a single polypeptide chain of 127 amino acids (14 kDa) and is present in the plasma as a tetramer of non-covalently bound monomers. The major sites of TTR synthesis are the liver and choroid plexus \[[@B1]-[@B3]\]. Under physiological conditions, the macromolecular complex plays an important physiological role in vitamin A homeostasis because it binds the specific transport protein for retinol, the lipocalin retinol-binding protein (RBP) \[[@B4],[@B5]\]. This reduces the glomerular filtration of the low molecular weight transport protein (21 kDa) in the kidneys. Any TTR or RBP molecules that are filtered are rapidly bound to megalin, the multiligand receptor expressed on the luminal surface of the renal proximal tubules and therefore internalized. Thus, under physiological conditions, TTR and RBP are present in urine if at all, only in trace amounts \[[@B6]\].
The TTR variants described thus far have mostly been associated with variable degrees of cardiac and/or neural tissue amyloid deposits \[[@B7],[@B8]\]. Therefore, mutations of the amino acid sequence of TTR are of clinical interest \[[@B9]\]. In general, mutations appear to be distributed randomly within the molecule and most of these mutations lead to the synthesis of TTR molecules which have the tendency to form insoluble protein aggregates. These so-called amyloid deposits accumulate extracellularly in various organs. Although the role of amyloid deposits in the pathogenesis of the disease is not clear, preventing their formation or promoting their disaggregation is necessary to control the development of clinical symptoms \[[@B10],[@B11]\].
With regard to nutrition, TTR is a so-called visceral protein that is synthesized in the liver in response to nutritional supply. TTR plasma levels have thus been proposed as sensitive biochemical parameters of subclinical protein malnutrition, because both the adequacy and levels of protein as well as energy intakes are reflected in plasma levels. Plasma levels of TTR, however, are as well affected by acute and chronic diseases associated with an acute-phase response. Under these conditions, liver activity is converted to the synthesis of acute-phase response proteins, resulting in a dramatic drop in visceral proteins, despite nutritional support \[[@B1]-[@B3]\].
This study was conducted to establish a sensitive and reproducible high-throughput SELDI-TOF-MS immunoassay for characterizing TTR variants in plasma and urine arising from amino acid substitutions, posttranslational modifications and/or products of protein degradation or proteolysis.
Results
=======
TTR levels in plasma and urine
------------------------------
TTR levels in plasma determined by ELISA in 10 healthy individuals were 489 ± 155 μg/ml. TTR levels in urine of the healthy individuals were one thousand times lower than in the 40 pregnant women with 46 ± 24 ng/g creatinine and 45 ± 65 μg/g creatinine, respectively.
TTR microheterogeneity in plasma and urine
------------------------------------------
In Figure [1](#F1){ref-type="fig"} the TTR variants found in serum and in urine of pregnant women and non-pregnant controls were compared using the Western blot technique. The results obtained with this method showed that TTR was present in plasma of both groups and in urine of pregnant women but not in the urine of non-pregnant individuals. The intensity of the immunoreactive band in urine of pregnant women was substantially lower than that in plasma. In all investigated TTR-positive plasma and urine samples TTR was present as a single band indicating a molecular weight of 14 kDa.
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Western blot of TTR in paired plasma (A) and urine (B) of seven (1--7) healthy individuals and in seven urine samples (C) of healthy pregnant women. S = TTR standard
:::
:::
SELDI-TOF-MS immunoassays showed that in healthy non-pregnant and pregnant females as well as in males TTR in plasma occurred rather consistently in two major variants of 13732 ± 12 and 13851 ± 9 Da, of which generally the 13851 Da variant is the dominant one. The mass difference between these two variant was 120 ± 9 Da. In addition to the two major signals a minor one at 14043 ± 17 Da was observed in plasma. The mass difference to the signal at 13851 Da was 192 ± 11 Da. In urine, traces of TTR were detected in samples from non-pregnant females and from males. In the urine of pregnant women however strong mass signals were observed. As shown in Figure [2c](#F2){ref-type="fig"}, the variant of 13736 ± 10 Da also present in plasma, as well as lower molecular immunoreactive species were observed at 12847 ± 29, 12984 ± 7, 13202 ± 16, 13349 ± 15 and 13575 ± 15 Da. In urine, although the TTR pattern was different to the one in plasma, there were similarities in all samples in which TTR was present.
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Mass spectra resulting from SELDI-TOF-MS immunoaffinity analysis of three (1--3) paired plasma (A) and urine (B) samples obtained from healthy individuals (a) and three urine samples (C) from healthy pregnant women.
:::
:::
Discussion
==========
The SELDI platform can be readily adapted for developing an immunoassay format. This approach, using antibodies as an affinity capture device has been successfully used to detect and quantify different proteins by MS in complex biological mixtures \[[@B12]\]. Unlike current ELISA technology that uses an indirect detection mechanism by \"sandwiching\" the targeted protein with antibodies, the SELDI-based immunoaffinity assay allows for direct detection without tags. The specificity of the mass spectrometry immunoassay is unsurpassed because there is the combined discriminating power of both the antibody and the high molecular weight accuracy of the detector. In terms of sensitivity, the detection limit can approach that of current assays for TTR. The antibody used as bait recognizes an epitope in different isoforms of TTR. This direct sampling is a unique advantage over the more traditional ELISA methods in which the resulting signal is a weighted average of all the bound species. The discriminating power of the assay is shown in the direct comparison between Western blotting (Figure [1](#F1){ref-type="fig"}) and SELDI-TOF-MS immunoassay (Figure [2](#F2){ref-type="fig"}). The small mass differences observed with mass spectrometry can not be resolved by the combination of electrophoresis and immunological detection.
The results support and confirm previous studies with regard to molecular variants of TTR in plasma and urine \[[@B13]-[@B15]\]. As in these studies, TTR in plasma was dominant in two variants. The 120 Da larger variant is the S-cysteinylated form of TTR. The inconsistently present smaller signal at 14043 Da can be attributed to the S-glutathionylated form of TTR \[[@B13],[@B16],[@B17]\]. Other forms due to dehydration, or phosphorylation were not observed. The reported isoforms of TTR result when the Cys10 residue makes a mixed disulfide with the amino acid cysteine, the peptide glutathione or the peptide cysteinyl-glycine. Recent studies show that the most prevalent modification of TTR renders it substantially more amyloidogenic than the non-cysteinylated form at pH 5 \[[@B18]\]. The possible importance as a risk factor for the onset of senile systemic amyloidosis remains to be elucidated. Additionally, the S-homocysteinylation of TTR has been described in plasma of humans with hyperhomocysteinemia \[[@B19]\]. These two aspects might support the importance of a diagnostic approach to characterize isoforms of TTR more easily.
Apart from the case of absence, some modifications might not be detected with this method due to limitations in resolution. Both methods, ELISA and SELDI immunoassay are sensitive enough to observe only trace amounts of TTR in body fluids as in the case of urine of healthy individuals. These amounts were not detected using immunoblotting. Despite the small signal it was obvious that additional variants to the ones in plasma are present in urine. Contrary to a pervious study using a different method \[[@B14]\] we were not able to observe the cysteinylated form of TTR in urine despite being the dominant one in paired plasma samples. Major differences to this method are the possibility of one step on chip-enrichment and the analysis of much smaller sample amounts but a lower mass resolution. This latter aspect however, can not explain these differences.
No study is available in which TTR has been described quantitatively in the urine of healthy individuals. In this study we are able to show for the first time that levels of TTR in urine of pregnant women are 1000-fold higher compared to the levels in urine of healthy non-pregnant individuals. The excretion of substantial amounts of TTR has only been described in individuals with different kidney diseases indicating disturbed glomerular filtration and/or insufficient tubular reabsorption \[[@B13]\]. The involvement of the megalin receptor in the tubular reabsorption of filtered TTR has been shown in patients with Dent\'s disease \[[@B6]\].
Interestingly, as shown by us also for the first time, TTR in the urine of pregnant women is present in different molecular variants. In contrast to plasma, the S-cysteinylated form dominant in plasma was if at all present only in trace amounts. It remains to be determined if this is limited to the excretion of TTR in pregnancy or if under other circumstances such as in different kidney diseases similar molecular variants occur as well. The lower molecular weight immunoreactive variants found in urine of pregnant women may arise from limited proteolysis. At this point it is not possible to determine location and extent of proteolysis within the molecule. The immunoreactive fragments might arise from a breakdown within the plasma or the kidney structures.
Conclusions
===========
The SELDI immunoaffinity-isolation of TTR in combination with mass spectrometry offers a rapid, highly reproducible and cost-effective system for the determination of molecular variants of microheterogenous proteins and peptides. This is of importance in \"second phase\" proteomics which is characterized by the repetitive investigation of the same protein to validate the protein phenotype in large population based studies. This provides the basis for a substantial progress in the diagnostic with regard to personalized medicine \[[@B20],[@B21]\]. With regard to TTR, this approach might not only be of importance in the diagnosis of TTR related amyloidosis but may also have the potential as alternative or new biomarkers related to the metabolism of TTR for use in nutrition related disease as well as in the diagnosis of kidney function.
Methods
=======
Participants
------------
Paired plasma and urine samples from 10 healthy individuals were obtained. The plasma was prepared by centrifugation of the blood (1500 × *g*, 10 min, 4°C) within 1--3 h after acquisition. Additionally, urine samples of the ten individuals and of healthy pregnant women (n = 40) undergoing routine medical examination, were collected and immediately mixed with protease inhibitors (Sigma, Deisenhofen, Germany). Hematuria was tested using a routine dipstick method (Combur 9 Test, Roche, Basel, Switzerland). Cells and other non-soluble material were cleared from the sample by brief centrifugation (1500 × *g*, 2 min). Aliquots of centrifuged urine were stored at -80°C and processed as soon as possible. The study protocol was approved by the hospitals and University of Potsdam Ethics Committee. Informed consent was obtained from each participant.
Determination of TTR using ELISA and Western blotting
-----------------------------------------------------
Polyclonal antibodies to TTR were produced in rabbit and affinity purified (Dako Diagnostics, Hamburg, Germany). TTR in plasma and urine was quantitatively determined by an enzyme-linked immunoassay (ELISA) method developed in our laboratory. To further assess the presence of TTR quantitatively and qualitatively, we performed a SDS-polyacrylamide gel electrophoresis (PAGE) immunoblot analysis as has been described \[[@B22]\].
Immuno SELDI-TOF-MS
-------------------
Protein A (Sigma, Deisenhofen, Germany) at 0.1 mg/ml in PBS was added (5 μl) to the spots of a pre-activated ProteinChip® Array (PS20; Ciphergen Biosystems Inc., Palo Alto CA, USA). The PS20 array consists of a surface with epoxy groups that dock proteins by covalently reacting with their amine groups. The arrays were incubated for 1 h at 25°C in a humidity chamber. After blocking residual active sites with 5 μl blocking buffer (0.5 M ethanolamine in PBS at pH 8.0) for 25 min, the array was washed three times in a 15 ml conical tube with PBS (pH 7.4). TTR antibody (4.1 μg/μl) was added to individual spots (2 μl) and incubated in a humidity chamber for 1.5 h with mixing. The unbound antibodies were removed by washing the array three times in a 15 ml conical tube with PBS (pH 7.4).
Before incubation urine was diluted 1:1 (v:v) in PBS and plasma 1:100 (v:v) in PBS. A total volume of 10 μl was applied to each spot and incubated for 1.5 h at 25°C in a humidity chamber. Samples were washed on the spot with 5 μl PBS three times and finally with 5 μl H~2~O. After drying, 0.6 μl of a saturated energy-absorbing molecule (EAM) solution (5 mg sinapinic acid dissolved in 75 μl acetonitrile and 75 μl 1% trifluoroacetic acid) was applied to the spot surface, and the sample was allowed to dry.
After insertion of the ProteinChip Array into the ProteinChip Reader, a laser pulse was focused on the sample under vacuum. The array was analyzed under the following settings: laser intensity 250/220, detector sensitivity 8, mass focus, molecular mass range 10 to 18 kDa, position 20--80 and a 150--200-shot average per sample.
CytochromeC (equine cardiac; 12360.1 MW), myoglobin (equine cardiac; 16951.5 MW), GAPDH (rabbit; 35688 MW), albumin (bovine serum; 66433MW) and β-galactosidase (E. coli; 116351MW) were used as calibrators.
Mass resolution (defined as m/Δm) is routinely achieved below 300 and mass accuracy was within 0.1%. Peaks with amplitudes at least 3 times greater than the average background noise level were considered. The reproducibility was tested with different aliquots of the same sample on eight different spots of the protein chip array.
Competing interests
===================
None declared.
Authors\' contributions
=======================
FJS participated in the conception, design, data analysis and the writing of the manuscript, KW in data analysis and writing of parts of the manuscript. JR participated in the conception, data analysis and the writing of the manuscript. All authors have read and approved the last version of the manuscript.
Acknowledgements
================
The SELDI-TOF MS was acquired through funds of the BMBF (program \"Innovations- und Gründerlabore\"). We thank Andreas Wiesner, Ciphergen Biosystems, for critical comments.
|
PubMed Central
|
2024-06-05T03:55:47.900676
|
2004-9-1
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC517953/",
"journal": "Proteome Sci. 2004 Sep 1; 2:5",
"authors": [
{
"first": "Florian J",
"last": "Schweigert"
},
{
"first": "Kerstin",
"last": "Wirth"
},
{
"first": "Jens",
"last": "Raila"
}
]
}
|
PMC518959
|
Background
==========
In recent years, the number of patients suffering from allergic asthma has increased \[[@B1]\], and allergic diseases including asthma have become a social problem affecting medical costs and quality of life. Allergic asthma is a complex disorder characterized by airway inflammation, bronchial hyperresponsiveness and reversible airway obstruction. Elevated numbers of activated Th2 cells, mast cells and eosinophils in the bronchial mucosa cause certain features of asthma, including increased serum IgE levels in allergic asthma. The available data suggest that there are many potential susceptible genes for allergic asthma, including genes for cytokines, receptors, transcription factors, immune recognition and regulation of lipid mediator generation. A few susceptible genes for allergic asthma have been identified that may be associated with the asthmatic phenotype \[[@B2]-[@B4]\], but definite susceptible genes have not been identified yet. Thus, large-scale analysis of gene markers is needed, along with identification of association between these genetic polymorphisms and the asthmatic phenotype, and its development mechanism. It has been reported that the human genome has 3 to 10 million single nucleotide polymorphisms (SNPs). A SNP in a coding region can cause amino acid substitution, resulting in functional modification of the protein; a SNP in a promoter region can affect transcriptional regulation; and a SNP in an intron region can affect splicing and expression of the gene. Thus, SNPs can be highly informative for identifying genetic factors of multifactorial disease such as allergic asthma.
In the present study, we analyzed associations between SNPs and childhood allergic asthma (CAA), which is more strongly influenced by genetic factors than other types of allergic asthma. We performed this analysis using an artificial neural network (ANN), which is a computer-based algorithm that can be trained to recognize and categorize complex patterns \[[@B5]-[@B8]\]. ANNs have been used for discrimination between subtly different clinical disease lesions; e.g., premalignant lesion Barrett\'s versus esophageal cancer, based on microarray data \[[@B6]\]. In a previous study, we performed severity assessment of senile dementia of Alzheimer type using ANN modeling of electroencephalogram data. The average error of the ANN model for assessment scale (HDS-R) score was 2.64 points out of 30 \[[@B7]\]. We have also used an ANN for prediction of 4 allergic diseases using SNP data \[[@B8]\]; 82 subjects with data for 6 SNPs were analyzed, and the ANN model predicted diagnosis with accuracy of more than 78%. Thus, we have achieved sufficiently high accuracy with ANNs using relatively little SNP data.
Here, we propose an ANN model (its structure is shown in Figure [1](#F1){ref-type="fig"}) suitable to diagnostic prediction of 172 subjects with CAA and 172 healthy subjects, using 25 SNPs in 17 genes shown in Table [1](#T1){ref-type="table"}. For comparison with ANN, we also used logistic regression (LR) analysis, which is currently used to analyze medical statistics and equivalent to ANN with a single hidden node \[[@B9]\]. In order to selectively identify susceptible SNPs, a susceptible marker-selectable ANN is proposed, in which a parameter decreasing method (PDM) is incorporated. Information on obtaining the execute code, example data and documentation of this software is available at <http://www.nubio.nagoya-u.ac.jp/proc/english/indexe.htm>. Associations between combinations of important SNPs and CAA pathogenesis were investigated. A χ^2^test was performed for all 2-SNP and 3-SNP combinations.
Results
=======
SNPs selected for diagnostic prediction with ANN
------------------------------------------------
Several reports have suggested linkage between asthma and chromosomes. For example, genes in the 5q31-5q33 region code for Th2-type cytokines (IL-4, IL-13, which regulate B cell heavy-chain class-switching to IgE production) \[[@B10]\] and ADRB2 (which mediates airway smooth muscle relaxation and protects against bronchial hyperreactivity) \[[@B11],[@B12]\]. IL-4 operates via the IL-4 receptor (IL-4R), which is encoded by a gene in chromosomal region 16q12. Mice deficient in the IL-4Rα chain lack IgE production and Th2 inflammatory reactions, and it has been shown that total IgE level is dependent on Ile50Val substitution \[[@B13]\]. In the present study, we analyzed 25 SNPs (Table [1](#T1){ref-type="table"}) in 17 genes known to be associated with development of asthma. Association between these SNPs and CAA was assessed by *P*-value. As shown in Table [1](#T1){ref-type="table"}, 21 of these 25 SNPs had a *P*-value greater than 0.1. The *P*-values of *CysLT2*(108 C/A), *IL-4Rα*(148 G/A), *ADRB2*(265 A/G) and *C5*(4266 G/A) were 0.0036, 0.0155, 0.0541 and 0.0581, respectively. When *CysLT2*(108 C/A), which had the lowest *P*-value of 25 SNPs, was used for discrimination between case and control as a sole factor, prediction accuracy was 54.4%, and the sensitivity and specificity was 12.8% and 95.9%, respectively, compared with the number of case and control subjects to assess discrimination performance (genotype CC; case 150, control 165, genotype CA or AA; case 22, control 7). Thus, we constructed a susceptible marker-selectable ANN model, which can discriminate between cases and controls using the selected susceptible SNPs, and which can include the association between combinations of SNPs and development of CAA.
Diagnostic prediction using 25 SNPs
-----------------------------------
We used a three-layered ANN with input, hidden and output layers (Figure [1](#F1){ref-type="fig"}). An ANN model and LR model, with 25 SNPs as input variables, were constructed with learning data, and we performed diagnostic prediction with evaluation data. The results of diagnostic prediction are shown in Figure [2a,2b](#F2){ref-type="fig"} and Table [2a](#T2){ref-type="table"}. The ANN had higher prediction accuracy than LR. Accordingly, sensitivity and specificity, with both evaluation data and learning data, were higher for the ANN than for LR (Table [2a](#T2){ref-type="table"}). In LR analysis, Monte Carlo study was performed to evaluate the effect of number of events per variable (EPV) \[[@B14]\]. It suggested that at least 10 events per variable analyzed were desirable to maintain the validity of the model. In the present study, we used 172 events per group and 51 variables (25 SNPs and 1 teacher value). LR would not have an enough power for parameter selection, because 172 events per group is small compared with that of variable. The construction of optimized LR model should be furthermore investigated.
Selection of susceptible SNPs for CAA
-------------------------------------
Ritchie *et al*. \[[@B5]\] reported the optimization of the architecture using genetic programming neural networks (GPNN) \[[@B5]\]. If important SNPs were previously determined, optimization of network architecture should be carried out. Genetic programming neural networks have contributed the construction of ANN model with high performance. In the present study, however, many candidate SNPs were used and the selection of SNPs is firstly desired. Therefore, in order to extract SNPs closely associated with CAA, we tried optimization of input variables by PDM in the ANN model, while the architecture of a neural network was not modified. Five PDM trials were performed. Figure [3](#F3){ref-type="fig"} shows typical results for change of accuracy during PDM procedure. When input variables were excluded one by one to preserve prediction accuracy (as described in Methods), the accuracy began to decrease after the number of SNPs used for modeling reached 10. When the number of SNPs used for modeling decreased, coincidence of genotyping pattern between cases and controls inevitably occurred. When genotyping pattern of a case was coincident with that of controls, the learning for model construction did not progress well. We investigated the rate of case subjects whose genotype patterns were coincident with that of control subjects at each step of PDM (Figure [3](#F3){ref-type="fig"}). Rate of case subjects \[%\] in Figure [3](#F3){ref-type="fig"} means *N\'*~*case*~/*N*~*case*~. In this case, *N\'*~*case*~is the number of cases whose genotype pattern is match to control\'s genotype pattern at least one control (*N*~*case*~= 172 subjects). As shown in Figure [3](#F3){ref-type="fig"}, there was little coincidence of genotype patterns when more than approximately 7 SNPs were used in ANN modeling. Therefore, the decrease in accuracy was considered to be due to omission of a highly important SNP. The remaining 10 SNPs were worth investigating as important factors.
To investigate the important SNPs, we counted the number of SNPs that remained within the last 10 input variables in 5 trials. The significance order of remaining SNPs was listed, and a score of order ranging from 1 to 10 points was determined, based on the significance order. The remaining SNPs were reordered according to sums of scores, as shown in Table [3](#T3){ref-type="table"}. We believe that SNPs with higher scores are more important for development of CAA, because significance of SNPs correlated with the order of elimination via the PDM procedure described in methods section. ANN models were reconstructed using SNPs listed in Table [3](#T3){ref-type="table"}. The number of input SNPs varied from three (*IL-4Rα*(148 G/A), *CysLT2*(2534 A/G) and *IL-10*(-571 C/A)) to 17 SNPs (all listed SNPs) according to the order of Table [3](#T3){ref-type="table"}. When more than 10 SNPs were used as input variables, average accuracy for learning and evaluation data was high (Figure [4](#F4){ref-type="fig"}), and was almost equal to that of the model using 25 SNPs. These results suggest that the 10 SNPs selected in Table [3](#T3){ref-type="table"} are very important for prediction of development of CAA.
The results of diagnostic prediction using the 10 SNPs selected by PDM are shown in Figure [2c](#F2){ref-type="fig"}, and the accuracy, sensitivity and specificity are shown in Table [2b](#T2){ref-type="table"}. In the ANN model, the accuracy, sensitivity and specificity with evaluation data were again sufficiently high, and were somewhat similar to the results from the analysis using 25 SNPs, although the number of input variables was markedly smaller than in the analysis using 25 SNPs. In particular, sensitivity was significantly high (77.9%), indicating that case subjects were more correctly diagnosed by this model. To compare with the LR model, LR model consisting of 10 SNPs selected by ANN was constructed (Figure [2d](#F2){ref-type="fig"}). As shown in Table [2b](#T2){ref-type="table"}, the LR model constructed showed low accuracy. This result indicates high performance of ANN modeling for CAA prediction although selected SNPs would not be suitable for LR analysis. We concluded that the ANN model constructed with 10 SNPs could discriminate between cases and controls as precisely as the model constructed with 25 SNPs.
Interaction between SNP and another SNP for CAA
-----------------------------------------------
To understand the importance of the 10 SNPs selected, we analyzed combinations of these 10 SNPs. We paid particular attention to SNP combinations associated with CAA, and assessed whether any combinations consisting of SNPs selected by ANN were associated with CAA. The relationships between 2-SNP or 3-SNP combinations and CAA development were examined by calculating *P*-value using the χ^2^test. In models using 10 SNPs selected by PDM or the other 15 SNPs, the total number of 2-SNP combinations and 3-SNP combinations (*N*~*comb*~) is 90 (~10~P~2~) or 210 (~15~P~2~), and 360 (~10~P~3~/2) or 1365 (~15~P~3~/2), respectively. With respect to 2-SNP combination between the SNP of interest and SNP A, *P*-value was calculated as follows. When patients were limited with certain pattern of another SNP, such as AA major homozygote of SNP A, patient distribution of the SNP of interest was investigated. With respect to 3-SNP combination, between the SNP of interest, and SNP A and B, *P*-value was calculated as follows. When patients were limited with certain pattern of two other SNPs, such as AA major homozygote of SNP A and BB major homozygote of SNP B, patient distribution of the SNP of interest was investigated.
To evaluate *P*-value of the combination, the usual Bonferroni correction of *P*-values was first investigated. To select the 2-SNP combination accompanied with minimum false positive, the criterion was *P*\< 0.05/300. Here 300 cases correspond to ~25~C~2~. Under this severe condition, there were no significant SNPs. As the same as 2-SNP combination, any significant combination was not obtained on 3-SNP combination under the threshold of *P*\< 0.05/2300. Next, to determine important combination, *P*-value without Bonferroni correction was used, that is *P*\< 0.05. Results are shown in Table [4](#T4){ref-type="table"}. In 2-SNP combination, there were 13 combinations with *P*\< 0.05 among total 90 combinations. In the case of 3-SNP, 72 combinations with *P*\< 0.05 were existed in 360 exhaustive combinations. However, combinations possibly include several false positive significant combinations. Therefore, we paid attention to the SNP, of which *P*-value effectively decreases by combining with genotype or allele of other SNPs. We defined effective combination value (ECV). ECV2 or ECV3 is the ratio of 2 or 3-SNPs *P*-value to the product of each *P*-value. ECV is not indicator for avoiding false positives but for evaluation of interaction. For example, in 2 SNP combinations, when patients were limited with certain pattern of another SNP, such as AA major homozygote of SNP A, patient distribution of the SNP X of interest is investigated (*P*= *P*~*ax*~). If the 2-SNP combination is independent (no interaction) each other, *P*~*ax*~equals multiplication of *P*~*a*~and *P*~*x*~. ECV\<1 means that the 2-SNP combination is not independent and two SNPs have any interaction each other.
The effect of ECV on number of effective combinations is shown in Table [4](#T4){ref-type="table"}. About half number of 2-SNP combination satisfied the condition ECV2\<1 (*N*~*ECV*2\<1~= 47). Among 13 combinations with *P*\< 0.05 mentioned above, 11 combination also satisfied the same condition (*N*~*ECV*2\<1,*P*~= 11). When ECV2\<0.5, *N*~*ECV*2\<0.5~decreased the number to 27 and 10 of *N*~*ECV*2\<1,*P*~= 11 still remained. When ECV2\<0.1, *N*~*ECV*2\<0.1~became small and it was thought that positive combination may be lost. In the case of 3-SNP combination, only 20% of the total combination satisfied the condition *P*\< 0.05. The combinations of 12% among the total combinations (43 combinations) satisfied ECV3\<1. All of these 43 combinations also satisfied the condition *P*\< 0.05. From these results, it was concluded that *P*\< 0.05 is not strict criterion for 3-SNP combination analysis. In the case of 2-SNP combination, ECV2\<0.5 was adequate as a selection of effective combination, because 77% of the combination with *P*\< 0.05 still remained. From these consideration, we selected these two evaluation bases (*P*-value and ECV) in order to determine effective combinations and the combination with *N*~*ECV*\<0.5,*P*~(*P*\< 0.05 and ECV\<0.5) was picked up. The combinations were used for the following investigation. The number of combination which satisfies the condition, *P*\< 0.05 and ECV2\<0.5 in 2-SNP combination and *P*\< 0.05 and ECV3\<0.5 in 3-SNP combination was designated as *N*~*ef*~, the number of effective combination, respectively (Table [5](#T5){ref-type="table"}).
It is very important to clearly determine whether effective combinations frequently occur among groups of 10 SNPs selected by ANN modeling with PDM. It would be difficult to investigate the phenotypes associated with each of such a large number of combinations. Identifying effective 2-SNP combinations using the conditions described above is a useful method of identifying 2-SNP combinations that merit further investigation. Ten effective combinations were found among the 10 SNPs selected by ANN; 23 effective combinations were found between those 10 SNPs and the remaining 15 SNPs; and 3 effective combinations were found among the remaining 15 SNPs. It is likely that the former 10 combinations are more important than the latter 26 combinations, because the ANN model constructed using only the selected 10 SNPs exhibited sufficiently high accuracy to predict development of CAA. Susceptible genes for development of a multifactorial disease like CAA can correctly classify many subjects as cases or controls, and it is very important that those genes involve SNP combinations that have important interaction with high concentration ratio. We defined the concentration ratio as the ratio of *effective rate*to *random selection rate*. When the effective rate, *N*~*ef*~/Σ*N*~*ef*~, was calculated, it was found to be 0.28 (10/36) for the 10 SNPs selected by PDM, 0.64 (23/36) for combinations between the 10 selected SNPs and the remaining 15 SNPs, and 0.08 (3/36) for combinations of the remaining 15 SNPs (Table [5](#T5){ref-type="table"}). The random selection rate, *N*~*com*~/~15~P~2~shown in Table [5](#T5){ref-type="table"}, represents the rate which the combination is selected from all 2-SNP combinations independently, 0.15 (90/~15~P~2~) for the 10 SNPs selected by PDM, 0.5 (300/~15~P~2~) for combinations between the 10 selected SNPs and the remaining 15 SNPs, and 0.35 (210/~15~P~2~) for combinations of the remaining 15 SNPs (Table [5](#T5){ref-type="table"}). The concentration ratio was found to be 1.85 for the 10 SNPs selected by PDM, 1.28 for combinations between the 10 selected SNPs and the remaining 15 SNPs, and 0.24 for combinations of the remaining 15 SNPs (Table [5](#T5){ref-type="table"}). The concentration ratio was higher for combinations among the 10 selected SNPs than for other combinations, so we can select 2-SNP combinations associated with CAA with high rate. The results are shown in Table [6](#T6){ref-type="table"}.
In the next step, 3-SNP combinations were analyzed. The effective rate, the random selection rate, and the concentration ratio were calculated as well as the case of 2-SNP combination (Table [5](#T5){ref-type="table"}). It was found to be 2.28 for each of the 10 selected SNPs alone (3:0 in Table [5](#T5){ref-type="table"}), 1.33 for 2 of the 10 selected SNPs and 1 of the remaining 15 SNPs (2:1 in Table [5](#T5){ref-type="table"}), 0.67 for 1 of the 10 selected SNPs and 2 of the remaining 15 SNPs (1:2 in Table [5](#T5){ref-type="table"}), and 0.94 for the remaining 15 SNPs alone (0:3 in Table [5](#T5){ref-type="table"}). The concentration ratio was higher for combinations among the 10 selected SNPs than for other combinations, so we can select 3-SNP combinations associated with CAA with high rate. The combination with the lowest ECV3 consisted of the genes *IL-4Rα*, and *C3*(0.03526). This is about 3% of the value multiplied each *P*-value of 2-SNP combination (0.5060). For patients with genotype GA of *IL-4Rα*(148 G/A: Val50Ile) and genotype CT of *C3*(4896 C/T), patient frequency against genotype of *C3*(1692 G/A) had a *P*-value of 0.01784. For *C3*(1692 G/A) alone, a *P*-value of 0.6993 was obtained, which was 40 times greater than the *P*-value of the 3-SNP combination. Thus the rate of correct identification of effective combinations evaluated by adjusted *P*-value and ECV selected based on PDM trials was higher than the corresponding randomized rate, implying that the ANN can reliably select SNP combinations that are associated with CAA.
The 2-SNP combinations with the conditions described above among selected 10 SNPs are shown in Table [6](#T6){ref-type="table"}. For example, in Table [6](#T6){ref-type="table"}, for combinations between *CysLT2*(2534 A/G) and *IL-4Rα*(148 G/A: Val50Ile), among subjects with a *CysLT2*(2534 A/G) genotype of AG or GG (CAA, 107 subjects; healthy controls, 103 subjects), there was an important correlation with *IL-4Rα*(148 G/A: Val50Ile) genotype of GG, GA, AA (*P*= 0.00030). We examined the distributions of important combinations among subjects. A total of 52 CAA subjects and 24 healthy controls had genotype AG or GG at *CysLT2*and genotype GG at IL-4R*α*(148 G/A) (Figure [5a](#F5){ref-type="fig"}).
The present findings also indicate that the 3-SNP combination consisting of *IL-10*(-571 C/A), *IL-4*(-590 C/T) and *C3*(1692 G/A) is a susceptible factor of CAA (*P*= 0.00426). No association with CAA was found for any of these 3 SNPs alone (*P*= 0.1074, 0.9085, 0.6993, respectively; Table [1](#T1){ref-type="table"}) or for any 2-SNP combinations of them (*P*= 0.1851, and 0.3002, respectively). Subjects with genotype CA at *IL-10*(-571 C/A), genotype CT at *IL-4*(-590 C/T) (CAA, 34 subjects; healthy controls, 38 subjects) and genotype GG at *C3*(1692 G/A) (CAA, 12 subjects; healthy controls, 6 subjects) were estimated to be at high risk for pathogenesis of CAA. Furthermore, among the subjects with the same genotype pattern, the number of subjects with genotype AA at *C3*(1692 G/A) were CAA, 3 and healthy controls, 13, respectively (Figure [5b](#F5){ref-type="fig"}).
Other remarkable combinations shown in Table [6](#T6){ref-type="table"} were also found among the 10 selected SNPs. For example, the number of cases with GG genotype at *IL-4Rα (*148G/A) and TT genotype at *C3*(4896C/T) was 4 times the number of controls with that genotype combination (CAA, 20 subjects; healthy controls, 5 subjects) (*P*= 0.00271). There are no previous reports of association between these genotype combinations and CAA. The combination of *IL-4Rα*(148 G/A: Val50Ile) and *IL-4*(-590 C/T) was also associated with CAA (*P*= 0.00689); association between allergic asthma and this combination has previously been reported \[[@B15],[@B16]\].
Discussion
==========
To characterize the development mechanism, we investigated several relationships between SNPs and development of CAA, referring to previous papers, as described below. IL-4 is produced by Th2 cells, and exerts its activity by interacting with the receptor IL-4Rα, located on the surface of B cells. It has been reported that the V50 (148G)/R551(1827G) combination of *IL-4Rα*polymorphisms may be associated with enhancement of IL-4Rα function \[[@B16]\]. As concerns the polymorphisms on *IL-4*, it was reported that the -590T allele increases the strength of the *IL-4*promoter compared with the -590C allele \[[@B15]\]. C3 is a proinflammatory mediator that binds to specific cell surface receptors and causes leukocyte activation, smooth muscle contraction and vascular permeability \[[@B17]\]. *C3*-deficient mice challenged with allergen show diminished airway hyperresponsiveness and lung eosinophilia, with dramatic reduction of the number of IL-4-producing cells and attenuation of IgE responses \[[@B18]\]. In the present study, we found that interaction between genotype TT at *C3*(4896 C/T) and genotype GG at *IL-4Rα*(148 G/A) may be associated with CAA, but details of interaction between these polymorphisms combinations and development mechanisms have not been clarified. The present findings indicate that, among subjects with an *IL-10*(-571 C/A) genotype of CA and an *IL-4*(-590 C/T) genotype of CT, there is important correlation with a *C3*(1692 G/A) genotype of GG or AA (Figure [5b](#F5){ref-type="fig"}).
CysLTs, which are produced by inflammatory cells including eosinophils, are mediators of leukotrienes, and have been implicated in the pathogenesis of allergic diseases. Recently, it has been reported that CysLTs can act as autocrine or paracrine mediators to stimulate rapid, nonexocytotic release of IL-4 \[[@B19]\]. These findings are consistent with the present results, in which subjects with CT or TT genotype at *IL-4*(-590 C/T), AG or GG genotype at *CysLT2*(2534 A/G) and GG genotype at *IL-4Rα*(148 G/A) were estimated to be at high risk for pathogenesis of CAA (*P*= 0.00022). However, 2-SNP interaction between *CysLT2*(2534 A/G) and *IL-4Rα*(148 G/A) (*P*= 0.00030) markedly affected the 3-SNP interaction.
In the present study, we examined correlation between CAA and 25 SNPs in 17 genes using an ANN model. We think that there are not a few main effects and interactions which can explain development of multifactorial disease like CAA, because it is thought that interactions of genetic risk factors might be different individually among CAA patients in spite of same disease. So it is very important to select multiple genetic factor models associated with multifactorial disease like CAA with high concentration ratio. We found that 10 of these SNPs are important factors in development of CAA. Important combinations among these 10 SNPs were also extracted. As described above, several of these combinations (listed in Table [6](#T6){ref-type="table"} etc.) have been found to be important factors in allergic disease, in previous biological and epidemiological studies. We also found several novel important combinations. The present data about important combinations suggests multiple patterns of CAA development. It should be noted that these findings were obtained automatically using an ANN model constructed without priori knowledge. Using an ANN model with 10 SNPs, we were able to discriminate between cases and controls with more than 70% accuracy. We concluded that the ANN is an effective tool for predicting development of CAA, using SNP data. However, further investigation of other genetic and environmental factors associated with CAA is needed. We previously constructed an advanced modeling method, the fuzzy neural network \[[@B20],[@B21]\], which is an ANN model. When this model is applied to analysis, the susceptibility rules of interaction can be explicitly and linguistically described. Also, it can be used to describe susceptible interaction between genetic factors such as SNPs and environmental factors such as favorite foods and life style. Using the rules obtained with this model, we can plan protocols for preventive treatment of subjects with high-risk genetic profiles. Network analysis tools such as ANNs can be applied to analysis of multifactorial disease using SNP data such as selection of important SNPs or description of interactions between SNPs.
Conclusions
===========
Relationships between CAA and 25 SNPs in 17 candidate genes were analyzed using an ANN. In diagnostic prediction, ANN discriminated cases from controls more precisely than LR. From among the 25 original SNPs analyzed, we selected 10 SNPs that were closely associated with CAA. Calculating *P*-value using the χ^2^test, we found that 2-SNP and 3-SNP combinations of these 10 SNPs were associated with CAA. The ANN was able to represent associations between CAA and these 2-SNP or 3-SNP combinations using complicated nonlinear relations. Thus, the ANN can be used to characterize development of complex diseases caused by multiple factors.
Methods
=======
Subjects and SNP data
---------------------
SNP data were kindly provided by the ethics committees of Tohoku University and RIKEN. We analyzed the SNP data for 25 polymorphisms in the 17 genetic regions listed in Table [1](#T1){ref-type="table"}. Each SNP was detected using the established method based on TaqMan PCR \[[@B22]\]. The study population comprised 172 subjects with childhood allergic asthma (CAA) who were under 17 years of age and 172 healthy subjects with no signs or symptoms of atopy-related diseases selected from general population, all of whom gave written informed consent for SNP analysis. The subjects were diagnosed by experienced doctors, as \"positive\" (with allergic asthmatic symptoms) or \"negative\" (without allergic asthmatic symptoms). In the present paper, the subjects with CAA are referred to as \"cases\" and the healthy subjects are referred to as \"controls\". Genotype patterns of the 25 SNPs were compared between cases and controls. None of the cases had genotype patterns coinciding with those of controls.
Data preprocessing
------------------
To use SNP data as input data for the ANN, we converted the genotyping data into 2-numeral data. In ANN modeling, input and output variables are normalized into 0.1--0.9 \[[@B8]\]. In SNP data, there are 3 genotypes per locus. Therefore, we provided 2 inputs per SNP: (0.1, 0.1) for homozygote of the major allele, (0.1, 0.9) for heterozygote, and (0.9, 0.9) for homozygote of the minor allele. Since from the genetic point of view it may be difficult to estimate that heterozygote affects a disease by half the extent that homozygote affects it, the coding of (0.1), (0.5) and (0.9) was never used. The diagnosis data were also converted into numerical data, referred to hereafter as \"teacher\" values: 0.9 for \"positive (case)\", and 0.1 for \"negative (control)\".
For LR, we converted SNP data into numerical input data as follows: (0.1, 0.1) for homozygote of the major allele, (0.1, 0.9) for heterozygote, and (0.9, 0.9) for homozygote of the minor allele. Positive and negative diagnoses were also converted into numerical data: 0.9 and 0.1, respectively.
ANN model and model construction
--------------------------------
For SNP analysis, we used a three-layered ANN with input, hidden and output layers (Figure [1](#F1){ref-type="fig"}). For model construction, the performance index of the ANN was assessed using a method we previously proposed \[[@B7],[@B8]\], with slight modifications. *N*~*error*~(number of missed points) and *Er*(sum of squared error) were defined and calculated for learning data and evaluation data as follows:
*N*~*error*~= *N*~*error*,*l*~+ *N*~*error*,*e*~ (3)
where *Y*and *T*represent the predicted value and the teacher value, respectively. *N*~*l*~and *N*~*e*~represent the number of subjects as learning and evaluation data, respectively. *N*~*error*~is the number of output data with an error of \>0.4 between the predicted value and teacher value as shown above. *Er*is calculated with the square of error as shown above. For ANN learning, the connection weights were initially randomly set from 0 to 1, and were altered using the back propagation methods \[[@B23]\] with learning data so as to minimize the value of *Er*~*l*~. Learning rates of 0.1, 0.2, 0.3, 0.4 and 0.5 were examined. The maximum learning time was 2000 iterations. The best ANN model (selected for SNP analysis) was that in which *N*~*error*~reached minimum within the maximum learning time. When minimum *N*~*error*~was equal to that of other models within the maximum learning time, the model with minimum *Er*value was selected.
Prediction accuracy of the constructed model was defined as follows. Threshold was set at 0.5. If the teacher value was 0.9, and the predicted value was greater than 0.5, the prediction was true (true positive; TP); for predicted values lower than 0.5, the prediction was false (false negative; FN). If the teacher value was 0.1, and the predicted value was lower than 0.5, the prediction was true (true negative; TN); for predicted values greater than 0.5, the prediction was false (false positive; FP).
We calculated the prediction accuracy (*Ac*) as follows:
The sensitivity (*Se*) and specificity (*Sp*) of predicted values were defined as follows:
where *N*~*TP*~, *N*~*FN*~, *N*~*TN*~and *N*~*FP*~are the number of TN, FN, TN and FP subjects, respectively. *N*~*case*~and *N*~*control*~are the number of case and control subjects, respectively.
Parameter Decreasing Method (PDM)
---------------------------------
In order to extract SNPs closely associated with CAA, we selected the input variables by parameter decreasing method (PDM) after the ANN model with 25 SNPs was constructed. In PDM, 1 SNP was excluded from input variables in turn, and ANN models were constructed with the remaining 24 SNPs by performing the cross-validation described below. From among the 25 models thus constructed, the model with minimum *N*~*error*~averaged in the cross-validation step was selected. When minimum *N*~*error*~was equal to that of other models within the maximum learning time, the model with minimum *Er*value was selected as described above. The PDM step was repeated until 1 SNP remained as input variable. The PDM procedure was performed 5 times with unifying learning rates of 0.1 and learning time of 2000, and the rank of importance of selected SNPs was determined as described in Results section. We performed 5 PDM trials so that the effects of randomized initial connection weights might be minimized. In 5 PDM trials, data set for cross-validation mentioned below was reconstructed every time.
Cross-validation
----------------
Cross-validation allows estimation of the prediction error of a model by leaving out a portion of the data as an evaluation data \[[@B24]\]. In the present study, to investigate the flexibility of the ANN, learning and evaluation were performed using the ANN and 5-fold cross-validation. With 5-fold cross-validation, the data set for the 172 cases and 172 controls was divided into 5 groups with randomizing and alternating the data. In each group, the number of cases was equal to that of controls. Four groups were assigned as learning data, and 1 group was assigned as evaluation data; this learning and evaluation process was repeated 5 times, so that each group was assessed once as evaluation data. Then, the prediction accuracy of evaluation data across all 5 trials was calculated and averaged for the overall prediction accuracy of the ANN model shown in Table [2](#T2){ref-type="table"}. Sensitivity and specificity were also calculated.
Logistic Regression (LR) Model
------------------------------
An LR model was constructed using SPSS 11.5J statistic software for Windows (SPSS Japan Inc., Tokyo), for comparison with the ANN model. All 25 SNPs were used as input variables of LR. For LR analysis, we used 50 main effects plus an intercept but not any interaction terms. As with the ANN model, the data set was divided into 5 groups and the cross-validation was performed. Prediction accuracy, sensitivity and specificity were calculated.
Determination of differences in frequency of alleles and genotypes
------------------------------------------------------------------
We also examined association between CAA and combinations of SNPs by calculating *P*-value using a χ^2^test. The χ^2^test was used to evaluate the differences in frequencies of alleles or genotypes between cases and controls. The *P*-values shown in Table [1](#T1){ref-type="table"} were calculated using 172 cases and 172 controls. Degree of freedom (D.F.) (shown in Table [1](#T1){ref-type="table"}) was 2 for 3 types of subjects; e.g., homozygote of the major allele, heterozygote, and homozygote of the minor allele. In the test with one SNP, when the expectancy for subjects homozygous for the minor allele (calculated from the frequency of the genotype) was less than 5 subjects for both case and control, we regarded the homozygote of the minor allele and the heterozygote as identical and defined degree of freedom as 1. In the tests with 2-SNP and 3-SNP combinations, we used the D.F. shown in Table [1](#T1){ref-type="table"} to find the change of differences in frequency under the same condition of SNP alone. If, in more than 5 subjects, all expectancies for subjects satisfied the test conditions, we calculated *P*-value with χ^2^test. In order to determine important combinations, we use two evaluation bases (*P*-value and effective combination value (ECV)) mentioned in Results section.
Authors\' contributions
=======================
YT carried out ANN modeling of SNP data including PDM and calculating *P*-value using a χ^2^test. ST and YH carried out the basic analysis using ANN and data preprocessing. YS and TS participated in providing of SNP data and the design of LR analysis. TK participated in the design of the study. HH conceived of the study, and participated in its design and coordination. All authors read and approved the final manuscript.
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Structure of ANN. For the analysis of 25 SNPs, 50 input layer units were provided. The number of hidden layer units was changed from the usual 6 to 10, to optimize the ANN for the highest possible prediction accuracy. The output layer had only 1 unit. Because the ANN model has connection weight parameters, which depend on the number of connection units, analysis of 25 SNPs with 6 hidden layer units requires 306 connection weight parameters.
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Diagnostic prediction of ANN (a) and LR (b) using 25 SNPs, and prediction of ANN (c) and LR (d) using the 10 selected SNPs. Prediction results of evaluation data are presented. Gray and white bars represent frequency of case subjects and control subjects, respectively.
:::
:::
::: {#F3 .fig}
Figure 3
::: {.caption}
######
Effect of number of input variables on ANN model accuracy during PDM procedure. Closed triangles represent average accuracy for learning and evaluation data. Closed squares represent the rate of case subjects that means *N\'*~*case*~/*N*~*case*~. In this case, *N\'*~*case*~is the number of cases whose genotype pattern is match to control\'s genotype pattern at least one control (*N*~*case*~= 172 subjects).
:::
:::
::: {#F4 .fig}
Figure 4
::: {.caption}
######
Reconstruction of ANN model using SNPs listed in Table 3. Closed triangles represent average accuracy for all data of learning and evaluation.
:::
:::
::: {#F5 .fig}
Figure 5
::: {.caption}
######
Distribution of *IL-4Rα*(148 G/A) genotype with *CysLT2*(2534 A/G) genotype AG or GG (*P*= 0.00030) (a), and distribution of *C3*(1692 G/A) genotype with *IL-10*(-571 C/A) genotype CA and *IL-4*(-590 C/T) genotype CT (*P*= 0.00426) (b). Gray and white bars represent frequency of case subjects and control subjects, respectively.
:::
:::
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Polymorphisms used in the present study.
:::
Gene Polymorphism D.F.^a^ *P*-Value^b^
---------- ----------------------- --------- --------------
*TGF-β* -509 C/T 2 0.6299
*IL-10* -571 C/A 2 0.1074
*IL-4* -590 C/T 2 0.9085
*IL-4Rα* 148 G/A (Val50Ile) 2 0.0155
*TXA2R* 924 T/C (synonym) 1 0.5603
*ADRB2* 265 A/G (Arg16Gly) 2 0.0541
*STAT6* 2964 G/A 2 0.7881
*FcεRIB* 811 A/G (Glu237Gly) 1 0.5382
*ITK* 2860 G/A 2 0.9623
*CysLT2* -580 T/C 2 0.7868
*CysLT2* 108 C/A 1 0.0036
*CysLT2* 2534 A/G 2 0.5664
*IL-12B* 1146 C/A 2 0.1154
*IKAP* 2446 A/C (Ile816Leu) 2 0.7988
*IKAP* 3214 T/A (Cys1072Ser) 2 0.2997
*IKAP* 3473 C/T (Pro1158Leu) 2 0.2779
*C*5 1155 A/G 2 0.1056
*C*5 4266 G/A 2 0.0581
*C*3 912 G/A 2 0.5020
*C*3 1692 G/A 2 0.6993
*C*3 4896 C/T 2 0.7205
*C5aR* 1289 C/A 2 0.1211
*C5aR* 1337 C/T 1 0.2398
*C3aR* 1526 G/A 1 0.7366
*IL-13* 329 G/A (Arg110Gln) 2 0.7924
^a^Degree of freedom (see text). ^b^Association between SNPs and CAA was evaluated as *P*-value, which was calculated with χ^2^test.
:::
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Accuracy, sensitivity and specificity of ANN and LR.
:::
a
------------ ---------------- ------------------- -------------------
ANN accuracy \[%\] sensitivity \[%\] specificity \[%\]
learning 98.8 99.1 98.4
evaluation 73.3 74.4 72.1
LR accuracy \[%\] sensitivity \[%\] specificity \[%\]
learning 68.8 69.2 68.3
evaluation 48.3 45.3 51.2
b
ANN accuracy \[%\] sensitivity \[%\] specificity \[%\]
learning 97.7 98.0 97.5
evaluation 74.4 77.9 70.9
LR accuracy \[%\] sensitivity \[%\] specificity \[%\]
learning 59.4 57.8 60.9
evaluation 47.7 48.3 47.1
\(a) with 25 SNPs.
\(b) with 10 SNPs selected by PDM.
:::
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Ranking of SNPs selected by PDM.
:::
SNP *P*-value^a^ n (/5)^b^ point (/50)^c^
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- -------------- ----------- ----------------
*IL-4Rα*(148 G/A) 0.0155 5 47
*CysLT2*(2534 A/G) 0.5664 5 38
*IL-10*(-571 C/A) 0.1074 5 27
*C*3 (4896 C/T) 0.7205 4 27
*C*3 (1692 G/A) 0.6993 2 18
*IKAP*(2446 A/C) 0.7988 5 17
*IL-13*(329 G/A) 0.7924 4 16
*C*3 (912 G/A) 0.5020 3 16
*STAT6*(2964 G/A) 0.7881 2 14
*IL-4*(-590 C/T) 0.9085 2 13
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*IKAP*(3473 C/T) 0.2779 2 12
*ADRB2*(265 A/G) 0.0541 4 8
*IKAP*(3214 T/A) 0.2997 2 8
*C5aR*(1289 C/A) 0.1211 1 6
*C*5 (4266 G/A) 0.0581 1 5
*CysLT2*(108 C/A) 0.0036 2 2
*C3aR*(1526 G/A) 0.7366 1 1
The 10 SNPs over the dotted line were used for the following experiments.
^a^*P*-value was calculated with χ^2^test.
^b^Number of SNPs selected within last 10 input variables during PDM procedure (5 trials performed).
^c^Point of SNPs selected within last 10 input variables during PDM procedure. The score of order ranged from 1 to 10 points, based on the significance order in 1 PDM procedure and totaled in 5 trials.
:::
::: {#T4 .table-wrap}
Table 4
::: {.caption}
######
Selection of effective combinations evaluated with two bases *P*-value and ECV among the 10 selected SNPs.
:::
combination 2-SNP 3-SNP
------------- ------- -------
*N*~*comb*~ 90 360
13 72
47/11 43/43
27/10 25/25
6/5 3/3
^a^The number of combination that satisfies the following conditions: *P*-value \< 0.05.
^b^The number of combination that satisfies the conditions: ECV\<1, 0.5 and 0.1, respectively.
^c^The number of combination that satisfies the conditions: both ECV\<1, 0.5, 0.1 and *P*-value \< 0.05, respectively.
:::
::: {#T5 .table-wrap}
Table 5
::: {.caption}
######
Number of effective combinations (*N*~*ef*~) and its concentration ratio.
:::
2-SNP combination
---------------------- ------- ------- ------- -------
10 SNP^a^:15 SNP^b^ 2 : 0 1 : 1 0 : 2
*N*~*comb*~ 90 300 210
10 23 3
0.28 0.64 0.08
0.15 0.5 0.35
1.85 1.28 0.24
3-SNP combination
10 SNP^a^: 15 SNP^b^ 3 : 0 2 : 1 1 : 2 0 : 3
*N*~*comb*~ 360 2025 3150 1365
25 82 64 39
0.12 0.39 0.30 0.19
0.05 0.29 0.46 0.20
2.28 1.33 0.67 0.94
^a^Selected by PDM
^b^Not including 10 SNP selected by PDM
^c^The number of 2-SNP combination that satisfies the following conditions:*P*-value \< 0.05 and ECV2\<0.5.
The number of 3-SNP combination that satisfies the conditions: *P*-value \< 0.05 and ECV3 \< 0.5.
:::
::: {#T6 .table-wrap}
Table 6
::: {.caption}
######
Two-SNP interactions among the 10 selected SNPs (*P*-value \< 0.05 and ECV2 \< 0.5)
:::
SNP 1 SNP 1 genotype SNP 2 *P*^a^ *P*^b^ *P*^c^ *P*^b^× *P*^c^ *P*^a^/(*P*^b^× *P*^c^)
-------------------- ---------------- -------------------- --------- -------- -------- ---------------- -------------------------
*C*3 (4896 C/T) TT *C*3 (1692 G/A) 0.01461 0.7205 0.6993 0.5038 0.0290
*CysLT2*(2534 A/G) AG+GG *IL-4Rα*(148 G/A) 0.00030 0.5664 0.0155 0.0088 0.0344
*C*3 (1692 G/A) AA *C*3 (4896 C/T) 0.02858 0.6993 0.7205 0.5038 0.0567
*C*3 (912 G/A) GG *C*3 (4896 C/T) 0.02345 0.5020 0.7205 0.3617 0.0648
*C*3 (4896 C/T) TT *C*3 (912 G/A) 0.03073 0.7205 0.5020 0.3617 0.0850
*C*3 (1692 G/A) GA *CysLT2*(2534 A/G) 0.04917 0.6993 0.5664 0.3961 0.1241
*STAT6*(2964 G/A) GG+GA *IL-10*(-571 C/A) 0.01752 0.7881 0.1074 0.0846 0.2070
*C*3 (4896 C/T) TT *IL-4Rα*(148 G/A) 0.00271 0.7205 0.0155 0.0112 0.2426
*C*3 (912 G/A) GG *IL-4Rα*(148 G/A) 0.00345 0.5020 0.0155 0.0078 0.4442
*IL-4*(-590 C/T) CT+TT *IL-4Rα*(148 G/A) 0.00689 0.9085 0.0155 0.0141 0.4896
^a^*P*-value of combination of SNP 2 with genotype consisting of SNP 1. In this case, D.F. of SNP 2 is identical to that of Table 1.
^b^*P*-value of SNP 1 calculated alone.
^c^*P*-value of SNP 2 calculated alone.
^a^*P*^/(*b*^*P*^×\ *c*^*P*^)\ represents\ effective\ combination\ value\ (ECV2).^
:::
|
PubMed Central
|
2024-06-05T03:55:47.902690
|
2004-9-1
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC518959/",
"journal": "BMC Bioinformatics. 2004 Sep 1; 5:120",
"authors": [
{
"first": "Yasuyuki",
"last": "Tomita"
},
{
"first": "Shuta",
"last": "Tomida"
},
{
"first": "Yuko",
"last": "Hasegawa"
},
{
"first": "Yoichi",
"last": "Suzuki"
},
{
"first": "Taro",
"last": "Shirakawa"
},
{
"first": "Takeshi",
"last": "Kobayashi"
},
{
"first": "Hiroyuki",
"last": "Honda"
}
]
}
|
PMC518960
|
Background
==========
Cancer is a leading cause of death in humans, and current studies in the clinical area focus on either the early detection of this disease or on the development of new selective treatment tools. New tumour markers can provide aid in cancer diagnosis and create novel treatment opportunities.
Ndrg1, also named Cap43, Drg 1, RTP and rit42 following the discovery of its gene (*NDRG1*) in different laboratories, is a stress responsive protein which shuttles between cytoplasm and nucleus upon certain insults \[[@B1]-[@B5]\]. After its independent discovery in our lab \[[@B1]\], we worked on the expression of this gene and the availability of its protein product in human cells and tissues under different conditions.
Since our origin for the induction of the *NDRG1*gene was nickel exposure, we worked on possible ways by which nickel could change the expression of this gene. Among the mechanisms investigated were epigenetic changes (DNA methylation and histone acetylation), signal transduction pathways (tyrosine phosphorylation, adenylate cyclase cascade, calmodulin, PKC, PI3-K), and ROS-mediated activation. However, none of these mechanisms were found to be involved in the induction of *NDRG1*gene by nickel compounds \[[@B1],[@B6]-[@B9]\].
On the other hand, it was shown that nickel induced the expressions of several hypoxia-responsive genes including vascular endothelial growth factor \[[@B10]\], erythropoietin \[[@B11]\], and glyceraldehyde-3-phosphate dehydrogenase \[[@B12]\]. Moreover, a well known hypoxia-mimicking agent is cobalt which is another transition metal adjacent to nickel in the periodic table. These facts led to the idea that the *NDRG1*could be another hypoxia-responsive gene, and nickel could induce the expression of this gene creating hypoxia-like state in cells, as does cobalt. In the present study, the effects of hypoxia and hypoxia-mimicking agents on the *NDRG1*gene expression have been investigated. Because HIF-1 transcription factor is a major regulator of hypoxia-responsive genes \[[@B13],[@B14]\], the relationship between *NDRG1*gene expression and HIF-1 has also been studied. Here, it is reported that hypoxia is an inducer of the *NDRG1*gene, and that HIF-1 transcription factor is involved in the regulation of this gene, but HIF-1 independent pathways also exist in the induction of the gene in the case of chronic hypoxia.
The process of tumour expansion is characterized by rapid growth of cancer cells as the tumour establishes itself in the host. Accompanying this rapid growth are alterations in the cancer cell microenvironment, typically caused by an inability of local vasculature to supply enough oxygen and nutrients to the rapidly dividing tumour cells. This makes hypoxia one common feature of solid tumours \[[@B15]\]. Exploration of Ndrg1 protein expression patterns in various tissues showed that Ndrg1 protein was overexpressed in cancers compared to normal tissues. Because of its differential expression in cancer tissues and the high stability of the protein, Ndrg1 is proposed as a useful new tumour marker.
Results
=======
Hypoxia and its mimetics induce in vitro expression of *NDRG1*gene
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To determine whether hypoxia could induce the transcription of the *NDRG1*gene, A549 cells were exposed to hypoxia (0.5% O~2~) for different time periods. The RNA transcript of *NDRG1*started to appear after 4 hours of incubation and increased up to 18 hours (Fig. [1A](#F1){ref-type="fig"}). To explore if this induction is also translated into protein response, Ndrg1 protein levels were determined after the exposure of cells to hypoxia and its mimetics. Figure [1B](#F1){ref-type="fig"} shows the accumulation of the protein following the incubation of A549 cells with these agents. To determine about the longevity of Ndrg1, at the end of hypoxia exposure cells were incubated under normoxic conditions for different time periods, and the levels of the protein were assessed. The results of this experiment showed that even after returning back to normoxia Ndrg1 protein levels remained elevated for at least 16 hours, indicating the stable nature of the protein (Fig. [1C](#F1){ref-type="fig"}). The induction of the Ndrg1 protein by hypoxia and transition metals has also been shown in several other cell lines (Fig. [2](#F2){ref-type="fig"}), confirming that this induction is a general phenomenon rather than being a cell-specific one.
::: {#F1 .fig}
Figure 1
::: {.caption}
######
**The induction of *NDRG1*gene expression by hypoxia and its mimetics.A)**A549 cells were exposed to normoxia (20% O~2~, control) for 20 hours or to hypoxia (0.5% O~2~) for the time periods indicated in the figure. 15 μg of total RNA was isolated and subjected to a Northern blot analysis as described in \'Methods\' section. The blot first hybridized with *NDRG1*probe (top panel), and then the membrane was stripped and rehybridized with *actin*probe (bottom panel) to show loading. **B)**A549 cells were exposed to 0.5 mM NiCl~2~(Nickel), 200 μM CoCl~2~(Cobalt), 200 μM desferrioxamine (DFX), or hypoxia (0.5% O~2~) for 20 hrs. 40 μg of whole cell protein extracts were loaded into each lane and subjected to Western blot analysis as described in \'Methods\' section, using antibody against Ndrg1. Bottom panel (actin) shows loading. **C)**A549 cells were first exposed to hypoxia (0.5% O~2~) for 20 hrs, then taken out of hypoxic chamber and incubated additionally for the time periods indicated under normoxic (20% O~2~) conditions. Western blot analysis with antibody against Ndrg1 was carried out in whole cell protein extracts. Bottom panel (actin) shows loading.
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::: {#F2 .fig}
Figure 2
::: {.caption}
######
**The confirmation of Ndrg1 protein induction in different cell lines.(A)**HTE cells were incubated with different concentrations of NiCl~2~(Ni), hypoxia, and 300 μM of CoCl~2~(Co) for 20 hrs. **(B)**HOS and MCF-7, **(C)**PW and DU-145 cells were incubated with 500 μM of NiCl~2~(nickel), hypoxia, and 300 μM of CoCl~2~(cobalt) for 20 hrs. Western blot analyses were done as described in \'Methods\' section. The membranes were first incubated with anti-Ndrg1 antibody (top panels), then stripped, and rehybridized with anti-actin antibody (bottom panels) to show loading.
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The regulation of *NDRG1*expression by HIF-1 transcription factor
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HIF-1 is a heterodimeric transcription factor consisting of HIF-1α and HIF-1β subunits. It is expressed by all cells of the human body in response to hypoxia and contributes to the regulation of hypoxia-responsive genes. HIF-1α is the unique, O~2~-regulated subunit that determines HIF-1 activity whereas HIF-1β is expressed ubiquitously and is a common partner of several other proteins. Therefore, the elimination of HIF-1α expression completely prevents the formation of HIF-1 protein. To investigate the relationship between HIF-1 transcription factor and the expression of *NDRG1*gene, HIF-1 proficient (HIF-1α^+/+^) and deficient (HIF-1α^-/-^) cells were exploited. Short-term hypoxia (20 hrs) experiment showed that *NDRG1*mRNA was induced in HIF-1 proficient but not in deficient cells (Fig. [3A](#F3){ref-type="fig"}). The transcriptional induction of the gene by both nickel and cobalt was also dependent upon HIF-1 transcription factor. These results have been confirmed with the data obtained at the protein level: the same agents (short-term hypoxia, nickel, and cobalt) caused the accumulation of Ndrg1 protein in HIF-1 proficient but not in deficient cells (Fig. [3B](#F3){ref-type="fig"}).
::: {#F3 .fig}
Figure 3
::: {.caption}
######
**The role of HIF-1 in the regulation of *NDRG1*gene expression.A)**HIF-1 proficient (HIF-1α^+/+^) and deficient (HIF-1α^-/-^) cells were exposed to 0.5 mM NiCl~2~, 300 μM CoCl~2~, and hypoxia (0.5% O~2~) for 20 hrs. 15 μg of total RNA was isolated and subjected to a Northern blot analysis using *NDRG1*probe (top panel). Ethidium bromide staining was used to adjust loading (bottom panel). **B)**HIF-1α^+/+^and HIF-1α^-/-^cells were exposed to 0.5 mM NiCl~2~, 300 μM CoCl~2~, and hypoxia (0.5% O~2~) for 20 hrs. 40 μg of protein extracts were subjected to Western blot analysis using antibody against Ndrg1 protein (top panel). Actin bands in the bottom panel show loading. **C)**Cells were first incubated for 24 hours under normoxic conditions for attachment (Day 0) and then exposed to hypoxia for up to three days. Western blot analysis with antibody against Ndrg1 was carried out in 25 μg of whole cell protein extracts (top panel). Actin bands in the bottom panel show loading.
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In another experiment, HIF-1α^+/+^and HIF-1α^-/-^cells were exposed to long-term hypoxia up to three days, to simulate the chronic conditions that cancer cells go through. The results revealed that hypoxia increased Ndrg1 protein levels even in HIF-1α^-/-^cells starting from the second day of hypoxia (Fig. [3C](#F3){ref-type="fig"}). However, the level of protein accumulation on the third day was considerably higher in HIF-1α^+/+^cells than in HIF-1α^-/-^cells. These observations implied that the Ndrg1 protein induction was not totally dependent on HIF-1 transcription factor, and that some other pathways were also involved in the induction of Ndrg1 protein by long-term hypoxia.
The detection of Ndrg1 and HIF-1α protein levels in normal and cancerous human tissues
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Figure [4](#F4){ref-type="fig"} shows a variety of human normal and cancer tissues stained immunohistochemically with anti-Ndrg1 polyclonal antibody. To understand whether elevations of Ndrg1 protein coincided with the expression of HIF-1 transcription factor, we also stained the tissues with an antibody to HIF-1α (Fig. [5](#F5){ref-type="fig"}). In lung, Ndrg1 preferentially stained malignant cells including both non-small and small cell types, whereas surrounding normal tissue remained negative for staining (Fig. [4A,4B](#F4){ref-type="fig"}). In contrast to Ndrg1, HIF-1α was present in both normal and lung cancer cells at similar levels (Fig. [5A,5B](#F5){ref-type="fig"}, and Table [1](#T1){ref-type="table"}). As shown in Figure [5B](#F5){ref-type="fig"}, HIF-1α was present at higher levels in some cancer cells but not to the extent of Ndrg1 (Fig. [4B](#F4){ref-type="fig"}). In brain tissue, Ndrg1 antibody selectively stained cancer cells whereas normal brain remained negative for this staining. Figure [4C](#F4){ref-type="fig"} shows the normal brain tissue staining and Figure [4D](#F4){ref-type="fig"} shows human glioblastoma multiforme. Ndrg1 preferentially stained the tumour cells adjacent to the necrotic areas which were supposed to be hypoxic. In both astrocytomas and hemangioblastomas there was intense staining for both Ndrg1 and HIF-1α in a number of different patients. Skin cancer melanoma cells showed the most intensive staining with Ndrg1 antibody (Fig. [4F](#F4){ref-type="fig"}), and a benign skin lesion nevus had very limited Ndrg1 staining (Fig. [4E](#F4){ref-type="fig"}). In contrast, staining with HIF-1α antibody showed little effect in melanoma cells (Fig. [5H](#F5){ref-type="fig"}). Ndrg1 protein was generally found at low levels in most normal tissues with the exception of some higher expression in the distal and proximal convoluted tubule of the kidney (Fig [4G](#F4){ref-type="fig"}, and Table [1](#T1){ref-type="table"}). The distal and proximal convoluted tubules of the kidney also expressed HIF-1α (Fig. [5C](#F5){ref-type="fig"}). There was also expression of Ndrg1 protein in normal colon mucosa and smooth muscle, as well as some expression in normal breast and prostate (Fig. [4I,4K](#F4){ref-type="fig"}, and [4M](#F4){ref-type="fig"}). However, with the exception of the colon samples, the expression of Ndrg1 protein in cancer cells of these tissues was considerably higher (Fig. [4L,4N](#F4){ref-type="fig"}). In normal human tissues that showed immune reactivity to Ndrg1 antibody (such as kidney, prostate, breast, and colon) staining was emphasized particularly in glandular structures and tubular epithelia. Table [1](#T1){ref-type="table"} summarizes the total number of tissues and staining intensities. As seen from the table, differential expression between normal and cancer tissues was much more apparent in Ndrg1 than HIF-1α.
::: {#F4 .fig}
Figure 4
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######
**Immunohistochemical detection of Ndrg1 protein in human tissues.**The nature of the tissue is indicated on top of each picture. Original magnifications are as follows: A, ×400; B, ×400; C, ×100; D, ×100; E, ×400; F, ×400; G, ×400; H, ×400; I, ×100; J, ×100; K, ×400; L, ×400; M, 100; N, ×100.
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::: {#F5 .fig}
Figure 5
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######
**Immunohistochemical detection of HIF-1α protein in human tissues.**The nature of the tissue is indicated on top of each figure. Original magnifications are as follows: A, ×400; B, ×400; C, ×100; D, ×100; E, ×100; F, ×100; G, ×40; H, ×40.
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::: {#T1 .table-wrap}
Table 1
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######
The presence of Ndrg1 and HIF-1α proteins in various normal and malignant human tissues
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**TISSUE (n)** **Ndrg1** **HIF-1α**
-------------------- ----------- ------------ ---- ---- ---- ---- ---- ----
Normal Lung (30) 24 6 \- \- 4 11 15 \-
Lung Cancer (30) \- \- 3 27 \- 6 21 3
Normal Liver (20) 7 13 \- \- 2 15 3 \-
Liver Cancer (20) \- \- 4 16 \- 11 2 7
Normal Breast (18) 3 13 2 \- 1 9 8 \-
Breast Cancer (20) \- \- 6 14 \- 4 7 9
Smooth Muscle (30) 12 15 3 \- 9 11 10 \-
S.M. Cancer (24) \- 6 7 11 \- 9 12 3
Normal Brain (28) 24 4 \- \- 18 10 \- \-
Brain Cancer (36) \- \- 11 25 \- \- 15 21
Normal Kidney (15) \- 6 8 1 \- 5 10 \-
Kidney Cancer (22) \- \- 7 15 \- 7 9 6
Normal Skin (20) 14 6 \- \- 11 9 \- \-
Melanoma (10) \- \- \- 10 4 6 \- \-
Tissues were stained immunohistochemically with antibodies against Ndrg1 and HIF-1α as described in \'Methods\' section. Each value shown in the table is from a single tissue sample from an individual patient. The numbers in parentheses (n) represent the total numbers of tissues stained with both antibodies. The expression levels were marked as follows: (-) no staining; (+) weak; (++) moderate; (+++) overexpression.
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Discussion
==========
Experiments conducted in this study provide clear evidence that hypoxia and its mimetics induce the expression of *NDRG1*gene at both the RNA and protein level (Figs. [1](#F1){ref-type="fig"}, [2](#F2){ref-type="fig"}, and [3](#F3){ref-type="fig"}). It is hypothesized that nickel induces this gene by creating hypoxia-like conditions in cells. Support for this hypothesis came with the discovery of the first molecular oxygen sensors in mammalian cells, namely proline and asparagine hydroxylase enzymes which regulate the oxygen-dependent post-translational modification of HIF-1α protein and thereby change its stability and transcriptional activity. Prolyl hydroxylase PHD hydroxylates HIF-1α at residue Pro^564^in the presence of oxygen which creates a signal for pVHL to bind it, causing consecutive ubiquitination and proteasomal degradation of HIF-1α protein \[[@B16],[@B17]\]. Likewise, in the presence of oxygen asparaginyl hydroxylase enzyme FIH-1 (factor inhibiting HIF-1) hydroxylates C-TAD domain of HIF-1α which in turn prevents it binding to coactivator p300/CBP and limits transactivation ability \[[@B18]-[@B21]\]. Under hypoxic conditions these modifications of HIF-1α by above mentioned enzymes do not occur, and the transcription of hypoxia-responsive genes are promoted \[[@B22]-[@B24]\].
The hypoxia-responsive element (HRE) is a specific five nucleotide-HIF binding-DNA sequence (5\'-RCTCG-3\') which is common in all hypoxia-responsive genes \[[@B25],[@B26]\]. *NDRG-1*gene has three HIF-1 binding sites in its non-coding sequence, one in its promoter and the other two in the 3\' untranslated region \[[@B27]\]. It is known that a HIF-1 binding site in the 3\' region of the erythropoietin gene regulates the transcription of this hypoxia-responsive gene \[[@B28]\]. Conceivably, *NDRG1*is likely to be regulated by HIF-1 through the binding sites in its untranslated sequences.
HIF-1 modifier enzymes, PHD and FIH-1, both have non-heme iron centres (29), and transition metals nickel and cobalt can interact with these centres, subsequently inhibiting the enzymes (30). By their effects on HIF-1 modifying enzymes, nickel and cobalt have the capacity of creating constitutive hypoxia-like conditions in cells \[[@B31]-[@B33]\].
Our hypothesis relating nickel, oxygen-sensing, hypoxia, HIF-1, pVHL, and *NDRG1*expression may be elaborated as follows: when we expose cells to nickel, internalized nickel inhibits PHD enzyme interacting with its iron centre. This prevents the hydroxylation of proline residue in the ODD domain of HIF-1α and subsequent pVHL binding, rescuing HIF-1α from proteasomal degradation (Fig. [6](#F6){ref-type="fig"}, *upper part*). Rescued and accumulated α subunits of HIF-1 form stable heterodimers with β subunits and translocate to the nucleus, and HIF-1αβ heterodimers bind to hypoxia responsive elements (HRE) of the *NDRG1*gene and promote the transcription of the gene. Nickel also inhibits the FIH-1 enzyme and subsequent hydroxylation of C-TAD domain of HIF-1α, and this in turn results in the recruitment of coactivators of HIF-1 to the *NDRG1*gene regulatory sequences thereby further stimulating the expression of the gene (Fig. [6](#F6){ref-type="fig"}, *lower part*). However, since the experiments to show the specific interaction between metals and HIF-1 modifying enzymes are yet to be executed, this aspect of the hypothesis remains unproven.
::: {#F6 .fig}
Figure 6
::: {.caption}
######
The illustration of the hypothetical mechanism by which nickel and cobalt upregulate the expression of the *NDRG1*gene
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Ndrg1 protein outlasts HIF-1 after hypoxia. Despite being a major regulator of hypoxia response, HIF-1 transcription factor is a very unstable protein which is rapidly degraded under normoxic conditions; the half-life of HIF-1α in post-hypoxic cells is less than 5 minutes. On the other hand our results showed that Ndrg1 protein levels remain high at least 16 hours after returning to normoxic conditions (Fig. [1C](#F1){ref-type="fig"}). Similar results have been reported by Lachat et al. (34) who showed that it took 48 hours for Ndrg1 levels to return to pre-anoxic levels after the cessation of hypoxia. Their experiment carried out in colon carcinoma cells (SW480) supports our results, indicating that the high stability of Ndrg1 protein is not cell specific.
Our study of relationship between HIF-1 and *NDRG1*expression indicated that the induction of the gene was primarily dependent on this transcription factor (Fig. [3](#F3){ref-type="fig"}). Neither RNA nor the protein product of *NDRG1*gene was induced in HIF-1α^-/-^cells upon short-term exposures to hypoxia. In the long-term hypoxia experiment we detected some amount of Ndrg1 protein in HIF-1α^-/-^cells starting from the second day, but the levels of protein accumulation on the second and third days were considerably higher in HIF-1α^+/+^cells than those in HIF-1α^-/-^cells. However, these results indicate that in chronic hypoxic conditions such as cancer, other factors additional to HIF-1 could be involved in the regulation of *NDRG1*gene expression. Several HIF-1 independent pathways have been described to date as being effective under hypoxic conditions (35--40).
Our work in several human tissues showed that in the majority of these organs Ndrg1 protein was differentially overexpressed in cancers compared to normal tissues (Fig. [4](#F4){ref-type="fig"}, Table [1](#T1){ref-type="table"}). Normal tissue samples of certain organs (lung and brain) were almost completely free of Ndrg1 expression, whereas these samples showed HIF-1 protein expression to some extent. In some cases (especially glioblastoma of brain) the expression of Ndrg1 coincided with HIF-1 protein, indicating that induction of HIF-1α by hypoxia probably resulted in Ndrg1 accumulation in these cancers. In most of the other cases though, diffuse and strong Ndrg1 expression did not coincide with HIF-1 protein expression. These differences in the detection of two proteins may be explained by (i) considerably higher stability of Ndrg1 protein compared to that of HIF-1, and (ii) reflection of HIF-1 independent hypoxia response by Ndrg1. With these features, Ndrg1 has the capacity of reflecting tumour hypoxia in a broader spectrum than does HIF-1 and could be considered as a better signature for hypoxic tumour cells than HIF-1. Therefore, despite the proposal of HIF-1 as a tumour marker \[[@B41]\], we present its down-stream product Ndrg1 as a stronger candidate of cancer marker especially for certain tissues (lung, brain, and skin).
Several normal tissue samples showed some Ndrg1 expression albeit at lower levels than in cancer samples of similar tissues. In their comprehensive study, Lachat et al. (34) showed the expression of Ndrg1 protein in normal human tissues, reporting also the intensities and sub-cellular localizations of the stainings. We observed similar staining patterns in several tissues; more emphasized stainings in the glandular, acinar, ductal, and tubular cells of normal breast, prostate, colon, and kidney tissues. We also share the observation that Ndrg1 exist in all three locations of the cells-cytoplasm, nucleus, and membrane. But, with the exception of colon mucosa, when we stained the cancerous tissues of above mentioned organs, the staining was more intense. However, since the differential expression of Ndrg1 between normal and cancer tissues of lung, brain, and skin was much starker (Table [1](#T1){ref-type="table"}), we propose Ndrg1 be initially tried as a marker for these tissues. For the reasons that are unknown, Ndrg1 was expressed at lower levels in colon cancer than it was in normal colon. Similar results have also been reported by others \[[@B42]\]. This could be due to fact that colon epithelium is a dynamic structure being continuously renewed. Studies addressing the mechanism of Ndrg1 down-regulation in colon cancers will shed more light on the function of Ndrg1 protein and its relation to cancer development.
Another common finding between our study and Lachat et al\'s (34) is no expression of Ndrg1 in normal brain and lung epithelium. Lachat et al. (34) showed at the transcriptional level that normal brain and lung express *NDRG1*, in fact these and many other tissues expressing *NDRG1*mRNA did not contain detectable levels of the protein product of this gene. This could be due to degradation of the mRNA under normal conditions. Stabilizing the mRNAs of hypoxia-responsive genes is one way cells promote the expression of these genes under hypoxic conditions (38, 39). More studies are needed to resolve how Ndrg1 levels are managed in normal cells, during hypoxia, and as well as in cancer cells.
Masuda et al. \[[@B40]\] report the down-regulation of *NDRG1*gene by VHL tumour suppressor protein (pVHL). They state that no hypoxia-responsive element exists on the 5\' flanking sequence of the gene and thus underplay the role of HIF-1 in the regulation of *NDRG1*. As mentioned previously, *NDRG-1*gene has three HIF-1 binding sites, one in its promoter and two in the 3\' untranslated region. Therefore, the down-regulation of *NDRG1*gene by pVHL is likely to be mediated through the HIF-1 pathway. The observation of *NDRG1*being down-regulated by a major tumour suppressor further supports our observation that it is up-regulated in several cancer tissues and could be used as a marker.
Hypoxia-responsive pathway (HRP) allows tumour cells to overcome harsh microenvironment conditions associated with tumour growth. The protein products of induced by this pathway (e.g. EPO, VEGF, several glycolytic enzymes) allow clones of tumour cells to gain growth advantage under unfavourable conditions, and this concept is pivotal in switching to a more malignant phenotype. Although the exact functions of Ndrg1 are still unknown, as another effector of HRP, it is also likely to help tumour cells establish themselves. Therefore, the use of drugs that specifically disrupt the functions of Ndrg1 protein may provide new cancer therapies. It is thus of interest to investigate the effects of the elimination of this protein on the cancer cell survival and proliferation. However, first Ndrg1 expression in normal hypoxic tissue (such as infarct tissues) should be determined to show the cancer specificity of the protein. Second, the potential side effects of its elimination should be assessed since several normal tissues express Ndrg1 ubiquitously.
Hypoxia is also an important determinant for the success of chemotherapy and radiotherapy \[[@B43]\]. Masuda et al. \[[@B40]\] even argue that Ndrg1 could be involved in limiting sensitivity to anti-cancer drugs. However hypoxia is an equally likely limiting factor in anti-cancer therapy, and Ndrg1 may be simply the signature of the hypoxic state.
Conclusions
===========
Hypoxia induces the *NDRG1*gene, and nickel probably causes the induction of the gene by interacting with the oxygen sensory pathway. Hypoxic induction of *NDRG1*is mostly dependent on HIF-1 transcription factor. However, regulation of the gene in long term hypoxia involves some other HIF-1 independent pathways.
Ndrg1 protein was overexpressed in the majority of cancers studied here. With the exception of colon cancer, staining with Ndrg1 antibody distinguished between normal and tumour cells in most cancerous tissues. The mechanism of this overexpression is related to the hypoxic state of cancer cells. Ndrg1 protein is a better indicator of tumour hypoxia than HIF-1 in immunohistochemical analyses. This is probably due to the stable nature of the Ndrg1 protein compared to the very unstable HIF-1 protein, and also to capacity of Ndrg1 in reflecting HIF-1 independent hypoxia response. Therefore, the determination of Ndrg1 protein in tissue samples may provide a more useful tool for cancer diagnosis. Even though the exact functions of Ndrg1 protein are still unknown, as another effector in hypoxia-response, it can help cancer cells to survive and grow under unfavourable conditions. Therefore, it may also be possible to direct therapy towards Ndrg1 protein using drugs that specifically disrupt the functions of this protein.
Methods
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Cell lines and culture conditions
---------------------------------
Human lung cancer cell line A549 (CCL185), human osteosarcoma cell line HOS (CRL 1543), human mammary carcinoma cell line MCF-7 (HTB 22), and human prostate cancer cell line DU-145 (HTB 81) were purchased from American Type Culture Collection (Rockville, MD, USA). Human trachea epithelium (HTE) cells, HIF-1α^+/+^, and HIF-1α^-/-^fibroblasts were gifts from Dr. Konstantin Salnikow of NYU. The production of HIF-1α^+/+^and HIF-1α^-/-^fibroblasts was described elsewhere \[[@B44]\]. PW cells were a gift from Dr. Qunwei Zhang of NYU.
The cell lines were maintained at 37°C as monolayers in a humidified atmosphere containing 5% CO~2~. Cells were passaged by trypsinization when they reached 70--80% confluence. A549 cells were grown in Ham\'s F-12K nutrient mixture (Kaighn\'s modification) supplemented with 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin \[equivalent to 100 units (U)/ml and 100 μg/ml, respectively\]. MCF-7, PW, HIF-1α^+/+^, and HIF-1α^-/-^cells were maintained in DMEM (Dulbecco\'s modified Eagle\'s medium) with the same supplements. HOS and HTE cells were grown in α-MEM (α-minimal essential medium) additionally supplemented with 2 mM L-glutamine. For Northern and Western blot experiments, 5 × 10^5^cells in 10 ml of media were plated in each of 10-cm dishes (Corning Inc, Corning, NY). Cell numbers were determined using the ZM Coulter Counter (Coulter Electronics, England). To render cells hypoxic, dishes were placed in an incubator chamber flushed with 95% N~2~and 5% CO~2~. This resulted in approximately 0.1--0.5% O~2~after several hours. After 20 hours, cells were released from hypoxia and quickly scraped in ice-cold phosphate-buffered saline (PBS), and analyses were performed as described below.
Northern blot analysis
----------------------
Total RNA was extracted from cells immediately after exposures by using TRIzol reagent (Gibco-BRL) according to instructions of the manufacturer. 15 μg of RNA/lane was separated by electrophoresis in 1.0% agarose-formaldehyde gels and then transferred to nitrocellulose membranes (BA-85; Scleicher & Schuell). *NDRG1*and *actin*probes were labelled with \[α-^32^P\]dCTP by using a randomly primed-DNA labelling kit (Promega). Cloning of *NDRG1*gene was as described previously \[[@B1]\]. The blot first hybridized with *NDRG1*probe, and then the membrane was stripped and rehybridized with *actin*probe to show loading. The bands were visualized by exposing X-ray films (Eastman Kodak Co, NY, USA) to hybridized membranes.
Western blot analysis
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Cells were lysed, and proteins were harvested in 125 μl of TNES buffer \[50 mM Tris-HCl (pH: 7.5), 2 mM EDTA, 100 mM NaCl, 1 mM sodium orthovanadate (Na~3~VO~4~), 10 mM sodium fluoride, and 1% NP40\] containing protease inhibitors (PMSF 1 mM, aprotinin 1 μg/ml, leupeptin 5 μg/ml, and chymostatin 2 μg/ml). 40 μg or 25 μg of protein was loaded into each lane of a 10% SDS-PAGE gel and separated by electrophoresis. Proteins were then transferred to PVDF membranes (Roche Diagnostics Co, IN, USA), and the membranes were first incubated with rabbit anti-Ndrg1 polyclonal antibody at the dilution of 1:1000 in 5% non-fat dry milk for one hour at room temperature. The antibody production is described elsewhere \[[@B3]\]. After washing four times for 15 min each with TBS buffer, the membranes were incubated with a second anti-rabbit peroxidase-conjugated antibody (Santa Cruz, CA, USA) at the dilution of 1:10^4^in 5% milk for one hour at room temperature. At the end the membranes were treated with chemiluminiscent substrate ECL (Amersham Pharmacia Biotech, UK) for 1 min at room temperature, and Biomax MR-1 films (Eastman Kodak Co, NY, USA) were exposed to the membranes. The molecular weight of Ndrg1 was determined using prestained molecular weight markers (Invitrogen Life Technologies, CA, USA).
Tissue staining
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For in vivo detection of Ndrg1 protein in human cancer and normal tissues, immunohistochemical (IHC) staining was exploited, using a rabbit polyclonal antibody against a 30-aminoacid-sequence at the C-terminal end of the Ndrg1 protein \[[@B3]\]. Tumour and normal tissue sections were obtained from the tumour registry of the Cancer Institute of New York University Medical School. The tissues were embedded in paraffin wax. Five-micron sections were cut and baked at 60°C for 30 minutes. After cooling, the sections were deparaffinized and hydrated through the following series: 3 × 5 minutes xylene, 3 × 5 minutes 100% Etoh (ethyl alcohol), 3 × 5 minutes 95% Etoh. The slides were then rinsed gently with distilled water and stained with hematoxylin-eosin for histopathological diagnosis. For antigen retrieval, the slides were heated in 1 mM EDTA buffer (pH: 8.0) in a microwave oven for 10 min, and then endogenous peroxide was blocked with methanol containing 0.35% H~2~O~2~for a further 30 min. After incubation with the antibody against Ndrg1 protein overnight, the slides were processed with a second anti-rabbit peroxidase-conjugated antibody (Santa Cruz, CA, USA). Identification of the protein was then achieved using Avidin-Biotin horseradish peroxidase complex and 3,3-diaminobenzidine (DAB) as the chromogen. Negative controls were performed using nonimmune serum instead of primary antibodies.
Immunohistochemical detection of HIF-1α protein was achieved by using Catalyzed Signal Amplification System (DAKO Corp., Carpinteria, CA) which is based on streptavidin-biotin-horseradish peroxidase complex formation. Antigen retrieval was done by 10 mM sodium citrate buffer (pH 6.0). The specimens were incubated overnight at +4°C with monoclonal anti-HIF-1α antibody (Clone MAb H1α 67, \#NB 100--123; Novus Biologicals, Littleton, CO) in a dilution of 1:1000. After the amplification of the signal according to manufacturer\'s instructions, the slides stained with chromogen DAB, counter-stained with hematoxylin, dehydrated, and then mounted.
Acknowledgements
================
I thank to Drs. Max Costa and Konstantine Salnikow of NYU for their help with the experimental design of this study.
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PubMed Central
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2024-06-05T03:55:47.908078
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2004-9-2
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC518960/",
"journal": "BMC Genet. 2004 Sep 2; 5:27",
"authors": [
{
"first": "Hakan",
"last": "Cangul"
}
]
}
|
PMC518961
|
Background
==========
The availability of complete genome sequences from different organisms makes it possible to identify, by similarity, potential homologs of genes that have been experimentally tested in other living beings, resulting in the recognition of putative functions for the proteins encoded by them. This research concept represents a revolutionary tool in modern biology, as the data generated allow for recognition of the presence or absence of genes, giving indications of the metabolic pathways present in such organisms and revealing possible particularities of the individuals in their natural habitat. Moreover, the possibility of obtaining gene sequences from organisms that have long diverged makes it feasible to use these data to trace their evolutionary origin \[[@B1]\]. Computer analysis of genome data, and its capacity to rapidly generate relevant information, contributes to a better understanding of the different evolutionary histories, especially within prokaryotes. The inferred relationship among organisms, as first defined by the use of 16S rRNA sequences, was later confirmed either by the utilization of many other conserved genes \[[@B2],[@B3]\] or even by alternative strategies to trace evolution with genetic data \[[@B4]\]. However, the utilization of a single gene to describe the organism evolution has been contested due to genomic complexity. In fact, the accumulated data have brought evidence to sustain that many prokaryotic genes do not follow vertical transmission, revealing the occurrence of gene exchange among different species, a phenomenon known as horizontal or lateral gene transfer (LGT, reviewed by Ochman \[[@B5]\]).
All known forms of life present efficient systems to maintain the integrity of their genetic material. As DNA is under constant attack by different environmental agents and metabolic by-products, evolution has provided organisms with several DNA repair pathways to remove or to tolerate lesions in their genetic material. In fact, these pathways have at least two important contrasting roles in evolution, safeguarding the genome, and allowing for a certain level of mutations in the course of evolution. The critical balance of these two activities is probably the best reason for the high levels of conservation observed in DNA repair related proteins, even across the three kingdoms, Bacteria, Archaea and Eukarya. Detailed studies of many of the different DNA repair genes and protein domains have been described previously \[[@B6],[@B7]\], confirming that information on DNA repair genes may be very useful as a source to track genome evolution.
In this work, we investigated the DNA repair genes in the recently described genomes from the Xanthomonadales group \[[@B8],[@B9]\] following an evolutionary perspective. The Xanthomonadales group bacteria have a great economic impact on agriculture in Brazil and worldwide. The characterization of DNA repair genes from these phytopathogens could help to understand the mechanisms by which these organisms respond to environmental conditions, including plant infection. On the other hand, this could contribute to defining universal features relating DNA repair with this life style. By comparing the evolutionarily close genomes of *Xanthomonas axonopodis*, *X. campestris*and *Xylella fastidiosa*, we found that certain DNA repair genes present duplications in both *Xanthomonas*species. The great relevance of gene duplication for expanding gene families, as well as for gene innovation, is a consensus among researchers. New genes can facilitate survival in new environments or make possible the use of new metabolites. We investigated the phylogeny of such duplicated genes, in search of evidence on the mechanisms by which cells evolve their DNA repair machinery. Although most DNA repair genes follow the conserved vertical transmission found for 16S rRNA phylogeny, the data clearly show that duplications may have arisen by different means. Examples of a recent duplication, as well as of other old or LGT events, generating paralogs, are presented. These results also help in tracing the origins of LGT events that lead to redundancy and also to functional diversification, especially of *Xanthomonas*bacteria.
Results and Discussion
======================
DNA repair-related genes are normally highly conserved, and grant good genetic information for investigating the evolution of organisms. Orthologs of known bacterial DNA repair proteins were identified in the plant pathogen bacteria of the Xanthomonadales group and are listed in Table [1](#T1){ref-type="table"}. The different gene content of these closely related bacterial species are of particular interest, given that they can reveal gene loss or acquisition as a consequence of their different lifestyles. Few genes are missing in the genome of *X. fastidiosa*, when compared to both *Xanthomonas*species: *ada-alkA*(fusion), *tag*, *phr*, *dinB*and *ligB*. For evolution purposes, however, the presence of several duplications, especially in the *Xanthomonas*genomes, will be focused here.
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Distribution of DNA repair genes in Xanthomonadales: presence of duplications.
:::
**Repair Pathway** ***Xanthomonas axonopodis***\[5.27 Mbp\] ***Xanthomonas campestris***\[5.08 Mbp\] ***Xylella fastidiosa***\[2.73 Mbp\]
-------------------------------------- -------------------------------------------------------------------------------------------- -------------------------------------------------------------------------------------------- --------------------------------------------------------------------------------------------
**Nucleotide Excision Repair (NER)** ***uvrA(2)***, *uvrB*, ***uvrC(2)***, ***uvrD(2)***, *mfd* ***uvrA(2)***, *uvrB*, ***uvrC(2)***, *uvrD*, *mfd* *uvrA*, *uvrB*, *uvrC*, *uvrD*, *mfd*
**Base Excision Repair (BER)** *alkA*^a^, *fpg*, *mag*, *mutY*, *nth*, *tag*, *ung*, ***xthA (2)*** *alkA*^a^, *fpg*, *mag*, *mutY*, *nth*, *tag*, *ung*, ***xthA (2)*** ***fpg (2)***, *mag*, *mutY*, *nth*, *ung*, *xthA*
**Mismatch Repair**^b^**(MMR)** *mutS*, *mutL* *mutS*, *mutL* *mutS*, *mutL*
**Direct Repair** *alkB*, *phr*, *ogt* *alkB*, *phr*, *ogt*, *alkB*, *ogt*
**Recombination Repair** *recA*, *recBCD*, *recF*, *recG*, *recJ*, *recN*, *recO*, *recR*, *recQ*, *ruvABC*, *sbcB* *recA*, *recBCD*, *recF*, *recG*, *recJ*, *recN*, *recO*, *recR*, *recQ*, *ruvABC*, *sbcB* *recA*, *recBCD*, *recF*, *recG*, *recJ*, *recN*, *recO*, *recR*, *recQ*, *ruvABC*, *sbcB*
**Other DNA Repair related genes** *ada*^a^, ***lexA(2)***, *dinB*, *ligA*^c^, ***ligB***^c^***(2)*** *ada*^a^, ***lexA(2)***, *dinB*, *ligA*^c^, ***ligB***^c^***(3)***, *umuDC* *lexA*, *ligA*^c^
Genome sizes are indicated within brackets. The DNA repair genes identified in the genome of the three organisms are shown. Those present in more than one copy due to duplications are marked in bold (numbers in parenthesis). ^a^*alkA*and *ada*regulatory domain genes are fused in these bacteria. ^b^*mutH*, found in *E. coli*, is not present in these 3 genomes. ^c^*ligA*corresponds to the NAD-dependent ligase and *ligB*to the ATP-dependent ligase (see text).
:::
The RecA protein is almost universal among bacteria and is a clear example of phylogeny that follows 16S rRNA gene evolution. In fact, this gene is always unique in all genomes analyzed and has been proposed as an alternative molecule to be used in systematic studies of Bacteria \[[@B2]\]. Figure [1A](#F1){ref-type="fig"} shows the phylogenetic tree generated for this protein, and confirms the distinction of the main groups of bacteria, such as Firmicutes, Chlamydiales, Spirochaetales and Proteobacteria. Among the proteobacteria, the Xanthomonadales branch is independently positioned at the root of gamma subdivision. It is important to note that although this seems to be consistent with the classification of these bacteria as part of gamma proteobacteria, very often the trees, from these and other proteins (see below), place the Xanthomonadales in the same branch as beta proteobacteria (*Neisseria*and *Ralstonia*).
::: {#F1 .fig}
Figure 1
::: {.caption}
######
**Consensus unrooted trees generated by the Neighbor-Joining distance method for the RecA (A) and for the LexA proteins (B).**The circles highlight the main groups of bacteria. The symbol \* indicates the beta proteobacteria. Some groups of bacteria included in (A) which are absent in the other trees: Spirochaetales: TREPA: *Treponema pallidum*(gi\| 7443874), BORBU: *Borrelia burgdorferi*(gi\| 15594476); Chlamydiales: CHLTR *Chlamydia trachomatis*(gi\| 7443880), CHLPN: *Chlamydophila pneumonia*e CWL029 (gi\| 7443883). The homologs of *X. axonopodis*and *X. fastidiosa*are indicated inside the square boxes.
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In *E. coli*, the RecA protein has been shown to participate in recombinational repair, as well as in the control of a set of physiological changes to DNA damage, known as SOS response. The induction of this regulon stems from the co-protease activity of the RecA protein, which cleaves a repressor protein, denominated LexA, allowing the expression of the set of SOS genes. The presence of *lexA*and *recA*homologs in the Xanthomonadales indicates that these bacteria also present a SOS regulon. However, in *Xanthomonas*genomes, there are two copies of the *lexA*gene. The phylogeny of LexA proteins is presented in Figure [1B](#F1){ref-type="fig"}. The general topology of this tree indicates that LexA evolution follows a similar pattern to RecA, although the *lexA*gene is not found in all groups of bacteria. The products of the two copies of the *Xanthomonas lexA*paralogs are positioned close together in the same branch of Xanthomonadales, indicating a recent duplication of such a gene. The fact that they had branched before *Xylella*\'s single *lexA*divergence indicates that this bacterium may have lost the duplication. Gene losses are expected to be extensive in *Xylella*, in agreement with this bacterium having a more specialized parasitic way of life \[[@B10]\]. The duplication of *lexA*in *Xanthomonas*points to a highly controlled SOS regulon, that may be important for fine-tuning the bacterial responses to stress induced in environmental changes. Indeed, functional characterization of *lexA1*in *X. campestris*has been performed by gene disruption, and the data indicate this protein controls the expression of the *recA*gene, as expected for the SOS regulatory circuit \[[@B11]\]. The function of the second paralog, however, remains to be elucidated. Recent report indicates that the disruption of the *lexA*gene in *Deinococcus radiodurans*does not change the level of RecA expression, suggesting that LexA protein may be related to functions other than controlling the SOS regulon in that organism \[[@B12]\].
The nucleotide excision repair (NER) pathway is one of the most important, versatile and conserved systems of DNA damage removal in bacteria. It recognizes damages, which cause significant helix distortions in the DNA molecule, these being excised as an oligonucleotide by several enzymes that act as helicases and endonucleases. The main proteins that participate in such a pathway are known as UvrA, UvrB and UvrC, which, in sequential steps, interact with one another, recognize the damaged strand (UvrA), open the double helix (UvrB), and cleave DNA (UvrC) at both sides, few nucleotides away from the lesion. Subsequently, the oligonucleotide containing the damage is removed by a DNA helicase known as UvrD. The *uvrB*gene from *X. campestris*has been cloned and it was shown to participate in the resistance of these bacteria after UV irradiation \[[@B13]\]. The NER proteins are very well conserved and universal among bacteria. A complete set of orthologs of these genes is also found in a few species of the group Euryarchaeote: *Methanothermobacter thermautotrophicus*, *Methanosarcina sp and Halobacterium*sp. NRC-1 \[[@B14]\]. Other archaea may have a different unknown NER system \[[@B15]\].
The genes *uvrA*, *uvrC*and *uvrD*are duplicated in *Xanthomonas*and the phylogenies of the proteins encoded by these orthologs, together with the single *uvrB*, are presented in figure [2](#F2){ref-type="fig"}. In general, the evolution of these proteins, particularly UvrB (figure [2B](#F2){ref-type="fig"}), follows a pattern similar to RecA, the NER protein of *Xanthomonas*being positioned in the same branch of the *Xylella*\'s ortholog, close to gamma proteobacteria as expected for a vertical descent. However, for the duplications, the patterns are different and more complex. The second ortholog of *uvrA*in *X. axonopodis*is phylogenetically closer to the also duplicated genes found in several other bacteria (figure [2A](#F2){ref-type="fig"}), thus indicating an old duplication event in evolution. The absence of this ortholog in most of the proteobacteria could be due to extensive gene loss. However, the phylogenetic proximity with unrelated organisms (including a duplication in *D. radiodurans*) points to an origin due to horizontal gene transfer from other bacteria. The functions of both *uvrA*orthologs are not necessarily related to DNA repair, since this activity can be provided by either one of them. It is relevant to mention that for the duplication found in *D. radiodurans*, White *et al*\[[@B16]\] have proposed a function related to the transport of damaged DNA out of the cell. This is due to the similarity of the UvrA protein with the ATP-binding subunit of a multifamily of genes involved in the transport across membranes, related to ABC transporters \[[@B17]\].
::: {#F2 .fig}
Figure 2
::: {.caption}
######
**Consensus unrooted trees generated by the Neighbor-Joining distance method for the UvrA (A), UvrB (B), UvrC (C) proteins and for the UvrD helicase family (D).**The numbers in front of organism names indicate the number of members of this gene family in the corresponding organism. The circles highlight the main groups of bacteria. Inside the square box, the homologs of *X. axonopodis*and *X. fastidiosa.*In (A) there is a clear distinction between the two UvrA orthologs separated by the line. In the upper part of the figure are grouped the organisms containing the second UvrA homolog, for which no function in DNA repair has yet been assigned. In (D) the names of the genes are based on annotation available.
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A similar pattern of evolution was observed for the phylogeny of UvrC protein (figure [2C](#F2){ref-type="fig"}). One of the two copies present in *X. axonopodis*is close to the *uvrC*orthologs from other gamma proteobacteria, following a vertical transmission. However, a protein with considerable similarity to the N-terminal of UvrC is found in both *Xanthomonas*species. These orthologs form an independent branch of the phylogenetic tree of UvrC, close to a heterogeneous group of gram-positive bacteria. The role of this second UvrC homolog of *E. coli*in DNA repair (named Cho protein, for Uvr***C ho***molog) has recently been investigated in detail, and was shown to have an endonuclease activity in damaged DNA \[[@B18]\]. This protein makes an incision only at the 3\' side of the lesion, while the well-known UvrC was demonstrated to incise both sides of the lesion *in vitro*\[[@B19]\]. Cho may backup UvrC in the repair process of certain kinds of obstructive damage, possibly broadening the repair capacity of the excision pathway in these bacteria \[[@B20]\]. The origin of such orthologs is not clear, and although other bacteria may present protein domains that have some similarity to Cho endonuclease, known complete Cho homologs are limited to the *Azotobacter vinelandii*, *Escherichia coli*, *Salmonella typhimurium*, *Shiguella flexneri*, and *Xanthomonas*. Curiously, in Beta proteobacteria, *Ralstonia metallidurans*and *Chromobacterium violaceum*, an endonuclease domain similar to Cho appears as a C-terminal fusion with a putative 3\'-exonuclease, corresponding to the epsilon subunit of DNA polymerase III. A similar fusion protein was found in *Mycobacterium tuberculosis*, and an interesting coordinated action of these two activities (endonuclease and exonuclease) was proposed as a new mechanism of DNA repair \[[@B20]\]. A former duplication could explain the origin of *cho*in these bacteria, but, again, one would have to concede extensive gene loss in other species. Once more, horizontal transfer events, involving part of the *uvrC*gene (the one that encodes the N-terminal) to some gamma proteobacteria, could explain the limited occurrence of *cho*only in these bacteria. Moreover, some organisms present a duplication of the complete *uvrC*gene (*Clostridium acetobutylicum*and *Listeria*). The proteins encoded by these paralogs are closely positioned in the tree, thus indicating a recent origin for them, and, possibly, functional redundancy.
The *uvr*D gene is part of a DNA helicase family, which includes the *pcr*A and *rep*genes \[[@B21]\]. The *uvrD*gene participates in the removal of damaged DNA strand, after the incision steps of NER or DNA mismatch repair have occurred. The evolution tree of these proteins is presented in figure [2D](#F2){ref-type="fig"}. Similar to *uvrA*and *uvrC*, there are two orthologs for these genes in the *X. axonopodis*genome. One of the orthologs encoded by the *uvrD*gene is closer to the gamma proteobacteria, branching with *X. fastidiosa*, following a typical vertical inheritance, while the second is similar to proteins from other prokaryotes, including Archaea and Bacteria, mainly from the firmicutes and alpha proteobacteria groups. The second ortholog of this gene from *Sinorhizobium meliloti*is found in plasmid DNA for which an alien origin is suggested, due to its lower GC content \[[@B22]\]. Additional analysis of the *uvrD*duplication in the *X. axonopodis*genome indicates that it is located close to transposon-related genes (Figure [3](#F3){ref-type="fig"}), the G+C content within this region (58.2%) being low when compared to what is found in the rest of the genome (average 64.7%). Moreover, the closest ortholog of this gene is also found in a plasmid of *Agrobacterium tumefaciens*(figure [2D](#F2){ref-type="fig"}). These data are compatible with a recent LGT event for this gene. The absence of *uvrD*duplication in the genome of *X. campestris*gives further support to the LGT hypothesis, indicating that it has been recently acquired in the *X. axonopodis*genome, possibly by means of plasmid transfer and/or transposon insertion.
::: {#F3 .fig}
Figure 3
::: {.caption}
######
**Location vicinity of the *uvrD*homolog (*uvrD*2) gene in the genome of *Xanthomonas axonopodis*pv. citri.**A bold arrow in the square box represents the ORF of this gene. The dotted arrows on each side represent transposon related proteins and the white ones represent hypothetical proteins. The numbers of Kb indicate the position at the genome. The accession numbers of the proteins corresponding to the genes shown in the figure are: gi\| 21244654 (XAC3935), gi\| 21244655 (XAC3936), gi\| 21244656 (XAC3937), gi\| 21244657 (XAC3938), gi\| 21244658 (XAC3939), gi\| 21244659 (XAC3940), gi\| 21244660 (XAC3941), gi\| 21244661 (XAC3942), gi\| 21244662 (XAC3943), gi\| 21244663 (XAC3944)
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Base excision repair (BER) protects genetic material from a wide range of DNA damaging agents \[[@B23]\]. The plasticity of this repair pathway is given by the presence of several different glycosylases, lesion recognition proteins that catalyze the first step in BER. The three organisms present similar sets of glycosylases, but *X. fastidiosa*bears two identical copies of *fpg*, probably due to its close proximity to the also duplicated rRNA genes \[[@B8]\]. This duplication may also provide to this bacterium, an enhanced protection against oxidative DNA damage. The presence of duplicated *xthA*homologs (apurinic/apyrimidinic endonuclease) in both *Xanthomonas*is another remarkable feature of BER in this group. Phylogenetic trees generated for this protein family show these orthologs located in different branches, indicating that the duplication is not a recent event. However, a miscellaneous branching pattern of the tree obtained for the different bacterial groups, results difficult to track the evolution of these genes (data not shown).
The DNA ligases catalyze the joining of breaks in the phosphodiester backbone of the DNA molecule and, thus, play an essential role in several processes of DNA repair, replication and recombination. These enzymes are evolutionary related, although two distinct families of DNA ligases are found: one that is typical for Bacteria, using NAD+ as cofactor, and a second that is typical of Eukaryotes and Archaea, but using ATP as cofactor (reviewed by Wilkinson *et al*\[[@B24]\]). As for all bacteria, only single copies of the *ligA*gene, encoding the NAD-dependent DNA ligase, is found in the *Xanthomonas*and *Xylella*genomes. The phylogeny for these proteins is presented in figure [4A](#F4){ref-type="fig"}, and it clearly follows a vertical descent, with the Xanthomonadales branch close to gamma and beta proteobacteria. However, as described for other bacteria, both *Xanthomonas*genomes present extra copies of putative ATP-dependent DNA ligases (two in *X. axonopodis*and three in *X. campestris*). The phylogenetic tree of ATP-dependent DNA ligases is shown in figure [4B](#F4){ref-type="fig"}. There is a clear independent branch, where most of the archaeal ATP-dependent DNA ligases are found, except for the orthologs observed in *Mycobacterium tuberculosis*and *Streptomyces coelicolor*. The other bacterial orthologs branch independently, wherein alpha proteobacteria predominate. A curious observation is the high and variable number of ATP DNA-ligases within the genomes of plant symbiontes, especially in the alpha proteobacteria (six in *Agrobacterium tumefasciens*, nine in *Sinorhizobium meliloti*and eleven in *Mesorhizobium loti*). It is possible that these *X. axonopodis*genes may have arisen from recent duplications, soon after gene introduction in alpha proteobacteria, probably by means of LGT from Archaea. The fact that these bacteria inhabit a common niche in plants could facilitate mutual gene exchange. However, the function of such ligases in these bacteria is unknown. As the NAD (+)-dependent ligase is present in all bacterial genomes, these Archaea-related ligase orthologs, present in certain bacteria, seem to be redundant, their roles in cell metabolism remaining a puzzle. Since NAD^+^-dependent DNA ligases are typically eubacterial, and cannot be replaced \[[@B24]\], the presence of additional ATP-dependent ligases is an unsolved question. Several lines of evidence indicate that the ligation reactions can be processed with different fidelity depending on the enzyme. Bacterial NAD^+^-dependent DNA ligases appear to perform more accurate ligation reactions, with few mispaired nucleotides being allowed in the DNA extremities \[[@B25]\]. NAD^+^-dependent DNA ligase from *Thermus*species exhibit enhanced mismatched ligations under certain conditions but catalyze reactions with 1--2 orders of magnitude more discriminative towards correct nucleotide matches than the ATP-dependent DNA ligase from T4-phage \[[@B26]\]. Working with the ATP-dependent DNA ligase from the hyperthermophilic archaeon, *Thermococcus kodakaraensis*, Nakatani *et al*\[[@B27]\] found that the enzyme could seal substrates with mismatched base-pairing at the 5\' end of the nick, but did not show activity towards the 3\' mismatched substrates.
::: {#F4 .fig}
Figure 4
::: {.caption}
######
**Consensus unrooted trees generated by the Neighbor-Joining distance method for the NAD+ dependent (A) and ATP-dependent DNA ligases (B).**The circles highlight the main groups of bacteria. The homologs in Xanthomonadales are in square boxes. The symbol \* indicates the beta proteobacteria. Some copies of homologs were excluded from this analysis given the low similarity among the DNA ligase ATP-dependent.
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Therefore, the presence of ATP-dependent DNA ligases in certain bacteria could be connected to the ligation of DNA breaks under several contexts that would generate genetic variability, with possible evolutionary advantages. In the alpha-proteobacteria group, a non homologous end joining appears to be important for the integration of inserting elements in the genome of host plants, as occurs with *Agrobacterium sp*T-DNA \[[@B28]\] or for the amplification of *Rhizobium*species *amplicons*present in pNGR234 plasmid \[[@B29]\]. In *Xanthomonas*the presence of the ATP-dependent DNA ligase could also be linked to the elevated number of transposable elements \[[@B9]\]. However, the association of this type of DNA ligase with specific processes that lead to genetic variability, as proposed above, is still under investigation.
Some other features of the DNA repair genes in Xanthomonadales are interesting to mention (Table [1](#T1){ref-type="table"}). The absence of a putative photolyase gene (*phr*) in *X. fastidiosa*, while present in both *Xanthomonas*, may be related to its limited habitat within the plant xylem or inside the insect vector \[[@B8]\]. It is also remarkable that only *X. campestris*bears the *umuC*and *umuD*genes, which encode the DNA polymerase V (UmuD\'~2~C), related to translesion synthesis \[[@B30]\]. In fact, both genes are located at the genome close to bacteriophage related genes \[[@B9]\], suggesting a recent acquisition by LGT, in a similar manner to *X. axonopodis uvrD2*gene.
Conclusions
===========
Since the genomes of *Xanthomonas*(5.1 Mbp) are much larger than that of *X. fastidiosa*(2.7 Mbp), it was not a surprise to find more duplicated DNA repair genes in the former bacteria. Mechanisms for the protection of genetic information may reflect how the organism deals with stress and a hostile environment. Thus, the increased number of DNA repair genes in *Xanthomonas*may be due to the fact that these bacteria have a more variable habitat when compared to *Xylella*, which lives most of the time inside its hosts as a parasite. In this work, DNA repair genes, which appeared duplicated in the genomes, were analyzed focusing on their evolution, although it should be pointed out that their functions in vivo remain to be investigated. The duplicated genes found in *Xanthomonas*have close orthologs in other bacteria. As *Xanthomonas*are very closely related to *Xylella*, it is thus possible that, in these cases, duplications arose before the split *Xanthomonas*-*Xylella*, and were lost in the latter.
For the genes investigated, evolution patterns indicate that duplicated genes may result mainly from relatively ancient origins. Phylogenetic errors of construction, such as long branch attraction effect, cannot be completely excluded, although the presence of close orthologs reinforce the trees generated. Moreover, the duplications are normally positioned near to orthologs also found in the genomes of some distantly related bacteria. A clear exception is the most likely recent duplication found for the *lexA*paralogs of *Xanthomonas*, but this seems to be an unusual example. The possibility that gene duplications would have occurred in an early common ancestor, followed by gene loss in most other bacteria, cannot be the only explanation for many of the genes analyzed. Therefore, horizontal gene transfer among different bacteria possibly originated some of these paralogs. A clear example of recent LGT is the *uvrD*duplication, which is often found associated with DNA mobile elements. An origin from other life kingdoms may also have occurred, as for the ATP dependent DNA ligase, a common ligase in Archaea, which may have been acquired and were established in certain bacterial genomes, including *Xanthomonas*. The LGT, more than any other genetic process, makes possible faster ecological changes with the immediate incorporation of a gene or group of genes \[[@B31]\]. Eventually, organisms may acquire pathogenic features by LGT events \[[@B32],[@B33]\]. In fact, a more efficient DNA repair system to protect genetic information would provide pathogenic organisms with tools to respond to stress caused in the host-pathogen interaction \[[@B10]\].
The new genes acquired by lateral gene exchange are expected to be maintained when they provide a selective advantage to the recipient cell \[[@B5]\]. For the DNA repair genes investigated in this study, most resulted in redundancy, pointing to function diversification among the orthologs. This seems to be the case of the *uvrC*homolog (*cho*), which has been found to have a complementary function in *E. coli*\[[@B18]-[@B20]\]. The fact that the closest orthologs, such as ATP dependent DNA ligases, are also observed in other bacteria that interact with plants may indicate both that they may play important roles in this interaction and in their necessity to adapt to the host. A common niche could also favor genetic exchange among these bacteria and would provide for the possibility of their sharing similar molecular mechanisms.
In *Mycobacterium tuberculosis*some DNA repair genes are induced by DNA damage, independently of the RecA protein \[[@B34]\]. Among them are orthologs of *uvr*A, *uvrD*and *ligB*, which are duplicated in Xanthomonas. This novel mechanism present in *M. tuberculosis*may also occur in *Xanthomonas*and support the idea that these duplications are also required protecting the genome against damage. Curiously, the duplicated genes found in *Xanthomonas*do not replace the orthologs that present vertical inheritance, similar to 16S rRNA. This reinforces the idea that they may complement the known DNA repair mechanisms with other different functions. The search for such novel functions for these genes may not only improve our knowledge on how cells protect their genomes against DNA damage, but also about how DNA repair processes evolve in bacteria.
Methods
=======
Sequences of DNA repair-related proteins were obtained at the National Center of Biotechnology Information GenBank database (35). The list of organisms, with abbreviations used and proteins analyzed, is shown in Table [2](#T2){ref-type="table"}. An expanded version, containing all accession numbers of the genes employed in phylogenetic analyses, is shown in Table S1 (see [additional file 1](#S1){ref-type="supplementary-material"}). The analysis of *Xanthomonas*was performed comparing the two different genomes of the species *X. axonopodis*and *X. campestris.*As most of their genes are very similar, only *X. axonopodis*homologs are shown, differences being described in the text. Protein sequences from complete genomes (Bacteria and Archaea) were aligned using the ClustalX multiple sequence alignment program \[[@B36]\] with manual adjustment with Genedoc (v2.6.02). Only unambiguously aligned positions (excluding poorly conserved and gap regions) were used in phylogenetic analysis. Phylogenetic trees were generated for each group of protein homolog from sequence alignments using the Phylip program version 3.5 \[[@B37]\]. Parsimony analysis was conducted using the Protpars program, and distance methods were performed using the Neighbor-Joining method in Phylip, with the distance PAM matrix model \[[@B38]\]. Bootstrap support (resampled 1,000 times) was calculated, and strict consensus trees constructed. Only bootstrap values greater than 50% are shown. Similar topologies were found for both algorithms employed, and only Neighbor-Joining is displayed. The consensus trees so obtained were viewed through TreeView software \[[@B39]\]. The same set of prokaryote species was used in all analyses, although few organisms were excluded from some trees, for simplification. The option for non-rooted trees aims at demonstrating only relationship among organisms without, however, linking ancestors and descendants.
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Presence of DNA repair genes investigated in this work.
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**Taxa** Genes^b^
------------------------------------------------------ ---------------------- ---------- ---- ---- ---- ---- ---- ----
*Aeropyrum pernix*(AEROP) Archaea \- 1 \- \- \- \- \-
*Archaeoglobus fulgidus*(ARCFU) Archaea \- 2 \- \- \- \- \-
*Halobacterium*(HALOB) Archaea \- 1 \- 1 1 1 1
*Methanobacterium thermoautotrophicum*(METTH) Archaea \- 1 \- 1 1 1 2
*Methanococcus jannaschii*(METJA) Archaea \- 1 \- \- \- \- \-
*Pyrococcus horikoshii*(PYHOR) Archaea \- 1 \- \- \- \- \-
*Sulfolobus solfataricus*(SULFO) Archaea \- 1 \- \- \- \- \-
*Mycobacterium tuberculosis H37*(MYCTU) Actinobacteria 1 4 1 1 1 1 3
*[Streptomyces coelicolor]{.underline} A3(2)*(STRCO) Actinobacteria 1 5 1 4 1 1 4
*Chlorobium tepidum TLS*(CLORB) Chlorobi \- 1 1 2 1 1 1
*Bacillus subtilis*(BACSU) Firmicutes 1 3 1 1 1 1 2
*Clostridium acetobutylicum*(CLOST) Firmicutes 1 2 1 2 1 2 2
*Listeria innocua*(LISTI) Firmicutes 1 1 1 3 1 2 1
*Oceanobacillus iheyensis*(OCENO) Firmicutes 1 2 1 2 1 1 1
*Deinococcus radiodurans*(DEIRA) Thermus/ Deinococcus 2 1 1 2 1 1 1
*Thermotoga marítima*(THEMA) Thermotogae 1 1 1 1 1 1 1
*Synechocystis*(SYNEC) Cyanobacteria 1 2 1 1 1 1 1
*Agrobacterium tumefaciens Cereon*(AGROB) Alpha proteobacteria 1 7 1 1 1 1 2
*Caulobacter crescentus*(CAULO) Alpha proteobacteria 1 2 1 1 1 1 2
*Mesorhizobium loti*(MESLO) Alpha proteobacteria 1 12 1 1 1 1 2
*Sinorhizobium meliloti*(RHIME) Alpha proteobacteria 1 10 1 1 1 1 2
*Neisseria meningitidis*Z2491 (NEIMA) Beta proteobacteria 1 1 1 1 1 1 1
*Ralstonia solanacearum*(RALST) Beta proteobacteria 1 1 1 2 1 1 2
*Buchnera sp*(BUCAI) Gamma proteobacteria \- 1 \- \- \- \- \-
*Escherichia coli.*(ECOLI) Gamma proteobacteria 1 1 1 1 1 2 1
*Haemophilus influenzae*(HAEIN) Gamma proteobacteria 1 1 1 1 1 1 1
*Pseudomonas aeruginosa*(PSEAE) Gamma proteobacteria 1 2 1 1 1 1 1
*Salmonella typhimurium LT2*(SALTY) Gamma proteobacteria 1 1 1 1 1 2 1
*Vibrio cholerae*(VICHO) Gamma proteobacteria 1 2 1 1 1 1 1
*Xanthomonas axonopodis*pv citri (XANTH) Gamma proteobacteria 2 3 1 2 1 2 2
*Xylella fastidiosa*(XYFAS) Gamma proteobacteria 1 1 1 1 1 1 1
a\. The organisms are listed in alphabetic order within the taxa. b. The numbers indicate the amount of homologs.
:::
Authors\' contributions
=======================
MM-P carried out the phylogenetic analyses and, together with RSG and CFMM, designed and conceived the ideas and the writing of the manuscript. CL gave substantial contribution on the possible involvement of ATP-dependent DNA ligases, when present in bacterial genomes. KML-B and KAA participated in the sequencing and DNA repair genes annotation in *Xanthomonas sp.*All authors read and approved the final manuscript.
Supplementary Material
======================
::: {.caption}
###### Additional File 1
Accession numbers for the genes indicated in the figures. Contains all accession numbers of the genes used in the phylogenetic analyses.
:::
::: {.caption}
######
Click here for file
:::
Acknowledgments
===============
The authors thank Dr. Sérgio Russo Matioli (University of São Paulo, Brazil) for helpful discussion. Financial support was obtained from FAPESP (São Paulo, Brazil) and CNPq (Brasília, Brazil).
|
PubMed Central
|
2024-06-05T03:55:47.911335
|
2004-8-27
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC518961/",
"journal": "BMC Evol Biol. 2004 Aug 27; 4:29",
"authors": [
{
"first": "Marinalva",
"last": "Martins-Pinheiro"
},
{
"first": "Rodrigo S",
"last": "Galhardo"
},
{
"first": "Claudia",
"last": "Lage"
},
{
"first": "Keronninn M",
"last": "Lima-Bessa"
},
{
"first": "Karina A",
"last": "Aires"
},
{
"first": "Carlos FM",
"last": "Menck"
}
]
}
|
PMC518962
|
Background
==========
How actively do populations of *Mycobacterium tuberculosis*cells undergo adaptive evolution on the spatial and temporal scales of individual infections? On the one hand, the long generation time and limited sequence diversity of this organism might suggest a slow pace of adaptive evolution. On the other hand, the rapidity and ease with which antibiotic resistance is generated during infection suggests otherwise. The physiology and immunology of tuberculosis pathogenesis have been well studied. The infectious agent *M. tuberculosis*is known to invade and replicate within alveolar macrophages. There is a spectrum of responses by the immune system, corresponding to the relative involvement of *Thl*and *Th2*immune cells, which respectively stimulate the cytotoxic response (more effective against infected cells), and the humoral/antibody response (more effective against extracellular pathogens) \[[@B1],[@B2]\]. Some progress has been made in describing the population dynamics of mycobacterial infection quantitatively \[[@B3]-[@B5]\]. At the wider spatial and temporal scales of populations, the molecular epidemiology and the evolution of *M. tuberculosis*have been carefully studied. Genotypic data are rapidly accumulating in the molecular epidemiology of infectious diseases. These are usually compiled and summarised to make inferences about the state of an epidemic in a given geographic location, or at the global level. For example, epidemiologists seek to identify risk factors for infection, and to locate particular strains that are especially transmissible or pathogenic \[[@B6]-[@B8]\]. The evolutionary history of *M. tuberculosis*has also been characterised. For example, it has been argued that the limited variation at the nucleotide is due to a recent population bottleneck \[[@B9]\], and that the common ancestor of *Mycobacterium bovis*and *M. tuberculosis*may well have been a human rather than bovine pathogen \[[@B10]\].
Less understood is the evolution of *M. tuberculosis*at the cellular level *inside*bodies. There has been little integration of the genetic information from markers with the population genetics of the bacterial population within hosts. In this article, I examine data collected for the purposes of molecular epidemiology to present three lines of evidence supporting the action of positive selection on *M. tuberculosis*. The data come from the marker IS*6110*, which is currently the standard method of typing tuberculosis isolates. These genotypic data will be considered under assumptions of neutrality, and then under the assumption that positive selection is acting. The case for the action of selection is based on the following three arguments.
• Under the assumption of neutrality, the observed mutation (or transposition) rate of the genetic marker IS*6110*is unusually high; the estimated mutation rate is lower if selection is acting.
• The observed times associated with change are too low to be explained by neutrality; positive selection lowers the expected substitution time.
• The observed level of polymorphism is too low to be explained by neutrality.
Results: Models and observations
================================
In each of the following sections a comparison is made between the strictly neutral model and a generalised model including selection through a single parameter *s*(described in the Appendix). Although the analyses start with strict neutrality (*s*= 0) in each argument, alleles for which *s*\< 1/*N*, where *N*is the effective population size, can be considered *nearly neutral*, in that the effects of drift outweigh the force of selection \[[@B11]\]. In each case, explaining observations in this range of selective coefficients requires very low effective population sizes.
Transposition rates of IS6110
-----------------------------
When genetic mutations are selectively neutral, the substitution rate is equal to the mutation rate \[[@B11]\]. In the present case, the *within-host*substitution process is of interest. Rosenberg *et al.*\[[@B12]\] determined the within-host substitution rate of the *IS6110*marker to be around 0.00184 to 0.0390 events per copy per year, with the maximum likelihood estimate at 0.0287. Under neutrality, therefore, this rate corresponds to a *per insertion*mutation rate of *μ*~*i*~\~ 7.9 × 10^-5^events per site per generation, assuming a generation time of 1 day in active infections. This figure comes from a measured doubling time of close to 24 hours, based on clinical isolates grown in human monocyte cultures and in culture media \[[@B13]-[@B15]\]. Rates of point mutation (events *per nucleotide*per generation) are usually in the vicinity of 10^-9^. In mutator strains, that is, genomes in which the DNA repair machinery is damaged, leading to elevated mutation rates, the mutation rate rises orders of magnitude, up to \~10^-7^-- 10^-6^\[[@B16]\]. The mutation rate of IS*6110*under neutrality therefore seems suspiciously high, although this is only \"circumstantial evidence\", since it is not inherently problematic. Indeed, mutation rates as high as 10^-4^per element per generation have been measured for IS*10 in vitro*\[[@B17]\]. Nevertheless, if positive selection is allowed the estimated mutation rate decreases. Leaving aside the complicating influence of clonal interference \[[@B18]\], the rate of substitution is
*K*= *uN μ*~*i*~ (1)
where *u*is the probability of fixation of a mutant, *μ*~*i*~is the mutation rate and *N*is the population size \[[@B11]\]. An estimate of the mutation rate when mutants have advantage *s*is  = *K*/(*uN*). The diffusion model of drift provides an expression for *u*as a function of the population size *N*and selective coefficient *s*(see the Appendix). Figure [1](#F1){ref-type="fig"} plots  over *s*for a few different values of *N*. In each curve the estimated mutation rate decreases as the selective coefficient rises. According to this analysis, lower mutation rates are possible when there is some selection and a large population size, or when selection is strong and the population size is small. Note that the estimated mutation rate remains high if mutations are nearly neutral.
::: {#F1 .fig}
Figure 1
::: {.caption}
######
**Estimate of mutation rate when positive selection is acting.**The estimate  is plotted on a logarithmic scale in base 10. Solid curve: *N*= 10; Dashed; *N*= 1000; Dotted: *N*= 10^5^.
:::
:::
Fixation times
--------------
Various studies have measured the stability of IS*6110*as a genetic marker by examining genotypes of serial isolates from patients with persistent infection. A small number of changes in the genotypes between serial isolates indicates a stable marker. Differences in genotypes due to exogeneous reinfection by unrelated strains are excluded from consideration. In the data of Niemann *et al.*\[[@B19]\] and Rosenberg *et al.*\[[@B12]\], the median time interval associated with changes in IS*6110*genotypes from serial samples of *M. tuberculosis*is 212 days, and the maximum is 683 days. Because the second sample is taken some time after fixation of the mutant, the actual substitution times are unknown, but they were clearly all under 683 days. I will now show that the expected substitution times under strict neutrality are well in excess of this value.
Let us start with the assumption that the expected time for substitution to occur is the average time taken for the successful mutant to appear plus the time taken for that mutant to reach fixation conditional on its eventual fixation. (I will later drop the assumption about waiting for the mutant to appear). The average appearance time is 1/(*μNu*) = 1/*μ*since *u*= 1/*N*under strict neutrality. The average time for a successful neutral mutant to reach fixation is 4*N*generations. The mutation rate of interest in this context is the rate *per genome*per generation, since what is of concern is whether any of the elements in a given genome produce change. For simplicity, assume that the genomic mutation rate scales linearly with copy number. (At the resolution of this analysis, this is a reasonable approximation.) Considering a typical strain has 10 copies of the IS element, the relevant mutation rate here is *μ*= *μ*~*i*~× 10 = 7.9 × 10^-4^. Therefore, for *N*= 10, 10^3^, 10^5^, the expected substitution times are roughly 1300, 5300, 4 × 10^5^generations, respectively. With the generation time set to one day, the upper bound of observed substitution times was 683 generations, which is well below theoretical expectations.
Now consider the possibility of positive selection under two alternative conservative assumptions. The earlier assumption that there are no successful mutants at the time of the first sample is favourable to the parental strain. A more conservative approach (favouring mutants) would be to say that the mutant destined to reach fixation appears exactly at the time of the first sample. We can then ask how long it takes on average for this mutant to reach fixation if it is positively selected. An even more conservative model would be that not only is the successor strain present at the time of the first sample, but is present at a frequency of 30%. Furthermore, let us say the subdominant strain only needs to be at 70% at the time of the second sample to be considered to have replaced the parental strain.
A model of the sojourn times of alleles in populations conditional on fixation must now be specified. Again using the diffusion model of drift (see Appendix), the mean time spent by a mutant in the range of frequencies (*a, b*) (provided *a*is greater than the initial frequency), conditional on fixation, was found by Ewens \[[@B20]\] and by Maruyama \[[@B21]\] to be
Figure [2](#F2){ref-type="fig"} shows the two conservative models, corresponding to two different boundary values for (*a, b*). Even in the extremely conservative model shown in the right-hand plot, the effective population size must be below 400 in order to explain the observed substitution times under strict neutrality. The data are difficult to account for even in terms of nearly neutral mutations (*s*\< 1/*N*) and an effective population size of *N*= 1000. The alternative explanation is that the effective population size is larger, but positive selection is acting to make changes sweep through the population faster.
::: {#F2 .fig}
Figure 2
::: {.caption}
######
**Mean sojourn times as functions of selective coefficient *s*, for different values of *N*.**Left: from *a*= 1/*N*to *b*= 1 - 1/*N*; Right: from *a*= 0.3 to *b*= 0.7.
:::
:::
Polymorphism
------------
Many analyses of pathogen genotypes assume isolated strains to be clonal, that is, to be monomorphic. This assumption has been scrutinised by De Boer *et al.*\[[@B22]\], who showed that, in fact, a large proportion (93%) of *M. tuberculosis*isolates are monomorphic using IS*6110*as the marker. They also show that the limits of detection of a second strain are around frequencies of 0.1 to 0.3. More sensitive instruments and refined genotyping procedures are likely to reveal greater polymorphism. The current information can be used, however, to study the population of the organism in hosts by using ranges of *detectable polymorphism*. In this section, two ranges will be considered in examining predictions from models: first, 0.1 to 0.9, and second, 0.3 to 0.7.
The polymorphism argument rests on the assumption that the isolates reported in \[[@B22]\] can be viewed as a random sample from a set of populations in mutation-drift equilibrium. It should be noted that because the isolate represents a sample of cells from the patient, it presumably does not always reflect the diversity of cells in the greater within-host population. Thus the polymorphism or heterogeneity observed from isolates is an underestimate of the actual levels.
Wright \[[@B23]\] found the stationary probability distribution of allele frequencies under the diffusion model with mutation and two alleles. Let *f*(*x*) be the probability density function of this distribution and *F(x)*be the cumulative probability function *F(x)*(see Appendix). The probability that a given population (patient) is between frequencies *a*and *b*(where *a*\<*b*) is
This quantity can be alternatively interpreted as the proportion of populations observed to be polymorphic according to the detection limits set by (*a, b*).
First consider the neutral case. When there is no selection (*s*= 0), the distribution described by *f(x)*is a Beta distribution. Figure [3](#F3){ref-type="fig"} shows the probability of an isolate being scored as a polymorphic population, using two alternative detectable polymorphism ranges (*a, b*) = (0.1, 0.9) and (0.3, 0.7), and a mutation rate of *μ*= 7.9 × 10^-4^per cell per generation.
::: {#F3 .fig}
Figure 3
::: {.caption}
######
**Probability of detecting polymorphism in the absence of selection, as a function of *N*.**Two different ranges of detectable polymorphism were used. Dashed curve: (0.1, 0.9); dotted: (0.3, 0.7). We use *μ*= 7.9 × 10^-4^. The horizontal bar indicates the observed fraction of polymorphic populations (0.074) from de Boer *et al*. \[22\].
:::
:::
Next, consider the model that includes selection. For the two detectable polymorphism ranges, Figure [4](#F4){ref-type="fig"} shows how selective coefficient *s*and effective population size *N*are related to the probability of observing polymorphism. As *s*increases, the predicted polymorphism decreases dramatically, particularly for large *N*. Again, an explanation of the observed level of polymorphism is only possibly by setting *N*to be extremely low.
::: {#F4 .fig}
Figure 4
::: {.caption}
######
**Probability of polymorphism as a function of *s*.**Left: the detection threshold is set at 0.3; Right: the detection threshold is set at 0.1. The mutation rate is set to *μ*= 7.9 × 10^-4^
:::
:::
Discussion
==========
The three lines of evidence presented in this article suggest positive selection on *M. tuberculosis*within hosts. There are, however, limitations to these analyses. In the first argument there is no inherent problem with finding transposition rates that are high. In the second argument, it is possible to lower the effective population size far enough to explain the speed of substitution. In the third argument, 1) the bacterial populations sampled in \[[@B22]\] might not be close to mutation-drift equilibrium, 2) the sampled cells might not reflect the true diversity of the bacterial population in a patient, and 3) the levels of polymorphism again may be explained by very low effective population sizes. Consistency with observations nevertheless requires *N*values of around 100 or lower, which seems grossly at odds with the usually large census population sizes of bacteria. In mouse models of TB infection, for instance, bacterial loads reach around 10^5^-- 10^7^colony forming units per lung \[[@B2],[@B24]\]. It has been noted, however, that effective population sizes of bacteria can be much lower than actual sizes \[[@B11],[@B25]\].
I will also comment on why I have not attempted to statistically fit the model to data to estimate *N*and *s*. First, from the plots shown here, it is clear that different combinations of the two parameters can explain the observations. This would make it difficult to locate the best fit. Second, although the model can be used to assess the possibility of neutrality in the current context, it cannot adequately serve as a framework for estimation given the intricacies of host-pathogen interactions. Further, adding more parameters to the model would increase the complexity of the analysis beyond what can be sustained by the resolution of the currently available data.
Taken together, the results suggest positive selection, although the evidence is not conclusive. A possible alternative is that the effective population sizes of *M. tuberculosis*within patients are very low due to population structure, background selection, or other factors. If there is indeed detectable adaptive evolution of tuberculosis within patients, what are the sources of selection? Two important candidates are antibiotic treatment and the host immune system. Studies using serial isolates have found no correlation between IS*6110*genotype instability and (a) drug resistance/susceptibility of the isolate \[[@B26],[@B27]\], (b) *change*in drug resistance status \[[@B19]\] or (c) drug adherence by the patient \[[@B26]\]. It is still possible, however, that the collection of observed changes involve a variety of different genetic loci, with at least some conferring drug resistance, although such events may not be statistically detectable. Further, mutation in drug resistance loci will not necessarily be revealed by a marker. Genetic analysis of isolates of *M. tuberculosis*from the lung lesions of six patients has shown heterogeneity in resistance-associated alleles, but not with respect to IS*6110*\[[@B28]\].
Alternatively, fingerprint changes may reflect (evolutionary) escape from the immune system. The analysis here hints at low effective population sizes -- perhaps the immune system induces a heavy decline in population sizes of *M. tuberculosis*within patients, i.e., bottlenecks -- which is overcome by survivors with new genotypes. If the observed patterns are to be explained by severe bottlenecks, the surviving cells are not necessarily better adapted to residing in the host than the parental cells that were eliminated by the immune response. It is noteworthy that Yeh *et al.*\[[@B26]\] found no relationship between HIV status of the patient and genotype instability. This suggests that genetic changes in *M. tuberculosis*are not primarily driven by the immune system. However, the extraordinary ability of *M. tuberculosis*to manipulate the T cell response \[[@B2]\] suggests the role of adaptation to the immune system in the deeper evolutionary history of the organism.
Interestingly, de Boer *et al.*\[[@B27]\] found an association between IS*6110*change and extrapulmonary disease or pulmonary+extrapulmonary disease and extrapulmonary origin of isolates. Dissemination is a major factor in the pathogenesis of tuberculosis. Since the lungs are the preferred environment of the organism, the new environments outside lungs may create opportunities for adaptive evolution. Adaptive evolution leading to specialisation to tissue types is to be expected. A recent article \[[@B29]\], for example, has found the occurrence of tissue-specific adaptations in *Streptococcus pyogenes*by examining ratios of non-synonymous to synonymous substitution rates (*d*~*n*~/*d*~*s*~).
Is IS*6110*directly responsible for adaptive mutations? On one hand, the apparently strict asexuality of *M. tuberculosis*implies that all genes good, bad or neutral are tightly linked to each other. It is likely then that IS-induced changes hitchhike to fixation with other mutations that confer advantage to the genome. On the other hand, it has recently been demonstrated that IS*6110*carries a promoter that can modify the the expression of neighbouring genes, raising the possibility of a direct role for the element in adaptive evolution \[[@B30]\]. Note that changes caused by IS*6110*can be not only beneficial, but also neutral or deleterious \[[@B31]\].
At the within-patient level, the best studied pathogen is perhaps HIV. While *M. tuberculosis*shares with viruses the characteristic of replicating within cells, a major difference is that mutation rates in viruses are much higher, particularly in retroviruses, which depend on reverse transcriptase (a low-fidelity enzyme) to copy their genomes. Hence, the extent of nucleotide variation of *M. tuberculosis*is not expected to be the same as is commonly observed for example in HIV \[[@B32]\]. There is ongoing controversy among HIV researchers about the role of stochasticity due to low effective population sizes in the evolution of the virus \[[@B33]-[@B35]\]. In any case, investigating the ratio of non-synonymous to synonymous substitutions (*d*~*n*~/*d*~*s*~) has established the action of positive selection on HIV within patients \[[@B32],[@B36]\].
In *M. tuberculosis*, the level of polymorphism at synonymous sites has been noted to be extremely low \[[@B9]\]. It would be of interest to measure the ratio of non-synonymous to synonymous polymorphisms in key genes, such as loci conferring resistance to drugs, or those implicated in interactions with the immune system. These *d*~*n*~/*d*~*s*~ratios may provide further insight into the nature of positive selection in *M. tuberculosis*.
Appendix: Bacteria and the Wright-Fisher process
================================================
The analyses here rely on the commonly used diffusion model of drift and selection in a population, based on the Wright-Fisher process \[[@B37],[@B38]\]. It is also possible to use the Moran model, in which at each time step an individual is chosen randomly to reproduce, and then another individual is chosen to die. The individual to die may be the same as the individual that reproduced, but not the offspring. Selection can be incorporated by including differential probability of birth or death for different genotypes. As noted by Ewens \[[@B38]\], the Moran model closely resembles the Wright-Fisher model; the critical difference between the two models arises from differences in the distribution of offspring number. The theory is usually discussed in relation to a diploid population of size *N*~*e*~in which there are 2*N*~*e*~copies of the (autosomal) gene in question. The diffusion model is used here with minor adjustments to describe bacterial populations. Let the number of bacterial cells in a population be *N*. Each mutant appears in the population at frequency 1/*N*. Realistically, population sizes fluctuate and only a subset of cells actively divide. The number *N*should therefore be considered to be the effective rather than the actual population size, which may be much larger than *N*.
Mean and variance of change
---------------------------
It can be shown that the deterministic dynamics of selection in a haploid model are well approximated by a logistic model. The mean change in frequency *x*of an allele per generation is *m*(*x*) = *sx*(1-*x*), which is identical to the diploid model with additive fitnesses (no dominance) if each copy of the advantageous allele adds *s*to the fitness (see \[\[[@B37]\], p. 192\]). That is, heterozygotes enjoy a fitness advantage *s*and homozygotes have advantage *2s*.
The variance component *v(x)*, the variance in change of allele frequency per generation, can also be taken from diploid theory. Replacing the diploid model of the random union of gametes with choosing cells randomly from each generation to the next, the effective population size is adjusted according to the distribution of offspring number under a given model of cellular division.
Binary fission
--------------
There are numerous ways to model drift in populations of organisms that reproduce by dividing to produce two daughters \[[@B39]\]. Here, cells are assumed to undergo fission synchronously and daughter cells are chosen randomly at each generation. In the absence of selective effects, the offspring distribution is *p*~0~= 1/4, *p*~1~= 1/2, *p*~2~= 1/4, where *p*~*i*~is the probability of producing *i*offspring. The variance in offspring number here is 1/2 and the variance-effective population size equals *N*/ = 2*N*. Thus in this case, the diploid theory can be directly used as far as *v(x)*is concerned (replacing 2*N*~*e*~with 2*N*). Johnson and Gerrish \[[@B39]\] consider alternative models. These alternatives are associated with different rates at which drift proceeds in a population, and would not affect the qualitative conclusions drawn here.
Fixation probability
--------------------
Diffusion models of genetic drift have shown \[[@B11]\] that the probability of fixation of an allele at frequency *p*in a randomly mating diploid population of size *N*~*e*~(with 2*N*~*e*~copies of the gene in question) is
Therefore, using *p*= 1/*N*rather than the usual *p*= l/(2*N*~*e*~) the probability of fixation of a mutant bacterial cell with selective advantage *s*is
Note that when 4*N*s \>\> 1, *u*\~ 4*s*. This agrees with a result of Gerrish and Lenski \[[@B18]\], using a branching process model (rather than the diffusion model) to find the fixation probability under this same model of binary fission. See \[[@B39]\] for discussion of *u*for alternative models.
Steady state distribution
-------------------------
Let the mutation rates from any genotype to any other be equal (*μ*). As stated above, selection is additive. As shown by Wright \[[@B23]\], the steady state distribution of allele frequency is then given by the density function
See also \[[@B37],[@B38]\] for further details.
Acknowledgments
===============
I thank Noah Rosenberg, Joanna Masel and Roland Regoes for helpful discussions. This work was supported by a Faculty Research Grant from the University of New South Wales.
|
PubMed Central
|
2024-06-05T03:55:47.915353
|
2004-9-9
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC518962/",
"journal": "BMC Evol Biol. 2004 Sep 9; 4:31",
"authors": [
{
"first": "Mark M",
"last": "Tanaka"
}
]
}
|
PMC518963
|
Background
==========
Mycoplasmas are the smallest living prokaryotes known, capable of self-replication. They belong to the class *Mollicutes*and are distinguished phenotypically from other bacteria by their minute size and lack of a cell wall. Genetically they differ by having a small genome size and low G+C content {1} \[[@B1]\]. Mycoplasmas have adapted to a wide variety of hosts and can colonize man, other animals and plants. The colonising organisms are host specific. In humans, mycoplasmas colonize mainly the upper respiratory tract and the genitourinary tract.
The first human *Mycoplasma*isolated was *Mycoplasma hominis*\[[@B2]\]. It is a heterogeneous genital mycoplasma \[[@B3]\] found in at least two-thirds of women with bacterial vaginosis (BV), compared to 10% of healthy women \[[@B4],[@B5]\]. *M. hominis*has also been isolated from the endometrium and fallopian tubes of 10% women with salpingitis. However, its role as a primary pathogen is doubtful since it co-exists with many other bacteria in BV \[[@B6]\]. Studies made on women undergoing *in vitro*fertilization showed the presence of *M. hominis*only in 2.1% of the women \[[@B7]\].
Isolation from other sites than the genitourinary tract has been reported. *M. hominis*has been found to cause wound, joint and central nervous system infections \[[@B8]\], it has been isolated from cavernous angioma, but was not the cause of the disease \[[@B9]\] and cases of brain and scalp abscesses and meningoencephalitis were also reported \[[@B10]-[@B15]\]. Those cases demonstrated the pathogenic potentials of *M. hominis*and indicated a need for rapid recognition. So far culture is most commonly used for detection of genital *Mycoplasma,*but it requires special handling, complex media, and cultivation positive samples need further testing to determinate the species cultivated \[[@B16]\]. A case report of brain abscess in a 22 year-old female patient with postpartum infection \[[@B10]\] showed that culture took 4 -- 5 days during which the patient\'s symptoms continued to worsen before the antibiotic treatment was changed.
Comparison between culture method and PCR has been performed and showed that a PCR assay was as sensitive as culture for detection of *M. hominis*from clinical samples. In addition it was very specific \[[@B17]\]. An advantage of using PCR is that the system can detect the presence of both live and dead microorganisms in the sample. When comparing the original PCR protocols with the newly developed real-time protocol, it offers interesting advantages such as rapidity, closed system, which eliminates the risk of carry-overs, real-time monitoring of PCR activity, quantification of amplification product and, if required, mutation analysis.
A recent study designed for the detection of *M. hominis*by real-time PCR in HIV-positive patient swab samples, suggested the use of SYBR Green with primers targeting another housekeeping gene, the 16S rRNA gene \[[@B18]\]. The 16S rRNA gene is the most conserved microbial gene, though, in *M. hominis*minor sequence variation was observed \[[@B19]\]. Because sequences from *M. hominis*isolates were available (see table [1](#T1){ref-type="table"} for accession nos.) and possible to compare with other mycoplasmas sequence \[[@B28]-[@B30]\], we selected the housekeeping gene glyceraldehyde-3-phosphate dehydrogenase (*gap*) as target for development of a quantitative real-time PCR. Comparison of the DNA sequences from different *M. hominis*isolates showed, however, some small variations in the amplified DNA sequence \[[@B31]\]. We determined sensitivity and specificity of the *M. hominis*LightCycler real-time PCR and tested it on clinical swab samples using specific hybridization probes for detection.
Results
=======
Design of primers and probes
----------------------------
The principles of the system we used are based on two specific hybridization probes located internally to the amplification primers, each of them labelled with a different fluorescent dye \[[@B32]\]. The DNA sequence of primers and probes is shown (table [2](#T2){ref-type="table"}).
We selected *M. hominis*PG21 type strain as a template for primers and probes. The primers and probes were designed with respect to conservation of the DNA sequence within the *M. hominis gap*gene \[[@B31]\] and difference from the related genital *Mycoplasma genitalium gap*gene (Accession no. U39710) (fig. [1](#F1){ref-type="fig"}). The amplified DNA fragment was of 144 bp in size.
Swissprot Protein Database was used to determine the amino acids sequence of GAPDH enzyme (E.C. no. 1.2.1.12). By use of the MOTIFS program the active site was predicted to consist of the amino acids: ASCTTNCL, located at nucleotides 451 to 474 (fig. [1](#F1){ref-type="fig"}) \[[@B31]\]. When comparing DNA sequences of the active site between *M. hominis*and *M. genitalium,*only 3 out of 24 nucleotides are mismatching (fig. [1](#F1){ref-type="fig"}), and therefore the probes and primers were placed before this region.
As seen from fig. [1](#F1){ref-type="fig"}, the G + C content of the *M. hominis gap*gene is very low. It was difficult to find a suitable location for the reverse primer, and therefore two reverse primers were designed (table [2](#T2){ref-type="table"}). The sequence of the reverse primer II was partly overlapping the encoding region of the active site of GAPDH enzyme. When compared it was found that use of reverse primer I gave the highest sensitivity of the LightCycler PCR assay. Concentration of 5 copies/μl of PG21 DNA was not always detected in PCR runs when reverse primer II was used, whereas with use of reverse primer I, 5 copies/μl of PG21 were present in every run, and therefore this primer was chosen for the following experiments.
In order to obtain optimal detection in the annealing phase of the PCR we designed the probes to anneal to the same strand as the forward primer and placed them as far as possible from that primer (fig. [1](#F1){ref-type="fig"}). One hybridization probe was labelled with fluorescein (FL) in the 3\' end, the other with LightCycler Red705 (LCred705) in the 5\' end. When the probes are hybridized less than 5 nucleotides apart, Fluorescence Resonance Energy Transfer (FRET) will be induced. The distance between the two probes was one nucleotide after annealing to template DNA allowing FRET light to be measured.
Sensitivity and specificity
---------------------------
Dilution series of the standard DNA from *M. hominis*PG21 were used to examine the sensitivity of the LightCycler PCR assay. The fluorescence curves are shown (fig. [2a](#F2){ref-type="fig"}). Detection of PCR product was possible for the lowest DNA concentration: 1 copy/μl, equal to 2 copies in the reaction mixture (fig. [2a](#F2){ref-type="fig"}). To reduce the noise, the cut-off value was set to 0.1. The standard curve had an average slope equal to -3.5, which means that the efficiency of the PCR reaction was 1.93 (oscillating between 1.9 and 2.0) (fig. [2b](#F2){ref-type="fig"}). Calculations of the efficiency derived from the function for the amount of PCR product that was formed, represented by equation: N = N~0~× 2^n^, where N is the number of amplified product, N~0~is the initial number of molecules and n is the number of the PCR cycles. Ideally the efficiency equals 2. Additionally, the sensitivity of the assay was determined for two other *M. hominis*isolates by making dilution series of DNA from *M. hominis*132 and 4712. As for PG21, detection of a PCR product was possible for the lowest DNA concentration of 1 copy/μl indicating similar sensitivity of the two other isolates. The standard curves had slopes equal to -3.552 for isolate 132 and -3.576 for isolate 4712, the efficiency of the PCR reaction was 1.91 and 1.9, respectively.
To determine the reproducibility of the assay, ten dilution series of PG21 DNA were analyzed in different PCR runs, and the values of crossing-points (also known as threshold cycles -- *C*~*t*~) were compared by calculation of the coefficients of variation (*CV*). The values of *CV*were between 3.8% and 6.7% (table [3](#T3){ref-type="table"}). In all runs 10 out of 10 samples were positive except for 1 copy/μl where a PCR product was seen in 6 out of 10 PCR runs. The reproducibility of the assay for the two other *M. hominis*isolates 132 and 4712 was analyzed in three different PCR runs. In both isolates dilution of 5 copy/μl was present in three out of three runs, similarly to PG21 the dilution of 1 copy/μl was present in two out of three LightCycler runs. Our detection limit was therefore 5 copy/μl, equals to 10 copies in the reaction mixture. The reproducibility of the assay was acceptable.
As a next step twenty *M. hominis*isolates (table [1](#T1){ref-type="table"}) were tested with the designed primers and probes in the LightCycler real-time PCR. All isolates gave a positive fluorescence signal and the concentration of DNA was similar to 10^4^copies/μl of PG21, measured by the LightCycler instrument (fig. [3](#F3){ref-type="fig"}).
The specificity of the LightCycler assay targeting the *gap*gene was evaluated by testing human DNA and DNA from different *Mycoplasma*species. With the specific probes there was no cross-reactivity to other *Mycoplasma*species or human DNA (fig. [4a](#F4){ref-type="fig"}). For human DNA we used a concentration of 10^4^copies/μl calculated by OD measurements of the purified DNA and the genome size.
Since DNA from different mycoplasmas was extracted by proteinase K treatment of PBS washed pellets, we tested such extracted DNA for presence of inhibitors. Two μl of DNA from five different mycoplasmas (*M. arginini, M. bovis, M. hyorhinis, M. pulmonis, M. salivarium*) were spiked with 2 μl of PG21 DNA of 100 copies/μl and added to the reaction mix. As illustrated (fig. [4b](#F4){ref-type="fig"}) there was no inhibition in the proteinase K treated samples.
Melting curve analysis
----------------------
Melting curve analysis can be used to determine the presence of non-specific amplification products. The melting temperature (*Tm*) is defined as the temperature at which half of a duplex-DNA becomes single-stranded \[[@B33]\]. As it was impossible to place probes in completely conserved regions (fig. [5](#F5){ref-type="fig"}), we analyzed the melting curves of the real-time PCR products of the different *M. hominis*isolates. *Tm*of PG21 DNA was 66°C and equal for high and low concentrations of DNA.
It was shown that the melting temperature of the PCR products of *M. hominis*DNA clustered in 3 major groups (fig. [6](#F6){ref-type="fig"}). The isolates V2785 and P71 had the same temperature of 66°C as PG21, the second group 93, 7357, 132, P2, P7, SC4, DC63, 7808, 183, 1893, 10, W2 had a melting temperature of 64°C, while the last group 5941, 4712, 3105, M1449, 6188, had the melting temperature of 62°C. These different melting points were in agreement with variation in the DNA sequence of the probe regions (fig. [5](#F5){ref-type="fig"}).
Coloured media and possible PCR inhibition
------------------------------------------
Many *Mycoplasma*species were cultured in SP-4 or BEa media for specificity of LightCycler analysis. Additionally, the clinical samples were transported in SP-4 medium, which can be used for the recovery of *M. hominis*\[[@B34]\], and BEa medium was used for cultivation of *M. hominis*. Therefore, to see the effect of the coloured media on the LightCycler assay, we constructed artificial samples consisting of SP-4 or BEa medium spiked with DNA of known concentration (10^5^, 10^4^, 10^3^). Two μl of the samples were analyzed by the LightCycler PCR. As shown (fig. [7](#F7){ref-type="fig"}), BEa medium completely inhibited the reaction, whereas SP-4 inhibited only partially, but markedly reduced the PCR efficiency.
Analysis of clinical samples
----------------------------
### Culture
Eighty-three endocervical samples from women attending fertility clinics in Denmark were cultured for the presence of *M. hominis*. Two samples were found positive. Three passages were examined for colour change, at each passage the colour of the medium turned pink, and samples were thus considered as positive cultures. Proteinase K treated culture materials were analyzed by *Mycoplasma*-genus-specific PCR \[[@B35]\], which gives PCR products from 16S rRNA gene of 265 bp in size. The PCR products from the two positive clinical samples were sequenced and the resulting DNA sequence confirmed them to be *M. hominis*.
Quantification by culture of these two positive samples was performed by limited dilution in growth medium. There was a colour change in 9 wells in both samples, which corresponds to 25.600 CCU/ml in the swab sample, calculated from titration.
### LightCycler PCR on DNeasy treated samples
The cervical swab samples were DNeasy treated and tested in duplicates by LightCycler PCR using the *M. hominis gap*-assay. Two samples (nos. 56 and 83) were positive when examined by LightCycler PCR (2.4%). The copy numbers were measured to be 220 (for 83) and 530 (for 56) copies/μl respectively. The amount of DNA copies per ml in the original sample was calculated to be 37.000 for sample 83 and 88.500 for sample 56. The two quantification methods for estimating bacterial load in positive samples thus showed that the number of live *Mycoplasma*cells was 69% (patient 83) and 29% (patient 56) of what was found by PCR. The positive clinical samples showed melting temperature of 64°C corresponding to the second group, in which the majority of the *M. hominis*isolates were found. Reproducibility of the quantification of DNA in the clinical specimens was analyzed in 10 negative patient samples. Four μl of samples were spiked with 2 μl of PG21 DNA of known concentration (100 copies/μl). The six μl were added to the LightCycler PCR reaction. No inhibition was observed (fig. [8](#F8){ref-type="fig"}).
In some DNeasy treated clinical samples a slight fluorescence response was seen at the very late PCR cycle. To analyze whether this slight fluorescence response was unspecific, different DNeasy samples were analyzed. We used different concentrations of human DNA from \"*Mycoplasma*free\" Hep2 cells, which were purified with Blood & Cell Culture DNA Mini Kit, and these samples did not give a positive fluorescence signal when run in LightCycler PCR (fig. [9a](#F9){ref-type="fig"}). In addition the results showed that there was no cross-reaction to human DNA. However, when DNA free water and standard dilutions of the human DNA extracted by the Blood & Cell Culture DNA Mini Kit were treated with DNeasy Tissue Kit, we experienced a slight fluorescence signal at the very late cycle numbers. Even DNA free water gave a positive signal (fig. [9a](#F9){ref-type="fig"}). The calculated copy numbers were between 1--8 copies/μl. The melting curve analysis showed an atypical flat and broad melting curve with the melting peak below the range of *Mycoplasma hominis*isolates (fig. [9b](#F9){ref-type="fig"}).
Clinical samples showing the low concentration (between 1--8 copies/μl) also had the flat melting curve with the melting peak below 61°C (fig. [9b](#F9){ref-type="fig"}) and were therefore considered as negative. One additional sample (no. 9) had an average concentration of 10 copies/μl, but when comparing the melting curve data, it had a melting curve identical to the DNeasy treated water and was therefore considered negative. There was thus 100% agreement between cultivation and detection by real-time PCR.
### LightCycler PCR on proteinase K treated clinical samples
To additionally confirm that samples which gave a slightly positive fluorescence signal in LightCycler PCR after DNeasy treatment were not containing *M. hominis*DNA, we analysed proteinase K treated samples from those patients by the LightCycler PCR. None of the samples gave a positive fluorescence signal. After confirming that all samples were negative, we spiked 2 μl of each sample with 2 μl of PG21 DNA of 100 copies/μl, as the control for inhibition. None of the proteinase K treated samples showed inhibition. This clearly indicates that those samples were negative.
Discussion
==========
A rapid quantitative real-time PCR for detection of *M. hominis*from cervical swab samples was developed. To our knowledge it is the first LightCycler PCR protocol where quantification of *M. hominis*is combined with melting curve assay. The LightCycler PCR reproducibility was able to detect down to ten copies/reaction of the genomic PG21 DNA. All other 20 *M. hominis*isolates were positive in the assay. Additionally, isolates 132 and 4712, which based on melting temperature belong to the two other groups than PG21, were used to document detection limits of *M. hominis*isolates. Similarly to PG21, the detection limits were 5 copies/μl, equals to 10 copies per reaction for both isolates.
The average efficiency was high, but small differences were seen. This can be caused by different factors such as presence of inhibitors in the sample and treatment of the sample.
The artificially constructed samples consisting of PG21 DNA and coloured BEa and SP-4 media showed that these media inhibited the PCR reaction indicating that it was crucial to wash the pellets of other *Mycoplasma*species with PBS. Additionally, a spiking assay where DNA from other mycoplasmas was used together with DNA from PG21 showed that there was no inhibition in the proteinase K treated samples.
Since swab samples may contain PCR inhibitors we introduced the DNeasy procedure to additionally purify DNA from proteinase K treated clinical samples. Analysis of the ten negative clinical samples spiked with DNA from PG21 (100 copies/μl) showed no inhibition after DNeasy treatment.
We experienced, however, some slight fluorescence response in the very late cycle number, which corresponds to the low concentration seen in DNeasy treated water or Hep2 cells (fig. [9a](#F9){ref-type="fig"}) and flat melting curves with lower melting temperature than those of *M. hominis*isolates (fig. [9b](#F9){ref-type="fig"}). DNeasy treated patient samples that gave such a weak fluorescence signal were considered as negative. Additionally, using the original proteinase K treated patient samples, for those patients that gave a weak fluorescence signal after DNeasy treatment, we did not see any reaction with LightCycler PCR. This strongly indicates that such slight fluorescence response is generated only in the DNeasy treated samples.
A previous study showed that women with bacterial vaginosis showed presence of *M. hominis*in 38.5% compared to 8.3% of women with normal microbial flora \[[@B36]\]. Since none of our patients had bacterial vaginosis we had expected approximately 8% of our samples to be positive. We found two positive samples that were confirmed to be positive by the culture and had a high concentration of DNA by LightCycler PCR (220 and 530 copies/μl). The low number of positive patients (2.4%) was surprising but comparable with a previous study made on patients undergoing the *in-vitro*fertilization \[[@B7]\].
Comparison of the number of DNA copies and CCU showed that the CCU was lower than the number of DNA copies. This can be explained by the presence of dead bacteria in the samples.
Even though the assay was designed for quantification, the variability in the melting peaks gave additional information of *M. hominis*. Differences in the melting temperatures between *M. hominis*isolates prove heterogeneity of the housekeeping gene sequence. The *Tm*value determines how well the sequence of probes matches the sequence of template DNA, and it will decrease if mismatched DNA is amplified. Single mismatch can decrease the *Tm*from 1°C up to 30°C \[[@B37],[@B38]\] depending on many factors, such as pH, duplex length and G + C content. This kind of analysis is used in detection of subtypes of Herpes simplex virus, since the *Tm*discriminates between two different subtypes \[[@B33],[@B39],[@B40]\]. In the present study, *Tm*of the clinical samples can suggest to which group of isolates they belong and how different they are from the PG21 template DNA. In this study, patient samples nos. 56 and 83 had melting peaks similar to isolates from the second and largest group.
The real-time technology where measurement of the fluorescence emitted during amplicon production is performed during each PCR cycle is considered as a breakthrough in PCR. Conventional PCR is an open, contamination-susceptible system where it is necessary to transfer the amplified product to other detection systems to confirm a positive result. Real-time PCR benefits by a closed system in which formation of a product is measured immediately without transfer \[[@B32]\]. Interpretation of LightCycler PCR results, presented as graphs and calculation of crossing points, introduces many advantages, but such a parameter of real-time PCR should be evaluated.
Conclusions
===========
LightCycler PCR appears very promising for detection of organisms that are difficult to culture or whose growth is slow. We have developed a quantitative, specific LightCycler protocol for detection of *M. hominis,*which offers rapid diagnosis of one hour after DNA extraction. The DNA extraction method used was not the best choice as unspecific fluorescence did occur in the late number of cycles. Results from cultivation and LightCycler PCR were identical. The method is both sensitive and specific. All tested isolates gave a positive fluorescence response, and final amplification and quantification was performed in closed tubes, which reduces the risk of contamination. The described target *gap*gene sequence should be preferred to more varying parts. A small variation in this part of the *gap*gene among different *M. hominis*isolates was observed by the melting curve analysis.
Methods
=======
Microorganisms and human DNA used for the study
-----------------------------------------------
Organisms used in this study are listed in table [1](#T1){ref-type="table"}.
Subjects
--------
A total of 83 consecutive women attending fertility clinics in Denmark (Brædstrup/Horsens and Holstebro) were studied. All patients were undergoing hysteroscopy and transvaginal hydrolaparoscopy (culdoscopy) \[[@B41]\] or laparoscopy due to infertility. The endocervical specimens for detection of presence of *M. hominis*were collected before the scopic examination.
Material collection
-------------------
Endocervical specimens were obtained using a sterile chlamydial swab and the contents transferred immediately into a tube containing 2 ml of transport medium, SP-4 \[[@B42]\], containing thallium acetate (0.01%), which inhibits growth of other microorganisms. Such prepared samples were then sent to the laboratory of Department of Medical Microbiology and Immunology, Aarhus University, where they were stored at -70°C.
Cultivation and harvesting of microorganisms and human Hep2 cells used in the study
-----------------------------------------------------------------------------------
All isolates of *M. hominis, M. buccale, M. salivarium, M. orale, M. arthritidis, M. arginini, M. lipophilum, M. primatum*were cultivated in 1.7 ml of broth BEa medium \[[@B22]\]. *U. urealyticum*and *U. parvum*were grown in 1.7 ml of SU medium \[[@B43]\]. *M. pneumoniae*and *M. genitalium*were grown in 100 ml of SP-4 medium \[[@B42]\] as described in detail elsewhere \[[@B44]\]. *M. fermentans, M. pulmonis, M. hyorhinis*were cultivated in 1.7 ml of BEg medium \[[@B43]\]. Finally, *M. bovis*was cultured in BE medium \[[@B43]\]. All cultures were incubated at 37°C. The BEa medium changed colour from orange to pink in 48 hours due to reduction of phenol red by arginine hydrolysis. SP-4 and BEg both changed colour from orange to yellow, whereas SU changed from yellow to orange. BE medium changed from yellow to light pink in 72 hours. Except for *M. hominis, M. genitalium*and *M. pneumoniae*, which were cultivated up to bigger volumes (100 ml), 500 μl of the colour changed cultures were then placed in 7 ml of the new medium, and harvested after the medium changed for the second time. One ml of logarithmic-phase culture was centrifuged in Eppendorf tubes at 20.000 × g for 30 min. Each pellet was washed twice by phosphate-buffered saline (PBS) and the pellets were stored at -70° prior to use.
Human Hep2 cells were cultured as described elsewhere \[[@B45]\].
DNA extraction and purification from microorganisms and human Hep2 cells used in the study
------------------------------------------------------------------------------------------
DNA from *M. arginini, M. bovis, M. hyorhinis, M. pulmonis, M. primatum*, *M. lipophilum, M. buccale, M. salivarium, M. orale, M. arthritidis, U. urealyticum, U. parvum, M. pneumoniae*and *M. fermentans*was extracted by suspending pellets in 160 μl TE buffer, and adding 40 μl 10 mg/ml proteinase K. The proteins were digested by incubation at 55°C for one hour, followed by inactivation of the enzyme by boiling for 10 minutes at 100°C.
The DNA from human Hep2 cells as well as *M. genitalium*DNA was extracted and purified by Blood & Cell Culture DNA Mini Kit (QIAGEN GmbH, Hilden, Germany).
Genomic DNA from all *M. hominis*isolates was extracted as described \[[@B46]\] and followed by ultracentrifugation in CsCl-ethidium bromide density gradient \[[@B47]\].
Concentrations of DNA from isolates PG21, 132 and 4712, and human Hep2 DNA were calculated after measuring OD (optical density) at 260 and 280 nm with Unicam 8625 UV/VIS spectrometer (ATI Unicam, Cambridge, United Kingdom).
Artificial \"Mycoplasma free\" samples treated with DNeasy Purification Kit
---------------------------------------------------------------------------
Fourfold dilution series of human Hep2 DNA purified by Blood & Cell Culture DNA Mini Kit (QIAGEN GmbH, Hilden, Germany) of initial concentration 8.000 copies/μl were prepared. Twenty-five μl of each dilution and DNA free double distilled water were then treated with DNeasy™ Tissue Kit (QIAGEN GmbH, Hilden, Germany) procedure. Samples were diluted twice, because of elution step with 50 μl of elute buffer, and therefore 4 μl instead of two of each sample were used in the LightCycler PCR run.
Cultivation of patient cervical samples
---------------------------------------
Broth BEa medium was used for culture of *M. hominis*. To avoid overgrowth by other bacteria, present in the urogenital tract, a special mixture of antibiotics (Niels Friis; containing: 0.15 mg/ml cycloserine, 0.2 mg/ml vancomycin, 0.2 mg/ml bacitracin and 0.2 mg/ml mecillinam) was used. Twenty μl of the swab sample was placed in 1 ml of medium with Niels Friis antibiotics and incubated at 37°C. The BEa medium changed colour from orange to strawberry pink in 48 hours due to reduction of phenol red by arginine hydrolysis. Finally, samples were described as positive when it was possible to pass them further 2 times. *Mycoplasma*-genus-specific PCR was performed on the two positive cultures and the PCR products were sequenced. Sequencing reactions were carried out bidirectionally using the ABI PRISM Dye Terminator Cycle Sequencing Ready Reaction Kit (Perkin Elmer, Narwalk, USA) on the purified PCR products according to the instructions supplied by the manufacturer. Sequencing was performed on an ABI PRISM 377 DNA Sequencer (Perkin Elmer, Narwalk, USA).
DNA extraction from cervical samples
------------------------------------
All 83 patient samples were treated identically. Briefly, three hundred μl of the original swab sample was subjected to microcentrifugation at 20.000 × *g*, and to remove transportation medium the pellets were washed twice with PBS. The pellets were suspended in 49 μl TE buffer, and 1 μl 10 mg/ml Proteinase K was added, proteins were digested while incubating at 55°C for one hour, which was followed by inactivation of the enzyme by boiling for 10 minutes at 100°C. Finally, in order to remove possible inhibitors present in swab samples, DNA extraction with DNeasy™ Tissue Kit (QIAGEN GmbH, Hilden, Germany) was performed on the resulting solution without repeating the proteinase K treatment. Twenty-five μl of the proteinase K treated sample was diluted twice because of elution with 50 μl of elute buffer, 4 μl of each sample was used for the PCR. The filter pipette tips were used for all DNA preparation steps to reduce possibility of sample contamination.
Quantification of the number of viable microorganisms by culture
----------------------------------------------------------------
Estimation of the number of *M. hominis*in patient swab samples was performed by titration in BEa growth medium. Two-fold dilutions were made in ELISA trays by adding 0.01 ml of the clinical sample to 0.19 ml of BEa medium. The plates were incubated at 37°C and reading was performed on the third day. Plates were left in incubator and observed for 3 additional days but no further change appeared. The last well with visible colour change was considered to contain one colour changing unit (CCU) allowing us to calculate the number of viable microorganisms in the original clinical sample.
Primer and probe design
-----------------------
Primers and probes were designed from the *gap*gene of *Mycoplasma hominis*type strain PG21 (Accession No. AJ243692). This gene belongs to the housekeeping genes and is therefore very conservative in all organisms. Primer and probe sequences and their locations are present in table [2](#T2){ref-type="table"}. Both primers and probes were placed in front of the conserved region of the *gap*gene that is almost identical in all organisms. Primers were obtained from DNA Technology, Aarhus, Denmark, and probes from TIB-MOLBIOL, Berlin, Germany. Probe and primer sequences were analysed by BIOBASE (The Danish Biotechnological Database, the University of Aarhus, Denmark) and BLAST (National Centre of Biotechnology Information, National Institutes of Health, Bethesda, MD, USA).
Real-time PCR assay with hybridization probes
---------------------------------------------
The PCR product was 144 bp in size, which according to the manual (Roche Molecular Biochemicals Technical Note No. LC 11/2000) is preferable to perform an efficient quantification of DNA.
Real-time PCR was performed in glass capillary tubes. The reaction mixture was composed of 0.5 μM of each primer, 0.2 μM of each probe, 5 mM of MgCl~2~(PCR buffer), 2 μl of ready-to-use Fast Start DNA Master Hybridization Probes (Roche Diagnostics, Mannheim, Germany) (contains a hotstart Taq DNA polymerase and reaction mixture), 1.5 μl Uracil-DNA Glycosylase (heat-labile) and 2 μl of the DNA template. Water was added up to 20 μl, which was the final volume of all reaction-mix. For the DNeasy treated patient samples 4 μl of DNA was used. When proteinase K treated patient samples were examined (without DNeasy treatment), we used 2 μl of the undiluted DNA.
To avoid contamination, mixing of the reagents (except of the DNA template) was performed in a separate room, away from rooms where culturing and DNA purification were done. The DNA template from *M. hominis*PG21 was added by use of filter pipette tips. Uracil-DNA Glycosylase (Roche Diagnostics, Mannheim, Germany) was used to prevent the samples from possible PCR \"carry-over\" contaminations from previous DNA synthesis reactions. Reaction mixes contained dUTPs instead of dTTPs, and therefore it was possible to avoid contamination of samples by adding an enzyme that hydrolyzes uracil-glycosidic bonds at U-DNA in single and double-strained DNA \[[@B48]\].
As negative control a sample containing all reagents except DNA was used in every PCR run. Quantification of DNA concentrations performed by LC-PCR Software was based on standard dilution series with known concentrations of genomic *M. hominis*PG21 DNA. The concentrations of standard dilution series were: 10^5^, 10^4^, 10^3^, 10^2^, 10^1^, 5 and 1 copy/μl. Siliconized tubes were used to prevent DNA from sticking to the wall of the plastic tubes. For carrier, yeast RNA was used in concentration 10 μg/ml.
The LightCycler PCR program was composed by: Hotstart Taq DNA polymerase activation done in 95°C for 10 minutes, followed by cycling: 95°C (20°C/s) for 15 s, 58°C (20°C/s) for 8 s and 72°C (20°C/s) for 8 s, repeated 45 times. Melting assay ended the analysis: samples were heated to 95°C (20°C/s) without hold, cooled to 55°C (20°C/s) hold for 15 s and then heated slowly at 0.1°C/s up to 95°C, finally cooled to 40°C (20°C/s).
Fluorescence emitted at 705 nm was measured at each annealing step since the fluorescence signal is emitted when both probes are hybridized. After annealing the temperature is raised and the hybridization probes are displaced by the Taq polymerase during the elongation step. Probe fluorescence was detected in canal F3 (measures at 705 nm) and F1 (measures at 530 nm). F3/F1 was used to correct differences in volume of the samples made during pipetting.
Quantification of LightCycler products
--------------------------------------
The results were interpreted with LightCycler software Vers. 3.5 (Roche Diagnostics). Quantification software performs all additional steps for generation of a standard curve. First step involves *Baseline Adjustment*with the use of a \"fit points\" method, second step allows background reduction using *Noise Band*correction, and the last step is *Analysis*where the standard curve is generated from the threshold cycles (*C*~*t*~) of the standard dilution series (fig. [1b](#F1){ref-type="fig"}). Samples with high DNA load had low *C*~*t*~values, and low DNA load had high *C*~*t*~values. The concentration of DNA in clinical samples was set as \"unknown\". Each sample was run in duplicate. Calculation of the DNA concentration in the unknown sample was based on the standard curve slope. The average of the two concentration measurements was used for further analysis.
Competing interests
===================
None declared.
Authors\' contributions
=======================
Author A.B. carried out the real-time PCR experiments, the analyses of data, and drafted the manuscript. Author H.F.S. participated in designing the LightCycler PCR method, analysis of data and coordination of the manuscript. Author J.F. participated in coordination of the study and provided clinical samples. Author S.B. participated in design and coordination of the study. Author G.C. participated in design, data analyses, coordination of the manuscript and study.
Acknowledgements
================
We are grateful to Karin Skovgaard Sørensen for skilled laboratory practice, Lisbet Wellejus Pedersen for linguistic assistance of this paper and Inger Andersen for making mycoplasma medium. This work was financially supported by \"Vestdansk Sundhedsvidenskabeligt Forskningsforum\" (Journal No. 1999-043-33).
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
**Orientation of primers and probes with sequence comparison to the closer related genital bacteria *M. genitalium.***The DNA sequence of primers and probes from *M hominis*PG21 is compared to the homologous *M. genitalium*sequence. Eight mismatches were present in the forward primer, 7 in the first probe, 15 in the second probe and 13 in the reverse primer I. Highlighted nucleotides correspond to mismatches. Letters in bold correspond to the beginnings and ends of designed primers (forward and reverse I) and probes (I, II). Letters in italic correspond to beginning and ending of reverse primer II. The active site region of GAPDH enzyme is underlined.
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
**Sensitivity of LightCycler PCR in standard dilution series.**(a) The LightCycler PCR run with *M. hominis*PG21 DNA and fluorescence probes was done. The fluorescence signal of 10-fold dilution series from 10^5^to 5 and 1 copy is shown. No reaction was noted in the negative control (0 copies). (b) Standard curve was generated from the threshold cycles (*C*~*t*~) also known as crossing points (*Cp*) of the *M. hominis*PG21 standard dilution series by the LightCycler software.
:::
:::
::: {#F3 .fig}
Figure 3
::: {.caption}
######
**Specificity of the LightCycler PCR.**The LightCycler PCR run with different *M. hominis*isolates. Concentration of DNA from different isolates used in the study was estimated to 10^4^copies/μl of PG21 DNA, which was used as a standard DNA.
:::
:::
::: {#F4 .fig}
Figure 4
::: {.caption}
######
**Specificty of the LightCycler PCR.**(a) LightCycler PCR with human DNA from Hep2 cells and selected *Mycoplasma spp.*run with the designed primers and probes. (b) Spiking assay showed no inhibition when DNA from five different *Mycoplasma*species (*M. arginini, M. bovis, M. hyorhinis, M. pulmonis, M. salivarium)*was spiked with PG21 DNA of 10^2^copies/μl. All curves came up at the same time as 10^2^copies/μl of PG21 from the standard dilution series (marked with squares).
:::
:::
::: {#F5 .fig}
Figure 5
::: {.caption}
######
**Sequence alignment of the probe region of *M. hominis*isolates.**The sequence of PG21 was used as a template. The probe sequences from the *M. hominis*isolates are shown. Highlighted base pairs corresponded to differences in probe sequences in comparison to PG21 standard. Groups are shown in boxes: top box represents the lowest melting temperature of 62°C, group 3, with isolates; 3105, 4712 and 5941; medium box contains: 7808, DC63, P2, SC4, 132, 7357 and 93 that have a melting temperature of 64°C; and bottom box with V2785 is almost identical to PG21 with only one mismatch and a melting temperature of 66°C.
:::
:::
::: {#F6 .fig}
Figure 6
::: {.caption}
######
**Melting peak analysis with *M. hominis*isolates.**Melting curve analysis of *M. hominis*isolates was performed after quantification step. The three melting temperatures are marked with arrows. Two concentrations of PG21 DNA standard dilution series are shown. All samples were run with concentration of 10^4^copies/μl.
:::
:::
::: {#F7 .fig}
Figure 7
::: {.caption}
######
**Inhibition of the BEa and SP-4 media on LightCycler PCR.**LightCycler PCR with SP-4 medium and BEa spiked with PG21 DNA of the concentrations: 10^5^, 10^4^, and 10^3^copies/μl, respectively.
:::
:::
::: {#F8 .fig}
Figure 8
::: {.caption}
######
**Reproducibility of the LightCycler assay in clinical samples.**The LightCycler PCR run of 10 negative clinical samples spiked with the known PG21 DNA concentration of 10^2^copies/μl. The assay showed no inhibition, all curves came up at the same time as 10^2^copies/μl of PG21 (marked with squares) from the standard dilution series.
:::
:::
::: {#F9 .fig}
Figure 9
::: {.caption}
######
**DNeasy treated samples.**(a) Two LightCycler PCR runs, first one with standard dilution series of human Hep2 DNA before (flat negative curves) and after DNeasy (indicated with squares and triangles), showed on the left and second with DNA free water before (marked with squares) and after DNeasy (triangles) on the right. (b) Melting curve analysis of DNeasy treated H~2~O (triangles), Hep2 DNA (squares) and clinical sample.
:::
:::
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
List of the source of microbial and human DNA used in the assay
:::
***M. hominis*isolates** Isolation reference Isolation Source Accession no.*gap*gene
-------------------------- ---------------------------------- ---------------------- ------------------------
PG21 Nicol and Edward \[20\] Lower genitalia AJ243692
183 Linn and Kass \[21\] vagina
7357 Christiansen and Andersen \[22\] cervix AJ298001
6188 Christiansen and Andersen \[22\] cervix
3849 Christiansen and Andersen \[22\] cervix
P2 Thomsen \[23\] upper urinary system AJ298004
93 Linn and Kass \[20\] vagina AJ279227
4712 Christiansen and Andersen \[22\] cervix AJ297999
5941 Christiansen and Andersen \[22\] cervix AJ298000
DC63 Taylor-Robbinson \[24\] cavum oralis AJ298003
1893 Christiansen and Andersen \[22\] cervix
V2785 Taylor Robbinson \[24\] cavum oralis AJ298006
3105 Christiansen and Andersen \[22\] cervix AJ243694
W2 Lee \[25\] wound
P7 Thomsen \[23\] upper urinary system
SC4 Hollingdale and Lemcke \[26\] urethra, male AJ298005
132 Linn and Kass \[21\] vagina AJ243693
P71 Thomsen \[23\] upper urinary system
7808 Christiansen and Andersen \[22\] urethra, female AJ298002
M1449 Friis \[27\] blood
10 Linn and Kass \[21\] vagina
***Mycoplasma species*** Source
*M. arginini* G230
*M. lipophilum* MaBy
*M. primatum* HRC 292
*M. pulmonis* ASH PB34
*M. hyorhinis* AMRC 108
*M. bovis* Donetta PG45
*M. buccale* 20247
*M. fermentans* PG18
*M. genitalium* G37
*M. pneumoniae* FH
*M. salivarium* PG20
*M. orale* CH19299
*M. arthritidis* PG6
*U. urealyticum* Serovar 8 (T960)
*U. parvum* Serovar 6 (Pirillo)
**Human** Source:
**Genomic DNA** Hep2; ATCC
:::
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Primers and probes sets used in the study
:::
Oligonucleotide Nucleotide position Sequence
------------------- --------------------- -----------------------------------------------------------
Forward Primer 295--322 5\'-GGAAGA-TATGTAACAAAAGAAGGTGCTG-3\'
Reverse Primer I 411--438 5\'-TTTATCTTCTGGCGTAATGATATCTTCG-3\'
Reverse Primer II 430--457 5\'- ATGAAGCGCCTGATAAAATTTTATCTTC-3\'
Probe I 336--368 5\'-AGCAGGTGCTAAAAAGGTGTTTATTACTGCTCC-FL-3\'
Probe II 370--408 5\'-LCred705-GCTAAAAGCGAAGGTGTTAAAACAGTT GTTTATTCAGTA-3\'
:::
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Reproducibility of the LightCycler-PCR
:::
Copy number No. of PCR runs where fluorescence gave positive signal CP SD CV % of CP
------------- --------------------------------------------------------- ------ ----- ------------
10^5^ 10 / 10 25.4 1.7 6.7
10^4^ 10 / 10 28.7 1.6 5.5
10^3^ 10 / 10 32.3 1.6 4.8
10^2^ 10 / 10 35.8 1.7 4.8
10^1^ 10 / 10 39.7 2.1 5.3
5 copies 10 / 10 40.6 2.3 5.6
1 copy 6 / 10 43.8 1.7 3.8
CP = crossing-points, mean value
CV = coefficient of variation
SD = standard deviation
Statistical analysis of standard dilution series of standard PG21 DNA was performed. Ten different runs were analysed for crossing-points values and for presence of fluorescence signal. Based on crossing-points values the standard deviation of single concentration was calculated and coefficient of variation as a function: CV% = (SD / Average CP value for each concentration) × 100%.
:::
|
PubMed Central
|
2024-06-05T03:55:47.917637
|
2004-9-6
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC518963/",
"journal": "BMC Microbiol. 2004 Sep 6; 4:35",
"authors": [
{
"first": "Agata",
"last": "Baczynska"
},
{
"first": "Helle F",
"last": "Svenstrup"
},
{
"first": "Jens",
"last": "Fedder"
},
{
"first": "Svend",
"last": "Birkelund"
},
{
"first": "Gunna",
"last": "Christiansen"
}
]
}
|
PMC518964
|
Background
==========
Major depressive disorder (MDD) is one of the most common and disabling of medical conditions \[[@B1]\]. The Canadian Community Health Survey recently reported a one-year prevalence rate of 4.5% for MDD, indicating that over 1.1 million Canadians suffer significant distress and impairment in function due to depression \[[@B2]\]. The economic costs of depression are estimated at over \$5 billion annually \[[@B3]\]. Depression is currently the fourth-ranked medical condition contributing to global burden of disease, and is estimated to rise to second overall by the year 2010 \[[@B4]\].
There are many effective treatments for MDD, including psychotherapy and antidepressants. Traditionally, efficacy in randomized controlled trials (RCTs) for depression has been determined on the basis of score changes in rating scales such as the Hamilton Depression Rating Scale (HDRS) \[[@B5]\] or the Montgomery-Asberg Depression Rating Scale (MADRS) \[[@B6]\]. Clinical outcome has been usually assessed by clinical response rates, typically defined as a 50% or greater reduction from baseline scores on these rating scales \[[@B7]\]. Although obtaining clinical response represents an important therapeutic milestone, it does not necessarily indicate a complete recovery from MDD, since many patients with clinical response will still be left with substantial residual symptoms of depression. Studies have shown that the presence of residual symptoms after an episode of MDD is associated with higher risk of relapse, recurrence, chronicity, suicide, development of cardiovascular disease, and poor quality of life \[[@B8]-[@B10]\].
Such findings suggest that the goals of acute treatment (approximately the first 8--12 weeks or so of treatment) for MDD should be clinical remission, a clinical state distinguished by minimal residual symptoms, rather than just response \[[@B11]-[@B13]\]. Clinical remission is typically defined as a score within the normal range on a given outcome measure (e.g., 17-item HDRS score of 7 or less; MADRS score of 12 or less; Clinical Global Impression \[CGI\] \[[@B14]\] severity score of \"Normal, not at all ill\"), although there is still some uncertainty as to the validity of these cutoff scores for symptom remission \[[@B15]\]. The achievement of remission is of considerable clinical importance as it predicts decreased risk of relapse and greater psychosocial functioning than typically observed in patients who have achieved clinical response alone \[[@B16]-[@B18]\]. Clinical remission is now identified and promoted as a clinical target for successful management of MDD in many clinical practice guidelines \[[@B13],[@B19]-[@B21]\].
Increasing numbers of treatment studies are now explicitly reporting both clinical response and remission rates in assessment of outcome. A meta-analysis of 8 antidepressant studies of venlafaxine versus selective serotonin reuptake inhibitors \[SSRIs\] and placebo reported mean remission rates of 45%, 35%, and 25%, respectively \[[@B22]\]. A subsequent meta-analysis of 32 RCTs comparing venlafaxine, SSRIs and other antidepressants reported a mean overall remission rate of 42% \[[@B23]\]. Finally, a meta-analysis of 6 RCTs comparing antidepressants and psychotherapy in patients with MDD reported mean remission rates of 46% for each treatment \[[@B24]\].
All the studies in these systematic reviews involved patients in psychiatric or mixed settings. However, most people suffering from MDD will be managed in the primary care setting \[[@B25]\]. Approximately 5% to 10% of all patients consulting a general practitioner have MDD, with prevalence estimates being two to three times higher when other depressive disorders (i.e., minor depression or dysthymia) are included \[[@B26]\]. It remains unclear whether the remission rates reported in psychiatric settings can be extrapolated to primary care environments, although it is of clinical importance for primary care physicians to know whether obtaining remission is a realistic goal for their patients. There has been a recent surge in studies assessing a variety of treatment interventions for depression in primary care settings, making this an opportune time to perform a meta-analysis to address this question. Hence, the primary objective of this study was to determine remission rates obtained in RCTs of treatment interventions for MDD conducted in primary care settings.
Methods
=======
Potentially relevant studies were identified using computerized and manual search strategies. The computerized search conducted in June, 2003 included the databases: Medline, Psych Info, Embase, Biosis, Cochrane Database of Systematic Reviews, and Cochrane Controlled Trials Register and Current Controlled Trials (1981--May 2003). The search terms used were \'depressive disorder\' or \'depression\' combined with \'primary care\' and \'remission\' and/or variants. The bibliographies of relevant articles were also manually searched. Two reviewers (MYD and RWL) collected and independently assessed abstracts for inclusion criteria. Disagreements were resolved with consensus.
Inclusion criteria
------------------
Studies were included if they were RCTs with original data comparing one or more interventions (e.g., antidepressant vs. cognitive behavioral therapy) and published in English. Only studies of predominantly adult populations, as opposed to exclusively child or elderly patient populations, were included. Although the focus was principally upon patients with MDD (studies primarily dealing with minor depression and dysthymia were excluded), the criteria for a diagnosis of MDD was intentionally broad in order to capture the heterogeneity of the sample and allow the results to be as generalizable as possible. Included studies also had to use a standardized outcome measure (e.g., HDRS, MADRS, Beck Depression Inventory \[BDI\] \[[@B27]\]) and provide explicit criteria for remission. While the definition of remission varied among the studies (Table [1](#T1){ref-type="table"}), for the purpose of this meta-analysis we accepted each study\'s definition of remission, which usually was a score within the normal range on the outcome measure.
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Summary of included studies in meta-analysis of remission rates.
:::
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
**Study** **Diagnostic Criteria** **Follow up Period** **Remission Criteria** **Total N** **Intervention** **Intervention Remission Rate** **Remission %**
-------------------------------------------------- ------------------------------------------------ ---------------------- ---------------------------------------------------------------------------- ------------- ---------------------------------- --------------------------------- -----------------
**Psychological Intervention Only**
Dowrick et al., 2000 \[31\] DSM-IV criteria for MDD or Adjustment Disorder 6 months No MDD detected by SCAN interview 425 • PST\ • 58/128\ • 45\
• Usual Care\ • 76/189\ • 38\
•Prevention course • 44/108 • 41
**Antidepressant Intervention Only**
Benkert et al., 2000 \[32\] DSM-IV criteria for MDD and HDRS ≥ 18 6 weeks HDRS ≤ 7 275 • Mirtazapine\ • 52/139\ • 37\
• Paroxetine • 42/136 • 31
Patris et al.,1996 \[33\] DSM-IIIR criteria for MDD 8 weeks MADRS ≤ 12 357 • Citalopram\ • 114/173\ • 66\
• Fluoxetine • 110/184 • 60
Wade et al., 2002 \[34\] DSM-IV criteria for MDD 8 weeks MADRS ≤ 12 380 • Escitalopram\ • 92/191\ • 48\
• Placebo • 64/189 • 34
**Psychological Intervention + Antidepressants**
Chilvers et al., 2001 \[35\] Diagnosed as MDD by GP 12 months RDC \<4, BDI \<10, or clear documentation in GP notes that patient is well 103 Randomised only:\ • 39/51\ • 76\
• Antidepressant\ • 33/52 • 63
• Counselling
Mynors-Wallis et al., 1995 \[36\] Diagnosed as MDD by GP 12 weeks HDRS ≤ 7 or BDI ≤ 8 91 • PST\ • 18/30\ • 60\
• Amitriptyline\ • 16/31\ • 52\
• Placebo • 8/30 • 27
Mynors-Wallis et al., 2000 \[37\] RDC criteria for MDD 12 months HDRS ≤ 8 151 • PST-group\ • 24/39\ • 62\
•PST-RN\ • 23/41\ • 56\
• Antidepressant\ • 20/36\ • 56\
• PST+antidepressant • 23/35 • 66
Schulberg et al., 1998 \[38\] DSM-IIIR criteria for MDD 8 months HDRS ≤ 7 184 • IPT\ • 49/93\ • 57\
• Nortriptyline • 52/91 • 53
Scott et al., 1992 \[39\] DSM-IIIR criteria for MDD 4 months HDRS ≤ 7 121 • CBT\ • 12/30\ • 40\
• Counselling\ • 22/30\ • 73\
• Amitriptyline\ • 18/31\ • 58\
• Usual care • 14/30 • 47
**Program Interventions**
Katon et al.,1999 \[40\] Diagnosed as MDD by GP 6 months Presence of 0 or 1 SCID-assessed symptoms 228 • Collaborative care\ • 50/114\ • 44\
• Usual Care • 35/114 • 31
Katzelnick et al., 2000 \[41\] Diagnosed as MDD by GP and HDRS ≥ 15 12 months HDRS ≤ 7 407 • Depression management\ • 92/218\ • 42\
• Usual care • 49/189 • 26
Kutcher et al., 2002 \[42\] Diagnosed as MDD by GP 29 weeks 8 weeks or longer with HDRS ≤ 10 269 • Sertraline\ • 84/138\ • 61\
• Sertraline + adherence program • 88/131 • 67
Rost et al., 2002 \[43\] Diagnosed as MDD by GP 24 months CES-D ≤ 16 211 • Enhanced depression care\ • 85/115\ • 74\
• Usual care • 39/96 • 41
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
(Abbreviations: BDI -- Beck Depression Inventory, CBT -- Cognitive Behavioural Therapy, CES-D -- Centre for Epidemiological Studies -- Depression Scale, HDRS -- Hamilton Depression Rating Scale, HSCL-D-20 -- 20-item Hopkins Symptom Check List, IPT-Interpersonal Psychotherapy, MADRS -- Montgomery-Asberg Depression Rating Scale, MDD -- Major Depressive Disorder, PST -- Problem Solving Therapy, PST-PC -- Problem Solving Therapy, administered by Primary Care Physician, PST-RN -- Problem Solving Therapy, administered by Registered Nurse, RDC -- Research Diagnostic Criteria, SCAN -- Schedules of Clinical Assessment in Neuropsychiatry, SCID -- Structured Clinical Interview for DSM-III-R.)
:::
Data extraction
---------------
Two independent reviewers (MYD and EEM) extracted data from studies using a checklist developed for this study, with disagreements resolved by a third reviewer (RWL). A conservative measure of remission rate was calculated from each study using an intent-to-treat analysis \[[@B28]\], even if this method was not used in the study. For example, some studies calculated remission rates using only patients who returned for one follow-up visit post-randomization, or who had completed a course of treatment. The denominator used for remission rate was the total number of patients randomized to treatment, whether or not they were counted in the ensuing analysis. The numerator was the number of patients in remission reported in the study, regardless of the denominator used in the study analysis.
The type of intervention was classified as placebo, \"usual care\" by clinician (standard treatment by a patient\'s own physician), psychotherapy treatment only, antidepressant treatment only, psychotherapy plus antidepressant treatment, or program intervention (e.g., collaborative care using other health professionals; educational programs targeted at quality improvement for prescribing practices).
Statistics
----------
Each set of rates was pooled based on a Bayesian approach to meta-analysis using the Fastpro software program (version 1.7) by Eddy and Hasselblad. Readers interested in a more detailed discussion of this approach should refer to Eddy et al \[[@B29]\]. The pooled means and confidence intervals were calculated using Jeffrey\'s prior and a random effects model.
Results
=======
The initial electronic and bibliographic search found 63 articles of which 47 warranted more detailed review based on the published abstract. Of these, 34 articles were excluded due to methodology (not RCTs, 4 studies), lack of remission criteria (18 studies), diagnostic criteria (not MDD, 11 studies) and age criteria (geriatric, 4 studies) (some studies were excluded for multiple reasons, see [Additional File 1](#S1){ref-type="supplementary-material"}). A final count of 13 studies met the full inclusion criteria (Table [1](#T1){ref-type="table"}). In total, 3202 primary care outpatients (75% female, 25% male) were included in the analysis. The mean age of the participants was 32.1 years (range 18--73 years). The average length of follow-up was 32 weeks (range 6--104 weeks).
The study interventions and methodologies were too heterogeneous to allow for a meaningful statistical comparison of results between treatments. Figure [1](#F1){ref-type="fig"} shows mean remission rates for specific interventions. Overall remission rates for active interventions, regardless of type, ranged between 50% and 67%, compared to 32% for pill placebo conditions and 35% for usual care conditions. There were a sufficient number of antidepressant arms in the studies to permit the summary of remission rates by duration of follow-up period. For antidepressant studies with follow-up of 6 months or less, mean remission rate was 51.4% (95% C.I., 43.1%--59.6%); for antidepressant studies with greater than 6 months of follow-up, mean remission rate was 62.3% (95% C.I., 48.9%--74.8%).
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Remission rates for specific treatment conditions from randomized controlled trials (RCTs) of interventions for depression in primary care settings. The white lines represent the mean remission rates and the boxes represent the 95% confidence interval. N is the number of treatment arms in the RCTs (Note: Psychotx = Psychotherapy, Antidepr = Antidepressants, pts = patients).
:::
:::
Discussion
==========
This review of research assessing remission of depressive symptoms in primary care populations identified 13 studies meeting the inclusion criteria. Overall remission rates (regardless of type of intervention but excluding placebo or usual care arms) ranged between 50% and 67%. These rates are equivalent to, or indeed greater than, those reported in meta-analyses of studies examining pharmacological or psychological interventions for depression in psychiatric populations, in which the overall remission rates ranged between 35% and 46% \[[@B22]-[@B24]\]. On the one hand, we might have predicted this finding as studies conducted in primary care settings tend to include more patients with mild to moderate depression (although we excluded studies that focused exclusively upon minor depression or dysthymia), whereas patients referred to psychiatric settings are more likely to have moderate to severe depression. Primary care treatment trials also tend to be longer, favouring a higher remission rate; whereas the mean follow-up period of studies included in the current analysis was 9 months, it was only 7 weeks and 10 weeks in the two previous meta-analyses of pharmacological interventions for MDD \[[@B22],[@B23]\], and 16 weeks in the meta-analysis of antidepressant versus psychotherapeutic interventions \[[@B24]\]. Conversely, we might have predicted that we would observe *lower*remission rates in the current meta-analysis as it included a number of studies with more lenient exclusion criteria than typically used in psychiatric clinical trials. In particular, the program intervention studies tend to include more heterogeneous patient populations as they do not routinely exclude patients with psychiatric or medical comorbidities, factors that may lessen the likelihood of obtaining remission of depressive symptoms \[[@B30]\].
While it was not within the scope of the current study to compare the effectiveness of different treatment interventions in improving remission rates, we can report on the trends we observed in the data. Antidepressant and psychotherapy interventions delivered in isolation showed similar remission rates (54% for both). Combination antidepressant plus psychotherapy interventions showed somewhat higher rates (67%), although this category included only 1 arm with only 35 patients. Program interventions had a mean remission rate of 50%, and all treatment interventions fared better than either placebo (32%) or usual care (35%).
The studies identified in our review were quite heterogeneous in nature, ranging from those that looked solely at the effects of a particular pharmacological agent, through to complex program initiatives that incorporated a variety of interventions at different levels of care. This heterogeneity limits our ability to make broad comments about remission rates in primary care, but was not unexpected, as we wanted to capture the diversity of treatment interventions for depression currently being tested in this setting. Other potential limitations of the study include that fact that we only assessed published studies written in English and that we used a conservative measure of remission rate. Finally, we also used the definition of remission as specified by each individual study. While these definitions were similar to those widely used in RCTs conducted in psychiatric settings, and thus are useful for comparison, there is current controversy about depression scales and which cutoff scores indicate true remission of symptoms \[[@B15]\].
Conclusions
===========
This meta-analysis serves to answer an important clinical question about the feasibility of obtaining remission of symptoms of MDD in primary care patients. Our results indicate that this is a realistic goal in this population, although further research is still required to determine whether certain treatment modalities (or combinations of treatment interventions) are superior to others in achieving higher remission rates. Future research should also focus upon developing pragmatic strategies for general practitioners to implement evidence-based guidelines concerning the treatment of depression to clinical remission.
Authors\' contributions
=======================
MYD and EEM conducted the data extraction, wrote the initial draft of the manuscript, interpreted results, and revised the manuscript. PW provided statistical consultation and analysis, and revised the manuscript. JEA interpreted the results and revised the manuscript. RWL conceived the initial idea, developed the method, interpreted results, revised the manuscript, and provided financial resources for the study. All authors read and approved the final manuscript.
Competing interests
===================
RWL is on advisory/speaker boards or has received research funds from: AstraZeneca, Biovail, Canadian Network for Mood and Anxiety Treatments, Eli Lilly, GlaxoSmithKline, Janssen-Ortho, Litebook, Inc., Lundbeck, Merck, Organon, Roche, Shire, Servier, and Wyeth.
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1471-2296/5/19/prepub>
Supplementary Material
======================
::: {.caption}
###### Additional File 1
Studies excluded from the review
:::
::: {.caption}
######
Click here for file
:::
Acknowledgments
===============
Dr. Michalak was supported by a Canadian Institutes of Health Research/Wyeth Canada Postdoctoral Fellowship Award.
|
PubMed Central
|
2024-06-05T03:55:47.921915
|
2004-9-7
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC518964/",
"journal": "BMC Fam Pract. 2004 Sep 7; 5:19",
"authors": [
{
"first": "Marliese Y",
"last": "Dawson"
},
{
"first": "Erin E",
"last": "Michalak"
},
{
"first": "Paul",
"last": "Waraich"
},
{
"first": "J Ellen",
"last": "Anderson"
},
{
"first": "Raymond W",
"last": "Lam"
}
]
}
|
PMC518965
|
Background
==========
The causative agent for SARS has been identified as a novel coronavirus \[[@B1]-[@B3]\] with genome sequence revealing no strong homology to existing known coronaviruses \[[@B4]-[@B6]\]. Coronaviruses belong to the family of enveloped viruses called *Coronaviridae*, and have the largest known single-stranded viral RNA genomes (27 to 32 kb). Coronaviruses, have both \"early\" and \"late\" phases of gene expression. Regulatory proteins are synthesized as \"early\" non-structural proteins, while the structural proteins are synthesized as \"late\" proteins. \"Late\" structural proteins are usually required in greater amounts thus, there is a necessity to regulate the expression of the viral genes quantitatively. After the viral entry via endocytosis or through specific receptors, the 5\'-end of the viral genome is translated directly giving rise to twenty-three viral proteins, including the RNA dependent RNA polymerase (RdRp), and other functional products involved in transcription, replication, viral assembly and cell death. Coronaviruses can be classified into species and three major antigenic groups based on, serology, natural hosts, monoclonal antibody recognition and nucleotide sequencing \[[@B7]\]. Most coronaviruses have restricted host ranges as they infect only one host species or, at most, a few related species, they are an important group of animal pathogens. Group one (I) includes human coronavirus 229E (HCoV), porcine transmissible gastro-enteritis virus (TGEV) and feline enteric coronavirus (FECoV). Group two (II) includes bovine coronavirus (BCoV), murine hepatitis virus (MHV), and HCoV-OC43; and Group three (III) includes avian infectious bronchitis virus (IBV) \[[@B7]\]. Some coronaviruses like HCoV have restricted tissue tropism, including macrophages \[[@B8]\], although most strains that infect humans cause only mild respiratory infections.
However, SARS has rapidly caused a world-wide problem. The earliest known cases of SARS was reported in Guandong Province, China in November 2002, becoming more widespread by March 2003, when it was introduced to Canada, Singapore, Taiwan and Vietnam via Hong Kong. The largest number of infected patients has been in China with a worldwide incidence totalling more than 8,400 by July 2003. Infection by the virus induces high morbidity and mortality, the latter being estimated at 15% by the World Health Organisation. SARS is characterized by high fever, non-productive cough or dyspnea and in many cases may progress to generalized, interstitial infiltrates in the lung, thus needing intubation and mechanical ventilation \[[@B2]\]. The characteristic compression of alveolar sacs seen in atypical pneumonia is largely due to fluid build up outside the alveoli. One possible cause of this could be interstitial inflammation, following a localised host response. To date, the details of the host response to SARS-CoV infection is still largely unknown and consequently the most appropriate treatment regime remains to be established. Typically a pro-inflammatory cytokine profile (up regulated TNFα, Il1, IL6 and IFNs) is seen in viral infections such as influenza \[[@B9]\], together with perhaps limited amounts of IL8 and other chemokines \[[@B10]\] that may depend on which cell type is infected \[[@B11]\]. In experimental systems the immediate innate immune response has been shown to be directed by the monocyte-macrophage-dendritic lineage to a range of different organisms \[[@B12],[@B13]\] and consists of a core set of pathways common to all, together with pathogen specific pathways. This data points to critical time points in the response, with the first 12 hours representing primary events while longer periods the consequence of this activity and a secondary (perhaps larger) cascade of responses.
We postulated that the pulmonary damage in SARS may not be a direct effect of the virus on the alveoli, but represents a secondary effect of cytokines or other factors proximal to but not from the lung tissue mediated by the host either as the primary or secondary response \[[@B2],[@B14]\]. In this study, we have addressed this question by developing a human *in vitro*model system that will in the future allow detailed investigations of the host response to be made.
Methods
=======
Cell culture and virus infection
--------------------------------
PBMCs were obtained by Ficoll-Hypaque separation of whole blood. 2 × 10^5^PBMCs were seeded into each well of a 24-well culture plate, 0.5 ml of complete RPMI-1640 (Life Technologies-Invitrogen, USA) added to each and cultured overnight at 37°C (5% CO~2~). A seed stock of SARS-CoV (strain SIN 2774) passaged in Vero E6 cells was used for infection. Vero E6 culture supernatants were added to each well in 50 μl volume at a concentration of 0.1 or 0.01 MOI (based on plaque forming units) and a control plate (media only). Each culture was set up in duplicate. After 4 hours of incubation, one set of the duplicate wells of the control plate and a 4 hours incubation plate were harvested while the rest received 0.5 ml media top-up and incubated for a further 2, 4, 6 and 8 days.
Cell harvest and RNA isolation
------------------------------
Harvesting was performed by gently flushing the wells with a Pasteur pipette to removed non-adherent cells, followed by a rinse of 1 ml RPMI. The rinsed fraction was pooled with the first harvest aliquot and spun at 1500 rpm. The cell pellet was washed twice with 2 ml RPMI to remove virus in the supernatant. 1.5 ml Trizol (Invitrogen, USA) was then added to the adherent cell fraction as well as the non-adherent cell fraction to lyse cells and stabilize the RNA. Extraction of total RNA was then performed following manufacturer\'s protocol and the resultant RNA dissolved in 40 μl water.
Real-time quantitative polymerase chain reaction (PCR)
------------------------------------------------------
The amount of SARS-CoV in each cell fraction was measured by real-time quantitative PCR assay. 2 μl of RNA was reverse transcribed and amplified in 20 μl using 0.9 μM each of forward (5\'-GGTTGGGAT TATCCAAAATGTGA-3\') and reverse (5\'-AGAACAAGAGAGGCCATTATCCTAAG-3\') primers, and 0.25 μM of TaqMan^®^MGB probe: 5\'-(6-FAM)AGAGCCATGCCTAACAT(NFQ)-3\') in a one step PCR using master mix from Applied Biosystems (USA) according to manufacturers\' recommendations. Reactions were performed using an ABI PRISM 7900 sequence detection system (48°C for 30 min, followed by 95°C for 10 min and 40 cycles of 95°C for 15 sec and 60°C for 1 min) and quantitation achieved using standard curves generated from *in vitro*transcribed RNA.
High density oligonucleotide array hybridization
------------------------------------------------
At each time point (4 hours, 8 hours, 12 hours, 24 hours), 5 × 10^7^cells of mock-infected and infected cells were harvested and lysed using Trizol (Invitrogen, USA). Total RNA was isolated according to the manufacturer\'s recommendation. Quality of the total RNA was judged from the ratio between 28S and 18S RNA after agarose gel electrophoresis. 20 μg of total RNA was labeled with Cy-3 or Cy-5 using the Superscript II reverse-transcription kit (Invitrogen, USA) and hybridization was carried out overnight (16 hours) at 42°C on high-density oligonucleotide arrays (\~19,200 gene features, Compugen) using universal human reference (Stratagene, USA) as a reference. Hybridized arrays were scanned at 5 μm resolution on a GenePix 4000A scanner (Axon Instruments) with variable photo-multiplier tube voltage to obtain maximal signal intensities, and the resulting images were analyzed via GenePix Pro v4.0 (Axon Instruments) as described in the manual.
Microarray data analysis
------------------------
Raw data were analyzed on GenePix analysis software version 4.0 (Axon Instruments) and uploaded to a relational database. The logarithmic expression ratio for a spot on each array was normalized by subtracting the median logarithmic ratio for the same array. Data were filtered to exclude spots with a size of less than 25 μm and any poor quality or missing spots. Since the correlation of the overall data from reciprocal labeling was good, values obtained from reciprocal labeling experiments were averaged. In addition, the data were distilled to the set of gene features that were present at all 4 time points in both the viral infected samples and the negative controls. The results were represented as the logarithmic ratio of gene expression between the viral infected samples and their corresponding negative controls at the various time points. Application of these filters resulted in the inclusion of \~12,900 of the total \~19,200 gene features in subsequent analyses.
To discover patterns of gene expression, the values associated with each gene feature *f*were translated so that their means were zero. Similar genes, whose translated gene-features exhibited same induction-repression pattern, were grouped together. Genes *g*~*i*~, *g*~*j*~were said to be similar if they satisfied the following condition:
, where *U*(*x*) = 1 if *x*\> 0, *U*(*x*) = 0 otherwise,
where *g*~*it*~and *g*~*jt*~denote the translated values of gene features *g*~*i*~, *g*~*j*~at time *t*respectively; and *N*is the number of time points for which the expression of a gene was observed. Similar genes, based on the above criteria, are grouped together. Within each group, the genes were ordered in the descending order of their expression range (defined as the difference between the maximum and minimum ratios of gene expression). This algorithm is a special case of the *Friendly Neighbor*algorithm currently under development. The final plots were generated using the original expression ratios while preserving the clustering and ordering discovered by the above algorithm. To determine whether a gene observed to be responsive could appear merely by chance, 100,000 expression profiles were generated by randomly sampling the expression ratios from the entire dataset with replacement. The *P*value of a gene is the fraction of the random profiles whose logarithmic expression range is as good as, or better than that of the selected gene.
Results and Discussion
======================
Kinetics of SARS-CoV replication
--------------------------------
We obtained PBMCs from 6 healthy volunteers by Ficoll-Hypaque separation of whole blood. Of the 6 donor PBMCs tested, all were able to support SARS-CoV replication when infected with multiplicity of infection (MOI) of 0.1. The first sampling, taken from cells infected for 4 hours, showed an average copy number of 32 × 10^3^(Fig. [1A](#F1){ref-type="fig"}) and represents the initial inoculum level. Over the course of the next 8 days, there was a steady rise in viral load, reaching as high as 480 × 10^3^copies per well in one donor, which could only be explained by active replication of the SARS-CoV intracellularly. This work is supported by recent *in vivo*evidence suggesting that SARS-CoV may have infected and replicated within PBMCs of SARS patients \[[@B15]\] and cells from humans and animals \[[@B16]\]. An indication of the PBMCs lineage involvement was provided by repeating the experiment using the monocyte-macrophage cell line THP-1 \[[@B17]\], in which viral replication was similar to the primary cell culture over the first 4 days (Fig. [1B](#F1){ref-type="fig"}). In the primary cultures, the non-adherent cell fraction which comprises mainly lymphocytes and granulocytes showed dramatically less viral replication in our assay as did all cells infected at MOI of 0.01 (Fig. [1A](#F1){ref-type="fig"}).
The kinetics of viral replication was variable among the 6 donors (Fig. [1C](#F1){ref-type="fig"}). There was a lag phase of 2 days in the case of donors a, c and e; and 4 days for donors b, d and f before any significant increase could be detected. The viral replication generally peaked at either day 4 or day 6. The exception was donor b, in which the virus seemed to replicate at a much slower pace compared to the other 5 donor samples. Equally interesting was the different levels of virus attained. Donor d seems to stand out from the rest, reaching a peak of 480 × 10^3^copies per well which is 4 times more than that attained by donor e, with 120 × 10^3^copies per well. Such variation strongly suggests that there is an underlying host-pathogen interaction influencing the kinetics of SARS-CoV replication efficiency. These *in vitro*observations may reflect the wide range of patient outcomes after SARS-CoV infection \[[@B18]\].
Antibody blocking experiments were also performed in which SARS-CoV was pre-incubated with convalescent patient sera for 30 minutes before introduction to the PBMCs and after a 4 day incubation period, the adherent cell fraction was harvested and assayed for SARS-CoV viral titer. Results clearly showed that even at high dilution, convalescent sera inhibited SARS viral replication (data not shown), presumably by blocking viral entry. This supports other reports indicating that SARS-CoV is not endocytosed through antibody mediated mechanisms and confirms a protective role for antibodies elicited either by the infection or through immunization \[[@B19],[@B20]\].
SARS-CoV specific gene expression changes
-----------------------------------------
To further elucidate the molecular processes of SARS-CoV infection, PBMCs from 3 healthy individuals were infected separately *in vitro*with SARS-CoV (0.1 MOI) and harvested at 4 hours, 8 hours, 12 hours and 24 hours time intervals post-infection. As controls, uninfected aliquots of the same PBMCs were also harvested at the corresponding time points. Total RNA extracted from the PBMCs of the 3 individuals were pooled, labeled and hybridized to human oligonucleotide arrays consisting of \~19,200 gene features. Reciprocal dye swap replicate hybridizations were performed to minimize technical noise. Analysis of variance in expression levels for each gene across all the time points indicated the \~1200 genes which showed the largest variability (Fig. [2A](#F2){ref-type="fig"} and [2B](#F2){ref-type="fig"}).
In order to focus the analysis, we queried the entire data set for genes related to the immune response by keyword searches on their gene ontology descriptions with the aim of describing the specific host-pathogen interaction. In common with other studies of respiratory pathogens \[[@B9]-[@B13]\], our data points towards two critical time points in the response, with the first 12 hours representing a primary pro-inflammatory cytokine profile while longer periods represent the consequence of this activity and a secondary cascade of responses \[[@B9]-[@B13]\]. We observed that within the first 12 hours of SARS-CoV infection, evidence of this monocyte-macrophage activation was seen, indicated by enhanced expression of CD14, TLR9 plus NFKβ1 and GATA signaling (Fig. [2C](#F2){ref-type="fig"} and Table [1](#T1){ref-type="table"}). In addition, the MRC2 endocytotic receptor was upregulated as was the complement pathway (C1q, C6). Taken together, these data suggest an early activation of the innate immunity pathway. This activation was accompanied by an unusual cytokine transcriptional profile (Fig. [2C](#F2){ref-type="fig"} and Table [1](#T1){ref-type="table"}). While IL1β (up regulated for the first 12 hours) would be expected following macrophage activation \[[@B21]\], TNFα, IFNγ and IL6 were noted by their surprisingly low level of expression. This is in spite of the presence of elevated IL19 which is thought to enhance their up regulation \[[@B22]\]. In some clinical investigation, concentrations of TNF and IL 6 measured during active disease were found to be relatively low \[[@B23],[@B24]\], reflecting our findings. This paper did not report on IFN levels, however, we found them to be low (Supplementary figure \[see [Additional file 1](#S1){ref-type="supplementary-material"}\]). This is of particular interest as IFNs have been shown to have significant anti-SARS-CoV effects \[[@B25]\]. Such effects suggest that alteration of the IFN response and perhaps other immune modulators might provide opportunity for novel treatment and management regimes for SARS patients to be developed.
A number of CC chemokines (CCL4, CCL20, CCL22, CCL25, CCL27) and their receptors (CCR4 and CCR7) were highly expressed in response to the infection (Fig. [2C](#F2){ref-type="fig"} and Table [1](#T1){ref-type="table"}), indicating a rapid mobilization and increased trafficking, in particular of the monocyte-macrophage lineage very early on in the infection \[[@B26]\]. CXC chemokines (CXCL9, CXCL12) were also highly expressed suggesting significant increase in neutrophil homing as well. These are likely to be lung directed as IL8 and IL17 were also highly expressed \[[@B27]-[@B32]\]. Specific trafficking of these cells to the lung may account for the localized nature of the response \[[@B33]\].
Surprisingly, a number of blood coagulation genes were highly expressed early during our *in vitro*infection (Fig. [2C](#F2){ref-type="fig"} and Table [1](#T1){ref-type="table"}), in particular TBXAS, which has been implicated in vasoconstriction, platelet aggregation, membrane lysis and increased permeability \[[@B34],[@B35]\]; fibrin (FGB and FGG) and the coagulation pathway directly (SERPINs D1 and A3 together with Factors 10, 3 and 2). This gives a pro-coagulation profile, which mimics the clinical-pathological observations: at autopsy, many SARS patients have unusually disseminated small vessel thromboses in the lungs without evidence of disseminated intravascular coagulation \[[@B1],[@B36]\]. Again, these expression profiles provide an experimental framework to explore an important aspect of SARS pathobiology and treatment.
It is interesting to note that the TLR9 was highly expressed in comparison to other TLR receptors, implying some degree of TLR specificity for the virus (Fig. [3A](#F3){ref-type="fig"}). TLR9 is known to respond to CpG signaling motifs (GTCGTT) \[[@B37]-[@B39]\] and one possibility is that the virus is activating directly through this mechanism. In support of this, we found that the SARS-CoV viral sequence contains the highest number (7 copies) of such specific signaling motifs compared to other coronaviruses and significantly more than several other viruses involved in respiratory diseases (Fig. [3B](#F3){ref-type="fig"}). It is conceivable that TLR9 may be aiding host recognition of the virus via the CpG groups and contributing to the initiation of the innate host inflammatory response. An alternative explanation is that TLR9 is being stimulated by mechanisms unrelated to CpG recognition.
The emerging picture from this study implicates a central role for the immune response in the pathobiology of a SARS infection. While detailed *in vivo*studies of the host response are now required, the *in vitro*model described here will allow responses to specific modulators (such as therapeutics) to be investigated. In future developments of the model, it will be interesting to compare the host response to different SARS-CoV isolates with inactivated preparations of the virus. In other diseases, *in vitro*models have revealed a number of key processes relevant to the clinical diseases \[[@B9],[@B12],[@B13]\] and it is likely that the responses identified here will prove to be equally important. Although some clinical parameters have now been used as prognostic markers \[[@B40]-[@B42]\], further study of the regulatory mechanisms for chemokine-cytokine production will likely improve their accuracy and perhaps allow development of new treatment protocols.
Competing interests
===================
None declared.
Authors\' contributions
=======================
LFPN, MLH, ETL and REC conceived the study, its design and coordination, results analysis and drafted the manuscript. EEO and KFT carried out the virus infections. SYN, KRKM, VNV and JMC were involved in the array and statistical analysis. JT carried out the real-time PCR assays.
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1471-2334/4/34/prepub>
Supplementary Material
======================
::: {.caption}
###### Additional File 1
**List of all immune related genes after SARS-CoV infection**Comprehensive list of 1087 immune related genes that were altered in PBMCs in response to SARS-CoV infection at 4 hours, 8 hours, 12 hours, and 24 hours. Genes were grouped and ordered using the algorithm described in Methods. Rows represent individual genes, columns represent individual time points. Each cell in the matrix represents the mean expression level from 3 subjects for a gene feature at a particular time point (non-infected PBMCs responses have been subtracted from infected responses). The red and green color bars reflect high and low expression levels respectively, while black indicates equivalent expression level. The magnitude of the log-transformed ratio is reflected by the degree of color saturation. The line graph indicates the average expression ratios for each group. The area above the axis indicates upregulation, while the area under the axis means downregulation.
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::: {.caption}
######
Click here for file
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Acknowledgment
==============
This study was supported by grants from the Agency for Science, Technology and Research (A\*STAR), Singapore. Lisa F. P. Ng is also supported by a postdoctoral scholarship from the Singapore Millennium Foundation, Singapore Technologies. We thank Lora V. Agathe, Patricia Tay Pei-Wen, Khoo Chen-Ai and Li Pin (Genome Institute of Singapore); Renita Danabalan (National Environment Agency) for technical assistance and Dr Ling Ai-Ee (Department of Pathology, Singapore General Hospital) for the SARS-CoV isolate.
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Kinetics of SARS-CoV replication. A. Viral copy number per well during culture. Two MOI infecting doses were used, 0.1 (▲,■) and 0.01 (□,△) with 2 × 10^5^PBMCs/well. Harvested PBMCs were separated into two fractions, adherent cells (mostly macrophages), (■,△) and suspended cells (mostly lymphocytes), (▲,□). Points represent the mean of six subjects, each done in duplicate. Increasing viral copy number is clearly seen in adherent cells using an MOI of 0.1. There was little increase in viral load in non-adherent cells infected with SARS- CoV. B. Replication of SARS-CoV in the THP-1 cell line. Using an MOI of 0.1, fold increase from day 0 in SARS-CoV infected THP-1 cells (◆) was similar to the PBMCs adherent fraction (▲). Infections were done in duplicate and assayed in duplicate. Error bars represent SEM. C. Variation in the PBMC response to SARS-CoV infection. Using an MOI of 0.1 adherent cells (■) but not suspended cells (▲) showed differing lag phase length and viral replication in 6 subjects (a to f). Points show means of two replicates.
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
SARS specific gene expression changes. A. Plot showing the variance of expression ratio for each of the gene features across all the time points. Dotted line indicates the \~1200 most variable gene features. B. Expression ratios of \~1200 gene features as grouped by the algorithm as discussed in Methods. Rows represent individual genes, columns represent individual time points. Each cell in the matrix represents the mean expression level from 3 subjects for a gene feature at a particular time point (non-infected PBMCs responses have been subtracted from infected responses). The red and green color bars reflect high and low expression levels respectively, while black indicates equivalent expression level. The magnitude of the log-transformed ratio is reflected by the degree of color saturation. C. Levels of PBMCs mRNA expression of 1087 immune-related genes at 4 hours, 8 hours, 12 hours, and 24 hours in response to SARS-CoV infection were grouped and ordered using the algorithm described in Methods. Rows represent individual genes, columns represent individual time points. Each cell in the matrix represents the mean expression level from 3 subjects for a gene feature at a particular time point (non-infected PBMCs responses have been subtracted from infected responses). The red and green color bars reflect high and low expression levels respectively, while black indicates equivalent expression level. The magnitude of the log-transformed ratio is reflected by the degree of color saturation. The line graph indicates the average expression ratios for each group. The area above the axis indicates upregulation, while the area under the axis means downregulation.
:::
:::
::: {#F3 .fig}
Figure 3
::: {.caption}
######
Expression of TLR9 in response to SARS-CoV infection. A. Expression range (log~2~) for TLR9, TLR2 and TLR4. The expression range for TLR9 was greater than expected (\* represents a *P*-value for TLR9 of 0.016). B. Comparison of the CpG motif (GTCGTT) copy number in coronaviruses and other viruses linked to respiratory diseases. Accession numbers are as follows: SARS coronavirus SIN2500 -- AY283794, Human coronavirus 229E -- NC\_002645, Murine hepatitis virus -- NC\_001846, Avian infectious bronchitis virus -- NC\_001451, Bovine coronavirus -- NC\_003045, Human rhinovirus B -- NC\_001490, Human parainfluenza virus 1 -- NC\_003461, Human respiratory syncytial virus -- NC\_001781, Human metapneumovirus -- NC\_004148.
:::
:::
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Representation of selected immune-related genes upregulated during the first 12 hours post-infection.
:::
**Gene** **Unique Gene ID.** **Function** **Expression range (log~2~)** **Cluster no.**
---------------------------------- --------------------- ---------------------------------- ------------------------------- -----------------
***Immune Response Genes:***
TGFBR1 Hs.220 Cytokine proinflammatory 10.66 4
CD36 Hs.75613 Macrophage receptor 8.61 3
TLR 9 Hs.87968 Macrophage activation 7.11 7
MST Hs.349110 Macrophage activation 7.07 6
IL 19 Hs.71979 Cytokine, proinflammatory 6.86 9
C1QR Hs.97199 Innate response 6.31 7
C6 Hs.1282 Innate response 6.22 6
GATA3 Hs.169946 Inflamation signaling 6.14 9
MMD Hs.79889 Monocyte to macrophage 6.13 7
CCL 25 Hs.50404 Chemokine, trafficking 6.10 6
CXCL 12 Hs.237356 Chemokine, trafficking 5.86 6
CCL 27 Hs.225948 Chemokine, trafficking 5.34 6
C4BPB Hs.99886 Innate response 5.12 6
CCR 4 Hs.184926 Chemokine, trafficking 5.11 3
CCL 4 Hs.75703 Chemokine, trafficking 4.62 3
IL 17C Hs.110040 Chemokine, trafficking 4.25 14
IL 1β Hs.126256 Cytokine, proinflammatory 4.20 3
MRC 2 Hs.7835 Macrophage activation 3.20 7
CXCL 9 Hs.77367 Chemokine, trafficking 3.00 2
CCL 20 Hs.75498 Chemokine, trafficking 2.88 3
CXCL 3 Hs.89690 Chemokine, trafficking 2.79 13
CXCL 2 Hs.75765 Chemokine, trafficking 2.78 3
CD 14 Hs.75627 Macrophage activation 2.73 3
IL 8 Hs.624 Chemokine, trafficking 2.70 3
NFκβ1 Hs.83428 Macrophage activation 2.61 13
CCL 22 Hs.97203 Chemokine, trafficking 2.60 3
CCR 7 Hs.1652 Chemokine, trafficking 2.55 9
***Blood Coagulation Genes:***
SERPINA3 Hs.234726 Inflammation activation 9.39 3
SERPINI2 Hs.158308 Proteinase inhibitor 8.82 11
TBXAS 1 Hs.2001 Blood coagulation 7.70 8
FGB Hs.7645 Fibrin 6.75 4
SERPIND1 Hs.1478 Blood coagulation 6.69 14
SERPINI1 Hs.78589 Proteinase inhibitor 6.68 6
SERPINA7 Hs.76838 Proteinase inhibitor 6.60 7
GP1bα Hs.1472 Platelet aggregation 5.68 6
PROC Hs.2351 Blood coagulation 5.63 6
Factor 10 Hs.47913 Blood coagulation 4.66 6
Factor 2 Hs.76530 Blood coagulation 4.50 6
GP 9 Hs.1144 Platelet aggregation 4.02 6
Factor 3 Hs.62192 Blood coagulation 3.60 2
FGG Hs.75431 Fibrin 2.60 3
SEPPINE1 Hs.82085 Anti-Fibrinolysis 1.75 9
***Signaling Genes:***
UNC 13 Hs.155001 Apoptosis induction 11.19 4
CARD 4 Hs.19405 Apoptosis, caspase activator 10.68 14
TNFRSF17 Hs.2556 Apoptosis signaling 10.19 14
ARL 1 Hs.242894 Cell-cell signaling 8.66 2
LGALS 3 Hs.79339 Signaling, scavenger activity 7.65 6
FAT Hs.166994 Tumour suppressor 7.15 2
TNFSF9 Hs.1524 Apoptosis signaling 6.85 6
BBC3 Hs.87246 Apoptosis signaling 6.77 9
TNFRSF13β Hs.158341 Apoptosis signaling 6.49 6
DDX24 Hs.155986 Apoptosis signaling 6.11 6
TNFRSF11β Hs.81791 Apoptosis signaling 6.11 7
TNFRSF10β Hs.51233 Apoptosis signaling 6.09 6
BNIP2 Hs.155596 Apoptosis signaling 5.81 1
MGST 2 Hs.81874 Cell-cell signaling 5.50 6
CUL 4 Hs.183874 Tumour suppressor 5.35 6
BAF 53A Hs.274350 Cell-cell signaling 5.26 6
MAPK 1 Hs.324473 Apoptosis induction 5.11 14
CUL 2 Hs.82919 Tumour suppressor 5.09 6
P2RX 1 Hs.41735 Apoptosis, ion channel activity 4.43 6
TYROBP Hs.9963 Intracellular receptor signaling 2.51 13
CNIH Hs.201673 Intracellular signaling 2.13 9
ADRα1A Hs.52931 Cell-cell signaling 2.08 3
DAPK 1 Hs.153924 Apoptosis induction 2.01 9
***Defense-related Genes:***
TFF 1 Hs.350470 Defense response, maintenance 7.65 9
TFF 3 Hs.82961 Extracellular defense response 6.98 7
GAGE 1 Hs.128231 Cellular defense response 6.82 6
DEFβ3 Hs.283082 Extracellular defense response 6.01 5
RU 2 Hs.61345 Extracellular defense response 5.83 6
DEFα4 Hs.2582 Extracellular defense response 5.81 6
***Interferons-related Genes:***
IFNαR1 Hs.1513 JAK-STAT cascade, recptor 5.41 8
IRF 7 Hs.166120 Transcription regulation 5.05 6
IF 144 Hs.82316 Invasive growth response 2.69 5
IRF 6 Hs.11801 Transcription regulation 2.06 14
IL 18 Hs.83077 Angiogenesis 1.76 6
ISGF3γ Hs.1706 Regulatory 1.28 9
IRF 5 Hs.334450 Transcription regulation 1.23 9
IFNαR2 Hs.86958 Receptor activity 1.06 2
IFNγR1 Hs.180866 Receptor activity 0.80 5
IFNγ Hs.856 Growth regulation 0.53 4
IRF 3 Hs.75254 Transcription regulation 0.40 5
IRF 2 Hs.83795 Transcription regulation 0.32 4
IRF 1 Hs.80645 Transcription regulation 0.30 3
Order is arranged from the highest to lowest value based on the expression range (log~2~).
:::
|
PubMed Central
|
2024-06-05T03:55:47.924850
|
2004-9-9
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC518965/",
"journal": "BMC Infect Dis. 2004 Sep 9; 4:34",
"authors": [
{
"first": "Lisa FP",
"last": "Ng"
},
{
"first": "Martin L",
"last": "Hibberd"
},
{
"first": "Eng-Eong",
"last": "Ooi"
},
{
"first": "Kin-Fai",
"last": "Tang"
},
{
"first": "Soek-Ying",
"last": "Neo"
},
{
"first": "Jenny",
"last": "Tan"
},
{
"first": "Karuturi R",
"last": "Krishna Murthy"
},
{
"first": "Vinsensius B",
"last": "Vega"
},
{
"first": "Jer-Ming",
"last": "Chia"
},
{
"first": "Edison T",
"last": "Liu"
},
{
"first": "Ee-Chee",
"last": "Ren"
}
]
}
|
PMC518966
|
Background
==========
Research in genetics and genome sequencing has led to a better understanding of the molecular genetic mechanisms and to the detection of inter-individual genetic differences, so-called polymorphisms, which may have a functional consequence on the response to drugs. Pharmacogenetic tests provide information to better predict and prevent therapeutic failures and adverse drug reaction and raise the hope for an individualised pharmacotherapy \[[@B1]-[@B3]\]. Although pharmacogenetic research has moved into several branches of medicine such as cardiology \[[@B4]\], oncology \[[@B5]\] and respiratory medicine \[[@B6]\], the implementation of pharmacogenetic testing into clinical practice is still at the very beginning \[[@B7]\].
The ACE polymorphism identified in 1990 by Rigat and co-workers \[[@B8]\] is one of the best-researched polymorphisms. This polymorphism of the ACE gene is based on the presence or absence of a 287-bp element on intron 16 on chromosome 17. Rigat et al. have shown that the level of circulating ACE enzymes depends on the insertion/deletion (I/D) polymorphism. Since then it has been speculated that these differences in plasma ACE activity associated with the ACE genotype might affect the therapeutic response of ACE inhibitors explaining interindividual variability in cardiovascular or renal response to equivalent doses of ACE inhibitors \[[@B9]\]. Several studies have investigated the extent of this effect modification on response to ACE inhibitors for different indications such as hypertension \[[@B10]\], diabetic nephropathy \[[@B11],[@B12]\] and coronary artery disease \[[@B4],[@B13]\]. There are however inconsistencies in trial findings \[[@B14]-[@B16]\] and as a result the extent of effect modification of this polymorphism remains unclear.
Therefore, our objective is to systematically review all randomised controlled trials that assessed to what extent the insertion/deletion polymorphism of the angiotensin converting enzyme gene influences the effect and adverse events of angiotensin converting enzyme inhibitors on any surrogate and clinically relevant parameters in patients with cardiovascular disease, diabetes, renal transplantation and/or renal failure.
Methods
=======
Search strategy
---------------
We will perform literature searches in (Pre-) MEDLINE (DataStar version, Cary North Carolina), EMBASE (DataStar version, Cary North Carolina), Biosis (Ovid version \"Previews 1989 to 2003\", New York, New York), the Cochrane Controlled Trials Register (CCTR \<3rd Quarter 2003\>, Oxford, United Kingdom) and the Science citation index. A preliminary literature search in Medline has been carried out to estimate the range of relevant literature. Out of the citations of the pilot searches (172 citations) we identified articles that met our inclusion criteria. Keywords of these articles were used to refine our search strategies. In collaboration with an information specialist we designed the final search strategies for the six databases avoiding any language restrictions \[see [additional file 1](#S1){ref-type="supplementary-material"}: the search strategies\].
In addition, authors of trials identified in the literature search will be contacted for additional published or unpublished data. Particular efforts will be made to obtain unpublished data on genetic test information and effect measures stratified according to the genetic subtypes examined. We will send our requests and subsequent reminders for additional data to the first and last authors.
Other contacts will include the relevant collaborative review groups of the Cochrane Collaboration, pharmaceutical companies and manufacturers and researchers known to have published pharmacogenetic analyses in the area of cardiovascular disease, diabetes, renal transplantation and/or renal failure. Hand searching will be accomplished by reviewing the bibliographies of all included studies to identify additional relevant articles as well as by using the \"related articles\" function of PubMed and the citation index of ISI Web of Science.
Anticipating that subgroup analyses investigating gene polymorphisms may not be specifically mentioned in titles or abstracts, we will study the full text of all randomised placebo-controlled trials (RCT) that assessed the effectiveness of ACE inhibitors in order to identify subgroup analyses investigating gene polymorphisms.
Inclusion criteria
------------------
Two reviewers will independently assess all obtained titles and abstracts of the literature search for inclusion. The criteria to be used to identify relevant studies will be 1) randomised controlled trials 2) the investigation of an angiotensin converting enzyme inhibitor used for one of the clinical domains mentioned below and 3) the determination of the deletion/insertion polymorphism of patients.
The two reviewers will then examine the full texts of all potentially relevant citations. The decision on in- and exclusion will be based on the following, more explicit inclusion criteria.
### Clinical domains
We will include studies investigating ACE inhibitors in the four major clinical domains namely cardiovascular diseases, diabetes, renal transplantation and/or renal failure.
### Patients
Studies should include patients with the following indications for ACE inhibitor therapy: Heart failure, primary and secondary hypertension, coronary artery disease, diabetic nephropathy, primary nephropathy and status after renal transplantation.
### Intervention
All licensed or unlicensed ACE inhibitors identified through the literature search will be included.
We will prefer placebo as control intervention in order to study the effect modification. However to assess all available evidence, we will also include pragmatic trials where patients with active treatments (e.g. usual care with any antihypertensive medication) served as controls.
### Co-intervention
We are mainly interested in studies investigating a single drug exposure with ACE-inhibitors. However we will also include those studies, which allowed co-medications.
### Description of the pharmacogenetic test
Studies must include a description on how determination of the angiotensin converting enzymes genotypes (DD/ DI/ II) has been performed. If a study does not report details of testing but provides relevant results, authors will be contacted to obtain information of testing technique.
### Outcomes
We will secure data on any reported outcome, surrogate endpoints (e.g. decrease in blood pressure, changes in hemodynamic parameters, proteinuria, creatinine levels, microalbuminuria) and clinically relevant outcomes (e.g. total and disease specific mortality, morbidity (none fatal myocardial infarction, reinfarction, stroke, transient ischemic attack, rehospitalisation kidney failure or end-stage renal disease)).
The two reviewers will resolve any discrepancies about in- or exclusion by discussion. If agreement cannot be achieved, a third reviewer will make the decision.
Data extraction strategy
------------------------
We will use a pre-designed data extraction form that includes different items to assess the studies\' external validity \[see [additional file 2](#S2){ref-type="supplementary-material"}: Data extraction and quality assessment sheet\]. Details on study design, treatment, patients and pharmacogenetic tests as well as outcome parameters will be registered onto the data extraction form independently by two reviewers. Also, bibliographic details such as author, journal, year of publication and language, will be registered. This list will be pre-tested on a small sample of included and excluded studies addressing the appraisal topic. A third reviewer will resolve any discrepancies. The data extraction shows the extent of insufficient reporting and authors will be contacted to obtain missing information.
Quality assessment strategy
---------------------------
All trials included in the review will be assessed using a list of selected quality items indicating components of internal validity and descriptive information \[[@B17]\]. In principle these selected items will enable us to define any process at any stage of inference tending to produce results that differ systematically from the true values (bias) \[[@B18]\]. We will also assess additional methodological aspects that might bias the results of pharmacogenetic studies (e.g. blinding of laboratory assessor of outcomes, blinding of outcome assessor for genotypes, blinding of treatment provider for genotypes. See Data extraction and quality assessment sheet).
In addition, we will assess the description of the methods to determine genotypes. Angiotensin converting enzymes genotypes (DD/ DI/ II) are traditionally determined using polymerase chain reaction (PCR) amplification according to previously published protocols \[[@B19]\]. The D allele is preferentially amplified; therefore each sample found to have the DD genotype should be confirmed in a second independent PCR amplification by the use of an insertion specific primer to avoid the misclassification of the 4--5 percent of samples with DI genotypes as DD genotypes \[[@B19]\]. Beyond the use of the standard PCR with/without the second round of PCR using an insertion-specific primer, there is also a \"tri-primer\" method, which has been shown to be the proper method to be used in genotyping ACE I/D polymorphism \[[@B20]\]. The methodology of the ACE genotyping will be considered as an explanatory variable for heterogeneity between studies \[see [additional file 2](#S2){ref-type="supplementary-material"}: Data extraction and quality assessment sheet\].
We will pre-test these quality assessment items on a small sample of studies in duplicate and if necessary add missing descriptive items.
Two reviewers will independently score the internal and descriptive validity. The initial degree of discordance between the reviewers will be reported. Discordant scores based on obvious reading errors will be corrected. Discordant scores based on real differences in interpretation will be resolved through consensus. A third party will be sought if necessary. The reviewers will not be blinded for names of authors, institutions, journals or the outcomes of the studies.
These detailed quality assessment will be used to describe the methodological quality of selected studies, to explore potential sources of heterogeneity, to make informed decisions regarding suitability of meta-analysis and to weigh the strength of any conclusions.
Methods of analysis and synthesis
---------------------------------
### Description of data
The results of the data extraction and assessment of study validity will be presented in different structured tables and in a narrative description \[see [additional file 2](#S2){ref-type="supplementary-material"}: Data extraction and quality assessment sheet\]. This will allow us to display variation in patient characteristics, study quality and results. Thus, the description will include the details about the clinical domain in which the ACE inhibitors have been assessed, information about the study design and quality, a list reporting co-interventions during the study period, details about the study population (baseline characteristics, e.g. severity of disease, ethnic groups, environmental and social characteristics) and a description of the outcome measures that were applied.
Finally the tables will provide the individual study results (all reported outcomes) of the different genotypes in the intervention and control group. Continuous outcomes (e.g. blood pressure) will be summarised in the table as mean differences between baseline and follow up measures. For data of dichotomous outcomes (e.g. cardiovascular death) the relative risks between the results of the DD genotype and the II genotype will be calculated and described in the table. A relative risk of one indicates no difference between two genotypes, where as relative risks lower respectively higher than 1 indicates variations in the treatment effect.
### Heterogeneity assessment
The heterogeneity assessments help us to examine study characteristics that might be related to variability in the observed outcome. Within each subgroup potential sources of heterogeneity that may affect the imprecision in the estimate of treatment effect such as the study methodology, population characteristics, intensity of intervention, co-medications and risk factors will be examined. We will perform multiple linear regression analyses (meta-regression) to explore sources of between-study heterogeneity. The log transformed odds ratio for dichotomous outcomes (myocardial infarction) and continuous outcomes (blood pressure) measurements will be used as dependent variables and the clinical and methodological items of the extraction sheet as described above will be entered into the model as independent variables.
When a factor is strongly associated with the variation in ln odds ratio or on the continuous outcome, we will stratify the studies on that variable and inspect residual heterogeneity using forest plots.
If a meta-analysis seems appropriate, that is when the p-value of the chi-squared test for heterogeneity is greater than 0.10, a fixed effects model will be used for pooling. Within clinically and methodologically cogent subgroups relative risks for dichotomous outcomes and weighted mean differences for continuous outcomes will be calculated comparing the contrast between the intervention and the control group within genotypes. The results between the different genotypes will be presented in a forest plot as shown in Figure [1](#F1){ref-type="fig"} and differences will be statistically assessed.
The pooled results of a cogent subgroup will produce an estimate of the differences in the average effect of ACE inhibitors observed between ACE genotypes. Thus the treatment effect of each genotype could be compared to the overall effect of ACE inhibitors regardless of the genotype.
All statistical analyses will be performed using the Stata statistical software package (StataCorp. 2004. Stata^®^Statistical Software: Release 8.2 College Station, Texas, USA).
::: {#F1 .fig}
Figure 1
::: {.caption}
######
**Example of analysis using virtual data**. *Forest plot: For clinically and methodologically cogent subgroups weighted mean differences (95% confidence interval) for reduction of systolic blood pressure in patients with hypertension have been assessed. This graph displays differences of the ACE inhibitor effect within genotypes. The diamonds below each of the three genotypes indicate the pooled results. The lowest (forth) diamond reflects the overall effect of ACE inhibitors across all genotypes. In this example, the DD genotype shows the largest ACE inhibitor effect and the II genotype shows the smallest effect. The size of the box is related to the number of studied patients.*
:::
:::
Discussion
==========
This review shows an efficient approach to quantify the effect modification of the ACE polymorphism on ACE inhibitors when applied in different clinical occasions. We aim to resolve part of the controversy in the literature by quantifying the influence of the three genotypes (DD/DI/II) on different outcomes and in the light of study methodology and participants characteristics. These results should inform clinicians about the potential of pharmacogenetic testing to individualise ACE inhibitor treatment.
Competing interests
===================
None declared.
Authors\' contributions
=======================
LMB, JS and MS initiated the project. MS wrote the first draft of the protocol. MP, JS and LMB critically reviewed and revised the manuscript. All authors approved the manuscript.
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1471-2350/5/23/prepub>
Supplementary Material
======================
::: {.caption}
###### Additional File 1
Search strategies: Search terms and number of citations listed for five electronic databases
:::
::: {.caption}
######
Click here for file
:::
::: {.caption}
###### Additional File 2
Data extraction and quality assessment sheet: Example of data extraction and quality assessment for the study of Hernandez \[21\]
:::
::: {.caption}
######
Click here for file
:::
Acknowledgment
==============
We would like to thank Dr. Pius Estermann, information specialist at the University Hospital of Zurich, for carrying out the literature searches and Dr. Peter Jacobsen, from the Steno Diabetes Center in Gentofte (Denmark), for his feedback on an earlier draft.
|
PubMed Central
|
2024-06-05T03:55:47.928652
|
2004-9-10
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC518966/",
"journal": "BMC Med Genet. 2004 Sep 10; 5:23",
"authors": [
{
"first": "M",
"last": "Scharplatz"
},
{
"first": "MA",
"last": "Puhan"
},
{
"first": "J",
"last": "Steurer"
},
{
"first": "LM",
"last": "Bachmann"
}
]
}
|
PMC518967
|
Background
==========
Myasthenia Gravis (MG) is the mostly known autoimmune disease in human, mediated by autoantibodies against the nicotinic receptor of acetylcholine in neuromuscular junctions \[[@B1]\]. Two cardinal features of this disease are muscle weakness and fatigability. Although periorbital area contains the only affected muscles in some patients, generalized weakness develops in approximately 85% of patients, affecting bulbar and limb muscles as well as the neck extensors and the diaphragm.
Myasthenic crisis refers to a rapid deterioration in neuromuscular function with respiratory compromise due to ventilatory muscle insufficiency or weakness of upper airway musculature or both \[[@B1]\]. These attacks might be triggered by multiple factors, including infections, physical or emotional stresses, aspiration, electrolyte disturbances, changes in medications and inadvertent administration of non-depolarizing muscle relaxants or other drugs. In this state, respiratory function should be monitored closely for evidence of respiratory failure and ventilatory support should be initiated in the setting of emerging respiratory failure \[[@B2],[@B3]\].
In general, four methods of treatment are currently in use \[[@B4]\]: anticholinesterase agents, immunosuppressives, surgical thymectomy, and short-term immunotherapies, including plasma exchange and intravenous immune globulin (IVIG). Since the first operation for MG in 1911 \[[@B5]\], thymectomy has become an increasingly accepted procedure for treatment of MG, as it can help to achieve complete clinical remission rate between 18% and 50% \[[@B6]-[@B9]\] and clinical improvement in majority of patients \[[@B10]\]. The rationale for thymectomy is that about 75% of MG patients have thymic abnormalities; of these, 85% have hyperplasia and 15% have thymoma \[[@B11]\].
Although there is no convincing evidence regarding the use of thymectomy in non-thymomatous MG patients \[[@B12],[@B13]\], most authorities recommend this procedure in all patients of ages between puberty and 60\'s \[[@B14],[@B15]\]. However, this is not a general idea.
Thymectomy effects on occurrence and intensity of respiratory crisis have not been studied yet. Concerning value of this life-threatening event in MG patients, we studied the role of thymectomy on long-term frequency and severity of these attacks.
Methods
=======
We reviewed the clinical records from 272 myasthenic patients diagnosed and treated in the neurology clinic of Shariati Hospital, Tehran, during 1985 to 2002. All included patients had positive history and physical examination, confirmed with positive Tensilon test and electromyography (with repetitive nerve stimulation test). Searching for thymomas, all patients had a chest computed tomography (CT) scan.
The following patients were excluded from the study: 3 patients with doubtful test results and unconfirmed diagnosis; 25 patients with ocular form of MG (as these patients have no presentation of crisis); 2 patients with thymoma (and two episodes of crisis in the previous year), but contraindicated for surgery because of coronary artery disease; 6 patients with thyroid function abnormalities (because of their known effects on induction and reduction of myasthenic crises); 2 patients with concomitant rheumatoid arthritis (and consumption of high doses of corticosteroids and immunosuppressives); and 15 patients lost from follow-up with incomplete data. 219 MG patients enrolled in the study.
Myasthenic crisis was defined as an attack that compels physicians to hospitalize the patient and carefully supervise patient\'s respiratory capacity \[[@B3]\]. In most of these conditions, ventilatory support was needed. However, sometimes patient could be managed without intubation as a result of spontaneous improvement or use of plasmapheresis or IVIG.
All included patients were eligible for surgery. Patients with CT confirmed thymoma underwent elective thymectomy as soon as possible. In the first visit after diagnosis confirmation in non-thymomatous patients, the advantages and drawbacks of operation (including risks of anesthesia in MG patients) had been explained to them and deciding between the two choices of thymectomy or conservative therapy had been left to the agreement between physicians and patients. No particular protocol had been established for these patients and physicians had only a consultant role for patients with no force on them.
For clinical assessment of the initial severity of the disease, the classification of Osserman \[[@B16]\] had been applied to all patients in the first visit and inserted into patient\'s clinical profile. In following visits, patients\' condition has been referred to this initial assessment. Data were collected on demographic factors, disease course at the first year of onset (or the year before surgery in thymectomized patients), time of surgery, pathology report, number of myasthenic crises (post-op in thymectomized patients), precipitating factors for attacks, ICU admission and the need for respiratory support, plasmapheresis or IVIG in each attack. 12 patients in thymectomy group had history of myasthenic crisis before surgery that were not considered.
The participants\' baseline characteristics and follow-up data were analyzed by Student\'s *t*test and analysis of variances (ANOVA) as parametric tests, Mann-Whitney *U*test as non-parametric test, and Pearson\'s chi-square test for qualitative differences (SPSS software, version 10.0). *P*values less than 0.05 were taken to indicate statistical significance. Continuous variables are shown as the mean ± standard deviation (SD) and non-parametric variables with their median and range. Odds ratios and relative risks with 95% confidence intervals (95% CI) were calculated to assess the proportional risk of crisis between two groups.
In the subgroup of patients without thymoma, multivariate logistic regression analysis was used to assess the relationship between frequency of myasthenic crisis and several risk factors such as sex, start age of the disease, Osserman score and thymectomy. According to its percentile, start age was divided into three categories as bottom one-third (under percentile 33), middle one-third (between percentiles 34 and 66), and top one-third (over percentile 67).
Results
=======
110 patients underwent thymectomy (76 by trans-sternal and 34 by trans-cervical approaches) and 109 patients were on conservative therapy. Baseline characteristics and follow-up periods are shown in Table [1](#T1){ref-type="table"}. Time interval between onset of myasthenic symptoms and thymectomy ranged from 1 to 192 months with median of 12. Mean age at thymectomy was 30.3 ± 12.8 years. During follow-up period, each patient had about 13 visits on average.
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Characteristics of thymectomized patients just before thymectomy and non-thymectomized patients at the first year of the diagnosis
:::
***Thymectomized patients (n = 110)*** ***Non-thymectomized patients (n = 109)*** ***P value***
-------------------------- ---------------------------------------- -------------------------------------------- ---------------
Age at diagnosis (years) 29.2 ± 13.7 33.0 ± 15.9 0.059
Gender (male/female) 41/69 53/56 0.089
Osserman Score\* = I 0 0
Osserman Score = IIa 46 48
Osserman Score = IIb 37 50
Osserman Score = III 25 11
Osserman Score = IV 2 0
Follow up period (years) 6.4 ± 4.3 7.9 ± 5.6 0.134
\* Mann-Whitney U test showed no significant difference between two groups (Z = \|1.421\| & P = 0.155)
:::
Totally, 62 patients in both groups experienced 89 attacks of respiratory failure during their follow-up, which accounts for 28.3% of the study population. As it is shown in Table [2](#T2){ref-type="table"}, 18.2% of thymectomized patients (20 of 110) and 38.5% of non-thymectomized patients (42 of 109) had history of these attacks. The difference between two groups was significant in this regard. Additionally, Odds ratio for being affected twice or more among patients on conservative therapy was 4.2 (with 95% CI of 1.1 to 16.7). Three patients in thymectomy group had history of crisis during post-op period in the hospital. Main triggering factors for myasthenic crises were lack of compliance to the drugs, pneumonia, and unknown causes Table [3](#T3){ref-type="table"}.
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
relation between myasthenic crisis frequency and thymectomy
:::
***Thymectomized patients (n = 110)*** ***Non-thymectomized patients (n = 109)*** ***P value***
------------------------------------------ ---------------------------------------- -------------------------------------------- ---------------
Patients with myasthenic crisis (n = 62) 20 42\* 0.001
Episodes of myasthenic crisis (n = 89) 25 64^†^ 0.016
\* This group had more probability of having crisis with an odds ratio of 2.8 (with 95% confidence interval of 1.5 to 5.2)
^†^Myasthenic crises were more prevalent in this group with a relative risk of 2.6 (with 95% confidence interval of 1.8 to 3.8)
:::
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Characteristics of patients with myasthenic crisis in thymectomized and non-thymectomized patients\*
:::
***Thymectomized patients (n = 20)*** ***Non-thymectomized patients (n = 42)***
----------------------------- --------------------------------------- -------------------------------------------
Age at diagnosis (years) 31.4 ± 10.6 30.5 ± 12.7
Age at first crisis (years) 33.5 ± 11.2 34.1 ± 11.3
Gender (male/female) 6/14 20/22
Triggering factors
Pneumonia 3 (15%) 13 (30%)
Other infections 2 (10%) 4 (10%)
Aspiration 2 (10%) 3 (7%)
Stresses^†^ 1 (5%) 2 (5%)
Drug intolerance 8 (40%) 10 (24%)
No obvious cause 4 (20%) 10 (24%)
\* *There were no statistical differences between two groups*
† Refers to physical and emotional stresses as well as menstruation
:::
To assess the severity of each attack, we considered duration of ICU admission (days), need to respiratory support and need to plasmapheresis or IVIG during crisis as indicating variables. As it is shown in Table [4](#T4){ref-type="table"} myasthenic crises were almost more severe in patients under conservative therapy. Two patients (both on conservative therapy) had passed away during respiratory failure (mortality rate = 2/89 = 2.2%) and these conditions were so protracted in some of patients that they were confined to ICU beds for more than one month.
::: {#T4 .table-wrap}
Table 4
::: {.caption}
######
Severity parameters for each attack in patients with myasthenic crisis
:::
***Thymectomized patients (n = 25)*** ***Non-thymectomized patients (n = 64)*** ***P value\****
-------------------------------- --------------------------------------- ------------------------------------------- -----------------
Median Days in ICU (Range) 7(2--38) 12(2--55) 0.044
Need to Ventilatory support 19 (76%) 59 (92%) 0.037
Need to Plasmapheresis or IVIG 7 (28%) 23 (36%) 0.476
\* P values from chi-square test for assessment of difference between two groups
:::
Pathology reports in thymectomized patients revealed 16 cases of thymoma. Fifty percent of these patients (8 of 16) had experienced crisis, which accounts for 40% (8 of 20) of thymectomized patients with history of crisis. Mann-Whitney *U*test revealed significant difference in this regard (P \< 0.001). Severity indexes did not differ significantly between thymomatous and non-thymomatous patients Table [5](#T5){ref-type="table"}.
::: {#T5 .table-wrap}
Table 5
::: {.caption}
######
Characteristics of thymectomized patients with respect to pathology of thymus
:::
***Thymus Pathology*** ***N (% of 110)*** ***Age at diagnosis\* (years)*** ***Sex (m/f)*** ***Patients with Myasthenic crisis (%)*** ***Number of Myasthenic crisis*** ***Days in ICU (Median & Range)*** ***Ventilatory support***
------------------------ -------------------- ---------------------------------- ----------------- ------------------------------------------- ----------------------------------- ------------------------------------ ---------------------------
***Normal*** 51 (46.4%) 29.7 ± 13.9 18/33 3 (5.9%) 3 3 & 2--4 3
***Hyperplasia*** 43 (39.1%) 27.4 ± 15.2 14/29 9 (20.9%) 10 7 & 2--30 7
***Thymoma*** 16 (14.5%) 37.3 ± 8.9 9/7 8 (50.0%) 12 9 & 3--38 9
\* Analysis of variances indicated that age at diagnosis in thymomatous patients was significantly higher than others (P = 0.007). There was no statistically significant difference regarding other variables.
:::
Totally, there were 203 patients without thymoma. Regression analysis in this subgroup of patients revealed that group of non-thymectomized patients as well as two third of patients with higher ages at the beginning of the disease were more prone to respiratory attacks Table [6](#T6){ref-type="table"}.
::: {#T6 .table-wrap}
Table 6
::: {.caption}
######
logistic regression model for predictors of myasthenic crisis among patients without thymoma (n = 203).
:::
***Predictors*** ***Odds Ratio*** ***Lower 95% CI*** ***Upper 95% CI*** ***P value***
---------------------------------------------------- ------------------ -------------------- -------------------- ---------------
Start age (years) 1.016 0.996 1.038 0.085
Sex (male) 0.926 0.482 1.778 0.612
Thymectomy (performed) 0.234 0.113 0.484 \<0.001
Osserman classification (score III) 1.269 0.410 3.928 0.529
Start age category (one third of younger patients) 0.272 0.097 0.759 0.021
:::
Discussion
==========
Persuasive evidence for thymectomy in non-thymomatous generalized myasthenic patients is not on hand. In an attempt to establish standards in this regard, American Academy of Neurology advised thymectomy as only an *option*to increase the probability of remission or improvement in these patients \[[@B13]\]. In this review, thymectomy was associated with a median relative rate of medication free remission of 2.1 and a relative rate of improvement of 1.7. However, these improvements were significant in only a small number of the studies reviewed and the majority did not show a significant benefit with thymectomy. In addition, none of the studies was randomized or used blinded outcome assessments, and in most thymectomy was performed in younger patients.
Surprisingly, none of these studies has considered myasthenic crisis frequency as their study endpoint. For instance, in the study of Cohen *et al.*in 1981, 15 of 28 thymectomized patients experienced 21 crises during follow-up period \[[@B17]\]. In another study, 13 of 27 patients with crisis had previous thymectomy, six with thymoma \[[@B18]\]. This study was the first one that sought thymectomy impact on occurrence of crisis.
In our experience, persistence on thymectomy for all myasthenic patients would not be so wisely. Response to thymectomy is highly variable among these patients. Method of gaining agreement between physicians and patients would bring some benefits. As it is shown in Table [3](#T3){ref-type="table"}, rate of intolerance to drugs was lower among the patients who preferred medical therapy. However, it is notable that there is a general tendency among both physicians and patients towards operation in younger ages and in patients with more severe course. In this study, thymectomized patients were about 4 years younger on average and had higher Osserman scores at the beginning (Table [1](#T1){ref-type="table"}); but the difference was not statistically significant because of large study population and dispersion of baseline characteristics.
When myasthenic crisis occurrence is considered as the main endpoint of treatment in myasthenic patients, thymectomy has a great impact. Patients on conservative therapy had risk of about 3-fold of thymectomized patients to encounter respiratory attacks. However, the overall frequency of myasthenic crisis among our study population could be considered more than similar reports \[[@B2],[@B4]\], perhaps reflecting some unidentified racial differences or lower compliance of Iranian patients to continuous medications.
Some previous studies have shown the benefit of thymectomy in the control of symptoms of MG. It has been revealed that delay in surgery could worsen the prognosis of MG \[[@B19]\] and the chance of benefiting from thymectomy increases when the history of MG is short and the stage of the disease is early \[[@B20]\]. Concerning differences of thymectomy effects in thymomatous and non-thymomatous patients, several studies have been conducted previously, showing some discrepancies in the results \[[@B21]-[@B23]\]. According to this study, thymomatous patients are more prone to respiratory attacks compared with all other MG patients. However, their attacks are not drastically different in severity of complications.
During myasthenic crisis, Weakness of the respiratory muscles may be out of proportion to that of other skeletal muscles. In rare cases, ventilatory failure is the only clinically apparent manifestation of the disease \[[@B24],[@B25]\]. In addition, sometimes prediction of incoming attack is very difficult. In the present study, a 27-year-old woman experienced an attack after 7 months of complete remission on no drug.
Generally, infection is the most common trigger for myasthenic crisis \[[@B1]\]. Higher rate of infection in non-thymectomized patients in this study could be logically due to higher amounts of immunosuppressives in the medication regimen of these patients that we could not evaluate in this study. However, concerning frequency of myasthenic crises, this reduction of immunosuppressives in the regimen of thymectomized patients could be interpreted as an important benefit of thymectomy in MG patients.
The main limitation of this study was its retrospective design and the lack of randomization. Apparently, within a period of 17 years, many changes have occurred to diagnostic and therapeutic facilities as well as knowledge and attitude of physicians. These changes could have significant consequences on the outcome of myasthenic patients. Although various operative approaches seem not to differ drastically \[[@B26]\], various types of immunosuppressives and dosage of them have important role in the prognosis of patients, which we did not assess them in this study. We also could not gather information about acetylcholine receptor antibodies, which play an important role in the pathophysiology of MG. Further studies concerning the role of these antibodies in the occurrence and severity of myasthenic crises are required.
Conclusions
===========
In conclusion, we suggest evaluation of various aspects of myasthenic crisis as an important endpoint in long-term assessment of generalized MG patients. Moreover, we showed that thymectomy has a preventive role on rate and severity of myasthenic attacks in age and disease severity matched groups of patients. However, this effect needs further evaluation in upcoming prospective studies.
Competing interests
===================
None declared.
Authors\' contributions
=======================
In advance, suggestion of the design of the study was from our professor AkS. Data extraction and initial analysis were done by AlS and HT. SA participated in the design and implementation of the study. AM performed additional analyses and wrote the first draft of the paper. MS and SA both had helpful and valuable comments in revising the paper. All authors read and approved the final manuscript.
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1471-2377/4/12/prepub>
Acknowledgements
================
We should thank our colleague Doctor J. Makarem for his grateful supports in the analysis of the data.
|
PubMed Central
|
2024-06-05T03:55:47.929907
|
2004-9-11
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC518967/",
"journal": "BMC Neurol. 2004 Sep 11; 4:12",
"authors": [
{
"first": "Ali",
"last": "Soleimani"
},
{
"first": "Alireza",
"last": "Moayyeri"
},
{
"first": "Shahin",
"last": "Akhondzadeh"
},
{
"first": "Mohsen",
"last": "Sadatsafavi"
},
{
"first": "Hamidreza Tavakoli",
"last": "Shalmani"
},
{
"first": "Akbar",
"last": "Soltanzadeh"
}
]
}
|
PMC518968
|
Background
==========
Cutaneous malignant melanoma is responsible for 1% of all malignant tumors with a rising incidence in the Caucasian population \[[@B1]\]. Initial diagnosis is based on asymmetry, border regularity, multiple colours, diameter as well as elevation of the pigmented lesion. However, it is sometimes difficult to differentiate between irregular dysplastic nevi and a melanoma without histological analysis. Hitherto risk groups for the development of melanoma are characterized by fair skin, multiple and/or dysplastic nevi and the history of sunburns in childhood \[[@B2]\]. Invasive melanomas have a rapid tendency to metastasize. In these stages of disease, therapy is very difficult and the 5-year survival rate of stage IV patients is below 20% \[[@B3]\].
On the molecular level, melanoma is associated with several genetic changes, including mutations or transcriptional variations in tumor suppressors like p53, CDKN2A/p16, CDKN1A/p21 or in oncogenes like N-Ras \[[@B4]\]. Recently, it has been discovered by Davies et al. that 66% of melanoma have a mutated BRAF gene which results in higher kinase activity due to a single amino acid exchange (B-Raf V599E) occurring in almost 90% of the mutations \[[@B5]\]. Most interestingly, this mutation is somatic \[[@B6],[@B7]\] and some authors describe the presence of the mutation already in benign nevi \[[@B8]\], whereas others fail to reproduce the high frequencies in early stages and speculate of mutated B-Raf being relevant for progression rather than initiation of melanoma \[[@B9]\]. Nevertheless, the high incidence of the mutations in melanoma qualify the B-Raf protein as a potential target for tumor therapy and preliminary results of phase II clinical trials with Raf kinase inhibitors suggest protective activity \[[@B10]\].
Promising results with new approaches for melanoma therapy have been obtained with active immunizations against tumor associated antigens (TAA) like MAGE-3 \[[@B11]\], MART-1 \[[@B12]-[@B14]\] tyrosinase \[[@B15]\] or survivin \[[@B16]\]. Regarding the high incidence of B-Raf mutations and the increased expression level in tumors, B-Raf should be an attractive target for immunotherapy \[[@B17]\] and most recently, independent findings demonstrated mutation specific CD4^+^T-cell responses in melanoma patients \[[@B18]\]. Moreover, we have recently demonstrated CD8^+^T-cells in melanoma patients reactive against an HLA B27 restricted B-Raf V599E epitope encompassing the mutation identified using computer assisted algorithms \[[@B19]\]. However, assessing CD4^+^or CD8^+^T-cell responses is not suitable for screening larger numbers of patients to estimate responder frequencies.
To determine the frequency of B-Raf specific responses in melanoma patients and to evaluate whether B-Raf specific immune responses could serve as a melanoma marker we examined the Raf specific humoral response using an ELISA assay with purified recombinant B-Raf, B-Raf V599E or C-Raf protein.
Methods
=======
Participants
------------
Patient sera were obtained from frozen stocks and were collected over a period of 5 years. All patients gave informed consent to use their sera for scientific analysis. Control sera were obtained from patients of the dermatology department without signs of melanoma. Control patients were fully anonymized and no further information is available.
Antigens for ELISA
------------------
Recombinant wild type B-Raf, B-Raf V599E and C-Raf proteins were expressed in Sf9 cells and purified as GST fusions (B-Raf V599E, C-Raf) or His-tagged proteins (B-Raf) as described \[[@B20]\]. Purity of the Raf kinase preparations was controlled by SDS-polyacrylamide gel electrophoresis and staining with Coomassie Blue.
ELISA
-----
372 sera of melanoma patients were analyzed for B-Raf V599E specific response, 271 sera were analyzed for B-Raf wt and C-Raf specific responses and 119 sera of non melanoma control patients of the dermatology department were used and analyzed for B-Raf V599E, B-Raf wt and C-Raf specific responses. For determination of serum levels of total Ig or IgG, an ELISA assay was developed. 1 μg/ml of purified B-Raf, B-Raf V599E or C-Raf protein in 100 μl coating-buffer or buffer alone as background control (carbonate buffer, pH 9,6) was coated on NUNC 96-Well MaxiSorp plates at 4°C overnight. Plates were washed twice with washing buffer (0,05% Tween (Sigma) in PBS) and blocked with 1% BSA (Sigma) in PBS. After washing twice, serial dilutions of human sera, starting at 1:100, in 100 μl conjugate buffer (1% BSA, 0,05% Tween in PBS) were incubated for 1.5 hours at 37°C. After four wash steps, alkaline phosphatase coupled goat anti human Ig (IgM + IgA + IgG, Dianova) or goat anti human IgG (Dianova) diluted 1:2000 in 100 μl conjugate buffer was added. After 1 h at 37°C and two washing steps, 50 μl of pNPP (Sigma) substrate in buffer was added. The reaction was incubated at room temperature and stopped after 20 min by 50 μl 1 M NaOH. Optical density was read at a wavelength of 405 nm (OD~405~) in a TECAN Spectra Thermo microplate reader.
For determination of specificity, a similar protocol was used, but plates were coated with different concentrations of antigen (0, 0.1, 1.0 and 2.0 μg/ml antigen in coating buffer). Each concentration was determined in duplicate. In addition, specificity was further confirmed using an unrelated antigen, prostate specific antigen (PSA, Sigma), at concentrations of 1 μg/ml for ELISA analysis. Two patients exhibited non-specific serum responses and were excluded from further analysis.
For competition ELISA performed with some positive sera, a similar protocol was engaged, using a fixed dilution of the sera and B-Raf or B-Raf V599E antigen for coating. Competition was performed by adding different concentrations of B-Raf or B-Raf V599E (0.0, 0.1, 1 or 2 μg/ml) to the human sera at the corresponding incubation step.
Data analysis
-------------
For the analysis of the ELISA data, the titer of the sera was defined as the last serial dilution with an OD~405~value exceeding the Cut Off 0.275, corresponding to the mean + 1.5 SD of the background values of positive sera at serum dilutions of 1:50. Raf specific titers were compared to the background values using a two tailed Mann-Whitney U test with a 95% confidence interval. The amount of positive sera within the two groups were defined as sera exceeding a given titer; the final definition of positive sera were sera with titers of 1:300 or higher. Frequencies of positive sera were compared using two sided Fisher\'s exact test with 95% confidence interval.
Results and discussion
======================
372 sera of 148 melanoma patients and sera of 119 control patients were screened for Raf specific antibody responses by an ELISA assay using a secondary antibody directed against IgG, IgA and IgM. Serial dilutions of the sera were analysed for their OD~405~and titers were attributed as described using a cut off OD~405~of 0.275 (fig. [1A](#F1){ref-type="fig"} and [1B](#F1){ref-type="fig"}). Positive sera reacted against B-Raf or B-Raf V599E, but not against an unrelated antigen (fig. [1A](#F1){ref-type="fig"}). Specificity was further confirmed by coating the ELISA plate using different concentration of the antigen (fig. [1C](#F1){ref-type="fig"}) and WESTERN Blot analysis (additional figure 1 \[see [additional file 1](#S1){ref-type="supplementary-material"}\]). In some positive sera analysed for IgG antibodies, very weak B-Raf specific titers could be detected (fig. [1D](#F1){ref-type="fig"}), but most sera were negative for specific IgG antibodies (data not shown). Some positive sera were additionally tested for specificity for the mutated epitope using a competition ELISA by coating B-Raf or B-Raf V599E and competing Raf specific human antibodies by titrating in unbound B-Raf or B-Raf V599E (fig. [2A,2B,2C](#F2){ref-type="fig"}). In all cases tested, competition was achieved in every combination at corresponding antigen concentrations, whereas a control serum with non-specific reactivity (fig. [2D](#F2){ref-type="fig"}) showed no competition as expected. Taken together these results demonstrate the presence of Raf specific antibodies. In most cases, titers against B-Raf and B-Raf V599E were consistently higher compared to titers for C-Raf (fig. [1B](#F1){ref-type="fig"}); only some weakly positive sera showed a response dominated by C-Raf antibodies and in a minority of positive sera the specific response was equilibrated. Even though antigen preparations were not checked for biological activity and correct refolding and therefore a direct comparison between C-Raf and B-Raf specific antibody levels based on these assays is difficult, the data suggest that the Raf specific antibody response in patients is mainly directed against B-Raf. The moderate cross reactivity against C-Raf but not against an unrelated antigen might be explained by the high conformational and sequence similarity between Raf family members. In contrast, the differences observed between the reactivity against B-Raf or B-Raf V599E are weak (fig. [1B](#F1){ref-type="fig"}) and suggest that B-Raf and B-Raf V599E are recognized to a similar extend. This notion is further strengthened by the results of the competition ELISA which failed to detect any differences in the pattern of competition for a given serum regardless of the antigen combination used (figure [2](#F2){ref-type="fig"}). Therefore we conclude that the antibodies can not discriminate between the naïve or the mutated form of B-Raf.
Comparison between Raf specific antibody responses in sera from melanoma patients and control patients reveals apparent differences (figure [3](#F3){ref-type="fig"}). Raf specific responses are significantly different from background values for melanoma patients and all Raf variants tested (two tailed Mann-Whitney U test). In contrast, the difference observed within the control group is not significant (Mann-Whitney U test). However, reactivity against C-Raf is rather weak in all sera tested and only 5 of 271 tested sera from melanoma patients reach C-Raf specific titers of 1:300. A comparison between the percentage of patients with B-Raf specific antibody levels above a given titer reveals that sera derived from melanoma patients show consistently higher values compared to the control group (fig. [4A](#F4){ref-type="fig"}). In contrast, the frequency of C-Raf specific responses are only marginally higher in the melanoma population and not detectable at titers above 1:300. If positive response is defined as sera with titers of 1:300 or higher, 2.5% of the control group is positive for B-Raf and 1.68% for B-Raf V599E antibodies (fig. [4B](#F4){ref-type="fig"}). However, 5.41% (P = 0.12, Fisher\'s exact test) and 8.86% (P = 0.028, Fisher\'s exact test) of sera derived from melanoma patients were positive for B-Raf V599E and B-Raf respectively (fig. [4B](#F4){ref-type="fig"}). Using this cut off, no control patients could be identified with C-Raf specific antibodies, and only 1.85% (P = 0.329, Fisher\'s exact test) of the melanoma patients had detectable C-Raf specific antibodies (fig. [4B](#F4){ref-type="fig"}). These results suggest that melanoma is associated with higher rates of patients with detectable B-Raf specific antibody responses. The difference between the values obtained for B-Raf V599E and B-Raf specific antibodies, which is expressed in lower scores for B-Raf V599E, is most probably due to differences in the antigen preparation and is less likely due to different specificity as in most cases the scores against B-Raf V599E are in the same range as the scores against B-Raf (see figure [1B](#F1){ref-type="fig"}), whereas the C-Raf response consistently shows much lower titers in positive cases and a different shape of the curve (figure [1B](#F1){ref-type="fig"}). Taken together, these data strongly suggest that 8.9% of melanoma patients have a B-Raf specific antibody response and 2.5% of the control patients. At this stage, it is far too early to foresee the consequences of this finding for diagnostics or therapy of melanoma. All melanoma patients were in a very advanced, rapidly progressing stage with high tumor loads (stage IV) and consequently the presence of antibodies was not correlated with survival (data not shown). However, at least some patients had low but detectable levels of B-Raf specific IgG antibodies which is in line with the independent finding of B-Raf V599E specific T-cells in melanoma patients \[[@B18]\].
Another interesting point to note is the small, although not significant, number of control patients with detectable levels of Raf specific antibodies. At least two out of 119 control patients showed a very strong B-Raf specific response in the same range as we have observed for positive melanoma patients (figure [3](#F3){ref-type="fig"}). Due to the design of the study, no information is available for this patient group. Serum was sampled during diagnostic procedures, therefore other underlying diseases as a cause for Raf specific antibodies cannot be excluded, including autoimmune diseases or neoplastic diseases of different origin. Furthermore, as the control group has been sampled in the dermatology department, this group might contain patients with high numbers or irregular melanocytic nevi or even unrecognised melanoma.
For different extracellular tumor antigens, including gangliosides, in melanoma, positive associations between the induction of IgM and IgG antibodies and survival time have been reported \[[@B21]\] and the protective effect was attributed to antibody dependent cellular toxicity \[[@B22]\]. Therefore, the induction of Raf antibodies might be a favourable goal for the design of melanoma vaccines. However it is questionable whether humoral responses against an intracellular antigen like Raf will have an effect. In this respect it is interesting to ask why responses against intracellular antigens like Raf or survivin \[[@B23]\] can be observed at all. The most straightforward explanation, which is particularly likely for advanced stage IV melanoma patients, relies on the fact that the partial necrosis of big tumor masses allows the crosspresentation of intracellular proteins. The longitudinal analysis of our patients, e.g. the one depicted in figure [1](#F1){ref-type="fig"}, illustrates, that the occurrence of humoral immune responses was correlated rather to tumor burden than therapeutic measures, since the conversion occurred during the period when no therapy was applied.
As oncogenic mutation of B-Raf and even transformation by other oncogenic events is frequently accompanied by Raf overexpression, the induction of an antibody response is not necessarily due to the presence of the mutation. Even though a polyclonal IgM response is very unlikely to be specific for a point mutation, this notion would explain the lack of specificity for the mutational epitope. However, it is also possible that a cellular immune response prior to the induction of Raf specific antibodies has occurred. Such a T-cell response directed against Raf or other tumor antigens, would also result in the lysis of tumor cells and the liberation of intracellular antigens. It is important to mention that the lysis leading to the formation of antibodies against intracellular antigens can be caused by T-cells other than the already observed B-Raf V599E specific CD4^+^or CD8^+^T-cells. This question still remains to be clarified as up to now only advanced stage patients have been examined. It is obvious that at this stage the occurrence of antibodies is not correlated with prognosis and that it is very unlikely that the antibody response itself will have an influence on the disease. However, as it is rather unlikely that the frequency of a B-Raf specific T-cell response exceeds the frequency of antigen responses, our data can help to set the upper limit for the expected frequency of B-Raf or B-Raf V599E specific T-cells as 8.5% which allows the rational design of search strategies especially for Raf specific CD8^+^T-cells.
Even though the detection of B-Raf specific humoral and T-cell responses suggest that B-Raf/B-Raf V599E is immunogenic and that a response could be induced in at least a part of the patients, this notion does not allow conclusions on its suitability as a target for immunotherapy per se. In theory, an optimal tumor antigen is exclusively expressed in the tumor tissue and essential for tumor cell growth and survival to avoid the emergence of escape mutants or antigenic loss, whereas the immunological attack of the tumor cell is independent of the function of the antigen \[[@B17]\]. To date, many TAA used for the immunotherapy of melanoma including MAGE \[[@B24]\] or tyrosinase provide no obvious advantage to the tumor cell and therefore there is no pressure to retain the antigen. In contrast, mutated B-Raf has a high prevalence in melanoma and the consequences of its activation, including induction of proliferation and block of apoptosis are well known. However, it is still a matter of debate whether B-Raf activity mainly drives melanoma initiation or whether its function is also relevant for later stages. The first conclusion is supported by studies demonstrating that the mutations already occur in melanocytic nevi at frequencies comparable to late stage melanoma \[[@B8]\], are not correlated with clinical outcome \[[@B25]\] and finally the Raf inhibitor Bay 43-9006 seems to have only moderate efficiency in advanced melanoma as reported by Ahmed et al. during the ASCO meeting 2004 \[[@B26]\]. However, other studies correlated B-Raf mutations with progression rather then initiation \[[@B9]\] and we and others suggested a role for B-Raf as a negative prognostic factor in metastatic melanoma \[[@B25],[@B27]\]. Despite these conflicting data on the clinical relevance of mutated B-Raf at late stages, the high prevalence would already justify to evaluate B-Raf/B-Raf V599E as a target for immunotherapy, as this prevalence is in the same range as for the TAA currently used without any evident advantage for tumor cell growth.
Conclusions
===========
Taken together we have demonstrated that B-Raf/B-Raf V599E specific antibodies are detectable in 8.9% of advanced stage melanoma patients and B-Raf V599E might therefore be a valuable target for immune therapy. Combined with the independently described B-Raf V599E specific CD4^+^and our earlier demonstration of B-Raf V599E specific CD8^+^T-cell responses this study makes the screening for novel B-Raf V599E MHC class I epitopes for vaccination approaches a promising task.
Competing interests
===================
None declared.
Authors\' contributions
=======================
JF and JCB designed the study and performed the data and statistical analysis. JF set up and supervised the ELISA and wrote the report. JCB set up and supervised the sample collection and was involved in writing the report. TP and VH were performing the ELISA assays, CSV was responsible for serum collection, transport and maintenance. EBB and URR were involved in providing the conceptual framework for this study. All authors approved the final version of the manuscript.
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1471-2407/4/62/prepub>
Supplementary Material
======================
::: {.caption}
###### Additional File 1
Supplementary figure with WESTERN Blot analysis of positive sera confirming specificity.
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::: {.caption}
######
Click here for file
:::
Acknowledgements
================
We are grateful to R. Götz for providing the B-Raf V599E encoding plasmid, I. Gentschev and S. Albert for helpful discussion and critically reading the manuscript. This work was supported in part by the research network \"New strategies in Immunotherapy\" (ForImmun) funded by the Bayerische Forschungsstiftung in Munich and the Mildred Scheel Stiftung.
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
**Raf specific antibody response in different patients\' sera.**Analysis of 2 representative positive (42) and negative (12) sera using a secondary antibody detecting human IgG, IgA and IgM is depicted in A. Sera no. 42 and 12 were tested for specificity against B-Raf, B-Raf V599E (V599E), an unrelated antigen (PSA) and without the addition of antigen (-). Serum 42 reacted against B-Raf and B-Raf V599E and not against an unrelated antigen. Sera 12 showed no measurable response. Sera withdrawn at different time points from patient no. 106 were tested at different dilutions in an ELISA and OD~405~was determined (B). In the case of this patient, sera were negative at the first two time points and became strongly positive within three months. Specificity of the response was confirmed using different concentrations of antigen for coating (0, 0.1, 1 and 2 μg/ml) and different serum dilutions (C). All 371 patient and 119 control serum samples were analysed in a similar way. In D, serum was analyzed in a similar way then in C using an IgG specific secondary antibody. Serum \#42 is weakly positive for B-Raf specific IgG antibodies, serum \#1 is representative for most other sera of healthy donors and melanoma patients which are negative for B-Raf specific IgG antibodies.
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
**Competition ELISA to test for specificity for mutated B-Raf.**ELISA was performed using 2 positive sera from melanoma patients (A, B) and 1 positive sera from the control group (C) as well as a human serum with known background reactivity (D; serum from a non-melanoma patient of the dermatology department with reactivity against BSA used for blocking). Plates were coated with B-Raf (■, ▲) or B-Raf V599E (▼, ◆) and competition was performed by titrating in increasing concentrations (0.0, 0.1, 1.0 and 5.0 μg/ml) of B-Raf (■ ▼) or B-Raf V599E (▲, ◆). Data is presented using relative OD~405~values that are adjusted relative to the first experimental OD values of the corresponding dataset. For the positive sera with specific Raf antibodies (A-C), competition reveals no differences between B-Raf and B-Raf V599E regardless of the combination suggesting that the antibodies can not discriminate between wt and mutated B-Raf. In contrast, the non-specific serum no. 79 showed, as expected, no sign of competition with whatever antigen combination. n.d. not determined.
:::
:::
::: {#F3 .fig}
Figure 3
::: {.caption}
######
**Comparison of B-Raf V599E, B-Raf and C-Raf specific antibody responses between control patients or melanoma patients.**The comparison has been performed between 119 control sera with 371 sera of melanoma patients tested for B-Raf V599E and 272 sera of melanoma patients tested for B-Raf and C-Raf. Titers correspond to the last serial dilution of the patients sera exceeding a cut-off OD~405~of 0.275. Compared to the background values in the absence of antigen (control -; melanoma -), the difference is not significant for control patients (P = 0.232; 0.471; 0.4054 for B-Raf V599E, B-Raf wt and C-Raf respectively, two tailed Mann-Whitney U test) and significant for melanoma patients (P = 0.012; 0.0009; 0.0022 for B-Raf V599E, B-Raf wt and C-Raf respectively, two tailed Mann-Whitney U test).
:::
:::
::: {#F4 .fig}
Figure 4
::: {.caption}
######
**Fraction of sera positive at different antibody levels.**In A, the percentage of B-Raf positive sera of control patients (△) or melanoma patients (■) is plotted as a function of the cut off titer, whereas sera are termed positive if the titer reaches or exacerbates the given cut off titer. The difference between control patients and melanoma patients was statistically significant for a cut off titer of 1:300 (P = 0.028; 0.073; 1.0, two sided Fisher\'s exact test for cut off titers equal to 1:300; 1:900 and 1:2700 respectively). In B, the percentage of sera with titers higher or equal than 1:300 is shown for B-Raf V599E, B-Raf and C-Raf specific responses. In all cases, the amount of antibody positive melanoma patients is higher compared to the control group. This trend was significant for the comparison of B-Raf positive sera (P = 0.028, Fisher\'s exact test) and not significant for the comparison of B-Raf V599E (P = 0.12, Fisher\'s exact test). However, C-Raf specific antibodies with titers of 1:300 were only detectable in 1.8% of the tested sera from melanoma patients and none of the control patients (P = 0.327).
:::
:::
|
PubMed Central
|
2024-06-05T03:55:47.932396
|
2004-9-12
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC518968/",
"journal": "BMC Cancer. 2004 Sep 12; 4:62",
"authors": [
{
"first": "Joachim",
"last": "Fensterle"
},
{
"first": "Jürgen C",
"last": "Becker"
},
{
"first": "Tamara",
"last": "Potapenko"
},
{
"first": "Veronika",
"last": "Heimbach"
},
{
"first": "Claudia S",
"last": "Vetter"
},
{
"first": "Eva B",
"last": "Bröcker"
},
{
"first": "Ulf R",
"last": "Rapp"
}
]
}
|
PMC518969
|
Background
==========
Airway inflammation is thought to cause much of the lung damage in patients with cystic fibrosis (CF) \[[@B1],[@B2]\]. Such inflammation has been found in infants with CF, even in the absence of bacterial infections or symptomatic lung disease \[[@B3]\].
Recent therapies for CF lung disease have been shown to preserve lung function by decreasing airway exposure to inflammation. For example, airway clearance, antibiotics (inhaled tobramycin and oral azithromycin), rhDNase, and oral corticosteroids have been used to help decrease airway inflammation \[[@B4]-[@B6]\]. High-dose ibuprofen therapy also has been shown to be effective in decreasing inflammation, probably by decreasing polymorphonuclear cell influx into the lungs \[[@B7]\]. We present a patient with CF who developed a rare complication of high-dose ibuprofen therapy related to his pneumonectomy.
Case presentation
=================
The patient was a teenager with CF who suffered for several years from right lower lobe consolidation, as a result of recurrent *Pseudomonas aeruginosa*pneumonia. The consolidation was unresponsive to intensive therapy including intravenous (IV) antibiotics, chest physiotherapy, systemic steroids, and rhDNase. The patient developed recurrent severe pulmonary exacerbations necessitating IV antibiotic therapy 4 times per year between the ages of 14 and 15 years. A computerized tomography scan of the chest when the patient was 15-years-old revealed complete collapse of his right lung. A ventilation/perfusion scan revealed only 8% of his ventilation and perfusion in his right chest, while the remaining 92% was in his left chest. In addition, the left lung had begun to herniate into his right chest. It was felt that the right lung was a recurrent source of infection, which was causing serious morbidity. Therefore, the patient underwent a total right pneumonectomy that he tolerated well.
Approximately one year later, in preparation for initiating high-dose ibuprofen therapy, the patient\'s stool was checked for occult blood. He was found to have occasional guaiac positive stools. An upper gastrointestinal endoscopy revealed chronic esophagitis, esophageal ulcerations, and Barrett\'s esophagus thought to be attributable to gastroesophageal reflux. A 24-hour pH probe revealed significant gastroesophageal reflux despite anti-reflux therapy. Therefore, a fundoplication was performed in order to prevent further esophageal damage. Subsequently, it was believed that his esophageal ulcerations resolved as multiple stools were documented to be guaiac negative.
High-dose ibuprofen therapy was initiated when the patient was 17-years-old, based on published recommended dosage and pharmacokinetic protocols \[[@B8]\]. The patient\'s dose was determined by a pharmacokinetic analysis \[[@B8]\] that documented a peak ibuprofen plasma concentration of 69 mcg/ml, following a test dose of 1,000 mg (22 mg/kg). A week after initiation of ibuprofen at a dose of 1,000 mg b.i.d. the patient developed severe abdominal pain, hematemesis and bright red blood per rectum. He became hemodynamically compromised and an emergency endoscopy revealed bleeding esophageal ulcerations in the distal 12 cm of his esophagus. After stabilization and observation without further bleeding, a barium swallow demonstrated that his esophagus was deviated towards the right side and the lower segment of the esophagus was relatively horizontal proximal to the gastro-esophageal junction (Figure [1](#F1){ref-type="fig"}). In addition, a pancreatic enzyme capsule emptied of the enzymes and filled with barium was retained within that esophageal segment for several minutes (Figure [1](#F1){ref-type="fig"}).
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Barium swallow in a patient with cystic fibrosis following right pneumonectomy. A -- The study demonstrates deviation of esophagus to the right side, and a relatively horizontal lower esophageal segment proximal to the gastro-esophageal junction. B -- A pancreatic enzyme capsule emptied of the enzymes and filled with barium (indicated by the arrow) is retained within the lower esophagus for several minutes.
:::
:::
Following this episode the patient\'s ibuprofen was discontinued, and his oral medications (e.g., antibiotics and vitamins) were switched to liquid form, whenever possible. His pancreatic enzymes were administered after removing the enzyme microspheres from their capsule and mixing them in applesauce.
Reported complications of pneumonectomy include mediastinal shift with herniation of the remaining lung, cardiac herniation, cardiac arrhythmias, bronchopleural fistula, esophageal motility disorders, and development of scoliosis \[[@B9]-[@B11]\]. It is thought that pediatric patients have more mediastinal shift following pneumonectomy than adults because of increased elasticity and compliance of the lung and mediastinum that allow for more severe anatomical derangements \[[@B9]\]. A study of 17 post-pneumonectomy pediatric patients revealed that all of the patients had marked herniation of the remaining lung with a mediastinal shift to the opposite side as evident on chest radiographs or computerized tomography scans \[[@B11]\]. One patient with a right pneumonectomy displayed excessive shift of the esophagus as well, but did not have any associated dysphagia or reflux \[[@B11]\]. In another study, esophageal motility was measured in 13 patients before and after pneumonectomy \[[@B9]\]. Patients post-pneumonectomy were shown to have esophageal dysmotility even without reporting dysphagia \[[@B9]\]. The dysmotility was thought to be attributable to the mediastinal shift \[[@B9]\]. Thus, for the patient in the present report, it is likely that the deleterious effects of gastroesophageal reflux may have been increased because of esophageal dysmotility after pneumonectomy.
In our patient, esophageal dysmotility along with the distortion of esophageal anatomy probably combined to slow the esophageal transit time of the ingested ibuprofen, which may have led to development of ulcerations as a result of prolonged concentrated contact within the esophagus. Also, the ibuprofen could have contributed to the development of ulcerations by inhibiting cyclooxygenase systemically, which decreased prostaglandin E production \[[@B12]\]. In turn, less prostaglandin E was available to promote bicarbonate and mucus secretion, which are protective of the gastrointestinal mucosa \[[@B12]\].
Delayed esophageal transit may have occurred with the patient\'s other oral medications prior initiation of ibuprofen. For example, his pancreatic enzymes likely were retained in the same esophageal segment, which placed him at risk of developing esophageal damage akin to the development of fibrosing colonopathy and strictures described in patients with CF who received high-dose pancreatic enzymes \[[@B13]\]. The enzymes may have remained inactive because the environment was not alkaline enough for their activation \[[@B14]\], which may be the reason that the patient did not demonstrate esophageal strictures.
According to the 2002 CF Foundation registry, only 3.8% of patients in North America with CF were treated with high-dose ibuprofen \[[@B15]\]. In 1999, a survey of 67 CF center physicians revealed that safety issues were a major reason that they did not prescribe this therapy \[[@B16]\]. Gastrointestinal bleeding, a known adverse effect of non-steroidal anti-inflammatory agents, was the safety issue of most concern to these physicians \[[@B16]\]. Other known side-effects of high-dose ibuprofen include renal failure (often transient), and epistaxis \[[@B3],[@B17]\].
The initial randomized, double-blind, placebo control study of high-dose ibuprofen in CF did not demonstrate serious side effects during 4 years of therapy with ibuprofen sufficient to achieve peak plasma concentrations of 50--100 mcg/L \[[@B8]\]. Seven of 85 study patients developed abdominal pain, while only 2 of these 7 were on ibuprofen. One patient in the placebo group developed esophagitis. Of note, abdominal pain, which is very common in patients with CF, actually improved in many patients. In another randomized, double-blind, placebo controlled study, involving 19 children with cystic fibrosis; 13 children received sufficient ibuprofen for 26 months to maximum concentrations 48 +/- 17 mcg/ml, but no adverse effects could be attributed to the ibuprofen \[[@B18]\].
The incidence of gastrointestinal disease in patients reported to the CF Foundation registry from 1996--2000, was compared between patients who were and were not taking ibuprofen \[[@B19]\]. Peptic ulcer disease was reported in 0.32% of 1,186 CF patients taking high-dose ibuprofen, as compared to an incidence of 0.22% in 18,587 patients not taking ibuprofen. Gastrointestinal bleeding was reported in 0.49% of patients taking ibuprofen, as compared to 0.23% of the others (p = .0004). In the first year after initiation of high-dose ibuprofen therapy for 91 patients at the Texas Children\'s Hospital CF Center, one patient developed upper gastrointestinal bleeding, and one developed gastritis \[[@B20]\]. In a published case report, a 12-year-old patient with CF on high-dose ibuprofen developed emesis and feeding intolerance \[[@B21]\]. She was found to have pyloric channel stricture as a result of healing antral and pyloric ulcers, which may have been caused by ibuprofen.
Conclusions
===========
The risk of developing gastrointestinal side-effects from high-dose ibuprofen therapy is low for patients with CF. However, ibuprofen may be contraindicated for those who are at increased risk because of gastroesophageal reflux, history of gastrointestinal ulcerations, or abnormal gastrointestinal motility or anatomy.
Competing interests
===================
None declared.
Authors\' contributions
=======================
JM wrote the case report. RA treated the reported patient, and edited the report.
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1471-2431/4/19/prepub>
Acknowledgements
================
Written consent was obtained from the patient\'s mother for publication of this report.
|
PubMed Central
|
2024-06-05T03:55:47.934767
|
2004-9-13
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC518969/",
"journal": "BMC Pediatr. 2004 Sep 13; 4:19",
"authors": [
{
"first": "Jennifer E",
"last": "Mackey"
},
{
"first": "Ran D",
"last": "Anbar"
}
]
}
|
PMC518970
|
Background
==========
Health information privacy has come to the forefront of ethical concern in the early 21^st^century \[[@B1]\]. The advent of electronic health records, information technology, and large databases (such as administrative and genetic) with the potential for extensive linkages have raised concerns about the security of health information \[[@B2],[@B3]\]. The details of where such information flows, who has access, and for what purposes have assumed paramount importance \[[@B4]-[@B6]\].
Health information is valuable for numerous purposes, first and foremost for patient care, but also for secondary uses including hospital administration and health services research \[[@B7],[@B8]\]. Such non-clinical care uses are required for system performance and evaluation, as well as to answer questions about disease trends and health outcomes. In general, there is a *prima facie*obligation for the protection of such intimate and privileged information \[[@B4],[@B8]\]. Scientific surveys and public opinion polls have shown that access to medical records is generally considered appropriate after consent has been obtained for a specific use \[[@B9]-[@B12]\]. Yet, this obligation admits to several exceptions and there is lack of clarity as to whether express consent is required for each and every use. Some have argued that requiring unique individual informed consent for each use of health information would be burdensome \[[@B13]-[@B15]\]; however, there are public opinion data suggesting that legislative initiatives to require such consent would be viewed favourably \[[@B9]\].
Internationally, legal initiatives have proposed solutions to the dilemma posed by health information. In Europe and North America, such initiatives have led to restrictive legislation that, according to some commentators, may endanger public health goods \[[@B4],[@B16],[@B17]\]. A privacy paradox thwarting further progress has been identified: individuals want both the guaranteed privacy of their personal health information (PHI) and the public benefits that accrue from the use of medical records \[[@B18]\]. Two distinct avenues have been proposed for the solution of this paradox; the first avenue concentrates on governance issues, whereas the second promotes the development of tools, programs, and systems to enhance the lay understanding of and control over the uses of health data and thereby facilitate informed consent for secondary uses, as advocated by Mandl and his colleagues \[[@B19]\]. This paper pursues the second avenue.
In 2001, Upshur and Goel first proposed the Health Care Information Directive (HCID), a patient decision aid analogous to an advance directive in end-of-life care \[[@B20]\]. The underlying logic was to combine ethical appropriateness of use of PHI with the sensitivity of the data. As shown in Table [1](#T1){ref-type="table"}, the HCID clearly presents the various permutations and combinations of sensitivity and usage in the form of a matrix. The goal of the tool is to allow individuals to make informed choices about the specific types of health information they are willing to disclose (if any) for a number of specified purposes.
In the original proposal, it was stated that pilot testing of the tool, and revision on the basis of such testing, is required \[[@B20]\]. In order to assess the feasibility of implementing the HCID, two segments of the population were studied: the general lay public and privacy experts such as ethicists, academics, and provincial privacy commissioners. In this paper, we report the results of the study conducted with the general public. Specifically, our objective was to investigate lay knowledge of the uses and accesses of health information and to solicit feedback on the prototype of the HCID.
Methods
=======
Participants and setting
------------------------
The study was set in Toronto, Canada, a large, culturally-diverse urban centre. In order to sample multiple views and perspectives, a series of focus group meetings was convened with the following four groups: senior citizens, urban professionals, immigrants with English as a second language, and consumer advocates. The latter group was comprised of volunteer members of a well-known national consumer advocacy association for which health care is an issue of primary interest and activity. We opted to employ focus group methodology as opposed to individual interviews or a questionnaire survey in order to capitalize on the effects of group interaction. These particular communities or target groups were selected in order to maximize the variability within our sample on important demographic characteristics such as age, gender, occupation, education, and native language, etc. (available funding allowed for a total of four focus groups). Potential participants were recruited using various methods: the seniors were recruited through a local community centre offering programs for senior citizens; participants in the immigrant/ESL group were recruited through an immigrants group at another community centre; the urban professionals were recruited by way of posters and fliers distributed at a number of hospitals and university sites; and the advocates were recruited through a national consumer advocacy association. In all cases, initial contact with potential participants was made either by telephone or e-mail and then followed up with formal letters of invitation describing the project. The focus group meetings were held in a convenient location for the participants and lasted for up to two hours.
We developed a topic guide for the focus group meetings in order to address the main issues related to the feasibility of the HCID (see Appendix 1). The topic guide was developed according to the principles of formative evaluation (also known as \'developmental\' evaluation) \[[@B21]\]. Focus group participants were initially questioned regarding their understanding of health information and its uses. Participants were then introduced to the HCID, which was presented as a patient decision aid currently under development by \"university researchers.\" Participants were informed that their feedback and suggestions would guide the continuing refinement of the tool and were asked to be as candid as possible. Following a brief period of approximately 5--10 minutes in which participants examined the HCID and jotted down any questions/concerns/suggestions, participants were asked to share their thoughts on its relative strengths and limitations. As per the topic guide, issues of content, utility, and feasibility were addressed in turn, followed by a discussion of perceived benefits and burdens. At the end of each meeting, participants were provided an opportunity to raise any issues or concerns that had not been previously addressed.
Two of the authors (GCD and CST) moderated the four focus group meetings, which lasted 90 minutes on average. A total of 28 participants took part (see Table [1](#T1){ref-type="table"} for a description of the sample). The meetings were audio-recorded with participants\' consent and transcribed verbatim by a professional transcriptionist. To ensure accuracy and to clarify any muffled passages, all transcripts were verified by one of the two group moderators. Participants received an honorarium of \$50 for their time, in addition to transportation costs.
The study was approved by the Research Ethics Board at Sunnybrook and Women\'s College Health Sciences Centre and the Office of Research Services at the University of Toronto. All participants signed and returned a consent form.
Data analysis
-------------
The analytic process was one of thematic content analysis. The topic guide developed for the focus group meetings served as the basis for the data analysis process. Two of the authors (GCD and CST) independently read each of the transcripts and identified passages of text relating to each of the various key issues from the topic guide (e.g., content, utility, benefits, etc.) which, for the purposes of coding and analysis, served as the macro-codes. Following this step, lists of themes were constructed and then compared. The transcripts were then independently coded according to an agreed-upon coding scheme. Tests for inter-coder reliability indicated a high level of agreement among the two coders; instances of disagreement were resolved through a process of discussion and negotiation. To strengthen the validity of the findings, the analytic processes of coding and interpretation were reviewed by the senior author (REGU). The results of our analysis are reported according to five key themes: participant knowledge and understanding of health information and its uses; control of access to health data; mistrust of data security provisions; need and utility for a tool such as the HCID; and, finally, perceived implementation barriers. Consenus statements reported below are not a reflection of any explicit consensus development techniques, but rather are summary statements of the research team\'s observation and interpretation of the focus group discussions. For each quotation, a specific code is provided to identify the speaker as a participant in one of the four focus groups (CA = consumer advocate; IM = immigrant; SC = senior citizen; and UP = urban professional).
Results
=======
Knowledge and understanding
---------------------------
The majority of participants possessed extremely limited knowledge of how their PHI is collected, used, and disclosed. Many confessed to having given little or no thought to the issues involved in the health privacy debate. This was particularly true for recent immigrants: \"I think the truth is that I don\'t know. I\'ve never thought of that before, who has my information.\"(IM-1). The level of understanding was low among participants in other groups as well, as a number of comments betrayed basic misperceptions of how PHI is currently managed within the Canadian health care system:
\"It \[personal health information\] goes in the computer and then it\'s available to every medical professional in Ontario.\" (SC-3)
\"Health providers have access to your file, to your information\... but everybody in the financial department, too, because they have to bill OHIP \[Ontario Health Insurance Program\] so they have to know everything about you.\" (IM-2)
One participant perceptively noted that the general population has limited knowledge of the issue of health privacy:
\"That\'s another thing. What do people know about what they can get access to, what they can ask for, and what they can expect? I think the majority of the population have no idea of what they can ask for and expect to get.\" (CA-4)
Control of access
-----------------
Participants\' accounts clearly suggested an absence of patient control over the collection, use, and disclosure of PHI. No participants recalled having ever been consulted about how their information was to be used. A great deal of concern was voiced about the extent to which health data appears to be freely accessible to a wide variety of users: \"Lawyers, psychologists, social workers, researchers, pharmaceutical companies. Where does it stop?\" (UP-4). In the course of describing how they feel about the issue of health privacy, participants repeatedly used terms such as \"scary\" and \"horrifying\":
\"I\'m scared to guess who has \[access to my health information\]. It looks so easy for a lot of people to have access. That\'s the scary part of it. Maybe your employer can have access to your files, too. I don\'t know, that\'s just a guess.\" (IM-6)
The majority of participants expressed concern that their PHI is not adequately safe-guarded and that the implementation of a tool such as the Health Care Information Directive would not result in significantly enhanced privacy or increased security. There was a widespread view that too much data is currently made available when only specific details are required. Doubts were raised about how consent for one specific use only would be managed:
\"What\'s going to prevent any leaking from one of these \[uses\] into the others? \... It just seems to me that if there\'s information on-line, things are going to be compromised. You know, people make a living doing that stuff. The more they find out about you, the more you can be exploited. It\'s that simple. These systems, they\'re not secure yet, and I don\'t know if they can ever be secure.\" (UP-3)
Health privacy concerns related to the security of electronic databases and the Internet were shared by others:
\"We\'ve all heard stories where there\'s been stolen identities. How difficult is it for the victim to get his or her own identity back? Same idea. Where does it end? Where does it stop? Who\'s got what information? How am I going to protect myself?\" (UP-6)
Participants suggested a number of other mechanisms that could work in conjunction with the HCID to enhance security and facilitate individual control over PHI. One such mechanism would be an online real-time audit system in which the details of all accesses to an individual\'s PHI are recorded and made available to those wishing to track access to their PHI over time. Also, the idea of a health data ombud was raised in several groups and received a great deal of support.
Mistrust
--------
Issues related to trust were raised in each of the four groups. Participants of all ages and socioeconomic status expressed feelings of mistrust in relation to the protection of their privacy and the security of their PHI. A great many participants spoke of how their past experiences with the health care system have fostered significant mistrust and suspicion where their right to privacy is concerned. These accounts revealed a growing distress that large corporations have too much access to and influence on government programs, especially in contrast to the access and influence accorded to patients:
\"What about the rights of the patient? Let\'s say I\'m the patient. What kind of power do I have? Let\'s say this \[the HCID\] was created next year. What power does the patient have to make sure any of this is happening? To me, a pharmaceutical company is way more powerful than the patient.\" (CA-2)
Others were even more sceptical, questioning the trustworthiness of the basic tenets of the model upon which the HCID is based:
\"By filling this out, I\'m buying into the concept of sharing information, but I don\'t have any faith that it can be kept private\.... It will spill, it will bleed, it will flow. So I\'m distrustful of the whole thing. This just sets up more spilling and more flowing. If I fill out a form like this, then I\'m validating the process, which I don\'t really trust.\" (UP-8)
Need and utility
----------------
While the majority were sceptical that the HCID would prevent all breaches of privacy, there was a general consensus that it would serve to enhance significantly the security of health data. One participant noted that the proposed decision aid may also serve a useful purpose as \"a sort of consciousness raising\" tool. Other impressions varied from \"it has some potential\" to \"it is a great step forward.\" Reactions were mixed in response to the question of whether the HCID will be successful in empowering individuals and increasing the amount of control over PHI:
\"I\'m very dubious as to whether this matrix will be useful because of the difficulty people will have filling it out. In spite of that, I think the idea has merit and principle. There\'s merit in what you\'re trying to do, but I don\'t think that this is going to succeed.\" (CA-5)
\"I guess the reality is our information will be shared, so we might as well get on the bandwagon with regulating it and controlling it\... You can\'t stop it from being shared, so maybe you can influence how it will be shared.\" (UP-2)
Despite the weaknesses and limitations of the present version of the directive, one participant neatly summarized the view of the majority of participants regarding the utility of the HCID or some such tool: \"Not having it allows total absence of control, therefore it is a necessary evil.\" (CA-4).
Implementation barriers
-----------------------
Participants provided numerous suggestions regarding the formatting of the HCID in order to facilitate implementation. Ideas ranged from simplifying the language and providing definitions of technical terms to modifying the layout and shading those areas where there is no discretion (i.e., for physician payment):
\"Maybe you\'ve got too many columns\.... Well, maybe you\'re trying to do too many different things at once.\" (CA-4)
\"This is too busy, it\'s too much. If I\'m sick, I friggin\' don\'t want to be bothered with it\.... Look at this. English is my first language. How would somebody whose mother tongue is something other than English? It\'s too complicated.\" (SC-1)
\"I think people tend to say \'no\' for things that are not clear. I would say \'yes\' if I knew what it means exactly, but I don\'t know, so I don\'t want to take a chance.\" (IM-1)
To address the complexity issue, suggestions were made concerning the need to provide a customer service representative either in a health clinic or via a toll-free helpline for assistance with completing the HCID.
Across the four groups, there was great variability in the preferred mode of implementation. The preference among participants in the health advocates and urban professional groups was for an on-line implementation format. In contrast, the majority of the senior citizens and immigrants preferred other options, the former favouring a postal format and the latter the primary care setting. As one senior citizen remarked: \"I prefer the doctor\'s office. I wouldn\'t fill it and send it back through the mail, no.\" (SC-3)
Discussion
==========
A recent editorial in the *British Medical Journal*suggested that perhaps patients should be asked whether certain items of their medical chart should only be shared with specified individuals or organizations or only for pre-determined purposes \[[@B16]\]. This paper reports the evaluation of the feasibility of a tool that seeks to accomplish exactly that purpose, namely, greater patient control over how personal health information is used and disclosed.
Study participants lacked substantial knowledge regarding the fate and uses of PHI within a publicly-funded health care system. Participants expressed mistrust concerning how their PHI is used and safe-guarded. Several suggestions were made towards customizing the use of data according to specific needs rather than broad and full access to their charts. Furthermore, concerns were expressed regarding the implementation of a tool such as the HCID. Nevertheless, there was hope that a refined instrument could contribute to improved data management and regulation and enhanced privacy protection.
Although this study reports on a small sample from a single large urban centre, the focus group participants were drawn from various different niches of Canadian society. This sampling strategy allowed us to explore a broad range of experiences and perspectives; however, further testing and evaluation are required. Ultimately, it will be necessary to evaluate the tool using a representative sample of patients who complete the HCID in a \'live\' test of its feasibility.
Our findings underscore the difficulties involved in accessing health care data for research and other secondary purposes. Participants acknowledge the myriad benefits derived from the use of health data; however, distrust, lack of respect, and insufficient patient control of the process threaten to undermine these very benefits. This finding has been previously reported by Willison and associates in Canada \[[@B22]\] and by Robling and colleagues in the UK \[[@B12]\]. The present results also suggest that the education and information needs of diverse groups such as seniors and immigrants who speak English as a second language should be taken into account when considering strategies to enhance individual control over PHI and minimize the problem of authorization bias when utilizing health information for secondary purposes.
Participants appreciated the benefits accorded by a tool such as the HCID. As opposed to forms of blanket consent or other opt in/opt out models, the possibility of exerting greater control over one\'s PHI was attractive. The participants provided concrete suggestions for improving the format and content of the HCID. It is evident that any method to enhance control of health information via explicit consent requires description of the various forms the data may take, the specific purposes for which the data would be used, and the various channels of the health care system through which the data might flow. To our knowledge, such detailed data flowmaps for PHI do not exist in Canada, although they have been laid out in Great Britain \[[@B23]\]. A model has been proposed by Schoenberg and Safran \[[@B24]\]. The creation of such maps is of high priority.
An intriguing finding was the appeal of an online data audit system. Possessing the ability to monitor who has accessed their PHI and for what purposes raises the possibility of additional strategies that could empower individuals to control the fate of their health information. This finding has also been verified by Pyper and colleagues \[[@B25]\] and was previously highlighted by MacDonald \[[@B26]\]. As well, the concept of a data ombudsperson was considered attractive to a number of participants, indicating that an improved governance framework would be acceptable to some segments of the population.
Finally, there is a distinction to be made between using the HCID to enforce the will of the patient versus its use as a documentation tool. Our vision is that the HCID will, ultimately, serve both of these important functions; further follow-up evaluation of a revised model of the HCID using a larger sample (comprised of patients as well as providers) is needed to address this distinction. As with any patient decision aid or empowerment tool, documenting the preference of the patient is only meaningful and useful to the extent that the documented preferences are known and ultimately acted upon by those providing care. We believe the present data illustrate the critical problem of mistrust that currently exists. Indeed, this is one of the greatest challenges to be overcome in the continuing development and validation of this tool.
Conclusion
==========
This study indicated poor knowledge concerning the uses of health data, distrust concerning current security provisions, and qualified support for a tool such as the HCID to improve patient control over health information. On the basis of this evaluation, the HCID will be revised significantly, including the addition of an educational component, and then submitted to further evaluation. The creation of data flowmaps and the exploration of audit functions and governance structures are strongly recommended as avenues for future research.
Competing interests
===================
None declared.
Authors\' contributions
=======================
CST participated in the collection, analysis, and interpretation of the data and is the primary author of the paper. GCD recruited the participants, moderated the focus group meetings, participated in the data analysis, and contributed to the editing and revising of the paper. REGU initiated and designed the study, participated as a reliability check in the process of data analysis, and contributed to the editing and revising of the paper. As principal investigator, he will act as guarantor. All authors have read and approved the final version of the paper.
Appendix 1
==========
FOCUS GROUP TOPIC GUIDE: EVALUATION OF THE \'HEALTH CARE INFORMATION DIRECTIVE\'
--------------------------------------------------------------------------------
### A. Personal Health Information
1\. What is your understanding of the term \'personal health information\'?
2\. Who do you believe has access to your personal health information?
3\. Do you believe that consent should be required to access your personal health information?
### B. Content
1\. What is your first impression of the Health Care Information Directive?
2\. Is it clear?
3\. Is it self-explanatory?
### C. Utility
1\. How useful do you believe the Health Care Information Directive would be in practice?
2\. Is it user-friendly?
3\. What kind of changes would you suggest?
### D. Feasibility
1\. How feasible is the application of the Health Care Information Directive?
2\. Who should present it to the patient?
3\. When should it be presented to the patient?
### E. Benefits and Burdens
1\. What are the potential gains of the Health Care Information Directive?
2\. What are the potential harms?
3\. Does it adequately protect privacy and confidentiality?
### F. Additional Comments
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1472-6947/4/13/prepub>
Acknowledgements
================
We would like to thank our three peer reviewers -- Drs. Kenneth Mandl, Barbara Yawn, and Michael Robling -- as well as members of the editorial board for their insightful, constructive comments on an earlier version of this article.
This research was supported by the Office of the Health Information Highway at Health Canada and HEAL*Net*(Health Evidence Applications and Linkage Network), a member of the Networks of Centres of Excellence program, which was a unique partnership among Canadian universities, Industry Canada, and the federal research granting councils (1995--2002). REGU is supported by a New Investigator Award from the Canadian Institutes of Health Research (CIHR) and a Research Scholar Award from the Department of Family and Community Medicine, University of Toronto. The authors are indebted both to Jennie Jones for transcribing the focus group meetings and to Shari Gruman for formatting the manuscript.
Figures and Tables
==================
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Demographic characteristics of focus group participants
:::
-------------------------------------------------------------------------------------------------------
**Focus Group** **Number of**\ **Male:Female**\ **Modal Age**\ **Some Post-Secondary**\
**Participants** **Ratio** **Group** **Education**
--------------------- ------------------ ------------------ ---------------- --------------------------
Urban professionals 8 4:4 30--39 yrs 8
Immigrants (ESL) 7 2:5 40--49 yrs 5
Health advocates 6 2:4 50--59 yrs 6
Senior citizens 7 0:7 \>70 yrs 1
-------------------------------------------------------------------------------------------------------
:::
|
PubMed Central
|
2024-06-05T03:55:47.935777
|
2004-9-10
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC518970/",
"journal": "BMC Med Inform Decis Mak. 2004 Sep 10; 4:13",
"authors": [
{
"first": "C Shawn",
"last": "Tracy"
},
{
"first": "Guilherme Coelho",
"last": "Dantas"
},
{
"first": "Ross EG",
"last": "Upshur"
}
]
}
|
PMC518971
|
Background
==========
The success of dopaminergic interventions in the treatment of Parkinson\'s disease (PD) symptoms has been significant. Nevertheless, a misdiagnosis of PD can cause psychological trauma and unnecessarily expose patients to PD drugs. Additionally, as new, and possibly neuroprotective, drugs become available for the treatment of PD, early and accurate diagnosis will become increasingly important. As the diagnosis of PD is usually based on subjective clinical assessment of overt symptomatology \[[@B1]\], the need for an objective and reproducible battery of diagnostic tests is great. Medical imagery offers some hope for the objective diagnosis of PD (e.g. ^18^F-dopa positron emission tomography \[[@B2]\]), but these techniques tend to be expensive, and inaccessible to patients living in remote areas. What is truly needed is a low-cost objective test battery that might be used in situations where (a) movement disorder specialists are unavailable to render expert diagnoses, and (b) medical imaging is inaccessible.
Montgomery et al. \[[@B3],[@B4]\] have published one of the better known objective PD batteries, incorporating measures of motor performance, olfaction, and mood. The aggregate of all subtests of this battery has demonstrated good diagnostic properties, with a sensitivity of approximately 70%, and a specificity of approximately 90%. Given that the primary symptoms of PD are motoric \[[@B1]\], however, it is interesting to note that the sensitivity of the motor task in this PD battery is approximately 50% \[[@B3],[@B4]\], indicating that diagnoses based solely on this subtest are not much better than chance. As the predictive power of a battery increases with the addition of each valid and independent subtest, it is important to evaluate motor performance paradigms that may produce better predictive validity.
The global slowing that is consistently demonstrated by PD patients suggests that measures of cognitive or motor speed are logical methods for obtaining quantitative measurements of PD severity. As reaction time (RT) and movement time (MT) have repeatedly been demonstrated to show substantive and significant deficits in PD populations (for a review of this literature, see Gauntlett-Gilbert et al. \[[@B5]\]), these indicators are (by definition) capable of distinguishing individuals with PD from healthy participants. Despite this fact, however, the motor subtest of the PD battery described by Montgomery et al. \[[@B3],[@B4]\] remains the only significant attempt at evaluating diagnostic accuracy with these chronometric indicators. Although this subtest measures both RT and MT, the task is performed in a biomechanically complicated fashion that requires the participant to move his/her hand in an arc (i.e. wrist flexion and extension) to aim at LED targets. This test assesses both rigidity and bradykinesia within the same task -- and while this is a conceptually defensible measurement decision, the resulting inter-subject variability may overwhelm group differences, and confound diagnostic accuracy. It is, therefore, worth examining the extent to which a simpler paradigm might be used to distinguish PD patients from healthy participants.
The goal of this study, therefore, is to evaluate the diagnostic properties of a choice reaction time task that uses a simple external response console (i.e. a \"button box\"), similar to other similar response time tasks extant within the PD literature.
Methods
=======
Two independent samples were drawn for this study, the first consisting of 40 PD patients (Age: [M]{.underline} = 62.13, [SD]{.underline} = 9.59) and 40 healthy participants (Age: [M]{.underline} = 65.02, [SD]{.underline} = 8.84), and the second consisting of 20 PD patients (Age: [M]{.underline} = 64.50, [SD]{.underline} = 10.88) and 20 healthy participants (Age: [M]{.underline} = 62.65, [SD]{.underline} = 12.02). To ensure that no baseline ability differences existed between groups, Wechsler Adult Intelligence Scale (WAIS) full scale IQ estimates were computed for all participants, using the National Adult Reading Test (NART) \[[@B6]\]. No significant age or IQ differences were identified between patients and controls, in either sample. During the course of testing, patients were also assessed by an experienced clinician (using the motor subscale of the Unified Parkinson\'s Disease Rating Scale; UPDRS), to determine the severity of their motor symptoms \[[@B7]\]. Patients demonstrated mild to moderate motor symptoms in both the first ([M]{.underline} = 24.49, [SD]{.underline} = 9.79), and the second sample ([M]{.underline} = 22.73, [SD]{.underline} = 7.66), with no significant severity differences demonstrated between samples. The spectrum of motor severity within the clinical group is graphically depicted with an area graph in Figures [1](#F1){ref-type="fig"} and [2](#F2){ref-type="fig"}, corresponding to the norming sample and the cross-validation sample, respectively. Finally, all participants were demonstrated to have a Mini-Mental Status Examination (MMSE) score of at least 27 at the time of testing.
The response time tasks used in this study started with an instruction to watch a fixation point (asterisk) in the centre of the computer screen, while depressing the home key (measuring 1.905 cm × 1.905 cm) in the centre of the response console. For the \'uncued\' task, participants were not given any advance information concerning the location of the upcoming stimulus. For the \'cued\' task, an arrow appeared in place of the fixation point (i.e. in the center of the screen) for a period of 2 seconds, immediately following the disappearance of the fixation point, and correctly cued the location of the upcoming stimulus on all trials. The visual stimulus to which the subject responded was presented on the right or left side of the monitor, at a random interval (between 500 and 1500 ms) following the fixation point (\'uncued\') or the arrow (\'cued\'). Participants responded to the stimulus by moving the index finger of their dominant hand from the home key to a response key (measuring 1.905 cm × 1.905 cm) placed 3.175 cm to the left or right of the home key, as directed by the stimulus placement on the screen. The time measured between the onset of the visual stimulus and a participant\'s movement from the home key was defined as reaction time (RT), and the time measured between a participant\'s lift from the home key and depression of the response key was defined as movement time (MT). Each task consisted of 10 practice trials, and 40 experimental trials. A participant\'s RT and MT was computed as the unit-weighted average of scores on the \'cued\' and \'uncued\' choice response time tasks. This testing apparatus is described in further detail by Johnson et al. \[[@B8]\].
All patients involved in the study were asked to remain drug-free overnight, and to delay taking their morning anti-Parkinsonian medications until after the testing. To avoid any confounding effects resulting from different levels of caffeine intake among participants, all participants were asked to have a normal caffeine-free breakfast prior to testing. None of the participants reported any acute physiological conditions that may have precluded them from putting forth their best effort during the testing session. All procedures and materials were approved by the Health Sciences Research Ethics Board at the University of Western Ontario.
Results
=======
In the first sample (40 patients and 40 healthy participants), separate receiver operator characteristic (ROC) curves were generated for the composite RT and MT scores. The best prediction (i.e. the largest area under the ROC curve) was achieved using the composite MT score. The cutoff score was identified as the point on the curve that maximized sensitivity, with a specificity of at least 70%. This cutoff score was determined to be 230 ms (i.e. individuals with a MT of at least 230 ms were identified as having PD). To control for the possibility that classification success in the first sample was the result of a capitalization on sample-specific variability \[[@B9]\], this classification strategy (i.e. the cutoff score identified from the ROC within the first sample) was cross-validated in the second sample (20 patients and 20 healthy participants). Classification results and diagnostic efficacy variables for both samples are presented in Table [1](#T1){ref-type="table"}.
To identify the extent to which response time predicted disease progression, correlations were computed between the UPDRS and the aggregate RT and MT scores. As the samples demonstrated no significant differences on the UPDRS, correlations were computed across all data collected in both samples. Both RT (r = 0.23, n.s.) and MT (r = 0.59, [p]{.underline} \< 0.025) were positively correlated with the UPDRS, suggesting that these response time tasks are good predictors of the severity of Parkinsonian symptoms, particularly when considering the MT component of response time.
Discussion
==========
This study confirms previous research that has shown significant movement time (MT) differences between PD patients and healthy participants \[[@B5]\]. The results of the present study also suggest that MT composites on biomechanically simple response time tasks demonstrate high cross-validated sensitivity and specificity for \'unmedicated\' patients (i.e. patients that have been temporarily withdrawn from their dopaminergic medications) -- and that these values may be higher than the demonstrated sensitivity and specificity of the motor subtest employed by Montgomery et al. \[[@B3],[@B4]\].
Standardized objective test batteries will be diagnostically useful in two general scenarios: (a) as an adjunct to the physical examination performed by a specialist (to improve diagnostic accuracy), and (b) as a standardized preliminary screening tool, for situations in which a movement disorders expert is unavailable for the physical examination. The latter situation is more important than the former, as primary care physicians are often the first point of contact for these patients. Given the waiting times to see a movement disorders specialist, patients that are considered likely to have PD (based on a screening measure) might be assigned a higher priority in their wait for an initial appointment. This assumes, of course, that primary care physicians will have access to the appropriate motor performance testing devices -- and while this is currently prohibitive from a logistical standpoint, it is technologically feasible for the simple tasks described herein to be packaged in smaller (perhaps handheld), less expensive devices.
A MT battery may also allow for the communication of results in a \"common metric\" -- without relying on subjective clinical judgments, thereby complementing other clinical tools. Aside from its diagnostic utility, MT batteries may also be useful in tracking a patient\'s progress as he/she undergoes treatment. At present, motor evaluations conducted during the clinical exam are the only method for tracking change, and this is considerably more qualitative than the MT measures described herein. Along similar lines, MT batteries could make useful adjuncts to clinical drug trial protocols, as they provide good quantitative measures of motor skill that may be used to gauge the effectiveness of the medication under study -- in the present study, MT was able to explain 34.81% of the variability in UPDRS motor scores.
It should, of course, be noted that the present research was only used to separate PD patients from healthy participants, and so it has not been demonstrated to have any differential diagnostic capabilities (e.g. distinguishing PD from progressive supranuclear palsy). Future research in this area should, therefore. investigate the differential diagnostic power of response time batteries -- it may be that the MT battery administered in this study are detecting a general \'impairment\' factor, and is not useful as a standalone instrument for the diagnosis of Parkinson\'s disease. Extending the study base to include patients with disorders such as progressive supranuclear palsy would provide important information concerning appropriate norming that may be done to maximize diagnostic utility.
At the very least, however, these results suggest that the use of simple response time batteries may serve as a useful adjunct to other clinical assessment batteries, and may also open interesting avenues of exploration into the consideration of the biological underpinnings of reaction time, and its relationship to movement disorders in general.
Competing interests
===================
None declared.
Authors\' contributions
=======================
AJ conceived and designed the study, collected all data in the norming sample, supervised data collection in the cross-validation sample, supervised data analysis, and contributed to the writing of the paper. PV supervised data collection in the norming sample, assisted in the development of the response time tasks, contributed to the data analysis, and to the writing of the paper. QA assisted with data collection in the cross-validation sample, and contributed to the writing of the paper. LG did all clinical testing on patients in the norming sample. RS assisted with data collection in the cross-validation sample. MJ provided patient diagnoses for participants in the norming sample and the cross-validation sample, and contributed to the writing of the paper.
All authors have read and approved the final manuscript.
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1472-6947/4/14/prepub>
Acknowledgements
================
This research was partially supported by grants from the Parkinson\'s Disease Foundation, and the Natural Sciences and Engineering Research Council (NSERC).
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Area graph depicting range of motor impairment in the norming sample (40 patients, 40 controls).
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Area graph depicting the range of motor impairment in the cross-validation sample (20 patients, 20 controls).
:::
:::
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Classification results
:::
Sample \#1 (40 Patients, 40 Controls) Sample \#2 (20 Patients, 20 Controls)
--------------------------------------- --------------------------------------- ------------------- ------------- -------------- ------------------- ---- ---------
Dx by Neurologist Dx by Neurologist
PD Control PD Control
Predicted Dx PD 33 12 Predicted Dx PD 18 2
Control 7 28 Control 2 18
Sensitivity 82.5% Sensitivity 90.0%
Specificity 70.0% Specificity 90.0%
:::
|
PubMed Central
|
2024-06-05T03:55:47.938608
|
2004-9-13
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC518971/",
"journal": "BMC Med Inform Decis Mak. 2004 Sep 13; 4:14",
"authors": [
{
"first": "Andrew M",
"last": "Johnson"
},
{
"first": "Philip A",
"last": "Vernon"
},
{
"first": "Quincy J",
"last": "Almeida"
},
{
"first": "Linda L",
"last": "Grantier"
},
{
"first": "Rene",
"last": "Singarayer"
},
{
"first": "Mandar S",
"last": "Jog"
}
]
}
|
PMC518972
|
Background
==========
Hospitals and regional health authorities in Canada and elsewhere are facing significant resource allocation challenges. Priorities must be set among competing opportunities because demand for health care exceeds available resources. Board members and senior administrators are looking for practical ways to improve how they set priorities under resource constraints. The priority setting literature describes priority setting in various health care contexts \[[@B1]-[@B9]\]. It identifies a number of decision-making principles and approaches that could be used to set priorities \[[@B10]-[@B16]\]. However, very little has been reported from the perspective of Board members and senior administrators themselves about what decision-making elements (criteria and processes) they would find most useful in setting priorities or how they would evaluate the success of a priority setting exercise.
Fairness is a key ethical goal of priority setting when health care resources are scarce. Experience shows that there is often disagreement on what principles should be used to make fair allocation decisions (i.e., distributive fairness) \[[@B8],[@B17]\]. This means that decision-makers must rely instead on a fair process (i.e., procedural fairness) to establish the legitimacy of priority setting decisions \[[@B16],[@B18]\]. Norman Daniels and James Sabin have developed a fair process model for priority setting called \'accountability for reasonableness\' (A4R) \[[@B16]\]. Based on justice theories of democratic deliberation, A4R identifies four conditions of a fair priority setting process (Table [1](#T1){ref-type="table"}). We, and others, have been exploring the application of A4R in various health care settings \[[@B19]-[@B23]\]. Our experience suggests that A4R can provide valuable practical guidance to improve the fairness of actual priority setting in health care organizations and to enhance public accountability for priority setting \[[@B9],[@B23]\].
To assist decision-makers in developing fair priority setting processes, we conducted one-day workshops for Board members and senior administrators at three Canadian academic health science centres (Saskatoon Health Region, Kingston General Hospital and The Ottawa Hospital), who were seeking ethics advice on how to improve priority setting in their organisations. Each organization was faced with setting priorities among their clinical services to guide resource allocation under significant budget constraints. The goal of each workshop was to help decision-makers develop a strategy for fair priority setting based on the conditions of A4R. Using case-based plenary sessions to introduce the key concepts (e.g., a case about how one organisation developed and used criteria to set clinical service priorities illustrated the importance of priority setting criteria for operationalising the Relevance condition of A4R) and facilitating consensus through small and large group discussions, we assisted workshop participants in reaching agreement on: a) the criteria decision-makers would use to set clinical service priorities, b) the processes they would follow, and c) the parameters according to which they would evaluate the success of the priority setting exercise.
We summarize key lessons learned from these workshops to help decision-makers in other health care organizations develop their own fair priority setting strategies and to improve understanding of researchers and policy makers about priority setting from the point of view of decision-makers.
Discussion
==========
Presentation of lessons learned
-------------------------------
### Priority setting criteria
When decision-makers were asked what criteria they would use to set clinical service priorities, we found that responses clustered around eight (8) criteria (Table [2](#T2){ref-type="table"}). As a step toward operationalising the Relevance condition of A4R, these criteria describe what decision-makers considered to be the most relevant decision factors (or \'reasons\') for setting clinical service priorities in their organisations.
\'Strategic fit\' described the extent to which clinical services contributed to advancing the strategic directions of the organisation, i.e., \"fit\" with the organization\'s vision, mission, values, and goals. This criterion was consistent with the idea that strategy should be a key driver of operational planning as a counterpoint to planning based on historical or short-term political considerations.
\'Alignment with external directives\' identified existing government mandates and legislated obligations as relevant considerations for setting priorities. For example, each organisation had government directives to provide particular health services at prescribed volumes. This criterion recognised explicitly the limited degrees of freedom within which priorities could be set, but also highlighted the importance for decision-makers of participating with government in achieving regional and provincial health service objectives.
\'Academic commitments\' consisted of two sub-criteria reflective of each organization\'s close affiliation with a local university and medical school. The \'education\' sub-criterion emphasised the role of clinical programs in educating future health care professionals and in facilitating the integration of these activities with health service delivery. The \'research\' sub-criterion emphasised the role of academic health science centres in establishing best practice standards, in generating new medical knowledge (including practice-based and bench research), and in developing technological innovation. Workshop participants felt that this criterion affirmed the unique role of academic health science centres in advancing society\'s health care knowledge and capacity.
\'Clinical impact\' was defined primarily in terms of the service volumes necessary to ensure the clinical competence of medical staff to provide safe and effective care to patients. Other relevant factors included: evidence of effectiveness in health promotion and disease prevention, uniqueness of the health service in the local area, and quality of the service provided. Workshop participants expressed concern about their ability to measure clinical impact given the limitations of their institutional decision support capabilities (e.g., data, trained decision support staff). However, they felt that by identifying these factors, this could provide direction for the collection of appropriate data and information.
\'Community need\' described the health service needs of patients in the organisation\'s local catchment area. This included current demand for health services, which could be measured on the basis of utilisation rates and waiting list data, as well as future demand based on population data and trends (e.g., aging population). Community need was further defined in terms of the availability of other health service providers. For example, community need was seen to be greater if the organisation were the sole provider of a health service to patients in the region than if there were other local providers whom patients might access for care.
\'Partnerships\' highlighted existing formal agreements and commitments with other organisations in coordinating delivery of health care to defined populations (e.g., referral agreements to ensure access to speciality care, or transfer agreements to coordinate the transition of patients from a hospital to a chronic continuing care facility). Partnerships were seen as effective ways to enhance service quality and to optimise resource utilisation within the region or local catchment area.
\'Interdependency\' described the coordination and collaboration between clinical services within the organization to enhance service quality (e.g., through interdisciplinary models of care) or to use institutional resources more efficiently. In the two organisations that had achieving a \"healthy\" workplace as a strategic goal, workshop participants also related this criterion to quality of work life factors as key enablers of effective clinical coordination and collaboration.
\'Resource implications\' included a cluster of factors related to the mobilisation and use of human and fiscal resources. Although recognising that strategic planning should not be over-determined by operational issues, workshop participants felt that the resource context was relevant for setting clinical service priorities. For example, the implications of prioritisation depended in part on the source of funding (e.g., base hospital budget, ministry of health volume-based funding, donation), the availability of staff (e.g., nurses) and capital resources (e.g., equipment, space), the flexibility of contractual agreements (e.g., union contracts), and the model of health service delivery, which could be more or less efficient in using available resources.
### Priority setting processes
When asked what key process elements would be needed in order for priority setting to be accountable and fair, workshop participants identified ten (10) elements (Table [3](#T3){ref-type="table"}). Some of these process elements reflected the Publicity, Revision, and Enforcement conditions of A4R. However, decision-makers identified additional process considerations that they felt were also essential for a successful priority setting process.
Workshop participants identified a number of preparatory steps that should be taken before priority setting can begin:
\(1) The organisation should establish, refine, or confirm its strategic plan. This is to ensure that the clinical service priorities that emerge through the priority setting process align with and advance the organisation\'s mission and strategic goals. In effect, workshop participants felt that they needed to know first where the organisation was going so that they could set the right priorities for getting there.
\(2) The programmatic architecture of the organization (i.e., what services are offered and how they are grouped administratively and programmatically) should be clarified in order to set clinical service priorities relative to current activities. This step was also felt to be important for defining precisely what order of clinical service activity was to be prioritised and for creating an accurate inventory of clinical services for prioritisation.
\(3) The specific responsibilities of the Board and senior management in relation to the priority setting process should be clarified explicitly and upfront. Decision-makers identified some confusion about these responsibilities given that clinical service priority setting involved an overlap of the strategic responsibility of the Board with the operational responsibility of Senior Management. During the workshop, Board members and Senior Managers drafted a memorandum of agreement delineating their respective roles and responsibilities in the priority setting process.
Workshop participants also identified a number of elements that were critical to the design of the priority setting process itself:
\(4) The executive decision-making group should be multidisciplinary and its role should be clearly and explicitly defined in advance of priority setting. Workshop participants emphasised the importance of shared accountability for priority setting across the clinical and administrative leadership. Engaging the medical leadership in a decision-making role was identified as key to developing a successful priority setting process. The engagement of other non-medical clinical leaders (e.g., nursing leadership) was also thought to be important for ensuring the legitimacy of the priority setting process.
\(5) Stakeholders should be engaged in the priority setting process. Although the organisational executive would ultimately be accountable for making the priority setting decisions, workshop participants felt that stakeholders could be engaged particularly as key informants through expert and broader stakeholder consultation. This consultation should include both internal stakeholders (e.g., staff, patient advisory groups) and external stakeholders (e.g., institutional partners, community groups, government officials).
\(6) Priority setting criteria should be clearly defined and understood by decision-makers and stakeholders. Data/information should be collected to support their application in the priority setting process. Workshop participants felt that the criteria identified in the workshop could be further refined through stakeholder engagement and tested with decision-makers to ensure a common interpretation of each criterion and consistency in their implementation.
\(7) An effective communication strategy should be developed to ensure a transparent priority setting process. The purpose of the communication strategy should be to ensure that stakeholders know and understand the scope and necessity of priority setting decision-making, the degrees of freedom within which priority setting would take place (including explicit identification of any \"sacred cows\" that would be immune from priority setting), and the particularities of the priority setting process (who will do what, how the process will work, and why). In addition, the rationales for priority setting decisions should be communicated to stakeholders and should clearly demonstrate how these decisions are defensible in light of the priority setting criteria and available data/information.
\(8) Decision review processes should be developed to incorporate opportunities to revisit and review decisions. Workshop participants saw these as additional opportunities to engage stakeholders around difficult priority setting decisions, although they also expressed concern that this might invite conflict between stakeholders and decision-makers. However, it was generally felt that this could be mitigated if decision review processes were focused explicitly on providing a vehicle for new data/information to be brought forward, material errors in the original decision to be corrected based on available data/information, and procedural inconsistencies to be addressed.
Workshop participants identified additional elements that were important to improve quality and strengthen capacity for fair priority setting in their organisations over time:
\(9) Process monitoring and formal evaluation strategies should be developed to ensure quality improvement and to realise a commitment to organizational learning. Workshop participants felt that the process should be monitored for adherence to the conditions of A4R, thus allowing for mid-course corrections to enhance fairness as the priority setting process unfolded. A formal evaluation process after priority setting would allow institutional good practices as well as opportunities for improvement to be captured so that this information could lead to improved priority setting in the future. For example, Martin & Singer have developed an ethics-based quality improvement model that focuses on evaluating and improving the fairness of priority setting processes \[[@B23]\].
\(10) The priority setting process should be supported by leadership development and change management strategies to strengthen institutional capacity for priority setting decision-making. Capacity strengthening should focus in particular on middle managers, who may not be among the decision-making group but who would play key roles in communicating with staff and in implementing the priority setting decisions.
### Parameters of successful priority setting
When asked how they would know that the priority setting process had been a success, workshop participants identified both outcome and process parameters (Table [4](#T4){ref-type="table"}). In either case, key marks of its success were whether the process were perceived to be an improvement over past priority setting initiatives and whether it were implemented in subsequent iterations of priority setting.
Outcome parameters focused on the effects of priority setting on organizational priorities and budget, on staff, and on the community. Effects on organizational priorities and budget concerned the extent to which the priority setting process was successful in changing organizational priorities and shifting resources, in supporting and/or enhancing the mission of the organization, in contributing to conditions for growth, and in balancing the organizational budget. Effects on staff involved an evaluation of the impact of priority setting on staff satisfaction and morale, organizational recruitment and retention initiatives, and overall understanding of new priorities across the organization. Effects on the community focused on how external stakeholders, including members of the public, regional partners, health care peers (e.g., other academic health science organisations), and affiliated academic institutions, responded to the priority setting initiative.
Process parameters focused on the efficiency and fairness of the priority setting process. Efficiency of the priority setting process could be evaluated in terms of whether priority setting improved institutional capacity for allocating resources and making priority setting decisions, and whether stakeholders and decision-makers felt that the priority setting process provided a worthwhile return on the time invested to set priorities. Fairness of the priority setting process could be evaluated in terms of whether stakeholders understood and felt engaged in the priority setting process, whether priority setting decisions were justified and seen to be reasonable, and whether \'winners\' and \'losers\' both felt that they had been fairly treated.
It was interesting to us that, although A4R was presented as an ethical framework for fair priority setting, workshop participants did not specifically identify conformity with its conditions as a parameter of success related to fairness. The importance of these conditions is clearly evident, however, among the fairness considerations they cited as well as the process elements they identified as key to setting priorities. Moreover, we had been invited to work with these executive teams precisely because they were seeking an ethical framework through which to improve how they set priorities in their organisations. This suggests to us that A4R was seen by workshop participants primarily as an ethical framework for process design rather than for the evaluation of priority setting processes *ex post facto*.
Implications of lessons learned
-------------------------------
Our findings from these three priority setting workshops illuminate the complex challenges faced by decision-makers in managing scarce health care resources. The range of criteria identified in the workshops provides insight into the competing goals (e.g., clinical vs. academic, local vs. systemic, strategic vs. operational) and multiple stakeholder relationships that decision-makers must consider in setting clinical service priorities. This is consistent with previous findings that efficiency considerations or simple technical solutions have only limited influence on decision-making and are not sufficient alone to guide priority setting decision-making \[[@B8],[@B17],[@B24],[@B25]\]. Given the range of interested stakeholders and competing values, our findings underscore the importance of procedural fairness to secure socially acceptable priority setting decisions and to ensure public accountability \[[@B8],[@B18],[@B26]\]. This suggests that a fair process model like A4R may be particularly suitable to help decision-makers set legitimate and fair clinical service priorities.
Although we report only on three health care organizations, the organisations were all academic health science centres facing similar resource challenges. Consensus around priority setting criteria and processes emerged independently among workshop participants in their large and small group discussions. However, this does not mean that these findings are exhaustive of the priority setting criteria that might be relevant for setting clinical service priorities (e.g., in community hospitals without academic affiliations) or the process elements that would be necessary to ensure a legitimate and fair priority setting process. Moreover, although our approach was based on the notion that fair priority setting requires a normative grounding in procedural justice -- in this case, A4R -- this does not mean that these findings are normatively \'right\' for clinical service priority setting in all health care organisations. An evaluation of the normative \'rightness\' depends to some extent on the specific institutional circumstances under which priority setting is taking place, the stakeholders who are affected, and the strategic goals that are being pursued. Experience shows, moreover, that the conditions of A4R are sufficiently general to guide fair priority setting in various institutional settings \[[@B9],[@B16],[@B20],[@B27]\]. Thus, decision-makers in other health care organisations may draw lessons from these workshops to operationalise fair priority setting processes that reflect the particularities of their institutional circumstances and ensure accountability for the reasonableness of their clinical service priorities.
Our experience shows that, from the perspective of Board members and senior leaders, our practical approach using A4R offers useful guidance for developing fair and publicly accountable priority setting processes under resource constraints. However, alternative priority setting approaches may also be beneficial. For example, program budgeting and marginal analysis, an economics-based approach, has been used with senior health care administrators in Canada and elsewhere to improve how priority setting optimises health and non-health benefits within available resources \[[@B13]\]. A comparison of priority setting approaches has not been done, however preliminary work has begun to explore a more interdisciplinary priority setting approach (Gibson JL, Mitton C, Martin DK, Donaldson C, Singer PA, manuscript submitted) \[[@B21]\].
Despite these possible limitations, the lessons we report here fill an important gap in the literature about the criteria, processes, and parameters of success decision-makers would use to set priorities using an ethical framework. We expect that decision-makers in other health care organizations may find themselves in the workshop participants\' experience of priority setting and may use these findings as a basis for discussing how they could enhance the fairness and public accountability of their own priority setting processes.
Summary
=======
• Hospitals and regional health authorities must set priorities in the face of resource constraints.
• Decision-makers seek pragmatic ways to set priorities fairly in strategic planning, but find limited guidance from the literature.
• We facilitated workshops for board members and senior leadership at three organizations to assist them in developing a strategy for fair priority setting.
• Workshop participants identified 8 priority setting criteria, 10 key priority setting process elements, and 6 parameters of success that they would use to set priorities in their organizations.
• Decision-makers in other organizations can draw lessons from these findings to enhance the fairness of their priority setting decision-making.
Competing interests
===================
The authors were compensated by the health care organizations for facilitating the priority setting workshops and continue to consult with these and other health care organizations.
Authors\' contributions
=======================
JLG conducted the workshops on which this paper is based, collated and analysed the data, and drafted the manuscript.
DKM participated in analysing the data and commented on earlier drafts of the manuscript.
PAS conducted the workshops on which this paper is based, participated in analysing the data, commented on earlier drafts of the manuscript, and conceived of the paper.
All authors read and approved the final manuscript.
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1472-6963/4/25/prepub>
Acknowledgments
===============
We would like to acknowledge gratefully the senior leadership at the Saskatoon Health Region, the Kingston General Hospital and the Ottawa Hospital who participated in the workshops and who have given us permission to share lessons learned from their workshops.
Grant support: The views expressed herein are those of the authors and do not necessarily reflect those of the supporting groups. Dr. Gibson was supported by a Canadian Health Services Research Foundation post-doctoral fellowship while writing this paper. Dr. Martin is supported by an Ontario Ministry of Health and Long-Term Care Career Scientist Award. Dr. Singer is supported by a Canadian Institutes of Health Research Distinguished Investigator award. This research was also supported by an Interdisciplinary Capacity Enhancement Grant from the Canadian Institutes of Health Research.
Figures and Tables
==================
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Accountability for reasonableness^16^
:::
----------------------- --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Relevance condition Decisions should be made on the basis of reasons (i.e., evidence, principles, arguments) that \"fair-minded\" people can agree are relevant under the circumstances.
Publicity condition Decisions and their rationales should be transparent and made publicly accessible.
Revision condition There should be opportunities to revisit and revise decisions in light of further evidence or arguments, and there should be a mechanism for challenge and dispute resolution.
Enforcement condition There should be either voluntary or public regulation of the process to ensure that the other three conditions are met.
----------------------- --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
:::
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Priority setting criteria
:::
--------------------------------------
• Strategic fit
• Alignment with external directives
• Academic commitments
-- Education
-- Research
• Clinical impact
• Community needs
• Partnerships (external)
• Interdependency (internal)
• Resource implications
--------------------------------------
:::
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Priority setting process elements
:::
------------------------------------------------------------------------------------
• Confirm the strategic plan
• Clarify programmatic architecture, including program groupings and definitions
• Clarify Board/Mgmt roles and responsibilities
• Determine who will make priority setting decisions and what they will do
• Engage internal/external stakeholders
• Define priority setting criteria and collect data/information
• Develop an effective communication strategy
• Develop a decision review process
• Develop process monitoring and evaluation strategies
• Support the process with leadership development and change management strategies
------------------------------------------------------------------------------------
:::
::: {#T4 .table-wrap}
Table 4
::: {.caption}
######
Parameters of success
:::
Outcome parameters Process parameters
-------------------------------------------------------------- ------------------------------------------------------------------------
*Effect on organizational priorities and budget* *Efficiency of priority setting process*
• Priorities change; resource shift • Increased ease in allocating resources
• Strategic plan supported/enhanced • Improved capacity for making priority setting decisions
• Conditions for growth created/enhanced • Perceived return on time invested
• Budget balanced
*Effect on staff* *Fairness*
• Staff satisfaction neutral or positive • Stakeholders understand the process
• Staff retention/recruitment neutral or positive • Stakeholders feel engaged
• Organizational understanding improved • Priorities are justified and seen to be reasonable
• Process is perceived to be consistent and fair
• Winners/losers issue well-managed
*Effect on community* *Conformity with conditions of \'accountability for reasonableness\'?*
• Public media recognition neutral or positive
• Public acceptance or community support improved
• Public perception of institutional accountability improved
• Health care integration through partnerships increased
• Education/research peer recognition enhanced
• Emulated by other organizations
:::
|
PubMed Central
|
2024-06-05T03:55:47.940190
|
2004-9-8
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC518972/",
"journal": "BMC Health Serv Res. 2004 Sep 8; 4:25",
"authors": [
{
"first": "Jennifer L",
"last": "Gibson"
},
{
"first": "Douglas K",
"last": "Martin"
},
{
"first": "Peter A",
"last": "Singer"
}
]
}
|
PMC518973
|
Background
==========
*Salmonella*Enteritidis is the most common serovar causing food-borne salmonellosis in humans, causing approximately 80% of salmonellosis cases reported in Europe \[[@B1]\]. During the 80s and early 90s, a steady increase in *S.*Enteritidis infections was reported in Europe and North America \[[@B2]-[@B4]\]. The most common phage types of *S*. Enteritidis varies between countries; while phage type (PT) 4 is reported to be dominant in most countries in Western Europe, PT 8 is common in North America and also a few European countries \[[@B5]-[@B7]\]. Epidemiological and environmental studies have implicated eggs and poultry products as primary risk factors for infection \[[@B3],[@B8]\]. Approximately 70% of outbreaks caused by S. Enteritidis in Europe during the 90s, were related to eggs and egg products \[[@B1]\]. Based on these findings, prevention and control measures in the egg and poultry industry have been implemented in the European Union and in the US \[[@B9],[@B10]\]. These measures seem to have been effective in reducing *S*. Enteritidis contamination of eggs \[[@B11]\] and are believed to have lead to a decrease in human incidence of *S.*Enteritidis in recent years \[[@B1],[@B9],[@B12]\].
In Sweden, about 85% of the reported salmonella infections are acquired during travel abroad and the levels in domestic animals and food products is low \[[@B13]\]. Therefore, trends in human salmonellosis in Sweden have mainly reflected trends in foreign travel and countries with popular package tour resorts account for the majority of infections.
In this study, we investigate trends in travel related *S.*Enteritidis infections, describe the phage type distribution of *S.*Enteritidis isolated from Swedish travellers returning from abroad related to country of infection, and discuss possible reasons for the emergence of a new phage type of *S.*Enteritidis in 2001. A preliminary analysis of a subset of these data was published as a short letter in the *Lancet*in 2002 \[[@B14]\].
Methods
=======
In Sweden, salmonellosis is a mandatory notifiable disease. Both clinicians and laboratories are required to report a case to the infectious disease register at the Swedish Institute for Infectious Disease Control (SMI). Based on the patient\'s travel history, information on probable country of infection is collected on the notification forms. Diagnosis of salmonella infections is made at regional microbiology laboratories, and all isolates are submitted to the national reference laboratory at SMI for serotyping and phage typing. In this study we have included all cases of *S.*Enteritidis notified to SMI from January 1, 1997 through December 31, 2002.
To investigate trends in travel-related infections, we collected information on air travel from the Swedish Civil Aviation Administration (CAA)\[[@B15]\]. The figures include all passengers carried on flights from any CAA airport to their first foreign destination, without indicating whether this destination is for transfer or the final destination. Using these figures as denominators, we calculated annual incidence rates for countries reported as place of infection for the three most popular countries for charter tourism among Swedes -- Spain, Greece and Turkey. The incidence rates were calculated by dividing the number of cases reported as infected in the respective countries by number of flight passengers to that country.
For the geographical description of dominant phage types in the different countries the analysis was restricted to infections acquired in countries in Europe during 1997 to 2002, and to countries from which more than ten cases were reported during this period. A phage type was considered dominant if it represented \>30% of the isolates and was at least twice as common as the second most common phage type. If none of the phage types fulfilled these criteria, the two most common phage types that together represented \>50% of the cases were defined as the dominant types. The pattern for 1997 to 2000 was compared with the pattern for 2001.
Results
=======
Of 13,271 cases of *S.*Enteritidis infections notified during 1997--2002, 11,570 cases (87%) were reported as infected abroad, 1,032 (8%) were reported as infected in Sweden, and information of probable country of infection was not available for 669 (5 %). The total number of cases reported each year varied from 1,598 to 2,629 cases, with the highest being reported in 1999 and the lowest in 2002. Imported cases varied between 1,404 and 2,164. The most common countries of infection during the six-year period were Spain, Greece and Turkey, accounting for 34%, 8% and 4% of all cases, respectively.
For six countries -- \'Spain, Greece, Turkey, Poland, Thailand and Portugal -- \>50 cases of infection with *S*. Enteritidis among Swedish travellers were reported each year during 1997 to 2002. These are all popular destinations for leisure travel among Swedes. Figure [1](#F1){ref-type="fig"} presents incidence rates for the three most popular countries for charter tourism, Spain, Greece and Turkey, using the number of flight passengers from Sweden to the first foreign destination as the denominator. The figure shows that the incidence rate among travellers to Spain and Turkey seemed to decrease during the six-year period, while for Greece the incidence peaked in 2001.
Eighty-six percent (10,049) of the isolates from 1997 to 2001 were phage-typed, increasing from 75% in 1997 to 95% in 2001. The most common phage types over the period were PT 4 and PT 1 (Figure [2](#F2){ref-type="fig"}), accounting for 35% and 16% of all cases, respectively. In travellers returning from most countries in Western Europe, PT 4 was the dominant phage type. In Eastern Europe, PT 1 was dominant, and this phage type was also common among travellers returning from the Iberian Peninsula. PT 8 seemed to be more common among travellers returning from central European countries.
In 2001 this pattern changed when PT 14b increased among travellers from several countries in Southern Europe (Figure [3b](#F3){ref-type="fig"}). PT 14b was the third most common phage type among returning travellers in 2001, accounting for 13% of all isolates that were phage-typed that year (272/2,132), compared with 2 % of all that were phage-typed in the previous four years (154/7,917). This trend continued into 2002 when PT14b accounted for 9% (134/1,489) of all typed isolates. The majority of the PT 14b cases in 2001 and 2002 were reported among travellers returning from Greece (Figure [4](#F4){ref-type="fig"}), and this phage type accounted for 54%(157/293), 47%(83/176) and 42%(50/117) of all cases of *S.*Enteritidis from Greece in 2001, 2002 and 2003, respectively.
Discussion
==========
We have described trends and phage type distribution of *S.*Enteritidis isolates among Swedish travellers infected abroad. Phage type 4 was the dominant phage type among returning travellers. There were, however, some differences in distribution between the countries and with time. Between 1997 and 2000, PT 1 dominated among travellers returning from Russia and the Baltic countries, PT 8 was commonly seen among travellers returning from some central European countries, and PT 4 dominated among travellers returning from most other European countries (Figure [3](#F3){ref-type="fig"}). In 2001 a change in phage type distribution was observed among Swedish travellers returning from some countries in South-Eastern Europe. PT 14b, a previously rare phage type, appeared to become predominant among travellers returning from Greece and also became more common among travellers from some other countries.
During the six-year period, the *S*. Enteritidis incidence rate among travellers to Spain and Turkey appeared to decline. This trend is in contrast to surveillance data from Spain, which seem to show an increasing incidence over the same period \[[@B16]\]. The reason for this declining trend among tourists was not investigated, but may be related to an increased awareness among tourists concerning the prevention of traveller\'s diarrhoea or to improved food control efforts in some of the popular tourist resorts.
There are some uncertainties when calculating incidence rates based on number of travellers. The number of travellers used as the denominator in the incidence rate calculations is based on the statistics of the airport of first landing after leaving Sweden. If the first airport is not the final destination, these travellers will not be included in the denominator for the destination country. Thus the calculated incidence rates for transit countries will be too low, while the incidence rates for the final destination countries will be too high.
When comparing *S.*Enteritidis phage types isolated from Swedish travellers with studies conducted in the countries visited, isolates found in travellers were generally consistent with the dominant strains reported among inhabitants in the respective countries. Table [1](#T1){ref-type="table"} summarises the results of published studies on salmonellosis from a number of countries. The percentages of PT 4 and PT 6 among human *S*. Enteritidis infections in Austria and Denmark, respectively, have been reported to be decreasing in the last years \[[@B6]\]. These same trends were reflected among returning Swedish travellers.
People returning from travel abroad may have a higher tendency to seek medical care and have a stool sample taken if an imported infection is suspected. In addition, visitors may be more susceptible to pathogens circulating in the community than the local inhabitants. The detection of new, emerging strains in travellers after returning to their home countries may therefore be helpful in detecting changes in the pathogen reservoir occurring in the countries visited, especially in tourist destinations. However, tourists have a tendency to aggregate in some smaller resorts that may have a different pathogen reservoir and rely on food supplies that are different from the rest of the country. This may lead to differences in risks and pathogens between the inhabitants and the tourists visiting the country that needs to be taken into consideration.
The change in phage type distribution observed among Swedish travellers returning from some countries in Southern Europe in 2001 was not observed among inhabitants in the countries visited. In total, the two most common phage types among Swedish travellers were, as in previous years, PT 4 and PT 1. However, the third most common was PT 14b, a phage type hitherto uncommon in Sweden with only 20 to 40 cases reported annually prior to 2001. The majority of the cases were among travellers returning from Greece (90%). More cases were also reported among travellers returning from Spain and Bulgaria than in previous years. During the same time period, an increase in the same phage type had also been registered among Norwegian and Finnish travellers returning from Greece \[[@B17]\]. A request on Enter-Net (European network for the surveillance of enteric infections -- *Salmonella*and VTEC O157) sent by the Norwegian Public Health Institute gave no response on increases of PT 14b in other countries. Spain reported an outbreak of the same phage in a school in January (unpublished data). But after this event, no further increase was noted. The UK later reported an increased number of the same phage type, both among travellers and among people who had been infected in the UK. However, there the 14b isolates of domestic origin were aerogenic, while isolates associated with travel to Greece were predominantly anaerogenic \[[@B18]\]. The isolates among Swedish travellers returning from Greece were also predominantly anaerogenic.
No explanation for the sudden increase in this phage type among Nordic travellers to different countries in Southern Europe has been found. PT 14b is not a new phage type and outbreaks reported previously have been mainly related to eggs and egg-products (ice-cream, tiramisu \[[@B19],[@B20]\]) or improper hygiene practices \[[@B21],[@B22]\]. However, these outbreaks were localised, of limited duration, and the incriminated food products found and the outbreaks contained. The cause of the increase of this phage type among Nordic travellers in 2001 is still unclear. It may represent a geographically more widespread outbreak than previously described, possibly due to increased trade in food products, animals or animal feed across the borders. Another possible explanation for this increase may be that changes in PT 14b could have contributed to increased resistance or virulence factors, thereby facilitating the spread of this phage type in the environment. Alternatively, acquisition or loss of a plasmid or spontaneous mutations may have resulted in a conversion from another phage type to PT 14b. Such change has been described for other phage types \[[@B23]-[@B25]\] and a conversion from PT 8 to PT 14b has been described after inoculation into pathogen-free chicken \[[@B26]\].
Our data presented are limited by the small numbers of cases from each country investigated on an annual basis. It is therefore difficult to evaluate trends with any certainty. However, the possibility of using surveillance data of infections among returning travellers to detect emerging pathogens should be further investigated. In addition, data from countries that routinely collect information on travel could be pooled in order to increase the numbers of travel-related infections. In several countries outside Europe, laboratory capacity is limited and it may take a long time to detect the emergence of new pathogens or subtypes. Not all countries in Europe collect information on the probable place of infection and phage typing of *Salmonella*isolates is not routinely performed in some countries. However, if available, this information will be included in the data reported to Enter-Net. Data from this network has previously been useful in detecting travel-related outbreaks \[[@B27],[@B28]\], and may also be useful in describing pathogen patterns in countries where laboratory capacities are limited or routine typing is not performed. Importantly, Enter-Net may expedite the dissemination of information concerning emerging pathogens.
Conclusions
===========
This study demonstrates that surveillance of infections among returning travellers may be helpful in detecting emerging infections and outbreaks in tourist destinations, and provides some useful supplementary data about infectious diseases and trends in other geographical regions. Characterization of isolates from travellers can detect changes in the pathogen and antimicrobial resistance patterns in the destination country. This information may be an important supplement in countries where surveillance systems are deficient or lacking, or where the laboratories have limited capacity to do detailed sub-typing and resistance testing. In addition, infections and outbreaks among tourists may not always affect the local residents and therefore may not be detected by the local public health authorities. If proper investigations, and appropriate prevention and control measures are to be implemented in the countries visited, it is important that the surveillance information compiled from the traveller\'s home countries is rapidly communicated to the affected countries.
Competing interests
===================
None declared.
Authors\' contributions
=======================
KN performed the data analysis and drafted the manuscript. PJG, YA and BdJ participated in the design and coordination of the study. AO conducted typing and provided advice regarding laboratory issues. JG participated in the design and discussion, and provided advice on data analysis. All authors read and approved the final manuscript.
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1741-7015/2/32/prepub>
Acknowledgements
================
We thank Dr Rebecca Grais-Freeman for her valuable comments on the manuscript.
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Incidence rates (IR) of *Salmonella*Enteritidis infections among Swedish travellers to Spain, Greece and Turkey. Country specific annual incidence rate of *Salmonella*Enteritidis per 100,000 air travellers from Sweden. Incidence rates are calculated based on the number of cases notified to the Swedish infectious Disease register using the number of flight passengers from Sweden to the first foreign destination as the denominator.
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Distribution of phage types of *Salmonella*Enteritidis cases notified in Sweden, 1997 to 2002.
:::
:::
::: {#F3 .fig}
Figure 3
::: {.caption}
######
Dominant phage types of *Salmonella*Enteritidis infections among Swedish travellers according to country visited. Only countries with more than 10 reported cases and phage types accounting for \> 25 % of all cases are shown. a) 1997 -- 2000 b) 2001
:::
:::
::: {#F4 .fig}
Figure 4
::: {.caption}
######
Notified cases of *Salmonella*Enteritidis PT 14b among Swedish travellers by country of infection, 1997 -- 2002.
:::
:::
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Dominant Salmonella Enteritidis phage types by country\*. Comparison between findings among Swedish travellers and studies conducted in the countries visited.
:::
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Country Number of *S*. Enteritidis-infections notified among Swedish travellers\ Most common *S*. Enteritidis phage types among returning Swedish travellers\ Predominant phage type described in studies from the country visited Year of study Reference
1997--2001 1997--2001(%\*)
------------------------ -------------------------------------------------------------------------- ------------------------------------------------------------------------------ ---------------------------------------------------------------------- --------------- -----------
Spain 4125 1 (33%), 4 (36%) 1, 4, 6 1990s \[29\]
Greece 1997--2000\ 916 4 (44%)\
14b (59%)
Turkey 496 4 (65 %) 4 Not mentioned \[30\]
Poland 354 4 (40 %) 4, 8 1986--95 \[31\]
Portugal 344 1 (43 %)
Morocco 310 4 (50 %)
Germany 235 4 (59%) 4 1998 \[32\]
Denmark 1997--1998\ 223 6 (42%), 8 (43%)\ 6, 8\ 1997--98\ \[33\]
1999\ 34 (73%)\ PT34 outbreak in DK\ 1999\
2000--2001 4 (30%), 8(30%) 4, 8 2000--2001
Czech Republic 194 8 (68%) 8 1989--98 \[34\]
Bulgaria 180 4 (55%
Cyprus 166 1 (36%), 4 (45%)
Tunisia 152 4 (75%)
Italy 152 4 (47%) 4 1990--93 \[29,35\]
United Kingdom 133 4 (76%) 4 1997--2000 \[36\]
Hungary 120 4 (50%) 4 1992--94 \[37\]
France 110 4 (56%)
Austria 1997--2000\ 81 4 (52%), 8 (38%)\ 4 1995--2001 \[6\]
2001 4 (33%), 8 (42%)
Latvia 1997--2000\ 76 1 (63%)\
2001 1 (60%), 4 (40%)
Egypt 63 4 (55%)
Croatia 53 4 (63%)
Belgium 45 4 (72%)
Russia 42 1 (62%) 1 1980--93 \[38\]
Estonia 1997--2000\ 37 1 (58%)\
2001 1 (25%), 4(75%)\*\*
Bosnia and Herzegovina 26 4 (64%)
The Netherlands 20 4 (75%) 4 1997--2001 \[6\]
Slovakia 14 8 (62%) 8 1995 \[39\]
Lithuania 12 1 (50%)
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
\* Calculated as a percentage of all isolates that were phage-typed during 1997--2001.
\*\* Based on less than 10 cases.
:::
|
PubMed Central
|
2024-06-05T03:55:47.942574
|
2004-9-2
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC518973/",
"journal": "BMC Med. 2004 Sep 2; 2:32",
"authors": [
{
"first": "Karin",
"last": "Nygård"
},
{
"first": "Birgitta",
"last": "de Jong"
},
{
"first": "Philippe J",
"last": "Guerin"
},
{
"first": "Yvonne",
"last": "Andersson"
},
{
"first": "Agneta",
"last": "Olsson"
},
{
"first": "Johan",
"last": "Giesecke"
}
]
}
|
PMC518974
|
Background
==========
Evidence on the journal-reading habits of clinicians comes from three separate groups of publications. First, several surveys have been used to ascertain the reading habits of physicians. Fafard and Snell \[[@B1]\] assessed house staff who reported reading an average of 8.7 hours per week, with about half of their time spent reading for specific patient situations. Reading time for family practice residents was more than three hours per week \[[@B2],[@B3]\] and ranged from 1--12 hours. Dermatology residents averaged 4.2 hours reading per week and read an average of seven journals, four of which were peer reviewed \[[@B4]\]. Internists read an average of 4.4 hours per week \[[@B3]\], while surgeons reported an average reading time of 3.5 hours across 3--16 journals \[[@B5]\]. This average of three-four hours of reading time per week is quite consistent across disciplines, level of education, time, and nationality.
A second set of surveys and studies center on general information-seeking behaviors of clinicians. These studies show how journal reading fits in with the other types of information that clinicians use. Two systematic reviews have been done recently.
Researchers at the Australian National Institute of Clinical Studies \[[@B6]\] reviewed preferred information sources in many clinician groups, including physicians (primary care/general practice/family practice, hospitalists, rural physicians, diabetologists); nurses (hospital and occupational health nurses); physical therapists; dental hygienists; and policy-makers. They reviewed 34 studies and concluded that all groups used multiple information resources, with information needs answered most often by other people, followed by books and journals. Dawes and Sampson \[[@B7]\] evaluated 19 studies of physician information-seeking behavior. They placed books and journals in one category (print resources) and found this to be the most used information source, with colleagues being the second.
The third source of information on clinicians\' use of information resources comes from marketing studies. The Association of Medical Publications \[[@B8]\] monitors physician use of printed journals and other information resources. Despite the rapid expansion of the Internet and all the information it contains, physicians continue to read and value journal articles, and their reliance on journals may be increasing. Data collected in 1983 and 1998 shows that physician reliance on journal literature as their main source of medical information increased from 61.8% to 76.3%, an absolute increase of 14.5% in 15 years.
The importance of reading journal articles for clinical care is evident. The increasing number of journals from which important and relevant articles are found, combined with the decreasing number of personal subscriptions \[[@B9]\], makes it more important than ever for physicians to choose carefully which journals to subscribe to and read. This decision should not be based on intuition alone, as shown in an important study by obstetricians and gynecologists. Weiner *et al.*\[[@B10]\] sought to determine which journals had published numerical data on the relation between oral contraceptive use and cancer--information they judged to be clinically important and readily available in their subspecialty journals. Assessing 3735 articles identified by MEDLINE searches, only 27 studies reported numerical data, of which 23 were published in mainstream general medical journals. Only four were published in obstetrics and gynecology journals.
Since the publication of the study by Weiner *et al.*\[[@B10]\], several groups have tried to determine targeted journal subsets that could provide the most important clinical information to physicians in different specialties. Birken and Parkin \[[@B11]\] assessed journals with pediatric content. Using data from pediatric-related systematic reviews in the *Cochrane Database for Systematic Reviews*for 1997, as well as policy statements from the American Academy of Pediatricians and the Canadian Paediatric Society, they determined that four general medical journals and three pediatric specialty journals provided access to most of the important advances: *Archives of Diseases in Childhood, BMJ, JAMA, Journal of Pediatrics, Lancet, New England Journal of Medicine,*and *Pediatrics*. Their results validate the findings of Weiner *et al.*--important studies in a discipline or specialty are often not published in specialty journals.
Gehanno and Thirion \[[@B12]\] used MEDLINE searches and the Science Citation Index (SCI) Impact Factors to identify journal subsets in occupational health. Eight journals provided coverage of 27% their discipline content; 38 journals increased this to 52%. Coverage needed to be expanded beyond their specialty journals for them to remain current in occupational health.
Lee *et al.*\[[@B13]\] sampled research articles from 30 randomly selected journals from a list of 107 general internal medicine journals defined by SCI. They found that journals with high citation rates, SCI Impact Factors, and circulation rates; low manuscript acceptance rates; and listing on the Brandon/Hill Library List \[[@B14]\] were predictive of higher article methodologic scores.
Ebell *et al.*\[[@B15]\] as well as our research group \[[@B16]\] present an alternative approach for clinicians to keep up to date with current literature. Both groups produce summaries of important advances in areas of clinical care so that individuals do not have to read primary journals and evaluate reports. Ebell *et al.*provided results of a hand search of 85 core journals of interest to family/general practice. Physicians read these journals for six months and identified articles that were considered to be POEMs (patient-oriented evidence that matters). A POEM addresses a clinical question encountered by a family physician at least once every two weeks, measures patient-oriented outcomes, and presents results that will likely affect practice. The report provides summaries of which journals publish important clinical advances for general/family practice.
In this article we report on a survey of the contents of 170 core clinical journals for the publishing year 2000 to assess which journals publish the highest number of methodologically sound and clinically relevant studies in the disciplines of internal medicine, general/family practice, general practice nursing, and mental health. In the \"Methods\" section we describe our two-step article selection process for clinical importance and methodologic rigor, which is very similar to that used by Ebell *et al.*\[[@B15]\]. The data we provide reflects the merit of individual journal titles from a clinical perspective; it may help clinicians to choose which journals to read, and health sciences libraries to include them in their collections.
Methods
=======
The Health Information Research Unit of the Department of Clinical Epidemiology and Biostatistics at McMaster University, Ontario, Canada, publishes several secondary \"evidence-based\" journals, systematically selecting, summarizing and appraising articles in a broad range of primary clinical journals. In 2000 we prepared *ACP Journal Club (ACP J Club)*to support internal medicine , *Evidence-Based Medicine (EBM)*to support general/family practice, *Evidence-Based Nursing (EBN)*to support general care nursing, and *Evidence-Based Mental Health (EBMH)*to support mental health. To identify potential candidate articles for inclusion in these journals, six Masters-level trained staff read each article in the major general healthcare journals and those in the disciplines and subdisciplines related to the content of each abstract journal. The list of these journals (see Additional File [1](#S1){ref-type="supplementary-material"}) is comprised of titles suggested by librarians, clinicians, editors, and editorial staff; SCI Impact Factors; and systematic examination of the contents of each title for at least six months. More than 400 journal titles have been assessed since the abstract journals were started in 1991.
We consider the *Cochrane Database of Systematic Reviews*to be a separate journal that publishes systematic reviews of the literature on a quarterly basis. This is consistent with the U.S. National Library of Medicine\'s decision to index the *Cochrane Database of Systematic Reviews*as a separate journal. We evaluate only the new reviews and those that are substantially updated each quarter. We do not consider the rest of the database or protocols that describe reviews that are in progress or being planned.
Original and review articles are placed in one or more of seven categories of study type--therapy and prevention, screening and diagnosis, prognosis, etiology and harm, economics and cost, clinical prediction guides, and qualitative studies \[[@B16]\]. All categories have a set of pass/fail rules for selection (see: <http://www.acpjc.org/shared/purpose_and_procedure.htm>), except for qualitative and cost studies. Basic inclusion criteria are that the articles i) are about the healthcare of humans; ii) have at least one clinically important outcome; and iii) use appropriate statistical analyses. As an example of category-specific criteria, an article on screening or diagnosis must meet these additional criteria:
• a spectrum of participants were included, some with the disease or condition of interest and some without
• objective diagnoses were made using the \"gold\" standard or current clinical standard for diagnosis of the disease or condition
• participants received both the new test and some form of the diagnostic standard
• the diagnostic standard was interpreted without knowledge of the test result and vice versa.
The basic inclusion criteria are based on study design and methodology principles for evidence-based healthcare. Their use identifies studies that have data related to patients or those at risk of disease, diseases and conditions, and real-life clinical settings. Therefore, a study or review article that meets the criteria can be considered to be appropriate for possible use in patient care decision-making. The article readers are trained and retested annually so that they can reliably apply these selection rules for inclusion in our evidence-based journals (kappa measuring chance-adjusted agreement \> 80% for all categories) \[[@B16]\].
With a research grant from the U.S. National Library of Medicine we intensified our data collection from the reading process related to the evidence-based journals for the publishing year 2000. All articles in 170 journals were classified as to whether they were \"of interest\" to the healthcare of humans and, if so, whether they reported original data or were systematic review articles. These original studies and reviews were classified into all possible categories (where more than one category could apply, for example, a therapy article that included economic data), and were then given a pass or fail methodologic designation for each category.
Articles passing methodologic criteria were assessed further for clinical interest by an editorial group of practicing clinicians for each abstract journal. These clinicians have expertise in methodology and specific areas of healthcare such as gastroenterology or neonatology nursing. At this point the clinician raters excluded all studies with preliminary results, interventions that were not readily available or proven useful, already known and applied findings, and topics addressing rare conditions or diseases. After review, often by a team of three-five clinicians (see <http://hiru.mcmaster.ca/more/RatingFormSample.htm> for a copy of the rating system that was used in paper format for this study) some articles were further processed. The editors chose articles to be abstracted that they considered to have the most important message for clinicians. The remaining pass articles were listed as \"Other Articles Noted\" if their content was of relevance to the disciplines covered by the abstract journals.
This dual selection process (methodologic rigor and clinical importance) provided insight into which journals yielded the highest numbers of pass articles. This had major implications for clinical practice at two levels of clinical relevance. The more stringent level includes articles that were summarized in each abstract journal. The second, less stringent level includes articles that are abstracted as well as those articles that are listed in the Other Articles Noted sections. Analysis was done by abstract journal title (*ACP J Club, EBM, EBN*, and *EBMH*) to ascertain which journal titles were most important to their target clinical audience (internal medicine, general/family practice, general practice nursing, and mental health, respectively). SCI Impact Factors were collected for each journal title for each discipline. If an SCI Impact Factor was not available we sought Social Science Index Impact Factors. These data were analyzed to determine if Impact Factors were related to yield of clinically important advances, as found by Lee *et al.*\[[@B13]\] and Gehanno and Thiron \[[@B12]\].
Results
=======
For 2000, the 170 core journals we selected published 60,352 articles. The total number of pass articles was 3059 for original studies and 1073 for reviews. An article could be counted more than once if it passed for multiple categories. Six journals did not publish any pass articles. The complete list of journals and their yield appears in the Additional File [1](#S1){ref-type="supplementary-material"}.
The category breakdown of pass articles for original studies and review articles, respectively, was 1639 and 662 for therapy and prevention, 152 and 47 for screening and diagnosis, 195 and 22 for prognosis, 290 and 308 for etiology and harm, 35 and 10 for economics, 358 and 8 for qualitative studies, and 93 and 4 for clinical prediction guides.
The top 20 journals for yield of pass articles are included in Table [1](#T1){ref-type="table"}. The titles varied considerably in both the total number and proportion of clinically relevant articles that they published. For example, 95.0% of the articles (all reviews) in the *Cochrane Database of Systematic Reviews*passed our criteria, while only 2.8% of the articles in the *American Journal of Gastroenterology*met standards for clinically applicable studies. (The *American Journal of Gastroenterology*is a specialty journal and a substantial proportion of its content is preclinical. These preclinical articles, by definition, did not meet the clinical criteria in this study.) Generally, a clinical reader would need to read in the range of 13--14 articles from these top 20 journals to obtain one that is directly clinically important in any healthcare area, although the range is substantial (1.1 to 36.9). We call this number the \"number of articles needed to be read\" or NNR.
The number of pass articles did not correlate with SCI Impact Factors for the top 20 journals (correlation coefficient 0.29, *P*= 0.24). Analysis of the top 50 titles showed a weak correlation (correlation coefficient 0.41, *P*= 0.004) for the same analysis.
The breakdown by discipline was done using the total number of articles that were selected for inclusion in each of the four abstract journals--internal medicine, general/family practice, general care nursing, and mental health (Tables [2](#T2){ref-type="table"},[3](#T3){ref-type="table"},[4](#T4){ref-type="table"},[5](#T5){ref-type="table"}). Both the total number of articles abstracted and the total number of articles in each journal (abstracted and \"Other Articles Noted\") are included in Tables [2](#T2){ref-type="table"}, [4](#T4){ref-type="table"}, and [5](#T5){ref-type="table"} giving a two-level assessment of \"clinical worth\". *EBM*does not publish an \"Other Articles Noted\" Section.
Internal medicine content (ACP J Club)
--------------------------------------
The journals contributing articles important to the practice of internal medicine (*ACP J Club)*are shown in Table [2](#T2){ref-type="table"}. Substantial drop-off is seen after the top three titles (*New England Journal of Medicine, JAMA,*and *Lancet)*. These three journals and the *Cochrane Database of Systematic Reviews*provided 56.5% of the articles abstracted, with 28 additional journals providing the other 43.5%. Fifteen titles provided only one article each and, overall, 32 journals provided at least one article for abstraction. Another 51 journals provided at least one article in the \"Other Articles Noted\" section. Thus, 83 journals from our list of 170 published studies important to internal medicine.
The NNR to obtain one high-quality and clinically relevant study or review varied considerably across the titles. For the more stringent definition of clinical relevance (article abstracted in *ACP J Club)*, the range of NNR for internal medicine was from 40.4 for the *Cochrane Database of Systematic Reviews*to 1334 for *Neurology*. For the less stringent definition (article abstracted or noted in *ACP J Club),*the NNR range for internal medicine was from 3.4 for the *Cochrane Database of Systematic Reviews*to 242 for *Acta Obstetrica et Gynaecologica Scandinavica*.
Correlating the number of articles published in *ACP J Club*with their SCI Impact Factor showed a large and positive correlation for both levels of clinical importance (correlation coefficient 0.786, *P*\< 0.001 for the more stringent definition; correlation coefficient 0.688, *P*\< 0.001 for the less stringent definition of clinical importance). These findings support the findings by Lee *et al.*\[[@B13]\] that SCI Impact Factors were correlated with quality articles for general internal medicine.
General/family practice content (EBM)
-------------------------------------
The most important articles for general/family practice (publication in *EBM*) were published in *BMJ, Lancet, Cochrane Database of Systematic Reviews, Archives of Disease in Childhood*, and *Annals of Internal Medicine*--these journals provided 55.6% of *EBM*content (Table [3](#T3){ref-type="table"}). Overall, 45 titles provided abstracts for general/family practice coverage. The \"shape\" of the data is different for general/family practice than for general internal medicine, with more journals providing articles for abstraction. This is consistent with the discipline because general/family practitioners must use knowledge from a broader range of health conditions (including pediatrics and obstetrics, for example) than general internists and other specialists. Only the most stringent definition for clinical worth could be evaluated for *EBM*content because the \"Other Articles Noted\" section of the journal did not exist in the year 2000. The NNR for general/family practice ranged from 55 for the *Cochrane Database of Systematic Reviews*to 1351 for *Circulation*.
Correlation analysis showed that the number of qualified articles in each journal title was associated with the journal\'s SCI Impact Factor (correlation coefficient 0.546, *P*= \< 0.001). This shows substantial agreement between SCI Impact Factors and number of articles but slightly less agreement than that found using the general internal medicine data (correlation coefficients \> 0.688).
General care nursing content (EBN)
----------------------------------
Nursing content came from many journals, including journals that are considered to be primarily targeted at physicians, and was not concentrated in a small set of journal titles (Table [4](#T4){ref-type="table"}). To reach 51.0% of the abstracted articles, seven titles were needed (*Qualitative Health Research, Cochrane Database of Systematic Reviews, Pediatrics, JAMA, Lancet, BMJ*, and *Journal of Advanced Nursing*). Thirty-two other journals provided articles for abstraction and 33 journals provided studies that were listed only in the \"Other Articles Noted\" section; 72 journals in total provided content for general care nursing. The NNR for general practice nursing was variable, ranging from 6.0 for *Qualitative Health Research*to 1530 for *New England Journal of Medicine*for the more stringent definition of clinical relevance. For the less stringent definition of clinical relevance the NNRs ranged from 4.7 for *Qualitative Health Research*to 923 for *American Journal of Gastroenterology*. The low NNR for *Qualitative Health Research*undoubtedly reflects the fact that only clinical criteria for relevance were applied in the selection of qualitative studies, not explicit methodologic criteria. The reason for lack of methodologic criteria for qualitative studies was that we have been unable to obtain agreement from qualitative researchers of what the quality criteria should be.
No correlation was seen between number of articles published per journal title and SCI Impact Factors for either the stringent definition of clinical relevance (correlation coefficient 0.096, *P*= 0.57) or the less strict definition (correlation coefficient 0.256, *P*= 0.038).
Mental health content (EBMH)
----------------------------
Mental health content was also spread over a broader range of journals than was internal medicine (Table [5](#T5){ref-type="table"}). To reach 53.2% of the articles abstracted, nine titles needed to be read: *Archives of General Psychiatry, Cochrane Database of Systematic Reviews, American Journal of Psychiatry, British Journal of Psychiatry, JAMA, Lancet, International Journal of General Psychiatry, Journal of the American Academy of Child and Adolescent Psychiatry,*and *Journal of Consulting and Clinical Psychology.*Forty-one titles provided at least one article for abstraction. The titles in Table [5](#T5){ref-type="table"} show that studies related to mental health are published in many journals and specialties--a reflection of the broad nature of the discipline. The NNR for mental health for the most stringent definition of clinical relevance ranged from 20.1 for *Archives of General Psychiatry*to 1142.7 for *BMJ*. *Archives of General Psychiatry*also has the lowest NNR for the less stringent definition (11.5), with *CMAJ*having the highest NNR (1007) of those journals with at least one article on mental health. *EBMH*has a smaller \"Other Articles Noted\" section. Only eight additional journals provide articles for this section beyond the 61 that provide articles for abstraction.
A weak association was shown between the number of published mental health articles and SCI Impact Factors (correlation coefficient 0.386, *P*= 0.02 for the more stringent definition; and correlation coefficient 0.381, *P*= 0.01 for the less stringent definition).
All disciplines
---------------
Combining the content across the four discipline areas, we again see the concentration of important clinically relevant articles in a small subset of journals. Eight journals provided at least one article for abstraction to all four abstract journals: *Annals of Internal Medicine, Archives of Internal Medicine, BMJ, CMAJ, Cochrane Database of Systematic Reviews, JAMA, Lancet,*and *New England Journal of Medicine.*Another 10 journals provided at least one article to three of the four abstract journals: *American Journal of Medicine, Archives of General Psychiatry, British Journal of General Practice, British Journal of Surgery, Health Psychology, Journal of Clinical Epidemiology, Journal of Clinical Psychopharmacology, Journal of Family Practice, Journal of the American Geriatrics Society,*and *Pediatrics.*Twenty-eight journals provided studies to two of the abstract journals, 36 provided articles to at least one abstract journal, and 82 titles provided no articles for abstraction (excluding the six titles that did not publish any pass articles).
Conclusions
===========
We found that the majority of articles for each discipline were sequestered in a small subset of journals. This is consistent with Bradford\'s Law of Scattering for journal subsets, which states that the important articles on any topic will be concentrated in a small subset of journals with exponential drop-off in numbers of relevant articles across journal titles \[[@B17]\]. Across disciplines and study areas, approximately 70% of articles are often found in 30% of journals in any given area of study.
Not surprisingly, for broad-based disciplines such as mental health and nursing, the number of titles was greater than for more focused disciplines such as internal medicine. SCI Impact Factors were highly correlated with the number of important clinical articles in separate titles for internal medicine and, to a lesser extent, for general/family practice, and mental health but not for general practice nursing. This likely reflects the volume of clinically important research activity in these fields--with especially high volumes in the disorders managed by internal medicine and its subspecialties--coupled with the avidity of authors from all disciplines to submit their best studies to the high-circulation general journals.
As found by Weiner *et al.*\[[@B10]\] and others, most of the important advances in any discipline are not published in specialty journals but in the more general healthcare journals such as *JAMA, Lancet, BMJ, New England Journal of Medicine,*and *Cochrane Database of Systematic Reviews*. Health professionals in all disciplines should be aware that major advances in any field will most likely be published in the main general medicine journals, while at the same time recognizing that specialty journals also publish important information. Much variation exists across journal titles in both the number and proportion of articles that are high quality, clinically important, and newsworthy. Variation also exists across disciplines. It is also interesting to note that all lists of important journals discussed in this report and also the one by Ebell *et al.*\[[@B15]\] include both North American and European titles. Reading choices for clinicians cannot be based on national or discipline boundaries alone.
Of the 45 titles that provided articles to *EBM*, 23 were on the list provided by Ebell *et al.*(POEM articles) \[[@B15]\]. Ebell *et al.*found common POEMs in 49 journals and any POEMs in 64 journals. POEMs and *EBM*cover the content of general/family practice by considering a similar number of journals, although both groups read approximately 50% unique titles. Ebell *et al.*read 85 titles for POEMs articles and we read 170 titles for this study. Our coverage of clinical content was broader and included internal medicine, general practice nursing, and mental health, but 53 titles were read by both groups. Correlational analysis for the ranking of each journal title according to the number of articles identified as clinically important showed a small but significant agreement (0.4397, *P*= 0.005) when comparing our list with the list by Ebell *et al.*
Consistent with the data from Weiner *et al.*\[[@B10]\], many advances important to general practice nursing are not published in nursing specialty or discipline-specific journals. Only four of the top 17 and eight of the top 41 journals in Table [4](#T4){ref-type="table"} are considered nursing specialty titles. Overall 39 titles provided at least one article for abstraction and an additional 33 titles provided at least one article to the \"Other Articles Noted\" section, again showing the broader spectrum of journals that publish articles important to general care nursing.
Clinicians in the target disciplines described here could use our findings to focus their fulltext readings. For other disciplines, a similar audit of clinical yield would be needed, either from an appropriate secondary journal that systematically reviews specified journals, or an independent audit. Another approach to staying current may be to subscribe to one or more secondary journals that highlight important clinical advances. These secondary publications have not only selected the most appropriate studies for clinical consideration, they highlight important aspects of methodology and implementation. This assessment of studies before application can be time-consuming and difficult for many clinicians, and involves a certain amount of training and practice to become proficient. Many examples of secondary publications exist in various disciplines and include the four studied in this report, POEMs \[[@B15]\], and *Journal Watch*. Use of these summaries of studies and reviews can be supplemented by access to fulltext articles.
Many academic medical centers and hospitals provide good online access to major healthcare journals. For example, the Health Sciences Library of the University of Pittsburgh, PA, USA, provides online access to 24 of the top 25 journals in this study and all 25 of the journals identified as high yielders by Ebell *et al.*\[[@B15]\]. Specialized health libraries with limited budgets may wish to focus on the journals, either in paper or electronic format, with the highest yield for the disciplines they serve.
List of abbreviations
=====================
ACP J Club *ACP Journal Club*(journal)
AHCPR Agency for Health Care Policy and Research (now AHRQ)
AHRQ Agency for Healthcare Research and Quality (formerly AHCPR)
CCOHTA Canada Coordinating Office for Health Technology Assessment
EBM *Evidence-Based Medicine*(journal)
EBMH *Evidence-Based Mental Health*(journal)
EBN *Evidence-Based Nursing*(journal)
NNR Number of articles needed to read to obtain one high-quality and clinically relevant study or review
POEM Patient-oriented evidence that matters
SCI Science Citation Index
Competing interests
===================
The authors all worked with *ACP Journal Club, Evidence-Based Medicine, Evidence-Based Nursing,*and *Evidence-Based Mental Health*at the time of this study, and were paid for this work, but the publishers of these journals were not involved in the study, which was funded externally. The authors do not hold stocks or shares in any company that may benefit from the publication of this paper.
Author contributions
====================
NLW and RBH prepared grant submissions in relation to this project. All authors drafted and commented on the manuscript and approved the final manuscript, as well as supplied intellectual content to the collection and analysis of the data. NLW and KAM did data collection and analysis, and supervised research staff.
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1741-7015/2/33/prepub>
Supplementary Material
======================
::: {.caption}
###### Additional File 1
Additional File 1 includes a list of the 170 journals read for 2000 along with the number of articles reviewed, the number and percentage that passed criteria, and the NNR (number of articles that are needed to be read to obtain one that is clinically relevant and has high-quality methods). The file name is \"Publishing Important Articles Appendix.doc\" and it is in Word 2000 format.
:::
::: {.caption}
######
Click here for file
:::
Acknowledgements
================
This research was funded by the U.S. National Library of Medicine. A preliminary version of the findings was accepted as a poster for the International Congress on Peer Review in Biomedical Publication, Barcelona, Spain, 14 September, 2001.
The Hedges Team who did the data collection, entry, and verification included Nancy Bordignon, Angela Eady, Brian Haynes, Susan Marks, Ann McKibbon, Doug Morgan, Cindy Walker Dilks, Stephen Walter, Nancy Wilczynski, and Sharon Wong. Marcus Loretti provided additional data analysis.
Figures and Tables
==================
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Number of high-quality, clinically relevant articles in the top 20 clinical journals for 2000
:::
**Journal title** **Number of articles with abstracts (from MEDLINE)** **Number of articles evaluated** **Number of pass articles / number evaluated (% pass)** **NNR\* for number evaluated** **SCI Impact Factor\*\* for 2000**
----------------------------------------------------- ------------------------------------------------------ ---------------------------------- --------------------------------------------------------- -------------------------------- ------------------------------------
*Cochrane Database of Systematic Reviews* 1004 444 422 (95.0) 1.1 Not available
***Lancet*** **669** **3858** **134 (3.5)** **28.8** **10.2**
*Journal of Clinical Oncology* 445 650 100 (15.4) 6.6 8.8
***BMJ*** **209** **3428** **93 (2.7)** **36.9** **5.3**
*Circulation* 925 1351 92 (6.8) 14.7 10.9
***Journal of Advanced Nursing*** **341** **611** **92 (15.1)** **6.6** **0.77**
*Obstetrics and Gynecology* 389 478 88 (18.4) 5.4 2.0
***JAMA*** **329** **1930** **87 (4.5)** **22.2** **16.4**
*New England Journal of Medicine* 228 1530 83 (5.4) 18.4 29.5
***Archives of Internal Medicine*** **340** **620** **81 (13.1)** **7.7** **6.1**
*Journal of the American College of Cardiology* 514 707 76 (10.7) 9.3 7.1
***Pediatrics*** **548** **811** **76 (9.4)** **10.7** **4.8**
*American Journal of Cardiology* 631 850 72 (8.5) 11.6 2.7
***American Journal of Obstetrics and Gynecology*** **539** **704** **72 (10.2)** **9.8** **2.5**
*Critical Care Medicine* 340 977 70 (7.2) 14.0 3.8
***Chest*** **589** **882** **66 (7.5)** **13.4** **2.5**
*Stroke* 402 609 59 (9.7) 10.3 6.0
***Neurology*** **814** **1334** **58 (4.3)** **23.0** **4.8**
*American Journal of Gastroenterology* 474 923 56 (2.8) 16.6
***Diabetes Care*** **263** **529** **55 (10.4)** **9.6** **5.0**
Average 7.3% 13.8
\*The NNR is the number of articles that would have to be read in each journal to identify one with high quality methods that is clinically relevant; \*\*The SCI Impact Factor is the Science Citation Index Impact Factor (rating of how important each journal is in relation to citations). Data are for 2000. Articles have not been screened for direct clinical relevance beyond basic criteria of having at least one clinically important outcome.
:::
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
*ACP J Club*(internal medicine) journal-specific content of high-quality, clinically relevant articles
:::
**Journal title** **Number articles reviewed in 2000** **Number abstracted (% included in *ACP J Club*)** **NNR for abstracted article** **Number abstracted or listed (% included in *ACP J Club*)\*** **NNR for abstracted or listed\*\***
------------------------------------------------------------------------- -------------------------------------- ---------------------------------------------------- -------------------------------- ---------------------------------------------------------------- --------------------------------------
*New England Journal of Medicine* 1530 25 (16.9) 61.2 67 (6.7) 22.8
***JAMA*** **1930** **25 (16.9)** **77.2** **53 (5.4)** **36.4**
*Lancet* 3858 22 (14.9) 175.4 62 (6.6) 62.2
***Cochrane Database Systematic Reviews\*\*\**** **444** **11 (7.4)** **40.4** **130 (13.1)** **3.4**
*Annals of Internal Medicine* 602 8 (5.4) 75.3 33 (3.3) 18.2
***Archives of Internal Medicine*** **620** **6 (4.1)** **103.3** **57 (5.8)** **24.8**
*BMJ* 3428 5 (3.4) 685.6 50 (5.1) 68.6
***Circulation*** **1351** **5 (3.4)** **270.2** **33 (3.3)** **40.9**
*AHRQ/AHCPR Reports\*\*\** N.A. 4 (2.7) N.A. 9 (1.0) N.A.
***American Journal of Gastroenterology*** **923** **4 (2.7)** **225.6** **21 (2.1)** **44.0**
*American Journal of Medicine* 435 3 (2.0) 130.5 21 (2.1) 20.7
***CMAJ (formerly Canadian Medical Association Journal)*** **1007** **3 (2.0)** **335.7** **12 (1.2)** **83.9**
*Diabetic Medicine* 188 3 (2.0) 62.6 13 (1.3) 14.5
***Thorax*** **336** **3 (2.0)** **112.0** **8 (0.8)** **42.0**
*Annals of Emergency Medicine* 294 2 (1.4) 147.0 11 (1.1) 26.7
***Journal of the American Geriatrics Society*** **384** **2 (1.4)** **192.0** **18 (1.8)** **21.3**
*Journal of Vascular Surgery* 544 2 (1.4) 272.0 6 (0.6) 9.0
***American Journal of Cardiology*** **850** **1 (0.7)** **850.0** **14 (1.4)** **60.7**
*Archives of Neurology* 313 1 (0.7) 313 2 (0.2) 156.5
***British Journal of Surgery*** **402** **1 (0.7)** **402** **6 (0.6)** **67.0**
*CCOHTA Reports\*\*\*\** N.A. 1 (0.7) N.A. 1 (0.1) N.A.
***Critical Care Medicine*** **977** **1 (0.7)** **977** **24 (2.4)** **40.7**
*Diabetes Care* 529 1 (0.7) 529 14 (1.4) 37.8
***Gastroenterology*** **543** **1 (0.7)** **543** **5 (0.5)** **108.5**
*Gut* 446 1 (0.7) 446 6 (0.6) 74.3
***Health Psychology*** **79** **1 (0.7)** **79** **3 (0.3)** **26.6**
*Journal of Clinical Psychopharmacology* 162 1 (0.7) 162 1 (0.1) 81.0
***Journal of Family Practice*** **263** **1 (0.7)** **263** **10 (1.0)** **26.3**
*Journal of Infectious Diseases* 760 1 (0.7) 760 6 (0.6) 126.7
***Neurology*** **1334** **1 (0.7)** **1334** **12 (1.2)** **111.2**
*Spine* 604 1 (0.7) 604 14 (1.4) 43.1
***Stroke*** **609** **1 (0.7)** **609** **26 (2.6)** **101.5**
*Acta Obstetrica et Gynecologica Scandinavica* 242 0 (0.0) 1 (0.1) 242.0
***Addiction*** **295** **0 (0.0)** **Infinity** **4 (0.4)** **63.8**
*Age and Ageing* 767 0 (0.0) Infinity 6 (0.6) 127.8
***Alimentary Pharmacology and Therapeutics*** **N.A.** **0 (0.0)** **N.A.** **4 (0.4)** **N.A.**
*American Journal of Epidemiology* 362 0 (0.0) Infinity 18 (1.8) 20.1
***American Journal of Obstetrics and Gynecology*** **704** **0 (0.0)** **Infinity** **2 (0.2)** **352.20**
*American Journal of Psychiatry* 508 0 (0.0) Infinity 1 (0.1) 508
***American Journal of Public Health*** **363** **0 (0.0)** **Infinity** **5 (0.5)** **72.6**
*American Journal of Respiratory and Critical Care Medicine* 783 0 (0.0) Infinity 9 (0.9) 87.0
***Annals of Rheumatic Diseases*** **266** **0 (0.0)** **Infinity** **1 (0.1)** **266.0**
*Annals of Surgery* 301 0 (0.0) Infinity 3 (0.3) 100.3
***Archives of Family Medicine (no longer published)*** **230** **0 (0.0)** **Infinity** **6 (0.6)** **38.3**
*Archives of General Psychiatry* 161 0 (0.0) Infinity 2 (0.2) 80.5
***Archives of Physical Medicine and Rehabilitation*** **337** **0 (0.0)** **Infinity** **4 (0.4)** **84.3**
*Archives of Surgery* 330 0 (0.0) Infinity 3 (0.3) 103.3
***Australian and New Zealand Journal of Psychiatry*** **214** **0 (0.0)** **Infinity** **1 (0.1)** **214.0**
*British Journal of General Practice* 453 0 (0.0) Infinity 3 (0.3) 151
***British Journal of Psychiatry*** **402** **0 (0.0)** **Infinity** **2 (0.2)** **201**
*Canadian Journal of Gastroenterology* 145 0 (0.0) Infinity 3 (0.3) 48.3
***Canadian Journal of Infection Control*** **31** **0 (0.0)** **Infinity** **1 (0.1)** **31.0**
*Canadian Respiratory Journal* 68 0 (0.0) Infinity 2 (0.2) 34.0
***Cancer*** **786** **0 (0.0)** **Infinity** **3 (0.3)** **262.0**
*Chest* 882 0 (0.0) Infinity 21 (2.1) 42.0
***Heart*** **450** **0 (0.0)** **Infinity** **6 (0.6)** **75.0**
*Heart and Lung* 59 0 (0.0) Infinity 1 (0.1) 59.0
***Hypertension*** **419** **0 (0.0)** **Infinity** **6 (0.6)** **69.8**
*International Journal of Geriatric Psychiatry* 169 0 (0.0) Infinity 6 (0.6) 28.2
***Journal of Affective Disorders*** **154** **0 (0.0)** **Infinity** **3 (0.3)** **51.3**
*Journal of the American Board of Family Practice* 121 0 (0.0) Infinity 1 (0.1) 121.0
***Journal of the American College of Cardiology*** **707** **0 (0.0)** **Infinity** **29 (2.9)** **24.4**
*Journal of Bone and Joint Surgery (US)* 360 0 (0.0) Infinity 1 (0.1) 360.0
***Journal of Clinical Epidemiology*** **173** **0 (0.0)** **Infinity** **8 (0.8)** **21.6**
*Journal of Epidemiology and Community Health* 205 0 (0.0) Infinity 6 (0.6) 34.2
***Journal of General Internal Medicine*** **155** **0 (0.0)** **Infinity** **9 (0.9)** **17.2**
*Journal of Internal Medicine* 177 0 (0.0) Infinity 4 (0.4) 44.3
***Journal of Neurology and Neurosurgery and Psychiatry*** **478** **0 (0.0)** **Infinity** **7 (0.7)** **68.3**
*Journal of Psychosomatic Research* 118 0 (0.0) Infinity 6 (0.6) 19.7
***Journal of Rheumatology*** **657** **0 (0.0)** **Infinity** **4 (0.4)** **164.3**
*Journal of Trauma Injury Infection and Critical Care* 562 0 (0.0) Infinity 2 (0.2) 281.0
***Medical Care*** **162** **0 (0.0)** **Infinity** **7 (0.7)** **32.1**
*Medical Journal of Australia* 598 0 (0.0) Infinity 1 (0.1) 598.0
***Pain*** **269** **0 (0.0)** **Infinity** **7 (0.7)** **38.4**
*Patient Education and Counseling* 94 0 (0.0) Infinity 1 (0.1) 13.3
***Pediatrics*** **811** **0 (0.0)** **Infinity** **2 (0.2)** **405.5**
*Psychology and Aging* 55 0 (0.0) Infinity 1 (0.1) 55.0
***Psychological Medicine*** **142** **0 (0.0)** **Infinity** **4 (0.4)** **35.3**
*Psychosomatic Medicine* 106 0 (0.0) Infinity 1 (0.1) 106.0
***Qualitative Health Research*** **60** **0 (0.0)** **Infinity** **1 (0.1)** **60.0**
*Radiology* 654 0 (0.0) Infinity 1 (0.1) 654.0
***Rheumatology*** **339** **0 (0.0)** **Infinity** **9 (0.9)** **37.7**
*Social Science and Medicine* 302 0 (0.0) Infinity 2 (0.2) 151.0
***Western Journal of Nursing Research*** **99** **0 (0.0)** **Infinity** **1 (0.1)** **99.0**
*TOTAL* 148 (100) 990 (100)
*Correlation with SCI Impact Factors-correlation coefficient (P-value)* N.A. 0.788 (\< 0. 001) N.A. 0.688 (\< 0.001) N.A.
\*Articles abstracted are those that pass methodological criteria and are deemed to be the most important by practicing internists. The other articles listed are articles with the same high-quality methods but are considered to be slightly less important clinically by practicing clinicians; \*\*The number of articles needed to read (NNR) is a measure of the ratio of number of relevant articles (abstracted or combined abstracted or listed) divided into the total number of articles for each journal title; \*\*\*SCI Impact Factors not available for analysis; \*\*\*\*Canada Coordinating Office for Health Technology Assessment Reports; N.A. Not applicable. Data are for 2000. Note that the AHRQ/AHCPR and CCOHTA reports were not considered journal titles and read as such for this report.
:::
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
*EBM*(general/family practice) journal-specific content of high-quality, clinically relevant articles^†^
:::
**Journal title** **Number articles in 2000 in journal** **Number abstracted (% included in *EBM*)** **NNR for abstracted article** **Number abstracted or listed (% included in *EBM*)\*** **NNR for abstracted or listed\*\***
------------------------------------------------------------------------- ---------------------------------------- --------------------------------------------- -------------------------------- --------------------------------------------------------- --------------------------------------
*JAMA* 1930 18 (12.5) 107.2 N.A. N.A.
***BMJ*** **3428** **17 (11.8)** **201.6** **N.A.** **N.A.**
*Lancet* 3858 17 (11.8) 226.9 N.A. N.A.
***New England Journal of Medicine*** **1530** **13 (9.0)** **117.6** **N.A.** **N.A.**
*Cochrane Database of Systematic Reviews\*\*\** 444 8 (5.6) 55.0 N.A. N.A.
***Annals of Internal Medicine*** **602** **7 (4.9)** **86.1** **N.A.** **N.A.**
*AHRQ/AHCPR Reports\*\*\** \-- 6 (4.2) N.A. N.A. N.A.
***Archives of Disease in Childhood*** **392** **4 (2.8)** **98.0** **N.A.** **N.A.**
*American Journal of Medicine* 435 4 (2.8) 108.8 N.A. N.A.
***Archives of Family Medicine (no longer published)*** **230** **3 (2.1)** **76.7** **N.A.** **N.A.**
*Journal of Family Practice* 263 3 (2.1) 87.7 N.A. N.A.
***Annals of Emergency Medicine*** **294** **2 (1.4)** **147.0** **N.A.** **N.A.**
*BJOG (formerly British Journal of Obstetrics and Gynaecology)* 334 2 (1.4) 157.0 N.A. N.A.
***British Journal of Psychiatry*** **335** **2 (1.4)** **167.5** **N.A.** **N.A.**
*Journal of Pediatrics* 444 2 (1.4) 222.0 N.A. N.A.
***American Journal of Gastroenterology*** **923** **2 (1.4)** **461.5** **N.A.** **N.A.**
*British Journal of Surgery* 402 2 (1.4) 201 N.A. N.A.
***Diabetic Medicine*** **188** **2 (1.4)** **144** **N.A.** **N.A.**
*Journal of Vascular Surgery* 544 2 (1.4) 272 N.A. N.A.
***Neurology*** **1334** **2 (1.4)** **667.0** **N.A.** **N.A.**
*Pediatrics* 811 2 (1.4) 405.5 N.A. N.A.
***Annals of Surgery*** **301** **1 (0.7)** **301** **N.A.** **N.A.**
*Archives of General Psychiatry* 161 1 (0.7) N.A. N.A.
***Archives of Internal Medicine*** **620** **1 (0.7)** **620** **N.A.** **N.A.**
*Archives of Neurology* 313 1 (0.7) 313 N.A. N.A.
***Archives of Pediatric and Adolescent Medicine*** **273** **1 (0.7)** **273** **N.A.** **N.A.**
*Arthritis and Rheumatology* 440 1 (0.7) 440 N.A. N.A.
***British Journal of General Practice*** **453** **1 (0.7)** **453** **N.A.** **N.A.**
*Canadian Respiratory Journal* 68 1 (0.7) 68 N.A. N.A.
***Circulation*** **1351** **1 (0.7)** **1351** **N.A.** **N.A.**
*CMAJ (formerly Canadian Medical Association Journal)* 1007 1 (0.7) 1007 N.A. N.A.
***Diabetes Care*** **529** **1 (0.7)** **529** **N.A.** **N.A.**
*Gastroenterology* 543 1 (0.7) 543 N.A. N.A.
***Gut*** **446** **1 (0.7)** **446** **N.A.** **N.A.**
*Health Psychology* 79 1 (0.7) 79 N.A. N.A.
***Heart*** **450** **1 (0.7)** **450** **N.A.** **N.A.**
*Journal of the American Geriatrics Society* 384 1 (0.7) 384 N.A. N.A.
***Journal of Clinical Epidemiology*** **173** **1 (0.7)** **173** **N.A.** **N.A.**
*Journal of Clinical Psychopharmacology* 162 1 (0.7) 162 N.A. N.A.
***Journal of Infectious Disease*** **760** **1 (0.7)** **760** **N.A.** **N.A.**
*Medical Care* 162 1 (0.7) 162 N.A. N.A.
***Medical Journal of Australia*** **598** **1 (0.7)** **598** **N.A.** **N.A.**
*Rheumatology* 339 1 (0.7) 339 N.A. N.A.
***Spine*** **604** **1 (0.7)** **604** **N.A.** **N.A.**
*Thorax* 336 1 (0.7) 336 N.A. N.A.
*Total* 144 N.A. N.A.
*Correlation with SCI Impact Factors-correlation coefficient (P-value)* N.A. 0.546 (\< 0.001) N.A. N.A. N.A.
^†^*EBM*does not include a listing of important but not abstracted articles (\"Other Articles Noted\" section); \*Articles abstracted are those that pass methodological criteria and are deemed to be the most important by a team of practicing general/family practitioners; \*\*The number of articles needed to read (NNR) is a measure of the ratio of number of relevant articles (abstracted) divided into the total number of articles for each title; \*\*\*SCI Impact Factors not available for analysis; N.A. Not applicable. Data are for 2000. Note that the AHRQ/AHCPR reports were not considered journal titles and read as such for this report.
:::
::: {#T4 .table-wrap}
Table 4
::: {.caption}
######
*EBN*(general practice nursing) journal-specific content of high-quality, clinically relevant articles
:::
**Journal title** **Number articles in 2000 in journal** **Number abstracted (% included in *EBN*)** **NNR for abstracted article** **Number abstracted or listed (% included in *EBN*)\*** **NNR for abstracted or listed\*\***
------------------------------------------------------------------------- ---------------------------------------- --------------------------------------------- -------------------------------- --------------------------------------------------------- --------------------------------------
*Qualitative Health Research* 60 10 (10.4) 6.0 14 (4.6) 4.7
***Cochrane Database of Systematic Review\*\*\**** **444** **8 (8.3)** **55.5** **33 (10.9)** **13.5**
*Pediatrics* 811 8 (8.3) 101.4 19 (6.3) 42.7
***JAMA*** **1930** **7 (7.3)** **275.7** **16 (5.3)** **120.6**
*Lancet* 3858 6 (6.3) 643.0 12 (4.0) 321.5
***BMJ*** **3428** **5 (5.2)** **685.6** **16 (5.3)** **214.3**
*Journal of Advanced Nursing* 611 5 (5.2) 122.2 14 (4.6) 43.6
***American Journal of Medicine*** **434** **3 (3.1)** **144.7** **6 (2.0)** **72.3**
*Critical Care Medicine* 977 3 (3.1) 325.7 3 (1.0) 325.7
***Health Psychology\*\*\**** **79** **3 (3.1)** **26.3** **5 (1.6)** **15.8**
*Stroke* 609 3 (3.1) 203.0 5 (1.6) 121.8
***Archives of Internal Medicine*** **620** **2 (2.1)** **310** **16 (5.3)** **38.8**
*Archives of Pediatric and Adolescent Medicine* 273 2 (2.1) 136.5 5 (1.6) 57.4
***CMAJ (formerly Canadian Medical Association Journal)*** **1007** **2 (2.1)** **503.5** **3 (1.0)** **335.7**
*Health Education and Behavior\*\*\** 67 2 (2.1) 33.5 2 (0.7) 33.5
***Journal of Pediatrics*** **137** **2 (2.1)** **68.5** **6 (2.0)** **22.8**
*Social Science and Medicine* 302 2 (2.1) 151 5 (1.6) 60.4
***Age and Ageing*** **767** **1 (1.0)** **767** **2 (0.7)** **383.5**
*Annals of Internal Medicine* 602 1 (1.0) 602 6 (2.0) 100.3
***Annals of Surgery*** **301** **1 (1.0)** **301** **1 (0.3)** **301**
*ANS Advances in Nursing Sciences* 25 1 (1.0) 25 3 (1.0) 8.3
***Applied Nursing Research*** **40** **1 (1.0)** **40** **2 (0.7)** **20**
*Archives of Disease in Childhood Neonatal and Fetal Edition* 157 1 (1.0) 157 3 (1.0) 52.3
***Archives of General Psychiatry*** **161** **1 (1.0)** **161** **4 (1.3)** **40.3**
*Birth* 105 1 (1.0) 105 1 (0.3) 105
***British Journal of General Practice*** **453** **1 (1.0)** **453** **4 (1.3)** **113.3**
*British Journal of Surgery* 402 1 (1.0) 402 2 (0.7) 201
***Canadian Journal of Gastroenterology*** **145** **1 (1.0)** **145** **1 (0.3)** **145**
*Canadian Journal of Infection Control* 31 1 (1.0) 31 1 (0.3) 31
***Image Journal of Nursing Scholarship*** **94** **1 (1.0)** **94** **2 (0.7)** **47**
*Journal of the American Geriatric Society* 384 1 (1.0) 384 4 (1.3) 96
***Journal of Clinical Epidemiology*** **173** **1 (1.0)** **173** **5 (1.6)** **57.7**
*Journal of Clinical Nursing* 107 1 (1.0) 107 3 (1.0) 35.7
***Journal of Consulting and Clinical Psychology*** **122** **1 (1.0)** **122** **5 (1.6)** **24.4**
*Journal of Manipulative and Physical Therapy* 117 1 (1.0) 117 1 (0.3) 117
***Midwifery*** **68** **1 (1.0)** **68** **3 (1.0)** **22.7**
*New England Journal of Medicine* 1530 1 (1.0) 1530 4 (1.3) 382.5
***Pain*** **269** **1 (1.0)** **269** **1 (0.3)** **269**
*Psychosomatic Medicine* 106 1 (1.0) 106 1 (0.3) 106
***Western Journal of Nursing Research*** **99** **1 (1.0)** **99** **1 (0.3)** **99**
*Acta Psychiatrica Scandinavica* 255 0 (0) Infinity 1 (0.3) 255
***Addiction*** **295** **0 (0)** **Infinity** **1 (0.3)** **295**
*American Journal of Cardiology* 850 0 (0) Infinity 1 (0.3) 850
***American Journal of Epidemiology*** **362** **0 (0)** **Infinity** **11 (3.6)** **32.9**
*American Journal of Gastroenterology* 923 0 (0) Infinity 1 (0.3) 923
***American Journal of Obstetrics and Gynecology*** **704** **0 (0)** **Infinity** **2 (0.7)** **352**
*American Journal of Public Health* 363 0 (0) Infinity 4 (1.3) 90.8
***American Journal of Respiratory and Critical Care Medicine*** **783** **0 (0)** **Infinity** **1 (0.3)** **783**
*Archives of Diseases in Childhood* 392 0 (0) Infinity 2 (0.7) 196
***British Journal of Psychiatry*** **335** **0 (0)** **Infinity** **2 (0.7)** **177.5**
*Canadian Journal of Nursing Research* 35 0 (0) Infinity 1 (0.3) 35
***Canadian Journal of Psychiatry*** **179** **0 (0)** **Infinity** **1 (0.3)** **179**
*Cancer* 786 0 (0) Infinity 1 (0.3) 786
***Cancer Nursing*** **61** **0 (0)** **Infinity** **1 (0.3)** **61**
*Chest* 882 0 (0) Infinity 1 (0.3) 882
***Child Development*** **141** **0 (0)** **Infinity** **1 (0.3)** **141**
*Gut* 446 0 (0) Infinity 1 (0.3) 446
***Heart and Lung*** **59** **0 (0)** **Infinity** **1 (0.3)** **59**
*International Journal of Geriatric Psychiatry* 169 0 (0) Infinity 1 (0.3) 169
***Journal of American Academy of Child and Adolescent Psychiatry*** **300** **0 (0)** **Infinity** **1 (0.3)** **300**
*Journal of Child Psychology and Psychiatry* 99 0 (0) Infinity 1 (0.3) 99
***Journal of Epidemiology and Community Health*** **205** **0 (0)** **Infinity** **3 (1.0)** **68.3**
*Journal of Family Practice* 263 0 (0) Infinity 7 (2.3) 37.6
*Journal of General Internal Medicine* 155 0 (0) Infinity 1 (0.3) 155
***Journal of Pediatric Nursing*** **68** **0 (0)** **Infinity** **2 (0.7)** **34**
*Journal of Pediatric and Oncology Nursing* 32 0 (0) Infinity 1 (0.3) 32
***Medical Journal of Australia*** **598** **0 (0)** **Infinity** **1 (0.3)** **598**
*Nursing Research* 51 0 (0) Infinity 3 (1.0) 17
***Obstetrics and Gynecology*** **478** **0 (0)** **Infinity** **3 (1.0)** **159.3**
*Patient Education and Counseling* 94 0 (0) Infinity 3 (1.0) 31.3
***Schizophrenia Bulletin*** **80** **0 (0)** **Infinity** **2 (0.7)** **40**
*Spine* 604 0 (0) Infinity 2 (0.7) 302
***Thorax*** **336** **0 (0)** **Infinity** **1 (0.3)** **336**
*Total* 96 305
*Correlation with SCI Impact Factors-correlation coefficient (P-value)* N.A. 0.096 (0.57) N.A. 0.256 (0.038) N.A.
\*Articles abstracted are those that pass methodological criteria and are deemed to be the most important by practicing nurses. The other articles listed are articles with the same high-quality methods but are considered to be slightly less important clinically by practicing nurses; \*\*The number of articles needed to read (NNR) is a measure of the ratio of number of relevant articles (abstracted or combined abstracted or listed) divided into the total number of articles for each journal title; \*\*\*SCI Impact Factor not available for analysis; N.A. Not applicable or available. Data are for 2000. Note that the AHRQ/AHCPR reports were not considered journal titles and read as such for this report.
:::
::: {#T5 .table-wrap}
Table 5
::: {.caption}
######
*EBMH*(mental health) journal-specific content of high-quality, clinically relevant articles
:::
**Journal title** **Number articles in 2000 in journal** **Number abstracted (% included in *EBMH*)** **NNR for abstracted article** **Number abstracted or listed (% included in *EBMH*)\*** **NNR for abstracted or listed\*\***
-------------------------------------------------------------------------------- ---------------------------------------- ---------------------------------------------- -------------------------------- ---------------------------------------------------------- --------------------------------------
*Archives of General Psychiatry* 161 12 (12.5) 20.1 14 (8.2) 11.5
***Cochrane Database of Systematic Reviews\*\*\**** **444** **6 (6.3)** **74.0** **27 (15.9)** **16.4**
*American Journal of Psychiatry* 508 5 (5.2) 101.6 9 (5.3) 56.4
***British Journal of Psychiatry*** **335** **5 (5.2)** **67.0** **8 (4.7)** **41.9**
*JAMA* 1930 5 (5.2) 386.0 9 (5.3) 214.4
***Lancet*** **3858** **5 (5.2)** **771.6** **7 (4.1)** **551.1**
*International Journal of Geriatric Psychiatry* 169 5 (5.2) 33.8 8 (4.7) 21.1
***Journal of the American Academy of Child and Adolescent Psychiatry*** **300** **4 (4.2)** **75.0** **4 (2.4)** **75.0**
*Journal of Consulting and Clinical Psychology\*\*\** 122 4 (4.2) 30.5 7 (4.1) 17.4
***BMJ*** **3428** **3 (3.1)** **1142.7** **4 (2.4)** **857.0**
*Journal of Clinical Psychopharmacology* 162 3 (3.1) 54.0 3 (1.7) 54.0
***Schizophrenia Bulletin*** **80** **3 (3.1)** **26.7** **4 (2.4)** **20.0**
*Annals of Internal Medicine* 602 2 (2.1) 301.5 2 (1.2) 301.5
***Journal of Child Psychology and Psychiatry, and Allied Disciplines\*\*\**** **99** **2 (2.1)** **49.5** **3 (1.7)** **33.0**
*Archives of Internal Medicine* 620 2 (2.1) 310 3 (1.7) 206.7
***Journal of Clinical Epidemiology*** **173** **2 (2.1)** **86.5** **2 (1.2)** **86.5**
*Journal of Family Practice* 263 2 (2.1) 131.5 2 (1.2) 131.5
***New England Journal of Medicine*** **1530** **2 (2.1)** **765.0** **2 (1.2)** **765.0**
*Psychosomatic Medicine* 106 2 (2.1) 53.0 3 (1.7) 35.3
***Acta Psychiatric Scandinavica*** **255** **1 (1.0)** **255** **2 (1.2)** **127.5**
*Addiction* 295 1 (1.0) 295 4 (2.4) 73.8
***Age and Ageing*** **181** **1 (1.0)** **181** **1 (0.6)** **181**
*American Journal of Public Health* 363 1 (1.0) 363 1 (0.6) 363
***Archives of Family Medicine (no longer published)*** **230** **1 (1.0)** **230** **1 (0.6)** **230**
*Behaviour Therapy* 44 1 (1.0) 44 3 (1.7) 14.7
***British Journal of General Practice*** **453** **1 (1.0)** **453** **1 (0.6)** **453**
*British Journal of Geriatric Psychiatry* N.A. 1 (1.0) N.A. 1 (0.6) N.A.
***Canadian Journal of Psychiatry*** **179** **1 (1.0)** **179** **1 (0.6)** **179**
*Child Development* 141 1 (1.0) 141 2 (1.2) 70.5
***CMAJ (formerly Canadian Medical Association Journal)*** **1007** **1 (1.0)** **1007** **1 (0.6)** **1007**
*Image Journal of Nursing Scholarship* 94 1 (1.0) 94 1 (0.6) 94
***Journal of Advanced Nursing*** **611** **1 (1.0)** **611** **1 (0.6)** **611**
*Journal of Affective Disorders* 154 1 (1.0) 154 1 (0.6) 154
***Journal of Neurology Neurosurgery and Psychiatry*** **83** **1 (1.0)** **83** **2 (1.2)** **41.5**
*Medical Care* 162 1 (1.0) 162 1 (0.6) 162
***Pain*** **269** **1 (1.0)** **269** **1 (0.6)** **269**
*Pediatrics* 811 1 (1.0) 811 2 (1.2) 405.5
***Psychiatric Services*** **356** **1 (1.0)** **356** **3 (1.7)** **118.7**
*Psychology and Aging* 55 1 (1.0) 55 1 (0.6) 55
***Research in Nursing Health*** **55** **1 (1.0)** **55** **1 (0.6)** **55**
*Social Science and Medicine* 302 1 (1.0) 302 1 (0.6) 302
***American Journal of Medicine*** **435** **0 (0)** **Infinity** **2 (1.2)** **217.5**
*AHCOR/AHRQ Reports\*\*\** N.A. 0 (0) Infinity 3 (1.7) N.A.
***Archives of Physical Medicine and Rehabilitation*** **337** **0 (0)** **Infinity** **1 (0.6)** **337**
*Australian and New Zealand Journal of Psychiatry* 214 0 (0) Infinity 1 (0.6) 214
***Journal of Clinical Nursing*** **107** **0 (0)** **Infinity** **1 (0.6)** **107**
*Journal of Psychosomatic Research* 118 0 (0) Infinity 2 (1.2) 59
***Neurology*** **1334** **0 (0)** **Infinity** **1 (0.6)** **1334**
*Psychosomatic Medicine* 106 0 (0) Infinity 1 (0.6) 106
*Total* 96 170
*Correlation with SCI Impact Factors-correlation coefficient (P-value)* N.A. 0.386 (0.02) N.A. 0.381 (0.01) N.A.
\*Articles abstracted are those that pass methodological criteria and are deemed to be the most important by practicing mental health professionals. The other articles listed are articles with the same high-quality methods but are considered to be slightly less important clinically by mental health professionals; \*\*The number of articles needed to read (NNR) is a measure of the ratio of number of relevant articles (abstracted or combined abstracted or B-listed) divided into the total number of articles for each journal title; \*\*\*SCI Impact Factor not available for analysis; N.A. Not applicable or not available. Data are for 2000. Note that the AHRQ/AHCPR reports were not considered journal titles and read as such for this report.
:::
|
PubMed Central
|
2024-06-05T03:55:47.945488
|
2004-9-6
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC518974/",
"journal": "BMC Med. 2004 Sep 6; 2:33",
"authors": [
{
"first": "Kathleen Ann",
"last": "McKibbon"
},
{
"first": "Nancy L",
"last": "Wilczynski"
},
{
"first": "Robert Brian",
"last": "Haynes"
}
]
}
|
PMC518975
|
Background
==========
With technological improvements and decreasing costs, microarrays are quickly becoming an affordable analytical tool for genetics analysis. Additionally, the arrays being used are of increasing spot density, allowing for more genes to be tested at once. One impact of the resulting increase in data flow is that it will become more likely that a researcher using microarrays will have greater difficulty making sense of results from preliminary statistical analyses without further computational exploration. In other words, once the researcher has received a list of genes, by whatever statistical means, that are differentially expressed, the task of determining the biological implications of that gene list will need to be performed by statistical methods utilizing computers.
Numerous research groups are developing software tools to perform an interpretation of the list of differentially expressed genes, generally by mapping against previously developed knowledgebases such as the Gene Ontology (GO) \[[@B1],[@B2]\] or GenMAPP \[[@B3]\] as a reference data set (reviewed briefly in \[[@B4]\]). Some tools, such as DAVID \[[@B5]\] and FatiGO \[[@B6]\] examine the percentage of the gene list that is directly associated with a node of the knowledgebase. This method is extremely fast due to its simplicity, but it does have disadvantages, which are also due to the simplicity of the analysis. For example, in some of these tools, information about how nodes (biological terms or steps in pathways) of the knowledgebase are related to each other is ignored. Additionally, in hierarchical structures such as GO, genes with a less precise functional definition will be associated with a node closer to the root than a gene with a more precise definition. In such a case, the information content about the two genes is split into different nodes, reducing the power of the analytical method.
Other tools such as GOMiner \[[@B7]\] and MAPPFinder \[[@B8]\] analyze the gene list in a broader context of the knowledgebase, looking for patterns of a larger scale than a single node. MAPPFinder searches for whole pathways (MAPPs) over-represented by the gene list. GOMiner performs analyses using genes associated with a node in GO or genes associated with any children of that node, sometimes called \"inclusive analysis\". In this way, GOMiner minimizes the power reduction of some simpler methods.
These tools provide a powerful way for the researcher to quickly get a summarization of the gene list within a biological context. One common problem for the inclusive analytical methods, especially those using knowledgebases with polyhierarchical structures (individual nodes can have multiple parents) like GO, is correcting for multiple statistical tests, usually thousands. In such a case, a Bonferroni correction is overly conservative to the point of being counterproductive since few if any results of the interpretation remain significant \[[@B7]\]. As of June, 2003, GODB had \>13,000 DAG nodes which may be tested, meaning a correction factor of greater than four orders of magnitude would be needed in a Bonferroni correction. Other standard methods used include controlling the Family-Wise Error Rate (FWER) using a numerical correction of the p-value (discussed in \[[@B9]\]) or controlling the False Positive Rate (FDR, discussed in \[[@B10]\]). In both cases the methodology should again be overly conservative since, when using inclusive analysis, the p-values for each GO term are not independent \[[@B11]\].
Here we present, in the context of the program GOArray \[[@B4]\], a preliminary analysis of the feasibility of using permutation-based simulations to provide an alternate method of handling the multiple-testing problem. GOArray analyzes the gene list in the context of GO. Permutations of the differentially expressed gene list are generated from the total list of genes represented on the microarray to estimate the distribution of significant GO terms expected by chance. We analyze the nature of the distribution of significant terms in reference to varying p-values and numbers of differentially expressed genes using publicly available data sets. We then compare the list of significant terms between data sets. Finally, we discuss the implications of this distribution to provide one solution to the multiple-test problem when analyzing microarray data in the context of GO.
Results
=======
Four of the test data sets analyzed were extracted from the National Center for Biotechnology Information\'s (NCBI) Gene Expression Omnibus (GEO) \[[@B12]\]. The first is an array of *Drosophila*markers used by Arbeitman et al. \[[@B13]\] (GEO accession GPL218) for a time-series study of the *Drosophila*life cycle. This array represents 5081 microarray spots, from which there are 2825 genes as represented by unique FlyBase \[[@B14]\] accession numbers. The estimation of the distribution took \~16.6 hours. The mean numbers of significant terms for each combination of p-value cutoff and \"Gene of Interest\" (GOI) count are presented in Figure [1](#F1){ref-type="fig"} (full tables of values for all figures are present in the [Additional File 1](#S1){ref-type="supplementary-material"}). A \"trough\" of less significant terms than the two surrounding GOI counts for the same p-value for term significance can be observed in the topology diagonally from 500 GOI and a p-value of 0.05 down to 250 GOI and a p-value of 0.0031. There are additional, similarly \"wave-shaped\" features, although of lesser degree. For example, there is one with a slower rate of change running diagonally from 250 GOI in the vicinity of p-values 0.0002 and 0.000098 (285.9 and 283.9 significant terms respectively), and from 500 GOI between p-values 0.0063 and 0.0.0031 (660.4 and 653.3 significant terms respectively). Overall, however, there is an increase in the number of significant terms with both increasing GOI and p-value cutoff. The increase is sharp from 50 to 100 GOI, and then more gradual with increasing GOI. The increase in significant terms with increasing p-value cutoff, however, is much more gradual.
The second data set is for an array of *Drosophila*markers used by Meiklejohn et al. \[[@B15]\] (GEO accession GPL356) for a study of interspecies variation. The array represents 5928 cDNA probes, from which there are 5375 unique FlyBase accession numbers. The estimation of the distributions took \~23.8 hours. The mean number of significant terms for each combination of p-value and GOI count were estimated by simulation (Figure [2](#F2){ref-type="fig"}). Again, there is a general increasing trend in the number of significant terms with increasing numbers of GOI and p-value cutoffs. There is another observed trough, however, starting from 500 GOI and a p-value cutoff of 0.0063 diagonally to 350 GOI and a p-value cutoff of 0.00078. As with the first data set, there are also \"wave-like\" structures in the topology such as from approximately 250 GOI and a p-value of 0.0016 to 400 GOI and a p-value of 0.013. Given the similarity in topology to the first data set, the possibility that these two sets of FlyBase accessions have large overlap was considered. Indeed, \~90% (2560) of the FlyBase accessions from the Arbeitman data set are observed as \~50% of the Meiklejohn data set.
That the two data sets would not be independent is to be expected, since one goal of both studies was to examine as many of the known *Drosophila*genes as possible. This non-independence will probably be observed for most pairs of *Drosophila*microarrays. Because of this, we extracted the 2815 FlyBase accession numbers from the Meiklejohn data set that did not overlap with the Arbeitman data set, and estimated the distribution of significant terms for just those genes as a comparison to the other two data sets. The simulation took \~18.3 hours and the results are presented in Figure [3](#F3){ref-type="fig"}. As with the previous two data sets, there is generally an increase in the number of significant terms with increasing numbers of GOI and p-value cutoffs. There is also another trough extending from 450 and 500 GOI with a p-value cutoff of 0.05 to 200 GOI with a p-value cutoff of 0.0016.
Since the two real *Drosophila*data sets and one simulated *Drosophila*data set all had a trough in the distribution, it was possible that this is due to inherent structure in GO specifically for *Drosophila*. Therefore, we extracted three other data sets for different species. The first of these non-*Drosophila*sets of genes was for *S. cerevisiae*(GEO accession GPL205), a set of 6084 genes. The overall topology is quite regular (Figure [4](#F4){ref-type="fig"}). Unlike the *Drosophila*data sets, within the range of GOI and p-values considered there was no evidence of a trough (region where some points would be predicted to have more significant terms than neighboring points but instead have less) in the distribution. There was one data point (500 GOI, p = 0.000391) with a mean number of significant terms (437.3) less than that for the same p-value and the next lower number of GOI (450 GOI, 438.7 terms). The difference between the two means is minute, and may not be meaningful. There are a few regions with leveling (little change in significant terms between points), but these were not large and overall pattern appears somewhat predictable.
The second and third non-*Drosophila*data set were constructed by taking all Wormbase \[[@B16]\] and Gramene \[[@B17]\] accessions from GODB. In the case of the Wormbase data set (8224 genes), the distribution again appears somewhat regular (Figure [5](#F5){ref-type="fig"}), with just a few regions of leveling, but no major trough. There was, however, more \"wave-like\" structure with increasing numbers of GOI and more stringent p-values. The same was noted for the Gramene data set (4798 genes), although the leveling was considerably more apparent (Figure [6](#F6){ref-type="fig"}). This was especially true in the region from 500 GOI and p = 0.00156 to 300 GOI and p = 9.8 × 10^-5^. Even with this region, however, the distribution appears somewhat smoother than that observed for the *Drosophila*data set. The region in question is located near the edge of the explored space, however, and a pattern may emerge with higher number of GOI.
Finally, to see if the same terms were consistently appearing as significant in the *Drosophila*data sets, we compared the actual number of significant occurrences for each term for the two data sets extracted from GEO (GPL218 and GPL356). Genes with a five-fold or greater change in expression were chosen as GOI. A p-value cutoff of 0.001 was chosen. The list of terms that came up as significant, and the number of permutations out of 1000 that were significant, was recorded and presented as a scatter plot (Figure [7](#F7){ref-type="fig"}). From the plot, it can clearly be seen that there is a lack of correlation between the number of times a term appears as a significant in one data set compared to the second data set, even accounting for a different maximum number of significant terms in the two data sets. A handful of terms were significant a similar number of times in each data set relative to the maximum count of significant terms for the respective data sets. In other words, a handful of terms mapped near the line extending from the origin to the point marked by the maximum value along each axis, which would mark roughly equivalent relative occurrences of the term as significant between the two data sets. However, these terms were near the origin and the vast majority of points were along the axes, showing a clear lack of correlation in how often terms were observed as significant between these two closely related lists of genes.
Discussion
==========
Based on this set of simulations, predictability appears to be limited to specific data sets. One method of correcting our expectations after performing multiple tests would be to calculate a factor by which to modify α based on the DAG of GO terms. In other words, one could use an adjusted p-value to control the FWER or FDR. Controlling for these two types of error by use of adjusted p-values, however, assumes independence of the tests \[[@B11]\]. Since there is currently no practical method for directly untangling the interdependence of terms in the GO hierarchy to generate a less conservative correction, adjusted p-values are limited to overly strict results.
Another method would be to determine a formula that conservatively approximates the simulated distribution. Unfortunately, the only commonality between the distributions is that, with the exception of the *Drosophila*data sets, the number of significant terms increases with an increasing number of GOI and an increasing p-value cutoff. The magnitude and detailed shape of the distribution varies between all tested data sets. Even in the more regular non-*Drosophila*data sets, there were some fluctuations in the distribution, and a smooth surface was not observed. Since neither of the two methods of correcting expectations is currently feasible, it appears that, for now, we are forced to rely on simulation-based methods to estimate the expected distribution of significant terms for each set of genes being examined.
While it would be desirable to have a smooth topology that allows for a simple formulaic calculation of the number of significant terms one would expect by chance, it is unfortunately not observed for the *Drosophila*data sets examined here. The trough that disrupts the *Drosophila*data sets was not observed, however, in the data sets for other species. The cause of this trough is undetermined, but may be due to structure within the graph of GO terms associated with FlyBase accessions. Alternatively, there could be structure within the chosen genes that is more evident with smaller data sets, since the trough appears to be deepest for the two smaller data sets. One way to approach the question of cause would be to examine which, if any, terms are observed disproportionately in the permuted sets. Based on the frequency of terms it may be possible to observe a pattern in either the genes tested or the set of associated GO terms. We have been unable to observe such a pattern, but that does not mean it does not exist. If one could be found, it may give insights into how to dissect the structure, possibly leading to a more elegant solution to the multiple test problem than a simulation-based approach.
Though we were unable to find hints of an easy formulaic way to correct our expectations, we may be able to find a practical (e.g., efficient) method of correction through simulations. There are several ways in which simulated estimates of the distribution could be implemented to provide a less conservative method, yet still statistically appropriate, than a Bonferroni correction to handle the problem of correcting our expectations after performing multiple statistical tests. The simplest to implement, and likely the most accurate, would be to perform a permutation-based simulation for each analysis of a microarray data set in the context of GO. The primary problem with this approach is that it is computationally intensive since the GOI would need to be permutated and scored a thousand or more times for every analysis of a microarray. While tools such as parallel processing can reduce the absolute time necessary to perform the simulations, it is not the most elegant way to solve the problem.
Another method would be to simply generate the estimated distribution, again using a permutation-based simulation, once for each set of accession numbers (e.g., each microarray design) for a range of GOI counts and p-value cutoffs, similar to what we have done here but in finer detail, and storing the results. The most conservative simulation distribution neighboring the experimental combination of p-value and GOI count could then be extracted from the stored table to provide an estimated distribution. One problem with this approach is determining how fine a table to design (e.g., the number of values to simulate for each of the two primary parameters). With a simple 10 × 10 matrix, the simulation took \~16--24 hours on a single 2.4 GHz Xeon processor. A finer matrix of parameter values will result in a better estimation of the topology, but consumes more time to compute in a non-linear fashion. However, if a large number of microarray experiments is to be conducted with a single geometry, this method would reduce the total time to estimate significance across all experiments since the simulation would only need to be performed once. Additionally, it will be necessary to determine what range of values should be considered. For the smallest data set tested here (\>2500 FlyBase accessions), GOI lists representing less than 20% (500) of the accession numbers were used. The amount of computation time that should be dedicated to simulating the distribution of significant terms expected by chance will likely be a balance determined by the computing resources available, estimates of how many experiments will use the array design, and minimal p-value cutoffs and maximal GOI parameter values determined by the predicted user needs.
Conclusions
===========
Based on the large simulations performed here, it appears that the rate at which terms are observed as significant is not predictable between sets of genes for a given GOI count and p-value cutoff. Even within a particular species, there is no correlation in relative frequency at which particular terms are significant. Therefore, permutation-based simulations appear to be the most reliable way to generate an estimate of the expected distribution of significant terms. As a result, we plan to extend the confidence tests in the next version of GOArray (version 2.0) by implementing a \"false positive frequency estimation\" for individual terms based on simulation results. Also, since which terms are observed as significant appears to be highly dependent on the structure of the gene list, and possibly the list of GOI, we plan to examine the merits of bootstrap methods (e.g. in the simulations choosing GOI from the original list of GOI with replacement) rather than a strict permutation method (e.g. choosing GOI from the total list of genes without replacement).
In the best case, it appears feasible to pre-generate the estimated distribution of the number of significant terms through a permutation-based simulation, then use a lookup table during analyses of experimental data sets. In the worst case, one would need to generate the distribution for each experimental data set, possibly testing various p-value cutoffs to determine where power is maximal. Even in the worst case, currently available processing power allows the test for a single set of genes and a single p-value cutoff to be performed in well under an hour. While near-instant results would be desirable by end users, the worst case scenario is still quite practical and will only improve over time alongside general computer performance. Thus, relying on permutation-based methods may not be a serious inconvenience, and in fact a highly accurate method of assessing our confidence in the results of the analysis.
Methods
=======
Test System
-----------
All tests were performed on a single processor of a dual Xeon 2.4 MHz CPU system with 2 gigabytes of RAM. The operating system was RedHat Linux 7.3 with an SMP kernel. All time calculations were determined using the Linux command *time*.
GOArray
-------
GOArray is a Perl script that maps genes of interest (GOI) and non-GOI (NGOI), where the difference between the two gene lists is determined by the researcher, from a microarray experiment to terms in GO and all of that term\'s parent terms. The GO rooted-DAG is represented in a hash table using the GODB field terms.id as the keys. A z-score is assigned to each term based on the number of genes associated with that term or any of its children relative to the total numbers of GOI and NGOI. Z-scores were used to calculate p-values since they are easy and efficient to compute, and they approximate the hypergeometric p-values when the number of NGOI and GOI for the entire data set is large compared to the NGOI and GOI for the individual nodes. Terms with only one gene in the numerator (GOI) are not given a z-score since it is not possible to have an overrepresentation of GOI with a single gene. P-values are determined using twice the value (e.g., a two-sided test) returned by the routine \"uprob(\$z)\" (where \"\$z\" is the z-score) from the Perl module Statistics::Distributions available from the Comprehensive Perl Archive Network (CPAN) \[[@B18]\]. The June 2003 GODB data set is used in this analysis.
Simulations of the GOI list are performed by permuting the status of each gene, keeping the total number of GOI constant. For example, in the case of an experiment examining 5000 total genes with 100 GOI, in each simulation 100 of the 5000 genes are assigned the status of GOI, and 4900 genes are assigned the status of NGOI.
The only modifications to the GOArray source code in this analysis are the addition of loop structures to iterate the numbers of GOI and count the number of significant terms under different p-value cutoffs to determine when a term is significant, the use of a user-determined random number seed rather than a computer determined one for reproducibility, and the addition of a routine to summarize the simulation data.
The source code for both GOArray and the modifications discussed here are available on the Web \[[@B19]\].
Distributions
-------------
Using the modified GOArray code, the number of significant terms were determined for p-values (determining which terms were significant, not which genes were GOI) from 0.05 down to \~0.000098 (starting with 0.05 and decreasing the p-value by a factor of 2 with each iteration), and GOI counts from 50 to 500 in increments of 50. This generates the number of significant terms for each of 1000 permutations for all combinations of ten different p-values and ten different GOI counts, for a total of 100 distributions of 1000 permutations for each data set.
Authors\' Contributions
=======================
MVO conceived of the study, performed the analyses, and drafted the manuscript. HYZ participated in the statistical design. KHC participated in the study design and coordination.
Supplementary Material
======================
::: {.caption}
###### Additional File 1
A Microsoft Word document containing the data tables used to generate Figures 1 through 6.
:::
::: {.caption}
######
Click here for file
:::
Acknowledgements
================
This work is supported in part by NIH grant K25 HG02378 (KHC), by NIH grants T15 LM07056 and P20 LM07253 from the National Library of Medicine (MVO), by NSF grant DBI-0135442 (KHC), and by NSF grant DMS 0241160 (HYZ).
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Overhead view of surface topology for the the Arbeitman data set. Different shadings represent different numbers of significant terms.
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Overhead view of surface topology for the Meiklejohn data set. Different shadings represent different numbers of significant terms.
:::
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::: {#F3 .fig}
Figure 3
::: {.caption}
######
Overhead view of surface topology for the portion of the Meiklejohn data set that did not overlap the Arbeitman data set. Different shadings represent different numbers of significant terms.
:::
:::
::: {#F4 .fig}
Figure 4
::: {.caption}
######
Overhead view of surface topology for the portion of the *S. cerevisiae*data set. Different colors represent different numbers of significant terms.
:::
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::: {#F5 .fig}
Figure 5
::: {.caption}
######
Overhead view of surface topology for the portion of the Wormbase data set. Different colors represent different numbers of significant terms.
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::: {#F6 .fig}
Figure 6
::: {.caption}
######
Overhead view of surface topology for the portion of the Gramene data set. Different colors represent different numbers of significant terms.
:::
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::: {#F7 .fig}
Figure 7
::: {.caption}
######
Correlation in significant terms between data sets. The number of times each term was observed as significant based on the analysis of two different sets of *Drosophila*genes are scatter plotted.
:::
:::
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PubMed Central
|
2024-06-05T03:55:47.953146
|
2004-9-6
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC518975/",
"journal": "BMC Bioinformatics. 2004 Sep 6; 5:124",
"authors": [
{
"first": "Michael V",
"last": "Osier"
},
{
"first": "Hongyu",
"last": "Zhao"
},
{
"first": "Kei-Hoi",
"last": "Cheung"
}
]
}
|
PMC518976
|
Background
==========
Limb-salvage is an important treatment objective for adults and children with extremity soft tissue sarcoma and often requires the use of limited surgery and irradiation \[[@B1]\]. Limiting the extent of resection balances the need for radical excision with the need to preserve the functional and structural integrity of the limb and tissues adjacent to those involved with tumor. Radiation therapy has been proven to compensate for incomplete resection or limited resections with involved, close or indeterminate margins as long as the dose and volume are adequate \[[@B2]-[@B5]\]. Excellent rates of local control have been achieved for adults and children with extremity soft tissue sarcoma using limb sparing approaches \[[@B6]-[@B11]\]. Little is known about the long-term morbidity of the combined effects of limited surgery and irradiation on bone and soft tissue in the pediatric population.
Surgery and radiation therapy both have the potential to cause significant morbidity including loss of function and deformity \[[@B6],[@B11]-[@B15]\]. Tumor resection often requires removal of normal tissue compartments and structural elements, even in a limb-sparing approach. This places the patient at risk for complications including destabilization and abnormalities in growth and function. Additive are the effects of high-dose irradiation, which is often required in the treatment of these tumors, and which may compound the effects of resection. The use of chemotherapy, when indicated, may also add to the combined effects of treatment. The timing of surgery and radiation therapy, the operative approach and the selection of the specific radiation treatment modality often depends on a number of important clinical factors including the size and type of tumor, site of involvement, prior surgical manipulation, extent of resection and the potential for as good functional outcome.
Individual cases of valgus and varus deformity after limited surgery and irradiation for extremity soft-tissue sarcoma are presented and discussed to identify factors that may be responsible for these treatment complications. Pre-existing orthopedic problems, multiple attempts at resection, post-operative infection, the use of chemotherapy and the addition of brachytherapy to external beam radiation therapy appear to be contributory. Because limb-sparing approaches will be an important component of the next generation of cooperative group studies for extremity soft tissue sarcoma in children, the incidence and severity of this and other treatment-related complications should be documented as well as efforts to limit the effects of these treatments and identify solutions for established problems.
Case Presentations
==================
Case 1
------
At the time of diagnosis, this patient was an 8 year-old male with an approximate 12--24 month history of mild pain and swelling in the left popliteal region. There was no complaint of fever or decreased range of motion. He presented to a local orthopedist (April 1995) and was found to have a palpable abnormality on the posterior aspect of the knee consistent with a Baker\'s cyst. Aspiration was unsuccessful and the patient was treated with ibuprofen for a 10-day course. Nearly one year later (April 1996) the family sought a second opinion and an MR study was ordered that revealed a cystic structure \[Figure [1](#F1){ref-type="fig"}\]. The patient returned to the original orthopedist and was found to have a painful and enlarging mass in the left popliteal region. He underwent resection of a solid and cystic mass (November 1996) measuring 7.0 × 6.0 × 3.0 cm. The tumor was described as a high-grade synovial cell sarcoma. The extent of resection was incomplete with gross residual tumor remaining about the lateral aspect of the knee and external to the joint capsule which also appeared to be the site of origin. The patient was transferred one month later to St. Jude Children\'s Research Hospital for further evaluation and treatment.
::: {#F1 .fig}
Figure 1
::: {.caption}
######
MRI at diagnosis (case one).
:::
:::
At the time of his evaluation after referral, he had strong popliteal pulses. There was a 7.0 × 4.5 cm area of swelling and numbness in the left popliteal region. The deep-tendon reflexes were brisk and the motor exam and gait were normal. MR showed residual abnormality consistent with tumor lateral to the joint capsule. Metastatic work-up including nuclear bone scan and CT scan of the chest was negative. Tumor bed re-excision with placement of afterloading catheters was performed in December 1996. All visible residual abnormality was removed without significant disruption of underlying ligaments and tendons. The walls of the tumor bed were biopsied to map the extent of microscopic residual disease. Microscopic residual disease was anticipated given the site of involvement and the limited ability to operate beyond the extent of the abnormal appearing tissues. Eleven afterloading catheters were placed in a parallel array to cover the tumor bed \[Figure [2](#F2){ref-type="fig"}\]. Radio-opaque clips were placed at the site of the biopsies and to demarcate the extent of the tumor bed for brachytherapy planning. The final pathology confirmed the presence of residual tumor in the operative specimen and microscopically involved margins at the central and superomedial aspects of the tumor bed.
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Afterloading catheters and dosimetry (case one).
:::
:::
Five days after surgery, the 11 catheters were loaded with a total of 135 seeds representing 408 millicuries of I^125^. The dwell time of the implant was 64 hours and the patient received a total implant dose of 2560 cGy delivered at 40 cGy/hr. Three weeks later, the patient began external beam irradiation at 180 cGy per day and received a total external beam dose of 4860 cGy using 6 MV photons with treatment delivered in a parallel-opposed beam arrangement using a CT based treatment plan \[Figure [3](#F3){ref-type="fig"}\]. Radiation therapy was completed in February 1997.
::: {#F3 .fig}
Figure 3
::: {.caption}
######
Treatment ports and dosimetry (3D).
:::
:::
A decision was made to initiate chemotherapy three weeks into the course of external beam irradiation based on the perceived high-risk nature of his case -- longstanding history of symptoms, known residual tumor and size of tumor at presentation. Chemotherapy included vincristine, ifosfamide, and adriamycin was eventually administered for a total of four cycles. There was central dehiscence of the wound prior to the completion of radiation therapy. The wound was colonized with Enterococci sensitive to ampicillin and managed with antibiotics, whirlpool treatment and daily dressing changes. There was a one-week treatment break during the external beam portion of the treatment.
At the completion of chemotherapy (June 1997) the patient underwent excision of scar tissue with rotation flap of gastrocnemius and skin and Z-plasty of the semi-membranous and semi-tendinous tendon for a non-healing ulcer in the operative region. There was also contracture of the knee joint without signs of abscess or cellulitis. One month later, a second procedure was required to debride and irrigate the left popliteal fossa wound at the site of previously irradiated tissue and contracture release with muscle and fasciocutaneous flap closure. One year after the completion of all therapy (June 1998) the patient reported full range of motion and softening of previously fibrotic tissue. He was actively playing baseball and had no imposed limitations.
Nearly two years after completion of treatment (March 1999), the patient was noted to have Trendelenburg gait after prolonged walking ascribed to poor endurance of weakened hip abductors bilaterally. Hip hiking was also noted on the contralateral side due to leg length and ASIS height discrepancy. A difference of 2.5 cm was noted when measured from the umbilicus to the medial malleolus. He had grown 7.0 cm since the time of diagnosis. He was instructed to stretch the heel cord and strengthening his weak hip abductors. Arrangements were made to provide a shoe lift to accommodate the leg length difference. The discrepancy improved to less than 1 cm over a three month period of time (March-June 1999). He was carefully monitored for growth discrepancy and 6 months later, nearly 3 years after the initiation of treatment, the discrepancy returned to its original value of greater than 2 cm. He also had difficulty with ambulation with slight left-sided limp. Orthopedic surgery was re-consulted. The discrepancy was followed and treated with additional shoe lift. The patient continued to engage in normal activities including sports and reported full range of motion and normal strength. More than four and a half years after initiating treatment (August 2001) \[Figure [4](#F4){ref-type="fig"}\], x-ray scanogram revealed estimated lengths of 49.0 cm and 46.5 cm for his right and left femora respectively, and 40.7 cm and 37.0 cm for his right and left tibiae respectively \[Figure [5](#F5){ref-type="fig"}\]. There was a clinically noticeable varus deformity of the left knee. All growth plates were still open radiographically. He was taken to surgery five years after the initiation of definitive therapy (December 2001) \[Figure [6](#F6){ref-type="fig"}\] for a panepiphysiodesis of the right leg. Using an image intensifier to locate the distal femoral growth plate, medial and lateral incisions were made and a wire-guided cannulated reamer was used to obliterate the plate. The same procedure was done to the proximal tibial growth plate. There were no complications from surgery and the wounds healed appropriately. He was started on physical therapy including quad sets to maintain adequate range of motion. There has been no evidence of tumor recurrence or metastatic disease nearly seven years after treatment. There are no limitations regarding activities and there has been no progressive angular growth deformities.
::: {#F4 .fig}
Figure 4
::: {.caption}
######
Serial plain films (case one).
:::
:::
::: {#F5 .fig}
Figure 5
::: {.caption}
######
Scanogram 4/2001 (case one).
:::
:::
::: {#F6 .fig}
Figure 6
::: {.caption}
######
Pre-Op MR and photograph (case one).
:::
:::
Case 2
------
At the time of diagnosis this patient was a 9 year-old female with a one year history of pain and swelling about her left knee. She had experienced a fall and related all symptoms to the fall. She was seen in her local emergency room by her family physician; there was no diagnosis or treatment. Approximately one month prior to her representation, she was struck in the left knee by a basketball and developed worsening pain. She was seen by an orthopedic surgeon (December 1999) and was noted to have a valgus posture of both lower extremities, exaggerated on the left by external rotation and she walked with a mild limp. The left knee had no effusion but was hypersensitive to light touch over the lateral aspect where there was soft tissue swelling just below the knee. There was no obvious mass in the area, although firm palpation was difficult because of patient discomfort. Plain films were normal and an MR was ordered that revealed an apparent meniscal cyst in the lateral aspect of the left knee \[Figure [7](#F7){ref-type="fig"}\]. Biopsy of the cystic structure was performed (November 1999) that revealed a high-grade synovial cell sarcoma. Metastatic work-up consisting of nuclear bone scan and CT of the chest were negative. Amputation was offered by the local care team that included a radiation oncologist because of their concern about possible contamination of the joint space and uncertain functional outcome. The patient was referred to St. Jude Children\'s Hospital for further evaluation and treatment.
::: {#F7 .fig}
Figure 7
::: {.caption}
######
MR Imaging (case two).
:::
:::
At the time of her evaluation after referral (January 2000), there was a well healed scar with no excessive swelling. There was mild tenderness on the lateral aspect of her left knee. Additional imaging studies showed abnormality at the site of prior surgery equivocal for residual tumor. There was no evidence of abnormality in the joint space. The tumor bed was explored. There was no physical evidence of compromise at the level of the joint space. She underwent wide local excision with placement of afterloading catheters. Six catheters were placed in a parallel array with 1 cm spacing. Radio-opaque clips were placed to delineate the tumor bed and assist in brachytherapy planning \[Figure [8](#F8){ref-type="fig"}\]. The margins of the resection were involved with tumor, as demonstrated by field biopsies and assessment of the margins of resection. Satellite tumor nodules were present in the resection specimen. Four days after surgery the six afterloading catheters were loaded with 82 seeds representing 302 mCi of I^125^(Figure). The dwell time of the implant was 62 hours and the patient received a total implant dose of 2480 cGy delivered at 40 cGy/hr. Two weeks later the patient began external beam irradiation at 180 cGy/day and received a course of treatment and total external beam dose of 5040 cGy using 6 MV photons with treatment delivered with two beams using a CT based treatment plan \[Figure [9](#F9){ref-type="fig"}\]. Radiation therapy was completed in March 2000.
::: {#F8 .fig}
Figure 8
::: {.caption}
######
Brachytherapy films and dosimetry.
:::
:::
::: {#F9 .fig}
Figure 9
::: {.caption}
######
External Beam films and dosimetry.
:::
:::
The patient suffered moist desquamation corresponding to the radiation therapy portal that was predicted based on the treatment and the use of a tissue equivalent bolus material which was placed on the wound on alternating days during her course of external beam irradiation. She was able to return home on the last day of treatment. On routine follow-up, only 4 months after treatment, left leg appearing to be slightly longer than her right leg by less than 1 cm. No corresponding gait problems were reported. Nearly one year after treatment (January 2000) physical examination showed good range of motion at the left knee; however, there was significant valgus angulation. An MR study was reviewed by Orthopedic Surgery and was noted to show growth arrest laterally and predominantly involving the distal femoral physis \[Figure [10](#F10){ref-type="fig"}\]. Based on these findings, the family was informed that an epiphysiodesis of the distal femoral physis would likely be required to prevent additional deformity. Due to the angulatory deformity, an osteotomy of the distal femur would be required. Because of high-dose irradiation and concerns about bone healing, osteotomy and epiphysiodesis were deferred until the three year evaluation was performed. At that time, the patient had a significant valgus deformity. The morbidity of the deformity was such that ambulation was difficult. The patient underwent a closing wedge correcting osteotomy, which was fixed with a contour plate. The patient subsequently fractured the plate secondary to early and unprotected weightbearing (against medical advice). She was placed in a cast and ultimately healed her osteotomy. She continues to have a significant limb length discrepancy and will require future lengthening procedures. She remains without evidence of disease nearly 4 years after treatment.
::: {#F10 .fig}
Figure 10
::: {.caption}
######
MR Imaging and photography.
:::
:::
Conclusion
==========
Due to its high propensity for local recurrence and metastasis, aggressive treatment of synovial sarcoma is imperative. While many different methods have been used in the treatment of these high-grade tumors, including mono-bloc soft part resection and amputation, the current standard includes local excision and radiation therapy when feasible \[[@B16]\]. Wide local excision with adjuvant radiation therapy is known to achieve a satisfactory rate of local control and good functional outcome \[[@B1]-[@B15]\]. Because these tumors commonly arise near tendon sheaths or joint capsules, treatment plans intending to achieve limb conservation may injury the epiphyseal growth plate affecting normal growth and development. Efforts should continue to improve our ability to delineate the tumor, achieve resection with microscopically negative margins and irradiate the region at risk in a manner that minimizes the effect on normal tissues \[[@B17]\].
Both patients in our study underwent two surgical procedures and were treated with brachytherapy and external beam irradiation. Brachytherapy was used to confine the highest doses to the region at risk and minimize the dose received by normal tissues. The use of brachytherapy shortens the overall treatment time and increases the rate of local control in the setting of involved margins of resection. CT-based treatment planning was used to define the volume of irradiation and to spare normal tissue structures. By reducing the amount of radiation dose delivered to normal tissues, the probability of growth deformity, radio-chemotherapy interactions, and even the hypothetical risk of second tumor formation may be lowered. No effort was made to symmetrically irradiate the physes, which would hypothetically lead to symmetrically diminished growth without the added effect of angular deformity. Because of concerns about the effects of total joint irradiation and its possible effects on functional outcome, the inhomogeneous and asymmetric approach was taken. Despite the valgus and varus deformity experienced by these children and the need for intervention, both children and parents were completely satisfied with their functional outcome and indicated that they would chose the same course of treatment if presented again with the same options.
The rationale for radiation therapy
-----------------------------------
The importance of achieving local control with aggressive surgery and high-dose irradiation cannot be overemphasized. Local control is crucial to long-term survival and avoiding the morbidity of local tumor progression. Local control, even in the setting of metastatic disease, is an important endpoint. Radiation therapy is highly successful in achieving local control in soft tissue sarcoma and is standard in the care of children with high-grade tumors such as those reviewed in this report. At our institution high-grade tumors with resection margins of 1 cm has an observed local control rate of 72% (5 of 7 patients) in the absence of radiation therapy and 100% (7 of 7 patients) when radiation therapy was given postoperatively. Among 20 unirradiated high-grade tumors that were completely resected with margins \> 1 cm only 15 (75%) were locally controlled for an extended period \[[@B18]\]. Our policy is to use external beam irradiation or brachytherapy alone for high-grade tumors that are completely excised, regardless of age or other considerations including anatomic location. We also recommend brachytherapy combined with external-beam irradiation for high-grade tumors with involved, close or indeterminate margins, regardless of size or anatomic location \[[@B19]\]. Low-grade tumors are treated with external-beam radiation therapy or brachytherapy only when the risk of recurrence and re-resection morbidity is high, or at the time of recurrence. These policies apply even to patients with metastatic disease who are likely to survive for an extended period of time after aggressive multimodality therapy including metastasectomy \[[@B19],[@B20]\]. Exceptions may be considered for small, superficial tumors in very young patients when resection can be performed with adequate margins, generally \< 5 mm although prospective studies demonstrating the appropriateness of this approach are limited \[[@B21]\].
Bone growth and development and the effects of various conditions and treatments
--------------------------------------------------------------------------------
Despite efforts to achieve local control and minimize the effects of treatment on normal tissues, damage to bone and soft tissues may be unavoidable. Synovial cell sarcoma commonly arises near tendon sheaths and joint capsules of adolescents and young adults and may be in close proximity to an epiphyseal growth plate during a time of rapid growth. The situation is made worse if the tumor is located around the distal femur or proximal tibia. Among the four epiphyseal plates in the lower extremity that contribute to the growth of the limb, those around the knee make the most significant contribution, with the distal femur and proximal tibia accounting for 50--90% and 57% of limb growth, respectively depending on age \[[@B22]\]. In our study, Case 1 was eight years old at the time of diagnosis and had a tumor lateral to the joint capsule of the left knee. Case 2 was nine years old at the time of diagnosis and had a tumor lateral to the left distal femur and in close proximity to the joint space. It was less than one year after diagnosis and definitive management that both patients developed a clinically significant angular deformity and leg length discrepancy.
There are two non-congenital mechanisms that are known to interfere with growth of the physis: direct trauma and environmental change around the plate. Trauma includes acute injury to the growth plate in manner that affects all or partial growth and results in premature closure or the formation of a physeal bar. Even if the region has retained its ability to grow it is hampered by solid bone formation across the plate \[[@B23]\]. Environmental change is less common and poorly understood. Roberts \[[@B24]\] discussed the disturbance of epiphyseal growth in the knee of infants with osteomyelitis and suggested that damage to the epiphysis might be due to an abscess or ischemia following occlusion of the blood supply. Infection is known to produce more severe leg length discrepancy problems than trauma, because the patients are typically younger at onset \[[@B23]\]. Tumors can contribute to leg length discrepancy either by direct invasion or by originating from the cartilage cells of the physis, thereby stealing growth potential from the plate \[[@B25]\]. Vascular malformations adjacent to the physis have been known to both inhibit and stimulate growth \[[@B26],[@B27]\].
Paralysis is also known to cause of growth inhibition, although the mechanism is poorly understood. Proposed contributors include reduced muscle activity, which indirectly alters the blood supply, and abnormal vasomotor control \[[@B23]\]. Avascular necrosis of the epiphysis can involve the growth plate, which obtains its blood supply from epiphyseal circulation, causing growth inhibition. Peterson described a case in which premature closure of the distal tibial physis occurred in an infant after a temporary but significant episode of vascular insufficiency during surgery to correct developmental dislocation of the right hip \[[@B28]\].
Rogalski et al. \[[@B27]\] observed that the proximity of vascular abnormalities to the epiphyseal growth plate was associated with growth disturbance. In his series, 11 out of 41 patients with extremity angiodysplastic lesions developed either hypertrophy or leg length discrepancy. Although vascular malformations have been associated with both undergrowth and overgrowth, all of the patients in this study with leg length discrepancies had overgrowth of the involved limb. These same authors postulated that increased oxygen uptake and increased flow often associated with such vascular malformation contributed to the alteration in growth.
It is also conceivable that repeated surgeries to the lateral aspect of the knee in both patients played a contributive role. A change in the environment surrounding the physis, such as muscle atrophy following prolonged bed rest, paralysis, or limb-sparing surgery with muscle loss, is known to cause a significant slowing of growth \[[@B23]\]. Although efforts were made to keep scarring from surgery to a minimum, re-resection of tumor combined with the damaging effects of radiation to soft tissues would inevitably cause a decrease in tissue vascularity potentially leading to subclinical or clinical necrosis, causing a continual mechanical compression of the physis and retarding growth. Such damage has been documented in heat-related injuries to extremities in which circumferential eschar causes a prolonged ischemia to the physis and subsequent growth inhibition \[[@B29]\].
The patients included in this report had many of the above noted contributions to abnormal growth and development including a pre-existing condition, vascular compromise due to multiple surgeries, loss of muscle mass, limited use of the extremity for a defined period of time, infection and chemotherapy. Chemotherapy may temporarily reduce bone growth through systemic effects that include the direct effects of specific agents or the indirect effects resulting from systemic infections and abnormalities in metabolism and nutrition.
The effects of irradiation on bone growth
-----------------------------------------
It has been known for almost a century that radiation therapy at sufficient levels can affect growing bone. Several factors contributing to the severity of effect including the total dose, dose per fraction, dosimetry (asymmetry and inhomogeneity) and age at the time of irradiation \[[@B24],[@B30],[@B31]\]. Probert and Parker \[[@B32]\] studied the standing and sitting height of 44 children who underwent total spinal irradiation for Hodgkin\'s disease, medulloblastoma or acute lymphoblastic leukemia. Among the patients receiving more than 3,500 rads of spinal irradiation, 8 out of 29 (28%) had a sitting height more than 2 standard deviations below the mean for age. Among those receiving less than 2,500 rads, 6 out of 15 (40%) had a sitting height more than 2 standard deviations below the mean for age. They concluded that doses in excess of 2,000 rads affect vertebral body growth in children. They further noted that children less than six years of age or those undergoing puberty experienced the most significant damage, suggesting that there is an increased sensitivity of bone to irradiation during specific developmental periods.
The conclusions of Gonzalez and Breur \[[@B33]\] were slightly different. In their study, that included 22 patients who experienced growth retardation of long bones as the result of radiotherapy in childhood, definitive limb shortening was strongly dependent on the age of the patient when the irradiation treatment began. When the growth remaining after irradiation was taken into account, no differences in radioresponsiveness were apparent. Their results suggested that despite, a temporary decrease in growth rate, irradiated bone will eventually grow at a similar rate to unirradiated bone. The total dose administered had a major influence on limb shortening as higher doses produced a greater effect. The authors noted that a \"saturation dose\" was apparent at 40 Gy because higher doses did not appear to produce further considerable increase in shortening.
The epiphyseal growth plate is the area of the developing skeleton most sensitive to the effect of radiation due in part to its rapidly proliferating stem cell population. Even low doses of radiation have been shown to cause histologic changes including temporary swelling, fragmentation, and degeneration of chondrocytes \[[@B31]\]. When higher doses are given, permanent changes including necrosis and premature closure of the physis become evident. Such was the case in our study, as both patients received a total radiation dose of over 50 Gy regionally and nearly 75 Gy focally, which undoubtedly contributed to the observed leg length discrepancies. Furthermore, the angular deformity can be attributed to the unequal dose distribution across the physis as depicted in Figures [3](#F3){ref-type="fig"} and [9](#F9){ref-type="fig"}.
Orthopedic intervention for valgus deformity
--------------------------------------------
Creating a treatment plan for patients with leg deformities who have undergone radiation therapy with or without chemotherapy can pose a difficult challenge. Because the osteocytes of neighboring bone are also destroyed, it may take years for the bone to revascularize and repopulate with healthy osteocytes \[[@B23]\]. The absence of healthy osteoblasts and precursors make lengthening procedures difficult due to unpredictable healing. Radiation damage to regional soft tissues is also an important consideration when planning a lengthening procedure. For these reasons, we decided to delay intervention to correct both the angular deformity and leg length discrepancy, and try to minimize further progression of leg deformity. At the time of surgery, Case 1 had a leg length discrepancy measuring 6 cm clinically. It was felt that epiphysiodesis of the growth plates in the healthy right knee should be the initial treatment, as it would halt progression of discrepancy and allow for some degree of correction, albeit unpredictable because of radiation damage to the growth plates of the left knee. Because of significant angular deformity, case 2 required an osteotomy to correct the defect. Future procedures are planned to address the anticipated leg length inequalities.
Historically, there have been two primary treatments for patients with angular limb deformities: epiphysiodesis and stapling. Both methods seek to achieve the same result while offering different sets of advantages and disadvantages. Partial epiphysiodesis of the knee to correct angular deformity was first described by Phemister in 1933 \[[@B34]\]. It has been used for the correction of idiopathic genu valgum or varum in the adolescent patient. Bowen \[[@B35]\] described a common surgical technique in which a bone block, centered on the physeal line, was removed through a 2 cm incision, rotated 90 degrees, and reset. This procedure causes growth arrest on the treated side and allows for continued growth and self-correction on the opposite side. Advantages to partial epiphysiodesis include a good assessment of further growth using the Green and Anderson technique \[[@B36]\], small surgical scar and high predictability of self-correction due to permanent physeal ablation. Disadvantages involve its confinement for use in adolescents due to the irreversibility of the physeal ablation. Also, estimation of skeletal maturity is difficult and unreliable. Physeal stapling, an alternative method, was first reported by Blount and Clark in 1949\[[@B37]\]. They used stainless steel staples to produce reversible growth retardation and it remains the only reversible means of manipulating growth. This procedure has traditionally been used for adolescents \[[@B38]\].
Newer radiation delivery techniques including high-dose rate brachytherapy, intraoperative radiation therapy \[[@B39],[@B40]\] and the spectrum of conformal external beam radiation therapy planning and delivery techniques \[[@B17]\] seek to confine the prescription dose to the region at risk and minimize the dose received by normal tissues. Computerized treatment planning technology and the use of 3-dimensional imaging permits the delineation of both target and normal tissue structures to the extent that the dosimetry for a defined normal tissue structure, such as bone or soft tissue, may be known with a high degree of precision. This information can be used relatively to compare different treatment plans for a given patient. Prospectively assessed, this information may be used as a clinical variable to correlate treatment dosimetry to abnormalities in growth and development including their time to onset and severity \[[@B41]\]. Until more complete knowledge is available regarding the effects of 3-dimensional dosimetry on bone and soft tissue, the full benefit of these newer treatment techniques will not be realized. We are concerned about the effects of newer treatment technology and the use of more focal irradiation. More focal treatment is likely to result in inhomogeneity and asymmetric irradiation of growth elements in bone. Prospective assessment of the use of these techniques is required.
Limited surgery and irradiation may result in growth abnormalities and deformity. These effects may have minimal or significant impact depending on functional outcome and the value attached to limb preservation for a particular patient. As mentioned in this report, both patients and families were queried about their decisions regarding treatment and both reported satisfaction with outcome recognizing that side effects were anticipated. Both families attached a high value to limb preservation.
Competing Interests
===================
None declared.
Authors\' Contributions
=======================
DTF reviewed the patient records and drafted the manuscript. WCW contributed to drafting the manuscript. MDN contributed to drafting the manuscript. TEM conceived of the study, participated in the review of the data, and helped draft the manuscript. All authors read and approved the final manuscript
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1471-2407/4/57/prepub>
Acknowledgements
================
Supported in part the American Lebanese Syrian Associated Charities (ALSAC)
The authors would like to thank Ms. Barbara Outlaw for secretarial assistance in the manuscript preparation.
|
PubMed Central
|
2024-06-05T03:55:47.955279
|
2004-8-27
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC518976/",
"journal": "BMC Cancer. 2004 Aug 27; 4:57",
"authors": [
{
"first": "Daniel T",
"last": "Fletcher"
},
{
"first": "William C",
"last": "Warner"
},
{
"first": "Michael D",
"last": "Neel"
},
{
"first": "Thomas E",
"last": "Merchant"
}
]
}
|
PMC518977
|
Background
==========
Root canal treatment is considered an essential element in the dental services provided to the population in developed countries. Various investigations were, therefore, carried out to explore the standard of root canal treatment carried out by general dental practitioners in Europe \[[@B1]-[@B3]\].
It is the responsibility of the academics and dental schools to prepare their students to adopt the guidelines and recommended standards in root canal debridement, shaping and obturation \[[@B4],[@B5]\]. Several studies have revealed that the majority of dentists do not comply with the formulated guidelines on the quality of root canal treatment \[[@B1]-[@B3],[@B6]\]. These studies investigated the attitude of dentists in Western countries such as Germany \[[@B1]\], UK \[[@B2]\], Belgium \[[@B3]\] and the USA \[[@B6]\]. On the other hand, few studies have investigated the attitude of general dental practitioners toward various aspects of endodontic treatment in developing countries \[[@B7]-[@B9]\].
The majority of endodontic treatment in Jordan is provided by the general dental practitioners due to absence of specialists in endodontics and to the lack of postgraduate programs in Jordan. The purpose of the current study was, therefore, to investigate the attitude of dentists toward endodontic treatment and to explore the materials and methods employed by general dental practitioners in North Jordan and to compare these findings with well-acknowledged international academic standards.
Methods
=======
A postal survey of general dental practitioners in Jordan was carried out to investigate common materials and methods employed in root canal treatment. A questionnaire was developed and piloted by sending it to 20 general dental practitioners. According to the replies, the questionnaire was modified. Few questions were added and others were reworded. Additionally, the questionnaire was provided in Arabic and English language. The finally modified questionnaire was posted to all registered general dental practitioners (n = 181) listed in the records of the Jordanian Dental Association and working in private practices in Irbid Governate in North Jordan, \'Questionnaire \[see [Additional file 1](#S1){ref-type="supplementary-material"}\]\'. The questionnaire consisted of 28 questions concerning different aspects of endodontic treatment including the provision of molar endodontics, root canal therapy stages, materials, the choice of instruments, the use of rubber dam and isolation methods, number of appointments, number of radiographs taken throughout the treatment, the use of canal irrigants, the use of intracanal medicaments, the choice of obturation technique, temporary and permanent coronal restoration, and case monitoring and follow-up. There was a space made available in the questionnaire for free comments of respondents. The questionnaire was accompanied by an explanatory covering letter.
To investigate the influence of the years of practical experience on the materials and techniques employed, the sample was divided into groups based on the years of professional experience: group 1, up to 5 years; group 2, 6--10 years; group 3, 11--15 years; group 4, 16--20 years, and group 5, more than 20 years. The collected data were entered into a personal computer and analyzed using the statistical package SPSS. Simple descriptive statistics were used together with Chi-square (χ^2^) test. The chosen level of significance was set at *P*\< 0.05. Unanswered questions were treated as missing values.
Results
=======
Of the 181 questionnaires distributed, 131 completed replies were received, which is a 72% response rate. The high response rate ensured that this study was representative for the general dental practitioners in North Jordan.
All the respondents performed endodontic treatment including molar teeth. However, none of the dentists reported that they would refer patients for a specialised endodontist opinion except cases, which were difficult or did not respond to initial treatment provided.
The distribution of the repondents according to the years of professional experience is shown in Table [1](#T1){ref-type="table"}. Years in practice were not evenly distributed amongst the total respondents. The number of the first two groups (0--5 and 6--10) consisted of more than half the total respondents due to the significant increase in the number of graduates in the last 10 years. Seventy four percent of the respondents were males, 26% were females. These findings are consistent with the statistics obtained from the Jordanian Dental Association. In the current study, no statistically significant differences were found between the different periods of professional experience and any of the materials, instruments or techniques employed (*P*\> 0.05).
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Data related to professional experience of the respondents.
:::
***Years of Professional experience*** Frequency Percentage %
---------------------------------------- ----------- --------------
0--5 43 32.8
6--10 28 21.4
11--15 26 19.8
16--20 20 15.3
\>20 14 10.7
:::
Table [2](#T2){ref-type="table"} shows the hand instruments used for preparation of the root canal. K-files were the most popular instruments. Root canal preparation was performed using K-files solely (30.5%) or in combination with other instruments (93.1%). Only one practitioner reported using engine-driven instruments (Profile, Dentsply Maillefer, ballaigues, Switzerland).
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
The choice of root-canal preparation techniques and instruments
:::
***Root canal preparation techniques*** ***Root canal instrument***
----------------------------------------- ----------------------------- ------ ------------------------------ ----------- ------
Technique Frequency \% Instrument Frequency \%
Filing (push-pull) 36 27.5 File 40 30.5
Step back 69 52.7 Reamer 3 0.2
Step down 26 19.8 Hedström file 6 4.6
File + hedström file 30 22.9
File + reamer 20 15.3
File, reamer + hedström file 32 24.4
:::
The majority of dentists instrumented the canal using the step back technique. The next most popular preparation technique was the filing (push-pull) technique followed by the step down technique (Table [2](#T2){ref-type="table"}).
The vast majority used gutta-percha points as their priniciple root filling material (87.8%), whilst 12.2% reported using only paste or cement to obturate the canal. Cold lateral compaction was the most common obturation technique (Table [3](#T3){ref-type="table"}). The majority of dentists reported the use of a zinc oxide based sealer with the gutta-percha points (72.5%) followed by a calcium hydroxide based sealer, Sealapex (13.7%) (Table [3](#T3){ref-type="table"}). Few dentists (n = 8) used the sealer Endomethasone as a paste root canal filling.
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
The choice of obturation technique and type of sealer.
:::
***Root canal obturation techniques*** ***Type of sealer***
---------------------------------------- ---------------------- ------ -------------------- ----------- ------
Technique Frequency \% Type of material Frequency \%
Single cone 41 31.3 Zinc oxide-eugenol 95 72.5
Lateral condensation 61 46.6 Sealapex 18 13.7
Vertical condensation 13 9.9 Endomethason 10 7.6
Cement only 16 12.2 Other 8 6.2
:::
Intracanal medication was used by 63% of the respondents. The most common material used was tricresol formalin followed by calcium hydroxide. Other formulations were also used (Table [4](#T4){ref-type="table"}).
::: {#T4 .table-wrap}
Table 4
::: {.caption}
######
The frequency and percentages of intracanal medications used.
:::
***Type of product*** Frequency Percentage %
----------------------- ----------- --------------
Calcium hydroxide 15 11.5
Formaldehyde 6 4.6
Tricresol formaline 45 34.4
Dexamethasone 1 0.8
Iodophorm 5 3.8
CMCP \* 2 1.5
Other 8 6.1
None 49 37
\* Camphorated monochlorophenol
:::
Sodium hypochlorite and hydrogen peroxide solutions were used equally as an irrigating solutions. The most popular concentration of sodium hypochlorite was 3% which was used by 14.5% (n = 19) of the repondents, with only 2.3% (n = 3) using a 0.5% concentration. The most commonly used concentration of hydrogen peroxide was 3%, which was used by 21.4% (n = 28) of the respondents. The remainder used either normal saline or local anesthetic solutions (Table [5](#T5){ref-type="table"}).
::: {#T5 .table-wrap}
Table 5
::: {.caption}
######
Data related to the choice of root-canal irrigants.
:::
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Root-canal irrigants used Concentration of NaOCl used Concentration of H~2~O~2~used\
--------------------------- ----------------------------- -------------------------------- ------------------- ----------- ------ --------------------- ----------- ------
Type Frequency \% Concentration (%) Frequency \% Concentration (%) Frequency \%
Sodium hypochlorite 43 32.8 0.5 3 2.3 1 2 1.5
Normal saline 32 24.4 1 3 2.3 2 2 1.5
Hydrogen peroxide 44 33.6 2 8 6.1 3 28 21.4
Local anesthetic solution 2 1.5 3 19 14.5 4 2 1.5
None 10 7.6 5 3 2.3 6 10 7.6
6 5 3.8 Do not use H~2~O~2~ 87 66.4
Do not use NaOCl 88 67.2
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------
:::
None of the dentists reported using rubber dam routinely to isolate the field of operation during root canal therapy. However, only five dentists reported using rubber dam occasionally but not as a routine practice. The majority of the general dental practitioners used cotton rolls solely (n = 68) or cotton rolls in combination with a high volume saliva ejector (n = 116) to reduce contamination with saliva (Figure [1](#F1){ref-type="fig"}).
::: {#F1 .fig}
Figure 1
::: {.caption}
######
The number of dentists using different isolation methods.
:::
:::
The number of visits required to complete root canal treatment related to the number of root canals in a tooth is shown in Figure [2](#F2){ref-type="fig"}. It demonstrates that general dental practitioners complete root canal treatment in more than two visits for teeth with two or more root canals. However, half the respondents (49.7%) reported completing root canal treatment for teeth with single root canal in two visits.
::: {#F2 .fig}
Figure 2
::: {.caption}
######
The number of visits according to the number of root canals per tooth.
:::
:::
Twenty seven percent of the practitioners took 3 radiographs for routine root canal treatment. 22.9% took only 2 radiographs. However, 23% reported taking only one preoperative radiograph with 4% taking only one radiograph for determining the working length. The remaining 22.9% of respondents undertook root canal treatment without taking any radiograph.
Only 14.5% of the respondents reported monitoring the root treated tooth radiographically after a period of 6 months. However, many of them mentioned that they would take a follow-up radiograph only if patients could afford to pay for it. The remainder indicated that they do not monitor their patients mostly for financial reasons and that patients would not return for follow-up appointment unless they have postoperative symptoms.
Zinc oxide eugenol cement was the most commonly placed temporary filling (92%). All dentists reported using amalgam for posterior teeth and composite for anterior teeth as a permanent coronal restorative material. All practitioners completed the restorations themselves. Sixty four percent of the respondents preferred to wait from 1 to 2 weeks after obturation before placing the permanent coronal filling, whilst the remainder placed the restoration immediately after completion of the treatment.
Discussion
==========
The response rate was 72%. It was higher than in many previous surveys conducted in Western countries with better communication infrastructure \[[@B2],[@B7],[@B10],[@B11]\].
The vast majority of the respondents did not practice single visit root canal treatment. This finding was in agreement with the results of a previous study undertaken in another developing country, Sudan \[[@B9]\]. However, a study from the US \[[@B12]\] demonstrated a clear inclination to single visit endodontics, especially in cases without apical periodontitis. Single visit treatment appears to have gained more popularity and an increased credibility in the pre-clinical endodontic teaching in America and Europe \[[@B4]\]. Another survey \[[@B3]\], showed that a high percentage of Flemish dentists performed single visit root canal treatment. Multiple visit endodontic treatment could be a direct result of lacking adequate clinical time to complete the treatment in a single visit. The dentists may prefer to wait till the complete subsidence of pain and other symptoms before obturating the canal system. Another possible explanation could be that the initial visit was spent for treating the pain and acute symptoms \[[@B3]\].
Although the application of rubber dam is always recommended as a standard during root canal treatment procedure to provide isolation, protection and improve visual access, only five dentists reported using rubber dam very occasionally and not as a routine practice. Similar findings were found in Sudan (2%) and among Flemish dentists (3.4%) \[[@B6],[@B8]\]. However, 59% of American dentists \[[@B6]\], 60% of dentists in UK \[[@B13]\] and 57% of general dental practitioners in New Zealand \[[@B14]\] reported using rubber dam routinely in endodontic treatment. The reasons for not using rubber dam could be the extra cost, additional time, lack of adequate skills or training, absence of patient\'s acceptability or inadequate education in the undergraduate teaching curriculum. It was found that continuing education course attendees seem to be encouraged to use rubber dam \[[@B14]\].
In the current survey, most general dental practitioners used hydrogen peroxide and sodium hypochlorite solutions as canal irrigants. The same result was demonstrated amongst dentists in Switzerland \[[@B11]\]. Sodium hypochlorite is recommended as the material of choice for irrigating the root canal system because of its effective antimicrobial and tissue solving action \[[@B15]\]. The selection of irrigant could be associated with the use of rubber dam, as it was found that 70% of rubber dam users among British dentists irrigated with sodium hypochlorite, whilst non-users tended to use local anesthetic solution \[[@B13]\]. The current findings do not mirror these findings. The vast majority of our respondents were non-users of rubber dam and one third of them use sodium hypochlorite routinely. A similar trend toward using sodium hypochlorite as an irrigant despite not using rubber dam for isolation, was noticed amongst Flemish dentists \[[@B16]\]. In the UK, the majority of dentists used local anesthetic solution to irrigate the canal space \[[@B2]\].
The use of either sodium hypochlorite or hydrogen peroxide without isolating the field of operation tightly with a rubber dam presents an obviously hazardous practice in the use of potentially irritant irrigation solutions.
Despite the fact that calcium hydroxide is recognized as the standard intracanal medicament for inter-appointment dressing \[[@B17]\], it was used by only 11.5% of the respondents. More than one third of the general practitioners reported using formaldehyde-containing materials. This finding is consistent with previous findings recorded for Sudanese dentists \[[@B9]\]. Although formaldehyde-containing products have been used for their antimicrobial and fixative properties, they are toxic to periradicular tissues \[[@B18]\] and may have mutagenic and carcinogenic potential \[[@B19]\]. The use of calcium hydroxide, as intracanal medication, should be encouraged among dentists in developing countries such as Jordan, as it is effective against most root canal pathogens and able to denature bacterial endotoxins \[[@B20],[@B21]\]. It has, also, been reported to be the material of choice by dentists in the Western world \[[@B11],[@B22]\].
The step back technique was the most popular canal preparation technique among North Jordanian general dental practitioners. The filing (push-pull) technique, on the other hand, was used by 27.5% of the respondents. In another study, 60.4% of Flemish dentists used the standard filing technique \[[@B16]\]. Generally, dentists in Jordan tended to use hand instruments and were not inclined to use more advanced engine driven techniques for shaping the root canal system.
Almost half of the general dental practioners in North Jordan used cold lateral compaction of gutta-percha to obturate the root canal space. This technique is acknowledged universally and is the most common obturation technique \[[@B4]\]. However, 31.3% of the dentists in the current survey used a single cone technique, in common with 68% of Swiss dentists \[[@B11]\]. Additionally, 12.2% of respondents used only paste to obturate the root canal system. Seemingly, dentists in North Jordan are not strong advocates of the more recently introduced advanced obturation techniques. This may be attributed to additional cost involved or the lack of skill and training.
Conclusions
===========
This study investigated the status of endodontic practice among general dental practitioners working in private offices in North Jordan. It demonstrated that dentists performed procedures which often deviated from well-acknowledged endodontic quality guidelines. Dentists did not use rubber dam for isolation and frequently use formaldehyde-containing materials for inter-appointments dressing. In addition, a significant proportion of dentists (n = 30) did not use radiographs at any stage of endodontic treatment. General practitioners did not seem to keep up with recently introduced techniques, but use more conventional methods.
The North Jordanian general dental practitioners carried out endodontic treatment with few referals to specialists. However, the absence of postgraduate endodontic programs and continuing education courses in addition to economic restrictions could explain why dentists in Jordan do not carry out endodontic treatment in accordance with recognized international standards.
Competing Interests
===================
None declared.
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1472-6831/4/1/prepub>
Supplementary Material
======================
::: {.caption}
###### Additional File 1
Endodontic Survey Questionnaire text of the file contains questions related to endodontic practice among general dental practitioners.
:::
::: {.caption}
######
Click here for file
:::
|
PubMed Central
|
2024-06-05T03:55:47.958362
|
2004-9-10
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC518977/",
"journal": "BMC Oral Health. 2004 Sep 10; 4:1",
"authors": [
{
"first": "Wael M",
"last": "Al-Omari"
}
]
}
|
PMC518999
|
Introduction {#s1}
============
The use of nucleotide sequence differences in a single gene to investigate evolutionary relationships was first widely applied by Carl Woese ([@pbio-0020312-Woese2]). He recognized that sequence differences in a conserved gene, ribosomal RNA, could be used to infer phylogenetic relationships. Sequence comparisons of rRNA from many different organisms led initially to recognition of the *Archaea,* and subsequently to a redrawing of the tree of life. More recently, the polymerase chain reaction has allowed sequence diversity in any gene to be examined. Genes that evolve slowly, like rRNA, often do not differ among closely related organisms, but they are indispensable in recovering ancient relationships, providing insights as far back as the origin of cellular life ([@pbio-0020312-Woese1]). On the other hand, genes that evolve rapidly may overwrite the traces of ancient affinities, but regularly reveal divergences between closely related species.
Mitochondrial DNA (mtDNA) has been widely employed in phylogenetic studies of animals because it evolves much more rapidly than nuclear DNA, resulting in the accumulation of differences between closely related species ([@pbio-0020312-Brown1]; [@pbio-0020312-Moore1]; [@pbio-0020312-Mindell1]). In fact, the rapid pace of sequence change in mtDNA results in differences between populations that have only been separated for brief periods of time. John Avise was the first to recognize that sequence divergences in mtDNA provide a record of evolutionary history within species, thereby linking population genetics and systematics and establishing the field of phylogeography ([@pbio-0020312-Avise4]). Avise and others also found that sister species usually show pronounced mtDNA divergences, and more generally that "biotic entities registered in mtDNA genealogies...and traditional taxonomic assignments tend to converge" ([@pbio-0020312-Avise2]). Although many species show phylogeographic subdivisions, these usually coalesce into single lineages "at distances much shorter than the internodal branch lengths of the species tree" ([@pbio-0020312-Moore1]). In other words, sequence divergences are much larger among species than within species, and thus mtDNA genealogies generally capture the biological discontinuities recognized by taxonomists as species. Taking advantage of this fact, taxonomic revisions at the species level now regularly include analysis of mtDNA divergences. For example, many newly recognized species of birds have been defined, in part, on the basis of divergences in their mtDNA (e.g., [@pbio-0020312-Avise3]; [@pbio-0020312-Gill1]; [@pbio-0020312-Murray1]; [@pbio-0020312-AOU1]; [@pbio-0020312-Banks1], [@pbio-0020312-Banks2], [@pbio-0020312-Banks3]).
The general concordance of mtDNA trees with species trees implies that, rather than analyzing DNA from morphologically identified specimens, it could be used the other way around, namely to identify specimens by analyzing their DNA. Past applications of DNA-based species identification range from reconstructing food webs by identifying fragments in stomachs ([@pbio-0020312-Symondson1]) to recognizing products prepared from protected species ([@pbio-0020312-Palumbi1]) and resolving complexes of mosquitoes that transmit malaria and dengue fever ([@pbio-0020312-Phuc1]). Despite such demonstrations, the lack of a lingua franca has limited the use of DNA as a general tool for species identifications.
If a short region of mtDNA that consistently differentiated species could be found and accepted as a standard, a library of sequences linked to vouchered specimens would make this sequence an identifier for species, a "DNA barcode" ([@pbio-0020312-Hebert1]). Recent work suggests that a 648-bp region of the mitochondrial gene, cytochrome *c* oxidase I (COI), might serve as a DNA barcode for the identification of animal species. This gene region is easily recovered and it provides good resolution, as evidenced by the fact that deep sequence divergences were the rule between 13,000 closely related pairs of animal species ([@pbio-0020312-Hebert2]). The present study extends these earlier investigations by testing the correspondence between species boundaries signaled by COI barcodes and those established by prior taxonomic work. Such tests require the analysis of groups that have been studied intensively enough to create a firm system of binomials; birds satisfy this requirement. Although GenBank holds many bird sequences, these derive from varied gene regions while a test of species identification requires comparisons of sequences from a standard gene region across species. Accordingly, the barcode region of COI was sequenced in 260 of the 667 bird species that breed in North America ([@pbio-0020312-AOU1]).
Results {#s2}
=======
All 260 bird species had a different COI sequence(s); none was shared between species. COI sequences in the 130 species represented by two or more individuals were either identical or most similar to other sequences of the same species. Furthermore, with a few interesting exceptions discussed below, COI sequence differences between closely related species were far higher than differences within species (18-fold higher; average Kimura-2-parameter \[K2P\] differences between and within species, 7.93% and 0.43%, respectively) ([Figure 1](#pbio-0020312-g001){ref-type="fig"}).
::: {#pbio-0020312-g001 .fig}
Figure 1
::: {.caption}
###### Comparison of Nucleotide Sequence Differences in COI among 260 Species of North American Birds
Pairwise comparisons between 437 COI sequences are separated into three categories: differences between individuals in the same species, differences between individuals in the same genus (not including intraspecific differences), and differences between individuals in the same family (not including intraspecific or intrageneric differences).
:::
:::
In most cases the neighbor-joining (NJ) tree showed shallow intraspecific and deep interspecific divergences ([Figure 2](#pbio-0020312-g002){ref-type="fig"}). However, in four exceptional cases, there were deep divergences within a species (*Tringa solitaria,* Solitary Sandpiper; *Sturnella magna,* Eastern Meadowlark; *Cisthorus palustris,* Marsh Wren; and *Vireo gilvus,* Warbling Vireo). COI sequences in each of these polytypic species separated into pairs of divergent clusters in the NJ tree. The intraspecific K2P distances in these exceptional species were 3.7%--7.2%, 9- to 17-fold higher than the average distance ([Figures 2](#pbio-0020312-g002){ref-type="fig"}, [3](#pbio-0020312-g003){ref-type="fig"}, and [S1](#s1){ref-type="sec"}).
::: {#pbio-0020312-g002 .fig}
Figure 2
::: {.caption}
###### NJ Tree of COI Sequences from 30 Species in Family *Scolapacidae* (Sandpipers and Kin)
The divergent pair of clustered sequences of Tringa solitaria is highlighted. An asterisk indicates a COI sequence from GenBank.
:::
:::
::: {#pbio-0020312-g003 .fig}
Figure 3
::: {.caption}
###### NJ Tree of COI Sequences from 260 Species of North American Birds
Intraspecific divergences were sampled in 130 species; these are marked in blue. Four species showed deep intraspecific divergence: (a) *Sturnella magna,* (b) *Cistothorus palustris,* (c) *Vireo gilvus,* and (d) *Tringa solitaria.* Higher-order classifications in families (gray) and orders (gold) are highlighted, and are labeled on the left and right of the figure, respectively. Gold numerals indicate the two species that appear as paraphyletic lineages at the family level: (1) Oenanthe oenanthe and (2) *Hirundo rustica.*
:::
:::
Setting aside these polytypic species, the average intraspecific distance was very low, 0.27%, and the maximum average intraspecific difference was only 1.24%. Most congeneric species pairs showed divergences well above this value, but 13 species in four genera had interspecific distances that were below 1.25%. They included *Larus argentatus, L. canus, L. delawarensis, L. glaucoides, L. hyperboreus, L. marinus,* and L. thayeri (Herring Gull, Mew Gull, Ring-billed Gull, Iceland Gull, Glaucous Gull, Great Black-Backed Gull, and Thayer\'s Gull); Haematopus bachmani and H. palliatus (Black Oystercatcher and American Oystercatcher); Corvus brachyrhynchos and C. caurinus (American Crow and Northwestern Crow); and Anas platyrhynchos and A. rubripes (Mallard and American Black Duck) ([Figure S1](#sg001){ref-type="supplementary-material"}).
Although species were the focus of this study, we noted that the NJ tree of COI sequences generally matched avian classifications at higher levels, with most genera, families, and orders appearing as nested monophyletic lineages concordant with current taxonomy ([Figures 3](#pbio-0020312-g003){ref-type="fig"} and [S1](#s1){ref-type="sec"}).
Discussion {#s3}
==========
The simplest test of species identification by DNA barcode is whether any sequences are found in two species; none was in this study. Although sequences were not shared by species, sequence variation did occur in some species. Thus the second test is whether the differences within species are much less than those among species. In this study we found that COI differences among most of the 260 North American bird species far exceeded those within species.
In order to conservatively test the effectiveness of COI barcodes as an identification tool, our sample must not have underestimated variability within species or have overestimated it among species. Our measures of intraspecific variation could be underestimates if members of a species show sequence divergence across their distribution that our study failed to adequately register. The two to three representatives of the 130 species used to examine this issue were collected from sites that were, on average, approximately 1,080 km apart, suggesting adequate representation of genetic diversity across their ranges. However, to further investigate this issue, we compared sequence differences within species to geographic distances between the collection points for their specimens and found these were unrelated ([Figure 4](#pbio-0020312-g004){ref-type="fig"}). Based on these results, high levels of intraspecific divergence in COI in North American birds appear uncommon, given that we analyzed 130 different species in a variety of orders. Our findings are supported by a review of 34 mostly North American birds which showed a similarly low average maximum intraspecific K2P divergence of mtDNA of 0.7% ([@pbio-0020312-Moore1]). Similarly, [@pbio-0020312-Weibel1] reported an average intraspecific divergence of 0.24% in their study of COI variation in woodpeckers. We conclude that our investigation has not underestimated intraspecific variation in any systematic fashion.
::: {#pbio-0020312-g004 .fig}
Figure 4
::: {.caption}
###### Genetic Difference versus Geographic Distance
For each same-species pair of specimens, the geographic distance between where specimens were collected is plotted against their COI divergence (K2P).
:::
:::
On the other hand, our discovery of four polytypic species within a sample of 130 makes it likely there are other North American birds with divergent populations that may represent hidden species. Recent studies have identified marked mtDNA divergences within North American populations of Common Ravens ([@pbio-0020312-Omland1]), Fox Sparrows ([@pbio-0020312-Zink2]), and Curve-billed Thrashers ([@pbio-0020312-Zink1]), leading to proposals to split each into two or more species. Species with Holarctic distributions are particularly good candidates for unrecognized species, and recent DNA and morphological investigations have led taxonomists to split several such species into two, including Wilson\'s and Common Snipes, American and Eurasian Three-toed Woodpeckers, and American and Water Pipits ([@pbio-0020312-Zink3], [@pbio-0020312-Zink4]; [@pbio-0020312-Miller1]; [@pbio-0020312-AOU1]; [@pbio-0020312-Banks1], [@pbio-0020312-Banks2], [@pbio-0020312-Banks3]). Widespread application of COI barcodes across the global ranges of birds will undoubtedly lead to the recognition of further hidden species.
Any critical test of the effectiveness of barcodes must also consider the possibility that our study has overestimated variability among species. We therefore looked at species individually, comparing their minimum distance to a congener with the maximum divergence within each species. This analysis included a number of well-recognized sibling species, including Calidris mauri and *C. pusilla, Fraternicula arctica* and *F. corniculata,* and *Empidonax traillii* and *E. virescens.* There were sufficient data to perform this analysis on three of the four polytypic species and on 70 of the 126 remaining species ([Figure 5](#pbio-0020312-g005){ref-type="fig"}). The average maximum K2P divergence within these 70 species was 0.29%, while the average minimum distance to a congener was 7.05% (24-fold higher), values comparable to those for the entire data set. Prior studies that looked exclusively at sister species of birds found an average K2P mtDNA distance of 5.1% in 35 pairs ([@pbio-0020312-Klicka1]) and 3.5% in 47 pairs ([@pbio-0020312-Johns1]). More generally, 98% of sister species pairs of vertebrates were observed to have K2P mtDNA divergences greater than 2% ([@pbio-0020312-Johns1]). Thus it appears that a COI barcode will enable the separation of most sister species of birds.
::: {#pbio-0020312-g005 .fig}
Figure 5
::: {.caption}
###### Intraspecific Compared to Interspecific COI Distances (K2P) for Individual Species
For each species in which this comparison was possible (*n* = 73), maximum intraspecific variation is compared to minimum interspecific congeneric difference. For illustration purposes shown here, 2.0% is chosen as a cutoff between usual values for intra- and interspecific variation. This divides the graph into four quadrants that represent different categories of species: (I) Intraspecific distance, \<2%; interspecific distance, \>2%: concordant with current taxonomy; (II) Intraspecific distance, \>2%; interspecific distance, \>2%: probable composite species (i.e., candidate for taxonomic split); (III) Intraspecific distance, \<2%; interspecific distance, \<2%: recent divergence, hybridization, or synonymy; (IV) Intraspecific distance, \>2%; interspecific distance, \<2%: probable misidentification of specimen.
:::
:::
There is a possibility that the North American bird fauna is not representative of the global situation. The recent and extensive glaciations in North America may have decreased within-species variability by inducing bottlenecks in population size or may have increased variation between species by pruning many sister taxa ([@pbio-0020312-Avise1]; [@pbio-0020312-Mila1]). This issue can only be resolved by evaluating the efficacy of barcodes in tropical and southern temperate faunas to ascertain if our results are general. We note that recent mtDNA studies in these settings have found both multiple sibling species in what were thought to be single species ([@pbio-0020312-Ryan1]) and geographically structured variation suggesting the presence of cryptic species ([@pbio-0020312-Hackett1]; [@pbio-0020312-Bates1]).
The diagnosis of species is particularly difficult when they are young. Moreover, hybridization is often common when the ranges of recently arisen species overlap, further complicating identifications. Such newly emerged species are sometimes referred to as superspecies ([@pbio-0020312-Mayr1]), or species complexes, to indicate their close genetic similarity. For example, the white-headed gulls are thought to have diverged very recently, some less than 10,000 years ago ([@pbio-0020312-Crochet1], [@pbio-0020312-Crochet2]), and hybridization is common among many of them. It is thus not surprising that their COI barcodes and other gene loci are very similar. DNA barcodes can help to define the limits of such recently emerged species, but more gene loci need to be surveyed and more work is required to determine which analytical methods can best deduce species boundaries in such cases. The NJ method used here has the advantage of speed, and performs strongly when sequence divergences are low, so it is generally appropriate for recovering intra- and interspecies phylogeny. However, a library of COI barcodes linked to named specimens will provide the large data sets needed to test the efficacy of varied tree-building methods (for review, see [@pbio-0020312-Holder1]).
Even between species that diverged long ago, hybridization will lead to shared or very similar sequences at COI and other gene loci. Because mitochondrial DNA is maternally inherited, a COI barcode will assign F~1~ hybrids to the species of their female parent. Hybridization leading to the transfer of mtDNA from one species to another can result in a mtDNA tree that is incongruent with the species tree, but it will not necessarily prevent species from being distinguished, unless the mitochondrial transfer is so recent that their sequences have not diverged ([@pbio-0020312-Moore1]). However, recent hybridization will lead species to share COI barcodes, and we expect that more intensive study will reveal such shared sequences in species that are known to hybridize, such as the white-headed gulls ([@pbio-0020312-Crochet2]) and Mallard/Black Ducks ([@pbio-0020312-Ankney1]; [@pbio-0020312-Avise5]).
In other cases, a lack of COI divergence may indicate that populations are part of a single species, helping to sort out misleading morphological classifications. For example, the blue and white morphs of *Chen caerulescens,* Snow Goose, were thought to be different species until recently ([@pbio-0020312-Cooke1]). The close COI similarity of American and Black Oystercatchers revealed in this study is consistent with suggestions that these are allopatrically distributed color morphs of a single species ([@pbio-0020312-Jehl1]). Low COI divergences between American and Northwestern Crows similarly support earlier suggestions that these taxa are conspecific ([@pbio-0020312-Sibley1]; [@pbio-0020312-Madge1]).
Just as COI similarities among species already questioned by taxonomists may reinforce these queries, deep COI divergences within species may reinforce suspicions of hidden diversity. For example, three of the four polytypic species in this study (Eastern Meadowlark, Marsh Wren, and Warbling Vireo) are split into two by some taxonomists ([@pbio-0020312-Wells1]), and the fourth, Solitary Sandpiper, contains two allopatric subspecies with morphological differences ([@pbio-0020312-Godfrey1]). In these cases, suspicions in the minds of taxonomists are reinforced by large COI divergences. If these species had not been the subject of prior scrutiny, COI barcoding would have flagged them as deserving of such attention.
The importance of sampling multiple individuals within each species is highlighted by a recent review which found evidence of species-level paraphyly or polyphyly in 23% of 2,319 animal species, including 16.7% of 331 bird species ([@pbio-0020312-Funk1]). This review provides a clear discussion of possible causes (imperfect taxonomy, hybridization, incomplete lineage sorting) and indicates the need for the careful reexamination of current taxonomy and for the collection of genetic data across both geographic ranges and morphological variants. Barcoding, together with related developments in sequencing technology, is likely to provide an efficient approach to the assembly of such genetic data.
We expect that the assembly of a comprehensive barcode library will help to initiate taxonomic investigations that will ultimately lead to the recognition of many new avian species. This process will begin with the discovery of novel COI barcodes. Some of these cases will simply represent the first barcode records for described but previously unanalyzed species, but taxonomic study will confirm that others derive from new species. We propose that specimens with barcodes diverging deeply from known taxa should be known by a "provisional species" designation that links them to the nearest established taxon. For example, the divergent clusters of Solitary Sandpiper specimens might be called T. solitaria PS-1 and T. solitaria PS-2, highlighting a need for further taxonomic study.
What threshold might be appropriate for flagging genetically divergent specimens as provisional species? This threshold should certainly be high enough to separate only specimens that very likely belong to different species. Because patterns of intraspecific and interspecific variation in COI appear similar in various animal groups ([@pbio-0020312-Grant1] \[sardines\]; [@pbio-0020312-Hebert1] \[moths\]; [@pbio-0020312-Hogg1] \[springtails\]), we propose a standard sequence threshold: 10× the mean intraspecific variation for the group under study. If applied to the birds examined in this study (0.27% average intraspecific variation; 2.7% threshold), a 10× threshold would recognize over 90% of the 260 known species, as well as the four probable new species. As this result demonstrates, a threshold approach will overlook species with short evolutionary histories and those exposed to recent hybridization, but it will be a useful screening tool, especially for groups that have not received intensive taxonomic analysis.
For 260 of the 667 bird species breeding in North America, our evidence shows that COI barcodes separate individuals into the categories that taxonomists call species. This adds to the evidence already in hand for insects and other arthropods that barcodes can be an efficient tool for species identification. Should future studies broaden this evidence, a comprehensive library of barcodes will make it easier to probe varied areas of avian biology. A DNA barcode will help, for example, when morphological diagnoses are difficult, as when identifying remnants (including eggs, nestlings, and adults) in the stomachs of predators. A DNA barcode could similarly identify fragments of birds that strike aircraft ([@pbio-0020312-Dove1]) and recognize carcasses of protected or regulated species ([@pbio-0020312-Guglich1]). DNA barcodes could also reveal the species of avian blood in mosquitoes carrying West Nile virus ([@pbio-0020312-Michael1]; [@pbio-0020312-Lee1]), help experts distinguish morphologically similar juveniles or nonbreeding adults in banding work, and allow expanded nonlethal study of endangered or threatened populations.
The two essential components for an effective DNA barcode system (and thus a new master key to the encyclopedia of life \[[@pbio-0020312-Wilson1]\]) are standardization on a uniform barcode sequence, such as COI, and a library of sequences linked to named voucher specimens. The present study provides an initial set of COI barcodes for about 40% of North American birds. More detailed sampling of COI sequences is needed for these species, and barcodes need to be gathered for the remaining North American birds and for those in other geographic regions. This work could represent a first step toward a DNA barcode system for all animal and plant life, an initiative with potentially widespread scientific and practical benefits ([@pbio-0020312-Stoeckle1]; [@pbio-0020312-Wilson1]; [@pbio-0020312-Blaxter1]; [@pbio-0020312-Janzen1]).
Materials and Methods {#s4}
=====================
{#s4a}
### {#s4a1}
Existing data can only yield limited new insights into the effectiveness of a DNA-based identification system for birds. Two mitochondrial genes, cyt *b* and COI, are rivals for the largest number of animal sequence records greater than 600 bp in GenBank (4,791 and 3,009 species, respectively). However, COI coverage for birds is modest; 173 species share COI sequences with 600-bp overlap. As these records derive from a global avifauna of 10,000 species, they provide a limited basis to evaluate the utility of a COI-based identification system for any continental fauna, impelling us to gather new sequences.
We employed a stratified sampling design to gain an overview of the patterns of COI sequence divergence among North American birds. The initial level of sampling examined a single individual from each of 260 species to ascertain COI divergences among species. These species were selected on the basis of accessibility without regard to known taxonomic issues. The second level of sampling examined one to three additional individuals from 130 of these species to provide a general sense of intraspecific sequence divergences, as well as a preliminary indication of variation in each species. When possible, these individuals were obtained from widely separated localities in North America. The third level of our analysis involved sequencing four to eight more individuals for the few species where the second level detected more than 2% sequence divergence among individuals. Our studies examined specimens collected over the last 20 years; 98% were obtained from the tissue bank at the Royal Ontario Museum, Toronto, Canada. Collection localities and other specimen information are available in the "Birds of North America" file in the Completed Projects section of the Barcode of Life website (<http://www.barcodinglife.com>). Taxonomic assignments follow the latest North American checklist ([@pbio-0020312-AOU1]) and its recent supplements ([@pbio-0020312-Banks1], [@pbio-0020312-Banks2], [@pbio-0020312-Banks3]).
Mitochondrial pseudogenes can complicate PCR-based studies of mitochondrial gene diversity ([@pbio-0020312-Bensasson1]; [@pbio-0020312-Thalmann1]). We used protocols to reduce pseudogene impacts that included extracting DNA from tissues rich in mitochondria ([@pbio-0020312-Sorenson1]), employing primers with high universality ([@pbio-0020312-Sorenson1]), and amplifying a relatively long PCR product because most pseudogenes are short ([@pbio-0020312-Pereira1]). DNA extracts were prepared from small samples of muscle using the GeneElute DNA miniprep Kit (Sigma, St. Louis, Missouri, United States), following the manufacturer\'s protocols. DNA extracts were resuspended in 10 μl of H~2~O, and a 749-bp region near the 5′ terminus of the COI gene was amplified using primers (BirdF1-TTCTCCAACCACAAAGACATTGGCAC and BirdR1-ACGTGGGAGATAATTCCAAATCCTG). In cases where this primer pair failed, an alternate reverse primer (BirdR2-ACTACATGTGAGATGATTCCGAATCCAG) was generally combined with BirdF1 to generate a 751-bp product, but a third reverse primer (BirdR3-AGGAGTTTGCTAGTACGATGCC) was used for two species of *Falco.* The 50-μl PCR reaction mixes included 40 μl of ultrapure water, 1.0 U of *Taq* polymerase, 2.5 μl of MgCl~2~, 4.5 μl of 10× PCR buffer, 0.5 μl of each primer (0.1 mM), 0.25 μl of each dNTP (0.05 mM), and 0.5--3.0 μl of DNA. The amplification regime consisted of 1 min at 94 °C followed by 5 cycles of 1 min at 94 °C, 1.5 min at 45 °C, and 1.5 min at 72 °C, followed in turn by 30 cycles of 1 min at 4 °C, 1.5 min at 51 °C, and 1.5 min at 72 °C, and a final 5 min at 72 °C. PCR products were visualized in a 1.2% agarose gel. All PCR reactions that generated a single, circa 750-bp, product were then cycle sequenced, while gel purification was used to recover the target gene product in cases where more than one band was present. Sequencing reactions, carried out using Big Dye v3.1 and the BirdF1 primer, were analyzed on an ABI 377 sequencer. The electropherogram and sequence for each specimen are in the "Birds of North America" file, but all sequences have also been deposited in GenBank (see [Supporting Information](#s5){ref-type="sec"}). COI sequences were recovered from all 260 bird species and did not contain insertions, deletions, nonsense, or stop codons, supporting the absence of nuclear pseudogene amplification ([@pbio-0020312-Pereira1]). In addition to 429 newly collected sequences, nine GenBank sequences from five species were included (these were the only full-length COI sequences corresponding to species in this study).
Sequence divergences were calculated using the K2P distance model ([@pbio-0020312-Kimura1]). A NJ tree of K2P distances was created to provide a graphic representation of the patterning of divergences among species ([@pbio-0020312-Saitou1]).
Supporting Information {#s5}
======================
Figure S1
::: {.caption}
###### Birds Appendix
Complete NJ tree based on K2P distances at COI for 437 sequences from 260 species of North American birds. Entries marked with an asterisk represent COI sequences from GenBank.
(100 KB PDF).
:::
::: {.caption}
######
Click here for additional data file.
:::
Accession Numbers {#s5a2}
-----------------
Sequences described in [Materials and Methods](#s4){ref-type="sec"} have been deposited in GenBank under accession numbers AY666171 to AY666596.
Funding for this study was provided by grants from NSERC, the Canada Research Chairs program, and the Canadian Wildlife Service to PDNH. We express our particular appreciation to Allan Baker, Jon Barlow, and Mark Peck for providing access to specimens held in the Tissue Collection at the Royal Ontario Museum. We thank Heather Cole and Angela Holliss for assistance with DNA sequencing, Sujeevan Ratnasingham and Rob Dooh for assistance with data analysis, and Ian Smith for aid with graphics. Finally, we thank Jesse Ausubel, Teri Crease, Carla Dove, Jeremy deWaard, Dan Janzen, David Thaler, Paul Waggoner, Jonathan Witt, and four anonymous reviewers for their comments on earlier drafts of the manuscript.
**Conflicts of interest.** The authors have declared that no conflicts of interest exist.
**Author contributions.** PDNH conceived and designed the experiments. TSZ performed the experiments. PDNH, MYS, and TSZ analyzed the data. CMF contributed reagents/materials/analysis tools. PDNH, MYS, and CMF wrote the paper.
Academic Editor: Charles Godfray, Imperial College, Silwood Park
Citation: Hebert PDN, Stoeckle MY, Zemlak TS, Francis CM (2004) Identification of birds through DNA barcodes. PLoS Biol 2(10): e312.
COI
: cytochrome *c* oxidase I
K2P
: Kimura-2 parameter
mtDNA
: mitochondrial DNA
NJ
: neighbor joining
|
PubMed Central
|
2024-06-05T03:55:47.960901
|
2004-9-28
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC518999/",
"journal": "PLoS Biol. 2004 Oct 28; 2(10):e312",
"authors": [
{
"first": "Paul D. N",
"last": "Hebert"
},
{
"first": "Mark Y",
"last": "Stoeckle"
},
{
"first": "Tyler S",
"last": "Zemlak"
},
{
"first": "Charles M",
"last": "Francis"
}
]
}
|
PMC519000
|
Introduction {#s1}
============
The frequency of cancer development varies depending on the age of the host. In humans, the most common childhood cancers include tumors of the hematopoietic system, nervous system, and skeletal muscle system. In contrast, in the adult population, solid tumors of the lung, colon, breast, and prostate are more common. Differences in types of cancers in hosts of different ages may reflect the abundance of cells in a differentiative state susceptible to tumorigenesis ([@plbi-02-11-03-Greaves1]; [@plbi-02-11-03-Klein1]). Indeed, many reports document that oncogene activation generally induces tumorigenesis in immature cellular lineages ([@plbi-02-11-03-Adams1]; [@plbi-02-11-03-Spanopoulou1]; [@plbi-02-11-03-Pelengaris1]; [@plbi-02-11-03-Blyth1]).
We recently reported that upon oncogene inactivation tumor cells can differentiate into mature cells, and in this new differentiative context the reactivation of an oncogene fails to restore tumorigenesis ([@plbi-02-11-03-Jain1]). Based on these results, we speculate that only specific differentiative windows provide the correct epigenetic program to permit oncogene activation to initiate and sustain tumorigenesis. Here we directly evaluate whether an oncogene\'s ability to induce tumorigenesis depends on the differentiative context when this oncogene first becomes activated. We have examined the ability of the *C-MYC* oncogene to induce tumorigenesis in mice of different ages using a novel conditional transgenic model system for *C-MYC*--induced hepatocellular carcinoma (HCC).
*C-MYC* (now referred to as *MYC*) is a member of a family of proto-oncogenes comprising *C*-*MYC, N-MYC,* and *L-MYC. MYC* encodes a transcription factor that, as part of a heterodimeric complex with MAX, regulates the expression of a multitude of genes involved in regulating cellular proliferation and growth ([@plbi-02-11-03-Johnston1]; [@plbi-02-11-03-Grandori1]; [@plbi-02-11-03-Oster1]; [@plbi-02-11-03-Pelengaris3]). Overexpression of MYC is commonly associated with tumorigenesis. MYC exerts its neoplastic function by inducing autonomous cellular proliferation and cellular growth, blocking differentiation, and inducing genomic destabilization ([@plbi-02-11-03-Dang1]; [@plbi-02-11-03-Felsher2]; [@plbi-02-11-03-Grandori1]; [@plbi-02-11-03-Oster1]; [@plbi-02-11-03-Pelengaris3]; [@plbi-02-11-03-Karlsson1]). It is generally assumed that MYC is restrained from causing tumorigenesis because it concomitantly induces cellular proliferation and apoptosis ([@plbi-02-11-03-Pelengaris3]).
HCC is a common and generally incurable human malignancy of epithelial cells ([@plbi-02-11-03-Thorgeirsson1]). HCC has been strongly associated with viral infections such as hepatitis B and C; exposure to toxins, such as alcohol, aflatoxin, and phenobarbital; and exposure to various carcinogens such as polyvinyl chloride ([@plbi-02-11-03-Thorgeirsson1]). Interestingly, the ability of these carcinogens, such as the hepatitis viruses, to induce HCC depends on the host age during infection. Hepatitis B infection acquired during neonatal development versus adulthood results in a several-magnitude increased risk of HCC ([@plbi-02-11-03-Chang1]). These results suggest that there are differentiative windows during liver development that may be more susceptible to neoplastic transformation.
Human tumors have been analyzed extensively for genetic events associated with HCC ([@plbi-02-11-03-Buetow1]; [@plbi-02-11-03-Tsuda1]; [@plbi-02-11-03-Boige1]; [@plbi-02-11-03-Piao1]). *MYC* oncogene activation is one of the more common events in the pathogenesis of HCC. MYC overexpression in human HCC is most commonly associated with genomic amplification ([@pbio-0020332-Elella1]; [@plbi-02-11-03-Kawate1]). Human HCCs exhibit amplification of *MYC* in up to 50% of tumors ([@pbio-0020332-Elella1]; [@plbi-02-11-03-Kawate1]). The presence of *MYC* amplification in HCC portends a more advanced and aggressive clinical phenotype ([@pbio-0020332-Elella1]). Thus, the *MYC* oncogene appears to play a critical role in the pathogenesis of HCC.
The most compelling evidence that *MYC* is causally associated with the etiology of HCC comes from animal models ([@plbi-02-11-03-Sandgren1]; [@plbi-02-11-03-Fourel1]; [@plbi-02-11-03-Murakami1]; [@plbi-02-11-03-Morgenbesser1]; [@plbi-02-11-03-Sargent1], [@plbi-02-11-03-Sargent2]; [@plbi-02-11-03-De1]; [@plbi-02-11-03-Santoni-Rugiu1]; [@plbi-02-11-03-Renard1]). *MYC* is frequently activated through insertional mutagenesis mediated by the hepadnavirus in woodchuck liver tumors ([@plbi-02-11-03-Fourel1]; [@plbi-02-11-03-Renard1]). Carcinogen-induced HCC in Wistar rats is associated with *MYC* amplification and overexpression ([@plbi-02-11-03-De1]). The overexpression of *MYC* (as a transgene) and other oncogenes (e.g., *RAS,* T antigen) in murine hepatocytes results in HCC ([@plbi-02-11-03-Sandgren1]). The latency of HCC in these transgenic mice is long, but is greatly accelerated by the transgenic overexpression of transforming growth factor-alpha ([@plbi-02-11-03-Murakami1]; [@plbi-02-11-03-Sargent1], [@plbi-02-11-03-Sargent2]; [@plbi-02-11-03-Santoni-Rugiu1]). These results highlight that the activation of *MYC* alone is not sufficient to induce HCC.
Traditional transgenic systems that have been previously used to study the role of oncogenes in tumorigenesis continuously overexpress transgenes and hence preclude the investigation of the initial and developmentally specific consequences of oncogene activation. To investigate the developmentally specific consequences of MYC overexpression in the pathogenesis of HCC in vivo, we used transgenic mice in which the MYC proto-oncogene is conditionally regulated via the tetracycline regulatory system (Tet system) ([@plbi-02-11-03-Felsher3]). We found that the ability of *MYC* to induce cellular proliferation versus cellular growth, and consequently its ability to induce tumorigenesis in murine hepatocytes, was dependent on the age of the host. Our results have implications for the mechanisms by which *MYC* and other oncogenes initiate and are restrained from causing tumorigenesis.
Results {#s2}
=======
A Conditional Model System for *MYC*-Induced HCC {#s2a}
------------------------------------------------
We used the Tet system to conditionally express *MYC* in murine hepatocytes ([@plbi-02-11-03-Kistner1]; [@plbi-02-11-03-Felsher3]). We mated the transgenic line TRE-*MYC* ([@plbi-02-11-03-Felsher3]), which contains the tetracycline response element adjacent to the human *MYC* cDNA, with the transgenic line LAP-*tTA* ([@plbi-02-11-03-Kistner1]), which contains a liver-specific enhancer that drives the expression of the tetracycline-transactivating protein. Mice possessing both transgenes exhibited increased expression of the *MYC* transgene in their hepatocytes ([Figure 1](#pbio-0020332-g001){ref-type="fig"}A). Mice possessing either transgene alone did not overexpress *MYC* and lacked evidence of morbidity or mortality. Similarly, mice possessing both transgenes that were treated with doxycycline to suppress *MYC* transgene expression did not exhibit a phenotype. Thus, we have developed a transgenic model that enables us to conditionally regulate *MYC* expression in murine hepatocytes.
::: {#pbio-0020332-g001 .fig}
Figure 1
::: {.caption}
###### MYC Overexpression in Adult Hepatocytes Results in HCC
\(A) Western blot analysis demonstrating that mice transgenic for both LAP-*tTA* and TRE-MYC conditionally express *MYC* protein in their hepatocytes in the absence (−) but not in the presence (+) of doxycycline.
\(B) Adult mouse with *MYC*-induced liver tumor.
\(C) Histology of an adult *MYC*-induced liver tumor.
\(D) Gross pathology of an adult liver tumor transplanted subcutaneously into a *scid* mouse.
\(E) Histology of an adult tumor transplanted subcutaneously into a *scid* mouse.
:::
:::
To investigate if MYC overexpression is sufficient to induce HCC in our model system, we removed doxycycline treatment in adult mice (6--12 weeks of age) transgenic for both TRE-*MYC* and LAP-*tTA*. Ninety percent of adult mice overexpressing MYC succumbed to liver tumors with a mean latency of 35 weeks. At necropsy, mice exhibited marked gross enlargement of the liver with multiple tumor masses ([Figure 1](#pbio-0020332-g001){ref-type="fig"}B). The normal liver architecture was disrupted by nodular tumors with histological features typical of HCC. Tumors were composed of dysplastic nests of cells with large pleomorphic nuclei, delicate vesicular chromatin, and very prominent nucleoli ([Figure 1](#pbio-0020332-g001){ref-type="fig"}C). Tumors could invade into the abdomen and the lung ([Figure 2](#pbio-0020332-g002){ref-type="fig"}A--[2](#pbio-0020332-g002){ref-type="fig"}C). These features demonstrated that MYC overexpression in adult mice resulted in HCC.
::: {#pbio-0020332-g002 .fig}
Figure 2
::: {.caption}
###### MYC-Induced Hepatic Tumors Are Invasive and Metastatic
\(A) Adult mouse with *MYC*-induced liver tumor that has metastasized to the abdomen and the lungs.
\(B) Histology of an adult *MYC*-induced lung metastasis.
\(C) Histology of an adult *MYC*-induced liver tumor.
\(D) Gross pathology of a liver tumor from a neonatal host transplanted subcutaneously into a *scid* mouse.
:::
:::
To confirm that these tumors were malignant, we transplanted them subcutaneously into *scid* mice. Tumors formed in the inoculated mice after an 8--10-week latency (see [Figure 1](#pbio-0020332-g001){ref-type="fig"}D). The transplanted tumors displayed identical histology to the primary transgenic tumor (see [Figure 1](#pbio-0020332-g001){ref-type="fig"}E versus [1](#pbio-0020332-g001){ref-type="fig"}C). Normal adult hepatocytes failed to induce tumors when inoculated into *scid* mice. We conclude that MYC overexpression in adult hepatocytes results in the formation of highly malignant liver cancers with features consistent with human HCC.
Developmental State of the Host Influences on Frequency and Latency of Tumor Onset {#s2b}
----------------------------------------------------------------------------------
To determine if the developmental state of host hepatocytes influenced the ability of *MYC* activation to induce tumorigenesis, we induced *MYC* in cohorts of different ages ([Figure 3](#pbio-0020332-g003){ref-type="fig"}A). Mice that overexpressed MYC during embryonic development of the liver succumbed to neoplasia within 10 d of birth. Mice in which *MYC* was activated at birth (neonates) succumbed to neoplasia within 8 weeks. Mice in which *MYC* was induced at 4 weeks or 6--12 weeks of age developed tumors after a mean latency of 15 and 35 weeks, respectively ([Figure 3](#pbio-0020332-g003){ref-type="fig"}A). We conclude that the ability of *MYC* activation to induce tumorigenesis in hepatocytes is inversely correlated with the developmental age of the host.
::: {#pbio-0020332-g003 .fig}
Figure 3
::: {.caption}
###### MYC\'s Ability to Induce HCC Is Inversely Correlated with the Age of the Host at the Time of *MYC* Activation
\(A) Survival of transgenic mice demonstrates that tumorigenesis in the liver is inversely correlated with the age of the host at the time of *MYC* induction. Shown are cases where *MYC* was constitutively expressed (▪), newborn mice in which *MYC* was activated at birth (▴), young mice in which *MYC* was activated at 4 weeks of age (•), adult mice in which *MYC* was activated at 6--12 weeks of age (♦), and transgenic mice treated with doxycycline (□). Cohorts consisted of 15--30 mice. Mice were scored when moribund. *MYC* transgene expression was induced to similar levels in the differently aged cohorts of mice. Survival time is measured as the time after *MYC* induction.
\(B) Western blot examining total MYC protein levels (human MYC and endogenous murine c-MYC) in mice when *MYC* is induced during embryonic development, activated at birth, and activated during adulthood (after 10 weeks of age). Adult mice exhibited a progressive increase in MYC protein levels during the course of *MYC* induction, with a significant increase in MYC protein in tumors. MYC protein levels in neonatal mice in which *MYC* was activated at birth were slightly increased at 10 d of age, and significantly increased at 18 d of age when these mice developed liver tumors. Liver tumors in 2- and 6-d-old neonatal mice that overexpressed MYC during embryonic development exhibited MYC protein levels similar to those observed in neonatal and adult tumors.
\(C) Real-time PCR analysis showing human *MYC* RNA levels in mice after different durations of *MYC* transgene induction. Adult livers exhibited a small increase in *MYC* RNA levels upon *MYC* activation, and a much greater increase in *MYC* RNA in MYC-induced tumors (black bars). In neonatal mice in which the *MYC* transgene was induced at birth, *MYC* RNA levels rose after 10 d of *MYC* activation. When these neonatal mice developed liver tumors, they exhibited *MYC* RNA levels similar to those seen in adult tumors (gray bars). Mice in which *MYC* was overexpressed during embryonic development developed liver tumors by 2 d of age and exhibited *MYC* RNA levels similar to those observed in neonatal and adult tumors (white bars).
:::
:::
One possible explanation for our results was that the levels of MYC induction were different in embryonic and neonatal versus adult hosts. To address this possibility, we examined total MYC protein levels by Western analysis using a polyclonal antibody that recognizes both the human c-MYC protein and the endogenous murine c-MYC ([Figure 3](#pbio-0020332-g003){ref-type="fig"}B). In neonatal and adult mice, MYC protein levels were induced at similar levels ([Figure 3](#pbio-0020332-g003){ref-type="fig"}B). In tumors from embryos, neonatal, and adult mice, MYC protein levels increased an additional 5- to 10-fold over the levels observed in nontransgenic and in *MYC*-induced nonneoplastic livers. Tumorigenic conversion of hepatocytes was associated, in all age groups of mice, with further increases in the levels of MYC protein ([Figure 3](#pbio-0020332-g003){ref-type="fig"}B). We obtained similar results by quantitative PCR analysis of mRNA expression of the human *MYC* transgene ([Figure 3](#pbio-0020332-g003){ref-type="fig"}C). In neonatal and adult mice, *MYC* transgene expression was induced at similar levels. In tumors from embryos, neonatal, and adult mice, the levels of *MYC* transgene RNA increased an additional 10-fold over the levels observed in nonmalignant hepatocytes ([Figure 3](#pbio-0020332-g003){ref-type="fig"}C). Hence, tumorigenic conversion of hepatocytes was associated, in all age groups of mice, with further increases in the levels of *MYC* transgene expression. However, differences in the ability of *MYC* activation to initiate tumorigenesis in mice of different ages did not appear to be related to differences in the levels of induction of *MYC* transgene expression. The increased levels of MYC expression we observed in tumors likely reflect that the proliferating tumor cells express more abundant levels of the *MYC* transgene than normal hepatocytes. This observation is consistent with observations described in other transgenic models in which expression of transgenes is generally higher in tumors than it is in the normal cellular counterparts ([@plbi-02-11-03-Weiss1]).
*MYC* Activation in Embryonic and Neonatal Hepatocytes Induces Cellular Proliferation and Tumorigenesis {#s2c}
-------------------------------------------------------------------------------------------------------
To evaluate how *MYC*\'s ability to induce tumorigenesis is influenced by the age of mice, we investigated the initial consequences of *MYC* activation in hepatocytes during different developmental periods. Mice that overexpressed MYC during embryonic development were born with livers similar in weight and gross architecture to normal age-matched livers, yet exhibited increasing numbers of neoplastic cells from birth through the first week of life associated with progressive abdominal enlargement. At necropsy, abdominal enlargement was associated with marked hepatomegaly with a 5-fold increase in total liver weight ([Figure 4](#pbio-0020332-g004){ref-type="fig"}A, and see [Figure 8](#pbio-0020332-g008){ref-type="fig"}B below). Although these livers were larger, the gross architecture was preserved ([Figure 4](#pbio-0020332-g004){ref-type="fig"}A, MYC ON versus MYC OFF). When we examined the histology of the livers in which MYC was overexpressed during embryogenesis, we found that they resembled liver cancers ([Figure 4](#pbio-0020332-g004){ref-type="fig"}B versus [4](#pbio-0020332-g004){ref-type="fig"}C) similar to the *MYC*-induced HCCs we observed in adult mice (see [Figure 1](#pbio-0020332-g001){ref-type="fig"}C versus [4](#pbio-0020332-g001){ref-type="fig"}C). Hence, MYC overexpression appears to induce cellular proliferation in neonatal hepatocytes that progresses rapidly to neoplasia.
::: {#pbio-0020332-g004 .fig}
Figure 4
::: {.caption}
###### *MYC* Activation during Embryonic Development Induces a Rapid Onset of Neoplasia
\(A) A normal neonatal liver and a neonatal liver in which *MYC* was activated embryonically.
\(B) Histology of a normal neonatal liver in which *MYC* was not activated.
\(C) Histology of a neonatal liver in which *MYC* was activated embryonically.
\(D) DNA content of normal neonatal hepatocytes.
\(E) DNA content of neonatal hepatocytes in which *MYC* was activated embryonically.
(F and H) Ki67 immunofluorescence and DAPI staining corresponding to a normal neonatal liver.
(G and I) Ki67 immunofluorescence and DAPI staining corresponding to a neonatal liver in which *MYC* was activated embryonically.
:::
:::
::: {#pbio-0020332-g008 .fig}
Figure 8
::: {.caption}
###### *MYC* Activation in Adult Hepatocytes Causes Cellular Hypertrophy
\(A) Relative volumes of neonatal hepatocytes and nuclei after *MYC* activation. Data are expressed as normalized volume plus or minus the standard error of the mean. The volume was normalized by dividing each measurement by the mean volume of normal 1-d-old neonatal mice. Three livers were measured per time point. T, tumor.
\(B) Neonatal liver weights of normal and *MY*C-activated livers. Three to five livers were weighed per time point. Data are expressed as the mean weight (grams) plus or minus the standard error of the mean.
\(C) Relative volumes of adult hepatocytes and nuclei after *MYC* activation. Volumes of cells are expressed as the mean volume divided by the mean volume of hepatocytes from normal mice plus or minus the standard error of the mean. Cells from two to three livers were measured per time point.
\(D) Adult liver weights after *MYC* activation. A total of nine livers were measured per time point after *MYC* activation. Data are expressed as the mean weight (grams) plus or minus the standard error of the mean.
:::
:::
To determine if MYC was inducing changes in cell cycle transit, we measured the DNA content of isolated nuclei from normal hepatocytes and hepatocytes in which *MYC* was activated during embryonic development ([Figure 4](#pbio-0020332-g004){ref-type="fig"}D and [4](#pbio-0020332-g004){ref-type="fig"}E). Normal neonatal hepatocytes mostly contained 2N DNA content, consistent with most of the cells residing in G1 ([Figure 4](#pbio-0020332-g004){ref-type="fig"}D). A minority of hepatocytes exhibited 4N and 2N--4N DNA content, demonstrating that few cells were in G2/M and S phase, respectively. In contrast, upon *MYC* activation the proportion of neonatal hepatocytes with 2N--4N DNA content substantially increased, suggesting that an increased number of cells were in S phase ([Figure 4](#pbio-0020332-g004){ref-type="fig"}E).
In order to confirm that *MYC* activation caused tumorigenesis by inducing cell proliferation, we performed Ki67 immunofluorescence and DAPI staining in tumors induced by *MYC* activation during embryonic development and in age-matched nontransgenic livers. Indeed, there was evidence for increased hepatocyte proliferation in the MYC-induced neonatal tumor, as demonstrated by an increase in Ki67-positive cells ([Figure 4](#pbio-0020332-g004){ref-type="fig"}G and [4](#pbio-0020332-g004){ref-type="fig"}I versus [4](#pbio-0020332-g004){ref-type="fig"}F and [4](#pbio-0020332-g004){ref-type="fig"}H). We conclude that *MYC* activation during embryonic development causes neonatal hepatocytes to undergo DNA replication, cell cycle transit, proliferation, and almost immediate neoplastic conversion.
To confirm that *MYC* activation during embryonic development induced tumorigenesis in neonatal livers, we transplanted neoplastic hepatocytes into *scid* mice. We found that neoplastic neonatal hepatocytes readily formed tumors, whereas the transplantation of normal neonatal hepatocytes did not form tumors (see [Figure 2](#pbio-0020332-g002){ref-type="fig"}D and unpublished data). Therefore, *MYC* overexpression during embryonic development of the murine liver causes hepatocellular tumorigenesis within the first 10 d of birth ([Figure 3](#pbio-0020332-g003){ref-type="fig"}). We conclude that *MYC* overexpression results in rapid neoplastic conversion of neonatal hepatocytes.
Mice in which *MYC* was activated at birth exhibited progressive abdominal enlargement during their second and third weeks of life, and they showed signs of tumorigenesis by 18 to 40 d of age. When these mice developed tumors their livers were ten times the normal size, were paler, exhibited a multitude of coalescing tumor nodules, and preserved a normal gross architecture (unpublished data). We did not observe any histological changes in the liver after 10 d of *MYC* activation ([Figure 5](#pbio-0020332-g005){ref-type="fig"}A versus [5](#pbio-0020332-g005){ref-type="fig"}B); however, by 18 d of *MYC* activation the histology resembled liver cancers ([Figure 5](#pbio-0020332-g005){ref-type="fig"}C versus [5](#pbio-0020332-g005){ref-type="fig"}D), similar to the MYC-induced HCCs we observed in adults ([Figure 5](#pbio-0020332-g005){ref-type="fig"}D versus [1](#pbio-0020332-g005){ref-type="fig"}C).
::: {#pbio-0020332-g005 .fig}
Figure 5
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###### *MYC* Activation at Birth Induces Proliferation of Neonatal Hepatocytes
\(A) Histology of a normal 10-d-old neonatal liver.
\(B) Histology of a 10-d-old liver in which *MYC* was activated at birth.
\(C) Histology of a normal 18-d-old neonatal liver.
\(D) Histology of a MYC-induced neonatal liver tumor that developed after 18 d of MYC overexpression; *MYC* was activated at birth.
(E--L) Ki67 immunofluorescence (E--H) and DAPI staining (I--L) of normal neonatal hepatocytes (E, G, I, and K), *MYC*-activated hepatocytes (F and J), and MYC-induced neonatal tumors (H and L). Upon initial *MYC* activation in neonatal mice, there was a small increase in Ki67-positive cells. MYC-induced neonatal tumors exhibited much higher levels of Ki67-positive cells.
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We performed Ki67 immunofluorescence and DAPI staining in order to determine if MYC overexpression in neonatal livers was inducing hepatocyte proliferation. At 10 d of age the liver is in an active state of proliferation; thus, there was little detectable difference in the number of Ki67-positive cells between the *MYC*-activated and nontransgenic livers ([Figure 5](#pbio-0020332-g005){ref-type="fig"}E and [5](#pbio-0020332-g005){ref-type="fig"}I versus [5](#pbio-0020332-g005){ref-type="fig"}F and [5](#pbio-0020332-g005){ref-type="fig"}J). However, once these livers became neoplastic, there was a great increase in the number of Ki67-positive cells ([Figure 5](#pbio-0020332-g005){ref-type="fig"}G and [5](#pbio-0020332-g005){ref-type="fig"}K versus [5](#pbio-0020332-g005){ref-type="fig"}H and [5](#pbio-0020332-g005){ref-type="fig"}L).
*MYC* Activation in Adult Hepatocytes Induces Cellular Growth, but Not Proliferation {#s2d}
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We examined the initial consequences of MYC overexpression in adult hepatocytes. In contrast to the rapid neoplastic conversion we observed in embryonic or neonatal hepatocytes ([Figures 4](#pbio-0020332-g004){ref-type="fig"} and [5](#pbio-0020332-g005){ref-type="fig"}), MYC overexpression in adult hepatocytes caused a marked cellular growth, accompanied by an even greater relative nuclear growth, as observed by histological analysis ([Figures 6](#pbio-0020332-g006){ref-type="fig"}--[8](#pbio-0020332-g008){ref-type="fig"}). The effects of MYC overexpression on the size of adult hepatocytes depended on the duration of *MYC* activation. After 2 weeks of MYC overexpression, no changes were observed in cell size compared to normal hepatocytes ([Figure 8](#pbio-0020332-g008){ref-type="fig"}C and unpublished data). However, after 4--8 weeks of *MYC* activation, adult hepatocytes exhibited increased cell and nuclear size ([Figure 6](#pbio-0020332-g006){ref-type="fig"}B versus [6](#pbio-0020332-g006){ref-type="fig"}A and [Figure 8](#pbio-0020332-g008){ref-type="fig"}C). Similar results were observed in over 20 different mice. Similarly, we observed that MYC induces hypertrophy of hepatocytes by flow cytometry analysis ([Figure 7](#pbio-0020332-g007){ref-type="fig"}). Further duration of *MYC* activation did not induce further cell growth, as measured up to 50 weeks of *MYC* activation (unpublished data). Thus, there may be an absolute limit to the ability of *MYC* to induce liver growth. *MYC* activation in adult hepatocytes was not associated with a change in overall liver weight ([Figure 8](#pbio-0020332-g008){ref-type="fig"}D). Since the cells were bigger, but the overall weight of the liver did not increase, we infer that the total number of hepatocytes was unchanged or slightly decreased. One possible explanation for these results is that MYC induced apoptosis, as described below.
::: {#pbio-0020332-g006 .fig}
Figure 6
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###### *MYC* Activation in Adult Hepatocytes Induces Increased Cell Size and Endoreduplication, and Only Results in Cell Proliferation upon Neoplastic Conversion of Hepatocytes
\(A) Histology of a normal liver.
\(B) Histology of a liver 2 months after *MYC* activation.
\(C) Histology of a MYC-induced liver tumor.
(D and G) Ki67 immunofluorescence and DAPI staining of a normal adult liver.
(E and H) Ki67 and DAPI staining of an adult liver after 8 weeks of *MYC* activation.
(F and I) Ki67 and DAPI staining of a MYC-induced adult tumor.
\(J) DNA content measured in normal hepatocytes.
\(K) DNA content measured after *MYC* induction for 2 months.
\(L) DNA content of a representative MYC-induced liver tumor.
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::: {#pbio-0020332-g007 .fig}
Figure 7
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###### *MYC* Activation in Adult Hepatocytes Induces Increased Cell Size
A histogram obtained by FACS forward versus light scatter analysis of adult hepatocytes from normal FVB/N livers (green), doxycycline-treated transgenic livers (red), and livers in which the *MYC* transgene was overexpressed for 3 months (blue). The *x*-axis represents cell size and the *y*-axis represents cell count. Adult mice were matched for age.
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To examine if *MYC* activation induced proliferation of adult hepatocytes, we measured Ki67 expression by immunofluorescence. We did not observe increased Ki67 expression when MYC was overexpressed in the adult liver ([Figure 6](#pbio-0020332-g006){ref-type="fig"}E and [6](#pbio-0020332-g006){ref-type="fig"}H versus [6](#pbio-0020332-g006){ref-type="fig"}D and [6](#pbio-0020332-g006){ref-type="fig"}G). Only upon neoplastic conversion of hepatocytes was there evidence for increased hepatocyte proliferation ([Figure 6](#pbio-0020332-g006){ref-type="fig"}F and [6](#pbio-0020332-g006){ref-type="fig"}I). We conclude that MYC overexpression in adult hepatocytes induces increased nuclear and cell growth, but not cell proliferation. Our observations are consistent with previous reports that *MYC* activation induces cell growth ([@plbi-02-11-03-Mateyak1]; [@plbi-02-11-03-Iritani1]; [@plbi-02-11-03-Johnston1]; [@plbi-02-11-03-Grandori1]; [@plbi-02-11-03-Kim1]).
*MYC* activation in adult hepatocytes eventually culminated in tumorigenesis, demonstrating that some adult hepatocytes acquire the ability to undergo cell division. To confirm this, we measured the nuclear and cellular sizes in liver tumors. When we examined the cell size in ten different tumors from adult hosts, we found that in all tumors, the cell size was reduced to below normal and the nuclear size was similar to that of normal hepatocytes ([Figures 6](#pbio-0020332-g006){ref-type="fig"}C and [8](#pbio-0020332-g008){ref-type="fig"}C). We were also able to confirm that the cell size of tumor cells was reduced to below normal by FACS forward versus side scatter (unpublished data). We conclude that *MYC*-induced malignant conversion of adult hepatocytes is associated with the acquired ability to undergo mitotic division.
MYC Overexpression in Adult Hepatocytes Results in Endoreduplication {#s2e}
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To further define the consequences of *MYC* activation on the cell cycle, we examined the DNA content of isolated nuclei from normal and *MYC*-activated adult hepatocytes. We expected that if adult hepatocytes were restrained from undergoing mitotic division, *MYC* activation might result in endoreduplication. Age-matched normal hepatocytes exhibited a 2N DNA content consistent with most of the cells residing in G1, and there was no evidence for cells in S or G2/M ([Figure 6](#pbio-0020332-g006){ref-type="fig"}J). After *MYC* activation for 2 months, we found that almost all nuclei had a 4N, 8N, or 12N DNA content, suggesting that the cells replicated their DNA repeatedly without dividing ([Figure 6](#pbio-0020332-g006){ref-type="fig"}K). Almost no cells contained the intermediate DNA content (2N--4N), demonstrating that very few cells were in S phase at any given time. We conclude that *MYC* activation induces endoreduplication of the genomes of normal adult hepatocytes. Our results are consistent with reports that MYC overexpression can enforce DNA replication, resulting in endoreduplication in normal cells ([@plbi-02-11-03-Cerni1]; [@plbi-02-11-03-Mai1]; [@plbi-02-11-03-Chernova1]; [@plbi-02-11-03-Felsher4]).
We reasoned that if *MYC* was causing endoreduplication in adult hepatocytes by arresting cell division and enforcing DNA replication, then upon neoplastic conversion these hepatocytes must acquire the ability to undergo mitotic division and would no longer endoreduplicate. As predicted, tumors did not exhibit evidence for endoreduplication ([Figure 6](#pbio-0020332-g006){ref-type="fig"}L). Greater than 70% of the tumor cells contained a 2N--4N DNA content and none of the cells contained greater than 4N DNA content. The majority of tumor cells were in S phase ([Figure 6](#pbio-0020332-g006){ref-type="fig"}L). Hence, *MYC*-induced tumorigenesis in adult hepatocytes is associated with the acquired ability to divide mitotically.
MYC Overexpression in Adult Hepatocytes Does Not Induce Apoptosis {#s2f}
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*MYC*-induced apoptosis is an important mechanism that restrains *MYC* from causing tumorigenesis ([@plbi-02-11-03-Evan1]; [@plbi-02-11-03-Pelengaris2], [@plbi-02-11-03-Pelengaris4]). We reasoned that MYC may induce cellular hypertrophy, but not an increase in liver mass, because MYC induces apoptosis. Normal neonatal and adult hepatocytes did not undergo apoptosis, as demonstrated by TUNEL assay or DAPI staining ([Figure 9](#pbio-0020332-g009){ref-type="fig"}A, [9](#pbio-0020332-g009){ref-type="fig"}B, [9](#pbio-0020332-g009){ref-type="fig"}E, and [9](#pbio-0020332-g009){ref-type="fig"}F). Surprisingly, we could not find evidence that *MYC* induced apoptosis in adult hepatocytes by TUNEL assay or DAPI staining after 2, 4, or 8 weeks of *MYC* induction prior to tumor formation ([Figure 9](#pbio-0020332-g009){ref-type="fig"}G and [9](#pbio-0020332-g009){ref-type="fig"}H and unpublished data). Contrary to what we expected, *MYC* activation was only associated with increased apoptosis in the hepatocytes of liver cancers ([Figure 9](#pbio-0020332-g009){ref-type="fig"}C, [9](#pbio-0020332-g009){ref-type="fig"}D, [9](#pbio-0020332-g009){ref-type="fig"}I, and [9](#pbio-0020332-g009){ref-type="fig"}J). Hence, apoptosis is not necessarily the mechanism restraining *MYC* from causing tumorigenesis, at least in hepatocytes ([@plbi-02-11-03-Pelengaris3]). However, we recognize that MYC could be inducing low levels of apoptosis in hepatocytes, perhaps not easily detected by TUNEL, since apoptotic cells may be rapidly eliminated from the liver through the host reticulo-endothelial system. Such a low level of apoptosis still could explain why in the adult liver hepatocytes become hypertrophic but the liver mass does not increase.
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Figure 9
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###### *MYC* Activation Does Not Induce Apoptosis in Murine Hepatocytes
TUNEL assay (A, C, E, G, and I) and DAPI staining (B, D, F, H, and J) of normal (A, B, E, and F) and *MYC*-activated (C, D, and G--J) hepatocytes of neonatal (A--D) and adult (E--J) mice. After 4 weeks of *MYC* activation in adult hepatocytes, there was no evidence of apoptosis either by TUNEL assay (G) or by DAPI staining of nuclei (H). *MYC* activation is associated with increased apoptosis with the neoplastic conversion of neonatal (C) and adult (I) hepatocytes. Representative data from one of three experiments are shown. Identical results were seen when *MYC* was activated for 2 or 8 weeks.
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Loss of p53 Function Cooperates with *MYC* to Induce Tumorigenesis in Adult Mice {#s2g}
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Previously, we have shown that the loss of p53 function is required to permit the cell division of normal mouse and human fibroblasts overexpressing MYC ([@plbi-02-11-03-Felsher4]). We speculated that loss of p53 function might be similarly required for *MYC* activation to induce cell proliferation and tumorigenesis in hepatocytes. First, we examined if *MYC* activation affected p53 protein expression. We found that *MYC* activation was associated with an increase in p53 protein levels in adult hepatocytes, as measured by Western analysis ([Figure 10](#pbio-0020332-g010){ref-type="fig"}A). Conversely, tumors in adult mice frequently exhibited reduced levels of p53 protein expression ([Figure 10](#pbio-0020332-g010){ref-type="fig"}A and unpublished data). Not all tumors exhibited reduced p53 expression. Since p53 mediates its function largely through inducing the transcription of many different genes, we evaluated if tumors exhibited a loss of p53 function by measuring the expression of these target genes. We found by Northern analysis that the p53 target genes, *p21* and *MDM2,* were induced upon *MYC* activation in adult livers ([Figure 10](#pbio-0020332-g010){ref-type="fig"}C). Conversely, *MYC*-induced adult HCCs frequently exhibited reduced or no expression of p53 downstream targets. Notably, a tumor that exhibited high p53 protein levels, tumor 2264, exhibited a loss in expression of p53 target genes. In contrast, tumors arising in neonatal mice expressed p53 protein and exhibited the induction of p53 target genes ([Figure 10](#pbio-0020332-g010){ref-type="fig"}B and [10](#pbio-0020332-g010){ref-type="fig"}C). We conclude that the adult, but not neonatal *MYC*-induced liver tumors require the loss of p53 function for tumorigenesis. Hence, HCCs that arise in adult versus neonatal hosts appear to occur through genetically distinct mechanisms.
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Figure 10
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###### *MYC* Activation Induces p53 Function, and Loss of p53 Function Is Necessary for MYC to Induce Tumorigenesis in Adult Hepatocytes
\(A) Western blot analysis for p53 protein expression after *MYC* activation for 1 month, 2 months, and in MYC-induced tumors. As a positive control, we used a lymphoma cell line that overexpresses a mutant p53, kindly provided by Dr. Kevin Smith.
\(B) Western blot analysis for p53 protein expression in a normal neonatal liver, in a neonatal liver in which MYC was activated during embryonic development that was obtained from a 2-d-old mouse, and in MYC-induced neonatal tumors. As a positive control, we used a lymphoma cell line generated in our lab that overexpresses a mutant p53.
\(C) Northern blot analysis for *p21* and *MDM2* in neonatal and adult liver tumors.
\(D) Survival of adult mice after activation of *MYC* in the presence of the wild type or the loss of one *p53* allele.
\(E) Loss of heterozygosity analysis of *MYC/p53^+/−^* tumors by PCR analysis.
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To directly address if loss of any of p53\'s functions accelerates the ability of *MYC* to induce HCC in adult mice, we generated transgenic mice that overexpressed *MYC* in their hepatocytes in the absence of one *p53* allele. We mated LAP-*tTA*/TRE-*MYC* mice with *p53^+/−^* mice that were in the FVB/N background. We activated *MYC* in mice when they were 6 weeks old and monitored them for morbidity. We found that even the loss of a single *p53* allele was sufficient to reduce the mean latency of tumor onset in 6-week-old adult mice from 20 weeks to 15 weeks ([Figure 10](#pbio-0020332-g010){ref-type="fig"}D). We found by PCR that tumors did not generally inactivate the second allele through deletion ([Figure 10](#pbio-0020332-g010){ref-type="fig"}E). Our results extend previous findings that suggest that the lack of p53 function cooperates with MYC to induce HCC ([@plbi-02-11-03-Klocke1]). We conclude that even a slight reduction of p53 function greatly facilitates the ability of MYC to induce tumorigenesis in adult hepatocytes.
Partial Hepatectomy Accelerates MYC-Induced Tumorigenesis {#s2h}
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Our results suggest that the ability of MYC to induce tumorigenesis in hepatocytes depends on the developmental context. We recognized that an alternative explanation is that MYC induces tumorigenesis more readily in hepatocytes that are already proliferating. Adult hepatocytes are known to undergo rapid proliferation in response to partial hepatectomy resulting in the complete regeneration of the liver within 2 weeks of surgical removal ([@plbi-02-11-03-Michalopoulos1]; [@plbi-02-11-03-Kountouras1]). We found that *MYC* activation in adult mice that have undergone partial hepatectomy exhibited a reduced latency of tumor induction in comparison with adult mice that had not undergone surgery (mean latency of 14 weeks versus 35 weeks). However, this latency of tumorigenesis in adult mice after partial hepatectomy was still up to two magnitudes longer than what was observed when *MYC* was activated in embryonic and neonatal mice (\<10 d and 4 weeks, respectively) ([Figures 11](#pbio-0020332-g011){ref-type="fig"} and [3](#pbio-0020332-g003){ref-type="fig"}A). In addition, tumors in mice that had undergone partial hepatectomy, unlike tumors arising in neonatal mice, were multifocal, suggesting that tumorigenesis was occurring infrequently ([Figure 11](#pbio-0020332-g011){ref-type="fig"}A versus [4](#pbio-0020332-g004){ref-type="fig"}A). Similarly, upon histological analysis, after *MYC* was activated for 7 weeks in mice that had undergone partial hepatectomy, mice exhibited many individual foci of HCC ([Figure 11](#pbio-0020332-g011){ref-type="fig"}B and [11](#pbio-0020332-g011){ref-type="fig"}C). Finally, in adult mice after partial hepatectomy, but not in neonatal mice, areas of the liver that had not undergone neoplastic conversion clearly exhibited increased cellular hypertrophy, and hence were unable to undergo mitotic division (unpublished data). We conclude that the ability of MYC to induce tumorigenesis in adult hepatocytes is accelerated after partial hepatectomy when adult hepatocytes are proliferating, but other developmentally specific parameters are more important in determining when oncogene activation will induce tumorigenesis than the ability of hepatocytes simply to proliferate.
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Figure 11
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###### Partial Hepatectomy Accelerates the Ability of MYC to Induce HCC in Adult Mice
\(A) Liver from an adult mouse 7 weeks after *MYC* activation exhibited no gross phenotypic changes (left), whereas the liver from an adult mouse 7 weeks after *MYC* activation that had undergone partial hepatectomy exhibited a multifocal liver tumor (right).
\(B) The histology of the liver from an adult mouse 7 weeks after *MYC* activation exhibited no evidence of a tumor.
\(C) The histology of a liver from an adult mouse after *MYC* activation that had undergone partial hepatectomy exhibited a multifocal HCC.
\(D) Survival after *MYC* activation in adult mice that have either not undergone surgery (▪) or undergone a partial hepatectomy (□). Results are pooled from two independent experiments with a total of ten mice per group.
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Discussion {#s3}
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Developmental Context Influences *MYC*\'s Ability to Induce Cellular Proliferation {#s3a}
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Here we demonstrate that *MYC*\'s ability to induce cellular growth versus proliferation and tumorigenesis depends on the differentiative context of a cellular lineage. Our results have general implications for the mechanisms by which *MYC* and other oncogenes induce and are restrained from causing tumorigenesis.
We found that the initial consequences of MYC overexpression, as well as its ability to induce tumorigenesis in murine hepatocytes, depend on the host age. The activation of *MYC* during embryonic development and at birth caused gross liver enlargement and rapid emergence of neoplasia. This increased liver size resulted from increased cell number or cellular hyperplasia. In contrast, in adult murine hepatocytes, *MYC* activation induced cell growth, resulting in cellular hypertrophy and endoreduplication. MYC overexpression caused HCC in adult mice less frequently than in neonates, and only after a prolonged latency. We conclude that the ability of *MYC* to induce cellular proliferation and tumorigenesis appears to be determined by the relative developmental maturation of a cellular lineage.
We recognized that an alternative explanation for our results is that only hepatocytes that are actively proliferating are susceptible to neoplastic transformation upon *MYC* induction. We were able to address this possibility directly by examining the consequences of MYC overexpression in adult hepatocytes after partial hepatectomy, which resulted in the immediate induction of adult hepatocyte proliferation associated with complete liver regeneration within 2 weeks. Adult mice only exhibited a modest increased susceptibility to *MYC*-induced tumorigenesis observed when *MYC* was induced in embryonic mice. This is despite the fact that after partial hepatectomy the total number of proliferating hepatocytes would be at least two magnitudes greater than in a neonatal or embryonic liver, whose total mass is much smaller. We conclude that developmentally specific parameters other than proliferation are more likely to play a causative role in the differential susceptibility of embryonic and neonatal hepatocytes to *MYC*-induced tumorigenesis.
Several different development-related factors could account for our observations. The relative ability of MYC to induce tumorigenesis in developmentally immature hosts may reflect the relative increased abundance of immature hepatocytes. Homeostatic mechanisms that regulate liver size and hepatocyte proliferation may permit MYC-induced proliferative expansion in the developing livers of young hosts and restrain proliferation in the mature liver of adult hosts. Differences in rates of tumorigenesis may be related to telomerase function that monitors the distance from senescence, as recently described ([@plbi-02-11-03-Artandi1]). An unlikely possibility is that higher doses of tetracyclines may impede liver carcinogenesis ([@plbi-02-11-03-NTP1]). The conditional model system that we have described should be useful for addressing these different possible mechanisms.
We conclude that mechanisms that regulate mitotic division play a critical role in preventing potent oncogenes, such as *MYC,* from inducing cancer in adult somatic cells. *MYC* activation alone is capable of enforcing DNA replication, but not cell division ([@plbi-02-11-03-Johnston1]; [@plbi-02-11-03-Felsher4]). Mitotic arrest may represent a critical fail-safe mechanism. If *MYC* were capable of enforcing mitotic division as well as cell growth and DNA replication, then aberrant activation of *MYC* alone would be sufficient to induce tumorigenesis. Activation of *MYC* in immature hepatocytes, cells already committed to a program of cellular proliferation, is sufficient to induce tumorigenesis. Activation of *MYC* in adult cells must require additional genetic events that permit mitotic cell division. Notably, our interpretation of our findings is supported by similar observations previously described in keratinocytes ([@plbi-02-11-03-Gandarillas1]).
We now can offer an explanation for what previously have been described as discordant results between reports that the *MYC* oncogene regulates cellular proliferation and other reports that *MYC* regulates cell growth ([@plbi-02-11-03-Mateyak1]; [@plbi-02-11-03-Iritani1]; [@plbi-02-11-03-Johnston1]; [@plbi-02-11-03-Grandori1]; [@plbi-02-11-03-Kim1]; [@plbi-02-11-03-Trumpp1]). *MYC* generally appears to coordinate cell growth with DNA replication ([@plbi-02-11-03-Mateyak1]; [@plbi-02-11-03-Iritani1]; [@plbi-02-11-03-Johnston1]; [@plbi-02-11-03-Grandori1]; [@plbi-02-11-03-Kim1]; [@plbi-02-11-03-Trumpp1]). However, contrary to what has been described, we show that the ability of *MYC* to induce cell division may depend on the developmental context of the cell. In adult hepatocytes, which normally do not proliferate, *MYC* activation can induce cell growth and DNA replication, but not cell division. In embryonic or neonatal hepatocytes, which are intrinsically committed to cellular proliferation, *MYC* activation induces cell growth, DNA replication, and mitotic division. Hence, the consequences of *MYC* activation appear to depend on the previous commitment of cells in a specific developmental state to a cellular program capable only of growth versus growth and cellular proliferation. It is not clear whether the hepatocytes that ultimately give rise to the tumors we observed derive from mitotically arrested diploid hepatocytes or from polyploid hepatocytes that acquire the capacity to undergo mitotic division.
MYC Is Restrained from Inducing Proliferation by an Arrest in Cell Division {#s3b}
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Many reports document that p53 functions as a general surveillance checkpoint that prevents oncogenes from inducing tumorigenesis ([@plbi-02-11-03-Sherr1]; [@plbi-02-11-03-Vogelstein1]; [@plbi-02-11-03-Wahl1]). *MYC* activation is known to induce *p53* function ([@plbi-02-11-03-Chernova1]; [@plbi-02-11-03-Zindy1]; [@plbi-02-11-03-Schmitt1]; [@plbi-02-11-03-Felsher4]; [@plbi-02-11-03-Grandori1]; [@plbi-02-11-03-Oster1]; [@plbi-02-11-03-Pelengaris3], [@plbi-02-11-03-Pelengaris4]), which in turn has been shown to cause apoptosis ([@plbi-02-11-03-Evan1]; [@plbi-02-11-03-Zindy1]; [@plbi-02-11-03-Schmitt1]; [@plbi-02-11-03-Grandori1]; [@plbi-02-11-03-Oster1]; [@plbi-02-11-03-Pelengaris3], [@plbi-02-11-03-Pelengaris4]). In contrast to these reports, we found that *MYC* is restrained from causing cell division in adult hepatocytes, at least in part, through a p53-dependent mechanism. Our results are consistent with many reports that demonstrate that p53 regulates checkpoints during DNA replication and during mitosis ([@plbi-02-11-03-Wahl1]).
We conclude that apoptosis is not the mechanism that precludes *MYC* from inducing neoplasia in hepatocytes. Rather, apoptosis is associated with *MYC*-induced neoplastic progression. Notably, similar results have been described in MYC-induced breast cancer and lymphoma ([@plbi-02-11-03-McCormack1]; [@plbi-02-11-03-Blyth1]). There are several possible explanations for this discordance between our results and many previous reports. *MYC* may only induce apoptosis in some cellular lineages or only in particular differentiative contexts. In this regard, we have shown that upon inactivating *MYC*, tumor cells differentiated, and upon *MYC* reactivation in this new differentiative state, cells underwent apoptosis ([@plbi-02-11-03-Jain1]). Thus, whether oncogene activation induces proliferation, growth, arrest, or apoptosis may depend on the gene expression program of a cell associated with a particular differentiative state ([@plbi-02-11-03-Felsher1]).
We found that the ability of MYC overexpression to induce tumorigenesis in adult hepatocytes often requires the loss of p53 function. *MYC*-induced HCC exhibited reduced p53 protein expression and transcriptional activity. The introduction of a single mutant *p53* allele greatly accelerated *MYC*\'s ability to induce tumorigenesis. Hence, in adult hepatocytes, loss of p53 function appears to be necessary to permit *MYC* activation to induce cellular proliferation and tumorigenesis. Our results here are similar to our previous observations that normal mouse and human fibroblasts overexpressing MYC replicate and even endoreduplicate their DNA, but are unable to undergo mitotic division unless p53 function has been lost ([@plbi-02-11-03-Felsher4]).
Specific Developmental Contexts Permit Oncogene-Induced Tumorigenesis {#s3c}
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We may be able to explain why the frequency and spectrum of neoplasia vary with the host\'s age. In general, children are susceptible to tumors of the hematopoietic system, musculo-skeletal system, and central nervous system, whereas adults are susceptible more frequently to tumors derived from epithelial lineages, such as colon, lung, breast, prostate, and liver. The ability of oncogenes to induce cancer may be dependent upon the differentiative context. Frequently, oncogene activation has been associated with the malignant conversion of immature cellular compartments ([@plbi-02-11-03-Adams1]; [@plbi-02-11-03-Spanopoulou1]; [@plbi-02-11-03-Pelengaris1]; [@plbi-02-11-03-Blyth1]).
We may be able to explain why neonatal versus adult humans that have become infected with hepatitis B succumb to HCC with a 100-fold-increased frequency and reduced latency of tumor onset ([@plbi-02-11-03-Chang1], [@plbi-02-11-03-Chang2]). We infer that oncogenes in general are more potent in inducing cancer in hepatocytes of younger hosts because these cells are committed to a developmental program permissive to tumorigenesis. Cancers frequently correspond to the malignant expansion of specific immature differentiative states within a given cellular lineage ([@plbi-02-11-03-Greaves1]; [@plbi-02-11-03-Klein1]). It would be advantageous for adult somatic cells, which are required to be long lived, to acquire mechanisms that prevent single oncogenes from inducing inappropriate cellular proliferation and thereby tumorigenesis. Two such mechanisms have been proposed: Some oncogenes induce premature senescence ([@plbi-02-11-03-Serrano1]; [@plbi-02-11-03-Lin1]; [@plbi-02-11-03-Zhu1]; [@plbi-02-11-03-Dimri1]), and other oncogenes induce apoptosis ([@plbi-02-11-03-Pelengaris2]). Here we have provided evidence for a different mechanism: The aberrant activation of proto-oncogenes, such as *MYC,* in the developmental context of adult somatic cells appears to be inherently prohibited from inducing mitotic division.
The intrinsic inhibition of a proliferative program in mature somatic cells may be a more parsimonious mechanism than apoptosis as a means of restraining tumorigenesis because it would permit otherwise normal fully differentiated somatic cells to continue to operate despite their acquisition of an activating mutation in an oncogene. In some cases, it would be advantageous to arrest cells rather than induce their apoptosis. Immature cells, which are committed to a program of proliferative expansion, are inherently more susceptible to oncogene-induced autonomous proliferation and tumorigenesis. In immature cells, apoptosis may be the only mechanism that could prevent tumorigenesis. Thus, the differentiative state and epigenetic program of a cell influences whether an oncogene induces cellular senescence, mitotic arrest, or apoptosis.
Generally, oncogenes may cause tumorigenesis most readily in developmental contexts that provide a gene expression program permissive to tumorigenesis ([@plbi-02-11-03-Jain1]; [@plbi-02-11-03-Felsher1]). Pathologic conditions that trigger the expansion of immature cells---tissue injury and regeneration, infection, and autoimmune processes---may be associated with cancer because they change the cellular state, now permitting a single oncogene, such as *MYC,* to initiate tumorigenesis. In this regard, we found that *MYC* accelerated tumorigenesis in adult hosts that had undergone partial hepatectomy and were undergoing liver regeneration---a state that induces robust cellular proliferation. However, tumorigenesis was not accelerated to the same degree as observed when *MYC* was activated in embryonic or neonatal hosts. Therefore, inducing the capacity of a cell to proliferate alone is unlikely to be sufficient to confer susceptibility to tumorigenesis. It has long been appreciated that conferring the ability of a cell to proliferate is not sufficient to induce tumorigenesis. Other developmentally specific parameters may play a more critical role in defining when oncogene activation results in tumorigenesis. The model system we have developed should prove useful in defining how particular developmental contexts and pathologic states contribute to tumorigenesis.
Materials and Methods {#s4}
=====================
{#s4a}
### Transgenic mice {#s4a1}
The TRE-*MYC* transgenic line generated for these experiments was described previously ([@plbi-02-11-03-Felsher3]). The LT-tTA transgenic line was kindly provided by H. Bujard ([@plbi-02-11-03-Kistner1]). The p53^+/−^ mice were generously provided by A. Bradley. Mice were mated and screened by PCR. *MYC* expression was activated by removing doxycycline treatment (100 μg/ml) from the drinking water of mice transgenic for both TRE-*MYC* and LAP-tTA.
### Tumorigenicity assays {#s4a2}
*MYC* was activated in the liver by removing doxycycline treatment from the water. *MYC* was activated during embryonic development by removing doxycycline treatment from the mating cage before conception. *MYC* was activated at birth by removing doxycycline from the mating cage immediately after the birth of the litter. Mice were monitored daily and were sacrificed when moribund. During necropsy, liver tissues were saved by fixation in 10% buffered formalin or by being snap frozen in liquid nitrogen. For transplantation, liver tumor specimens were sliced into small pieces, incubated first in calcium-free Hank\'s Buffered Saline Solution (HBSS) on a stirring plate at 37 °C for 20 min, then washed and resuspended in 1× digestion buffer with 1.5 mg/ml collagenase, and incubated on a stirring plate at 37 °C for an additional 40 min. The solution was then filtered through a 100-μm filter, washed, and resuspended in PBS twice. After the first wash, the solution was resuspended in 10 ml of PBS. After the second filtering and wash, the solution was resuspended in 500 μl of PBS. A quantity of 10^6^ cells was injected subcutaneously into *scid* mice (250 μl per injection) using a 1-ml syringe and 27-gauge needle. Mice showed signs of tumorigenesis within 2--3 weeks of inoculation. Mice were sacrificed when tumors reached 2 cm in size. To prepare 5× digestion buffer, 1.12 g of KCl, 37.94 g of NaCl, 0.69 g of NaH2PO~4~\*H~2~O, and 9.9 g of dextrose monohydrate were dissolved in 1 liter of H~2~O.
### Partial hepatectomy {#s4a3}
The median and left lateral lobes comprise about 70% of the liver and their removal is recognized classically as a partial hepatectomy. We performed a one-third partial hepatectomy, removing only the median lobe of the liver. Mice were anesthetized with 16 mg/kg ketamine/xylazine. An incision was made through the midline ventral abdominal skin and abdominal muscles, extending from just above the xiphoid cartilage to about halfway towards the base of the tail. A small bolster was placed under the thorax, causing the liver to fall forwards away from the diaphragm. The liver was pushed out and the suspensory ligaments were cut with blunt-end scissors. The median lobe was raised and a ligature was tied around it with the blood vessels at the base. The liver lobe was removed by cutting close to the ligature with sharp scissors. The bolster was removed and the muscle and skin incisions were closed. The mice were monitored hourly for pain and dehydration after the procedure.
### Histology {#s4a4}
Liver tissues were fixed in 10% buffered formalin for 24 h and then transferred to 70% ethanol until embedding in paraffin. Tissue sections 4 μm thick were cut from paraffin-embedded blocks and placed on glass slides. Hematoxylin and eosin (H&E) staining was performed using standard procedures. The Stanford Histology Core laboratory prepared paraffin sections and performed H&E staining. We measured Ki67 expression by immunofluorescence using a mouse anti-human Ki67 monoclonal antibody (BD Biosciences, Palo Alto, California, United States). We used the Vector M.O.M. Basic Kit (Vector Laboratories, Burlingame, California, United States). Sections were deparaffinized with xylene and rehydrated through graded alcohol washes, followed by antigen retrieval in a microwave for 15 min in Vector Antigen Unmasking solution (H-3300). The slides were then incubated in 100 mM glycine for 2 × 8 min to reduce fluorescent background. Slides were blocked by incubation in avidin for 10 min followed by biotin for 10 min using the Dako biotin blocking system (DAKO Corporation, Carpinteria, California, United States) and subsequently incubated for 1 h in M.O.M. IgG-blocking reagent diluted 1:4 in PBS. Slides were then incubated for 1 h in mouse anti-human Ki67 monoclonal antibody diluted 1:100 in M.O.M. diluent. Slides were washed in TBST for 3 × 5 min to reduce background and were then treated with M.O.M. biotin-labeled anti-mouse IgG, diluted 1:250 in M.O.M. diluent. Following another 3 × 5 min of TBST washes, slides were incubated for exactly 45 min in Cy3-conjugated streptavidin diluted 1:800 in PBS (Amersham Biosciences, Piscataway, New Jersey, United States) in the dark. To visualize nuclei, slides were counterstained with 0.2 μg/ml DAPI. Ki67-positive cells were visualized by fluorescence microscopy.
### Western blot analysis {#s4a5}
Western analysis was performed using conventional techniques. Liver tissues were disrupted and protein was isolated using a pestle and tube homogenizer in NP-40 lysis buffer. Equal protein was loaded in each lane, as quantitated by the Bicinchoninic Acid (BCA) Protein Assay (Pierce, Rockford, Illinois, United States). Proteins were electrophoresed on 10% Tris-HCl polyacrylamide gels at 100 V for 60 min and transferred on PVDF membranes at 100 V for 60 min. The membrane was blocked in 5% nonfat dry milk solution in TBS at 4 °C overnight. MYC protein expression was detected using the C-19 rabbit polyclonal antibody that recognizes mouse and human MYC (Santa Cruz Biotechnology, Santa Cruz, California, United States). p53 protein expression was detected using the NCL-p53-CM5p rabbit polyclonal antibody (Vector Laboratories). As a positive control, we used a hematopoietic tumor previously shown to overexpress p53 that was generously provided by Dr. Kevin Smith.
### Cell and nucleus size measurements {#s4a6}
Images of H&E-stained liver sections were made with a Nikon Eclipse E800 microscope utilizing a Spot RT Slider digital camera (Diagnostic Instruments, Sterling Heights, Michigan, United States) and Spot Advanced Software (version 3.2.4, Diagnostic Instruments). To estimate cellular and nuclear volume, the radii of at least five hepatocytes per field were measured in at least three fields.
### Hepatocyte isolation {#s4a7}
Hepatocytes were collected by a two-step in situ perfusion technique ([@plbi-02-11-03-Seglen1]; [@plbi-02-11-03-Bumgardner1]). First, the inferior vena cava was cannulated and the liver perfused with calcium-free EGTA buffer followed by calcium-containing collagenase buffer (Invitrogen, Carlsbad, California, United States). After the perfusion, the liver was excised and mechanically disrupted in Williams\' E medium (Sigma-Aldrich, St. Louis, Missouri, United States). The resulting slurry was filtered through a 40-μm filter, and viable hepatocytes were isolated by Percoll gradient centrifugation. The pelleted hepatocytes were washed serially with Williams\' E medium and counted prior to further analyses.
### Cell size measurements by FACS analysis {#s4a8}
Cell size was determined by FACS forward versus light scatter of isolated hepatocytes utilizing a Becton Dickinson FACSCaliber (BD Biosciences). Data were analyzed using Cellquest v3.3 Software (BD Biosciences).
### DNA content {#s4a9}
Nuclei were prepared for staining by touching a cut piece of liver to superfrost slides. The smears were then air dried, fixed in formalin for 5 min, and stored in 70% ethanol. The nuclei were stained for DNA content analysis according to the Feulgen technique ([@plbi-02-11-03-Oppedal1]).
### Apoptosis assay {#s4a10}
Apoptosis was detected using terminal deoxyribonucleotidyl transferase-mediated dUTP nick end labeling (TUNEL) staining, using the In Situ Death Detection Kit (Boehringer Mannheim, Indianapolis, Indiana, United States). In order to visualize the nuclei, cells were counterstained with DAPI (0.2 μg/ml). TUNEL-positive cells were visualized by fluorescence microscopy.
### Northern blot analysis {#s4a11}
Northern blotting and probing were performed using standard methods. RNA samples were isolated according to the Trizol product manual specifications using a Kontes 1-ml glass tissue homogenizer. A formaldehyde, 1% agarose gel was used to run the Northerns, and transferring was done overnight in 20× SSC. Blots were washed in 2× SSC, cross-linked twice in a Stratalinker UV source, and pre-hybed and hybridized using the UltraHyb (Ambion, Austin, Texas, United States) product specifications. cDNAs corresponding to *p21, MDM2,* and glyceraldehye-3-phosphate dehydrogenase *(GAPDH)* were used as probes ([@plbi-02-11-03-Macleod1]; [@plbi-02-11-03-el-Deiry1]). The probes were generated through random priming reactions. Kodak BioMax MS film was used to expose the blots.
### Loss of p53 heterozygosity analysis by PCR {#s4a12}
To evaluate loss of heterozygosity of liver tumors derived from mice heterozygous for p53 deletion, PCR analysis was performed as previously described ([@plbi-02-11-03-Timme1]).
### RNA isolation and quantification {#s4a13}
Total cellular RNA was isolated from snap-frozen liver tissue using the Invitrogen Micro-to-Midi Total RNA Purification System according to the manufacturer\'s instructions. The amount of total RNA isolated from tissues was quantified using spectrophotometric OD~260~ measurements. The quality of RNA was measured on a formaldehyde, 1% agarose gel.
### Real-time PCR {#s4a14}
The RNA of human c-*MYC* and rodent *GAPDH* were measured by real-time quantitative RT-PCR using the 5′ nuclease technology on an ABI PRISM 7900HT Sequence Detection System (Applied Biosystems, Foster City, California, United States). The probe sequences for human *c-MYC* were forward primer 5′-CCCCTGGTGCTCCATGAG-3′ and reverse primer 5′-GCCTGCCTCTTTCCACAGA-3′. The human c-*MYC* probe, 5′-TCCTCCTCAGAGTCGC-3′, was labeled with FAM dye-MGB. A VIC TaqMan rodent *GAPDH* control reagents kit (Applied Biosystems) was used to measure mouse *GAPDH.* The RNA was reverse transcribed using the High-Capacity cDNA Archive Kit (Applied Biosystems) according to the manufacturer\'s protocol with a minor modification, the addition of RNase inhibitor (Applied Biosystems) at a final concentration of 1 U/μl. Samples were incubated at 25 °C for 10 min and 37 °C for 180 min. PCR reactions were prepared in a final volume of 20 μl, with final concentrations of 1× TaqMan Universal PCR Master Mix (Applied Biosystems) and cDNA derived from 20 ng of input RNA as determined by spectrophotometric OD~260~ measurements. Thermal cycling conditions comprised an initial UNG incubation at 50 °C for 2 min, AmpliTaqGold DNA polymerase activation at 95 °C for 10 min, 40 cycles of denaturation at 95 °C for 15 s, and annealing and extension at 60 °C for 1 min. Each measurement was performed in triplicate and the threshold cycle *(C~t~),* the fractional cycle number at which the amount of amplified target reached a fixed threshold, was determined. For calibration and generation of standard curves, we used cDNA prepared from Universal Human Reference RNA (Stratagene, La Jolla, California, United States) and cDNA prepared from Universal Mouse Reference RNA (Stratagene). Universal Human Reference RNA was used for human *c-MYC* and Universal Mouse Reference RNA was used for rodent *GAPDH.*
Supporting Information {#s5}
======================
Accession Numbers {#s5a1}
-----------------
Swiss-Prot accession numbers (<http://us.expasy.org/sprot/>) for the loci discussed in this paper are the following: Cdkn1a (mouse), P39689; Mdm2 (mouse), P23804; Myc (human), P01106; Myc (mouse), P01108; and Tp53 (mouse), P02340.
We thank the members of the Felsher laboratory for their helpful suggestions, and Dr. Michael Cleary and Dr. Paul Khavari for a critical reading of the manuscript. We thank Debbie Czerwinski for her guidance with the real-time PCR and the Levy and Chu laboratories for providing us with primers and probes. We thank Dr. Jackie Maher for assistance in performing partial hepatectomies. We thank Dr. Kevin Smith and Flora Tang for providing us with help performing the Western analysis for p53 expression. We thank Dr. Alexander Borowsky and Dr. Richard Sibley for assistance in examining histology. We thank Dr. Herman Bujard for generously providing us with the LAP-tTA mice. We thank Dr. Alan Bradley for generously providing us with the p53^+/−^ mice. We thank Dr. Alice Fan and Kim Komatsubara for helping editing the text. This work was supported by the National Cancer Institute (grant numbers K08-CA75967--01, R01-CA85610), an American Society of Clinical Oncology Young Investigator Award, a Pilot Feasibility Grant from the University of California, San Francisco Liver Center, a Pilot Grant from the Stanford Digestive Disease Consortium, the Emerald Foundation (DWF), the National Cancer Institute (Grant Number 5T32 CA09302--27) (SB), the Swedish Cancer Society, and the Cancerföreningen in Stockholm (AZ).
**Conflicts of interest.** The authors have declared that no conflicts of interest exist.
**Author contributions.** SB and DWF conceived and designed the experiments. SB, AZ, RAI, RAM, QY, NB, CA, LDA, SF, and DWF performed the experiments. SB, BR, RDC, and DWF analyzed the data. RAM, CA, LDA, BR, RDC, and DWF contributed reagents/materials/analysis tools. SB and DWF wrote the paper.
Academic Editor: Nicholas Hastie, MRC Human Genetics Unit, Western General Hospital
Citation: Beer S, Zetterberg A, Ihrie RA, McTaggart RA, Yang Q, et al. (2004) Developmental context determines latency of MYC-induced tumorigenesis. PLoS Biol 2(11): e332.
HCC
: hepatocellular carcinoma
Tet system
: tetracycline regulatory system
|
PubMed Central
|
2024-06-05T03:55:47.963427
|
2004-9-28
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519000/",
"journal": "PLoS Biol. 2004 Nov 28; 2(11):e332",
"authors": [
{
"first": "Shelly",
"last": "Beer"
},
{
"first": "Anders",
"last": "Zetterberg"
},
{
"first": "Rebecca A",
"last": "Ihrie"
},
{
"first": "Ryan A",
"last": "McTaggart"
},
{
"first": "Qiwei",
"last": "Yang"
},
{
"first": "Nicole",
"last": "Bradon"
},
{
"first": "Constadina",
"last": "Arvanitis"
},
{
"first": "Laura D",
"last": "Attardi"
},
{
"first": "Sandy",
"last": "Feng"
},
{
"first": "Boris",
"last": "Ruebner"
},
{
"first": "Robert D",
"last": "Cardiff"
},
{
"first": "Dean W",
"last": "Felsher"
}
]
}
|
PMC519001
|
Introduction {#s1}
============
Intercellular signaling pathways control many diverse processes, such as cell proliferation, differentiation, survival, migration, shape changes, and responses to the environment. In most instances, the release of the signaling molecules by the signal-sending cells constitutes a rate-limiting step that determines the spatial distribution and temporal duration of the response ([@pbio-0020334-Freeman1]). On the other hand, the binding sites on the receptors that are presented by the signal-receiving cells are usually in excess of the available ligands ([@pbio-0020334-Freeman1]). Specificity is achieved by the tissue-specific expression of the signal or by the regulated activation of an inactive precursor molecule. For example, growth factor peptides are often produced as inactive precursors that need to be processed before they can be released and activate their cognate receptors on the signal-receiving cells ([@pbio-0020334-Arribas1]).
The epidermal growth factor (EGF) receptor (EGFR) acts in a highly conserved signal transduction pathway that controls various cell fate decisions in metazoans ([@pbio-0020334-Bogdan1]). EGFR ligands of the transforming growth factor-α (TGF-α) family are produced as membrane-tethered precursor proteins with a single extracellular EGF repeat that is cleaved off the membrane anchor ([@pbio-0020334-Pandiella1]; [@pbio-0020334-Bosenberg1]). The best-studied example of EGF processing is probably the *Drosophila* growth factor Spitz, which activates the EGFR in multiple developmental processes ([@pbio-0020334-Rutledge1]; [@pbio-0020334-Golembo1]). Genetic analysis of *Drosophila* EGFR signaling has identified Rhomboid-1 as a protein necessary for Spitz activation in the signal-sending cell ([@pbio-0020334-Bier1]; [@pbio-0020334-Golembo1]; [@pbio-0020334-Guichard1]; [@pbio-0020334-Wasserman2]). *Drosophila* Rhomboid-1 is the founding member of a family of seven-pass transmembrane proteins that function as intramembrane serine proteases ([@pbio-0020334-Urban3]). Site-specific cleavage of Spitz by Rhomboid-1 in the Golgi apparatus allows the secretion of the extracellular portion of Spitz by the signal-sending cell ([@pbio-0020334-Lee1]; [@pbio-0020334-Urban2]). The *Drosophila* genome encodes a total of seven *rhomboid* genes with partially overlapping functions in different tissues that utilize the EGFR pathway ([@pbio-0020334-Wasserman2]; [@pbio-0020334-Urban4]). There are four predicted Rhomboid homologs in humans and five in C. elegans ([@pbio-0020334-Wasserman2]). Rhomboid-like proteins are even found in yeast and bacteria ([@pbio-0020334-Gallio1]; [@pbio-0020334-McQuibban1]). Rhomboids are part of the larger family of I-Clip proteases that includes the aspartyl protease Presenilin ([@pbio-0020334-Wolfe1]) and the Zn^2+^ metalloprotease S2P ([@pbio-0020334-Urban1]). On the other hand, the secretion of vertebrate TGF-α involves processing by a disintegrin metalloprotease (ADAM), TNF-α-converting enzyme ([@pbio-0020334-Peschon1]). Whether a Rhomboid protease is also involved in the processing of TGF-α is currently unknown.
The development of the C. elegans hermaphrodite vulva serves as a simple model by which to study signal transduction and cell fate determination during organogenesis ([@pbio-0020334-Kornfeld1]; [@pbio-0020334-Sternberg2]). During C. elegans postembryonic development, the anchor cell (AC) in the somatic gonad induces three out of six equivalent vulval precursor cells (the VPCs, termed P3.p through P8.p) in the ventral hypodermis to adopt vulval cell fates ([@pbio-0020334-Sulston2]; [@pbio-0020334-Kimble1]). The AC produces the LIN-3 growth factor, which is similar to *Drosophila* Spitz and mammalian TGF-α ([@pbio-0020334-Hill1]). The VPCs express the EGFR homolog LET-23 on the basolateral surface that faces the AC ([@pbio-0020334-Whitfield1]), and they are all competent to activate the RAS/mitogen-activated protein kinase (MAPK) signaling pathway in response to the inductive LIN-3 EGF signal. The VPC closest to the AC, P6.p, adopts the primary (1°) cell fate characterized by a symmetrical cell lineage leading to eight 1° vulval cells ([@pbio-0020334-Sternberg3]). The neighbors of P6.p, P5.p and P7.p, adopt the secondary (2°) cell fate, which is characterized by an asymmetrical lineage leading to seven 2° vulval cells. The more distally located VPCs, P3.p, P4.p, and P8.p, adopt the uninduced tertiary (3°) cell fate. After dividing once, they fuse with the surrounding hypodermal syncytium (hyp7). LIN-3 EGF dosage experiments have suggested that the inductive signal acts in a graded manner ([@pbio-0020334-Katz1]). According to this model, P6.p receives the highest amount of the inductive signal and thus adopts the 1° fate, while an intermediate level of the LIN-3 signal specifies the 2° fate in P5.p and P7.p. The distal VPCs, P3.p, P4.p, and P8.p, receive too little signal to adopt vulval cell fates. However, in response to the inductive signal, P6.p produces a lateral signal that activates the LIN-12 NOTCH signaling pathway in the neighboring VPCs, P5.p and P7.p ([@pbio-0020334-Greenwald1]). The LIN-12 NOTCH signal is both necessary and sufficient to induce the 2° cell fate ([@pbio-0020334-Sternberg1]; [@pbio-0020334-Simske1]). Thus, the graded LIN-3 EGF signal may act redundantly with the lateral LIN-12 NOTCH signal to specify the 2° vulval cell fate in the neighbors of P6.p ([@pbio-0020334-Kenyon1]).
Like its *Drosophila* and vertebrate homologs, LIN-3 EGF is synthesized as a transmembrane precursor protein ([@pbio-0020334-Hill1]). Experiments with *dig-1* mutants in which the AC is dorsally displaced indicate that the AC is capable of inducing vulval cell fates from a distance, suggesting that proteolytic cleavage of membrane-bound LIN-3 occurs in the AC ([@pbio-0020334-Thomas1]). Here, we report the identification of the C. elegans Rhomboid homolog ROM-1 as a positive regulator of vulval induction. Surprisingly, we find that ROM-1 acts in the signal-receiving VPCs rather than in the signal-sending AC. Furthermore, we uncover an AC-independent function of LIN-3 EGF that depends on ROM-1 activity in the VPCs. Two LIN-3 splice variants, termed LIN-3S and LIN-3L, that differ by an insertion of 15 amino acids in the region in the juxtamembrane domain critical for processing, have been described ([@pbio-0020334-Hill1]). Genetic epistasis experiments indicate that LIN-3L activity in the VPCs depends on ROM-1, while LIN-3S or a truncated form of LIN-3 lacking the transmembrane domain act independently of ROM-1. We propose a relay model in which ROM-1 is required for the activation of LIN-3L in the proximal VPCs to transmit the inductive AC signal to the distal VPCs.
Results {#s2}
=======
Five Rhomboid-Like Proteins in C. elegans {#s2a}
-----------------------------------------
Since the LIN-3 EGF growth factor is produced as a transmembrane precursor protein ([@pbio-0020334-Hill1]), we asked whether an intramembrane serine protease of the Rhomboid family is involved in the proteolytic processing of LIN-3 EGF. Rhomboid proteins in metazoans share a characteristic secondary structure consisting of seven transmembrane domains ([@pbio-0020334-Bier1]; [@pbio-0020334-Urban3]). We searched the complete C. elegans genome sequence for genes with similarity to *Drosophila rhomboid-1* and identified five *rhomboid-*like genes termed *rom-1* (F26F4.3), *rom-2* (C48B4.2), *rom-3* (Y116A8C.14), *rom-4* (Y116A8C.16), and *rom-5* (Y54E10A.14) ([Figure 1](#pbio-0020334-g001){ref-type="fig"}A). All five C. elegans ROM proteins display the typical secondary structure of Rhomboids ([@pbio-0020334-Wasserman2]). The transmembrane domains show the highest degree of sequence conservation, while the hydrophilic N termini are more divergent ([Figure 1](#pbio-0020334-g001){ref-type="fig"}B). ROM-1 is most similar to *Drosophila* Rhomboid-1 (35% identity), followed by ROM-2 (29% identity) and the more diverged ROM-3 (24% identity), ROM-4 (26% identity), and ROM-5 (29% identity). Mutagenesis experiments with *Drosophila* Rhomboid-1 have identified a catalytic triad formed by conserved asparagine, serine, and histidine residues that are necessary for the serine protease activity ([@pbio-0020334-Urban3]). This catalytic triad is conserved only in ROM-1 (black triangles in [Figure 1](#pbio-0020334-g001){ref-type="fig"}B), suggesting that the other four Rhomboid-like proteins do not function as serine proteases*.*
::: {#pbio-0020334-g001 .fig}
Figure 1
::: {.caption}
###### The C. elegans Rhomboid Genes
\(A) Dendogram showing the relation between the seven-pass transmembrane domains of Rhomboids from C. elegans (C.e.), Drosophila melanogaster (D.m.), and Homo sapiens (H.s.) calculated with the neighbor joining method using CLUSTAL X ([@pbio-0020334-Thompson1]).
\(B) Alignment of C. elegans (C.e.) ROM-1 and ROM-2 and Homo sapiens (H.s.) Rho-1 relative to Drosophila melanogaster (D.m.) Rho-1. Residues identical to those of *Drosophila* Rho-1 are highlighted in black, and similar residues are highlighted in grey. The thick black lines indicate the predicted seven-pass transmembrane domains. The three black triangles point at the residues forming a catalytic triad that forms a charge-relay system to activate the essential serine residue during peptide bond cleavage, and the three open triangles indicate other conserved residues necessary for the enzymatic activity as identified in D.m. Rho-1 ([@pbio-0020334-Urban3]). The region underlined with a dotted line indicates the extent of deletion in the *rom-1*(*zh18*) allele.
\(C) Intron-exon structure of the *rom-1* locus and extent of the deletion in the *rom-1(zh18)* strain. The numbers indicate the position of the deletion break-points relative to the A in the ATG start codon.
:::
:::
In order to confirm the predicted intron-exon structure of *rom-1,* we isolated *rom-1* cDNA by RT-PCR. An SL1 trans-spliced leader sequence was identified at the 5′ end of the message that was spliced to the second of the six exons predicted by the C. elegans genome project ([Figure 1](#pbio-0020334-g001){ref-type="fig"}C) (see <http://www.wormbase.org>). The remaining intron-exon boundaries were confirmed experimentally and corresponded exactly to the predicted boundaries. The conceptual translation of the 1,071-bp open reading frame (ORF) predicts a protein of 356 amino acids, with very short stretches of hydrophilic amino acids between the seven-pass transmembrane domains, except for a longer loop consisting of 43 amino acids between the first and second transmembrane domains (see [Figure 1](#pbio-0020334-g001){ref-type="fig"}B).
ROM-1 and ROM-2 Are Not Essential for Normal Vulval Development {#s2b}
---------------------------------------------------------------
As a first step to examine the biological function of the *rom* genes, we used RNA interference (RNAi) to transiently knock down their expression ([@pbio-0020334-Fire1]; [@pbio-0020334-Fraser1]; [@pbio-0020334-Kamath1]). Double-stranded RNA derived from a 352-bp *rom-1* or a 718-bp *rom-2* cDNA fragment of the divergent N-terminal portion was injected into the hermaphrodite gonads, and vulval development was examined in the F1 progeny under Nomarski optics. No obvious vulval phenotype was observed when *rom-1* or *rom-2* RNAi was performed in a wild-type background. Also, feeding wild-type or *let-60(n1046gf)* animals with bacteria producing *rom-3* dsRNA had no effect on vulval development (unpublished data). Due to the high degree of sequence similarity between *rom-3* and *rom-4* (69.8% identity), *rom-3* RNAi is likely to simultaneously reduce *rom-4* function.
Using a PCR-based assay to screen a library of mutagenized worms, we isolated a 1,556-bp deletion in the *rom-1* gene (see [Figure 1](#pbio-0020334-g001){ref-type="fig"}C) ([@pbio-0020334-Jansen1]; [@pbio-0020334-Berset1]). The *zh18* deletion removes 206 amino acids from the N terminus, including the first three transmembrane domains and 384 bp of promoter sequences. Thus, the *zh18* deletion probably results in a complete loss of *rom-1* function and will be referred to as *rom-1(0)*. The *rom-1(0)* single mutants exhibited no obvious phenotype; they were healthy and fertile. In addition, we obtained the *rom-2(ok966)* allele from the C. elegans Gene Knockout Consortium. The *rom-2(ok966)* animals carry a 530-bp deletion that removes the fifth exon, which contains the predicted catalytic center with the essential histidine residue (see [Figure 1](#pbio-0020334-g001){ref-type="fig"}B) ([@pbio-0020334-Urban3]). Since this allele is predicted to inactivate any potential protease activity of ROM-2, we refer to it as *rom-2(rf)*. Consistent with the RNAi experiments, both *rom-1(0)* and *rom-2(rf)* single mutants exhibited normal vulval development ([Table 1](#pbio-0020334-t001){ref-type="table"}, rows 2 and 3). Also, in *rom-1(0) rom-2(rf)* double mutants, no defects in vulval development were observed, ruling out a possible redundant function of the two genes ([Table 1](#pbio-0020334-t001){ref-type="table"}, row 4). Thus, neither ROM-1 nor ROM-2 are required for vulval induction under normal conditions.
::: {#pbio-0020334-t001 .table-wrap}
Table 1
::: {.caption}
###### Suppression of Multivulva Mutants by *rom-1(0)*
:::
Vulval induction was scored using Nomarski optics as described in [Materials and Methods](#s4){ref-type="sec"}. % Vul indicates the fraction of animals with fewer than three induced VPCs, % Muv indicates the fraction of animals with more than three induced VPCs, and the induction index indicates the average number of VPCs per animal that had adopted 1° or 2° vulval fates. Number of animals scored is designated by *n*. Alleles used: *pry-1(mu38), rom-1(zh18), rom-2(ok996), lin-12(n137gf), dpy-19(e1259), huIs7\[hs::bar-1*Δ*NT\], let-60(n1046gf), gaIs36\[hs::mpk-1, D-mek-2(gf)\], lin-15(n309), zhEx22\[lin-3(+), sur-5::gfp, unc-119(+)\],* and *syIs12\[hs::lin-3extra\].* Statistical analysis was done as described in [Materials and Methods](#s4){ref-type="sec"}
^a^ Five independent transgenic lines generated with this construct displayed induction indices ranging from 4.1 to 5.4, and one of the lines displaying a penetrant Muv phenotype (*zhEx22*) was used for the further analysis in the different backgrounds
^b^ dsRNA was injected into the syncytial gonad of the parents, and vulval induction in the F1 progeny was scored for rows 4 and 11 by inspection under a dissecting microscope
^c^ To provide a low dose of LIN-3extra, L1 larvae were heat-shocked for 5 min at 33 °C and grown at 25 °C until L4
^d^ To provide a high dose of LIN-3extra, or MPK-1 or BAR-1ΔNT, respectively, early L21 larvae were heat-shocked for 30 min at 33 °C and grown at 25 °C until L4
^e^ These strains carried the *dpy-19(e1259)* mutation in cis to *lin-12(n137gf)*
\*\* *p* ≤ 0.001; \*\*\* *p* ≤ 0.0001; numbers in brackets next to asterisks indicate the row to which a dataset was compared
n.d., no data
:::
ROM-1 Positively Regulates the EGFR/RAS/MAPK Pathway in Distal VPCs {#s2c}
-------------------------------------------------------------------
Next, we examined whether loss of *rom-1* or *rom-2* function affects vulval induction in a sensitized genetic background by using mutations that hyperactivate the EGFR/RAS/MAPK pathway. The *rom-1(0)* mutation as well as *rom-1* RNAi partially suppressed the multivulva (Muv) phenotype caused by overexpression of the LIN-3 EGF growth factor *\[lin-3(+)\]* ([@pbio-0020334-Hill1]) or by the *n1046* gain-of-function *(gf)* mutation in the *let-60 ras* gene, which renders vulval development partially independent of upstream signaling ([@pbio-0020334-Beitel1]; [@pbio-0020334-Chang2]) ([Table 1](#pbio-0020334-t001){ref-type="table"}, rows 5--7 and 12--14). In addition, the *rom-1(0)* mutation suppressed the Muv phenotype of *hs::mpk-1* animals that overexpress the wild-type MAPK MPK-1 under control of a heat-shock promoter together with *Drosophila* MEK-2 under control of the interferon-1α promoter ([@pbio-0020334-Lackner1]) ([Table 1](#pbio-0020334-t001){ref-type="table"}, rows 16 and 17). In contrast to *rom-1,* neither the *rom-2(rf)* mutation nor *rom-2* RNAi affected the Muv phenotype of *let-60(gf)* animals ([Table 1](#pbio-0020334-t001){ref-type="table"}, row 15; unpublished data).
The *rom-1(0)* mutation did not significantly enhance the vulvaless (Vul) phenotype caused by the *lin-3(e1417), lin-2(n397), sem-5(n2019),* or *let-60(n2021)* mutations that reduce the activity of the receptor tyrosine kinase (RTK)/RAS/MAPK pathway (unpublished data). Since these Vul mutants affect the cell fates of only the proximal VPCs (P5.p, P6.p, and P7.p), ROM-1 plays no role in the induction of the proximal VPCs by the AC. Thus, ROM-1 enhances the activity of the EGFR/RAS/MAPK pathway to allow the induction of the distal VPCs P3.p, P4.p, and P8.p.
ROM-1 Regulates LIN-3 EGF Activity during Vulval Induction {#s2d}
----------------------------------------------------------
A soluble form of LIN-3 that consists of the extracellular domain with the EGF repeat but lacks the transmembrane and intracellular domains is biologically active and causes a Muv phenotype when overexpressed under control of a heat-shock promoter *(hs::lin-3extra)* ([@pbio-0020334-Katz1]). Unlike full-length LIN-3, the Muv phenotype induced by a low or high dosage of LIN-3extra was not suppressed by *rom-1(0)* ([Table 1](#pbio-0020334-t001){ref-type="table"}, rows 8--11). In *lin-15(rf)* mutants, all VPCs adopt vulval cell fates independently of the LIN-3 signal, though induction in *lin-15(rf)* mutants depends on the activity of LET-23 and the other components of the EGFR/RAS/MAPK pathway ([@pbio-0020334-Clark1]; [@pbio-0020334-Huang1]). The *rom-1(0)* mutation did not suppress the Muv phenotype of *lin-15(rf)* animals, suggesting that loss of *rom-1* function affects the LIN-3-dependent induction of vulval cell fates rather than the LIN-3-independent activity of the EGFR/RAS/MAPK pathway ([Table 1](#pbio-0020334-t001){ref-type="table"}, rows 18 and 19).
Finally, we examined the genetic interaction between *rom-1* and the Notch and Wnt pathways, since both pathways control vulval cell fate specification in parallel with the RTK/RAS/MAPK pathway ([@pbio-0020334-Wang1]). In *lin-12 notch(gf)* animals, no AC is formed, and all VPCs adopt the 2° cell fate ([@pbio-0020334-Sternberg4]). The same phenotype was observed in *rom-1(0) lin-12(gf)* double mutants ([Table 1](#pbio-0020334-t001){ref-type="table"}, rows 20 and 21). In addition, the Muv phenotype caused by hyperactivation of the Wnt pathway through a reduction-of-function mutation in *pry-1 axin* or by overexpression of a N-terminally truncated BAR-1 β-catenin protein was not suppressed by the *rom-1(0)* mutation ([Table 1](#pbio-0020334-t001){ref-type="table"}, rows 22--25) ([@pbio-0020334-Gleason1]).
In summary, these experiments suggest that ROM-1 promotes the LIN-3-dependent activation of the EGFR/RAS/MAPK signaling pathway. ROM-1 likely acts at the level or upstream of LIN-3 since full-length but not a soluble form of LIN-3 was sensitive to loss of *rom-1* function.
ROM-1 Is Required to Transmit the Inductive Signal to the Distal VPCs {#s2e}
---------------------------------------------------------------------
To assess how much inductive signal each VPC receives, we examined the expression pattern of the *egl-17::cfp* reporter, which is a transcriptional target of the EGFR/RAS/MAPK pathway ([@pbio-0020334-Yoo1]). In mid L2 larvae, before the LIN-12 NOTCH-mediated lateral inhibition becomes effective, *egl-17::cfp* is expressed in a graded manner with highest levels in P6.p, intermediate levels in P5.p and P7.p ([@pbio-0020334-Yoo1]), and lower levels in P3.p, P4.p, and P8.p ([Figure 2](#pbio-0020334-g002){ref-type="fig"}A and [2](#pbio-0020334-g002){ref-type="fig"}B). We therefore examined the effect of the *rom-1(0)* mutation on the *egl-17::cfp* expression pattern in mid L2 larvae. For this purpose, larvae were synchronized in the mid L1 stage at 13 h of development by letting them hatch in the absence of food, and then development was allowed to proceed by adding food for another 24 h until they reached the mid L2 stage (approximately 37 h of development). Loss of ROM-1 function had no effect on *egl-17::cfp* expression in the proximal VPCs (P5.p, P6.p, and P7.p), but significantly reduced *egl-17::cfp* expression in the distal VPCs when compared to wild-type animals ([Figure 2](#pbio-0020334-g002){ref-type="fig"}C and [2](#pbio-0020334-g002){ref-type="fig"}D). Thus, ROM-1 increases the range of the inductive LIN-3 signal, allowing the distal VPCs to activate the EGFR/RAS/MAPK pathway. The altered *egl-17::cfp* expression pattern in *rom-1(0)* animals is consistent with the epistasis data, which showed that loss of *rom-1* function affects the induction of only the distal VPCs (see above).
::: {#pbio-0020334-g002 .fig}
Figure 2
::: {.caption}
###### Expression of the *egl-17::cfp* Reporter in *rom-1(0)* and *lin-3(rf)* Mutants
Photographic images on the left (A, C, E, G, and I) show the expression of the *arIs92\[egl-17::cfp\]* reporter in the VPCs of mid-L2 larvae of the different genotypes indicated.
Pie graphs on the right (B, D, F, H, and J) show semi-quantitative representations of the expression levels observed in individual VPCs in the different backgrounds. A solid black color indicates the strongest expression of EGL-17::CFP as it was observed in P6.p of many (59%) wild-type animals; dark grey indicates intermediate, light grey weak, and white undetectable expression. The numbers inside the pie charts are the corresponding percentage values, and *n* refers to the number of animals examined for each case. EGL-17::CFP expression in each VPC of *rom-1(0)* or *lin-3(e1417rf)* animals was compared against the same VPC in wild-type animals (considered as expected value) with a Chi^2^ test for its independence; \*\*\* *p* ≤ 0.0001, \*\* *p* ≤ 0.001. The row to which a dataset was compared is indicated on the right. All photographs were taken with identical exposure and contrast settings. The scale bar in (I) is 20 μm.
:::
:::
ROM-1 Is Expressed in the VPCs but Not in the AC during Vulval Induction {#s2f}
------------------------------------------------------------------------
To analyze the expression pattern of ROM-1, we generated a transcriptional *rom-1* reporter by fusing 6.9 kb of the 5′ *rom-1* promoter/enhancer region to the *green fluorescent protein (gfp)* ORF carrying a nuclear localizing signal *(zhIs5\[rom-1::nls::gfp\])*. With a translational full-length *rom-1::gfp* fusion construct, we failed to obtain transgenic lines that consistently expressed ROM-1::GFP. Moreover, a genomic DNA fragment encompassing the entire *rom-1* locus failed to produce stable transgenic lines even when injected at relatively low concentrations (1--10 ng/μl), suggesting that elevated levels of ROM-1 are toxic to the animals.
The transcriptional *rom-1::nls::gfp* reporter was widely expressed in somatic cells throughout development. Surprisingly, we did not detect any *rom-1::nls::gfp* expression in the gonadal AC before the L4 stage, while consistent expression was observed in the Pn.p cells and the Pn.a-derived neurons from the L1 stage on. In early L2 *zhIs5* larvae, the six VPCs expressed *rom-1::nls::gfp* at equal levels ([Figure 3](#pbio-0020334-g003){ref-type="fig"}A and [3](#pbio-0020334-g003){ref-type="fig"}B). The Pn.p cells that are not part of the vulval equivalence group and had fused to hyp7 at the end of the L1 stage showed relatively higher *rom-1::nls::gfp* expression than the VPCs (for example, P1.p, P2.p, and P9.p in [Figure 3](#pbio-0020334-g003){ref-type="fig"}C and [3](#pbio-0020334-g003){ref-type="fig"}D). Toward the end of the L2 stage, *rom-1::nls::gfp* expression decreased in distal VPCs adopting the 3° uninduced fate and persisted in the proximal VPCs adopting induced vulval fates ([Figure 3](#pbio-0020334-g003){ref-type="fig"}C and [3](#pbio-0020334-g003){ref-type="fig"}D). In 60% of *zhIs5* animals, we observed an up-regulation of *rom-1::nls::gfp* in P6.p, and in 35% and 45% of the cases, *rom-1::nls::gfp* expression was higher in P5.p and P7.p, respectively (*n* = 20). After vulval induction, *rom-1::nls::gfp* was down-regulated in the 1° and 2° descendants of P5.p, P6.p and P7.p, while the 3° descendants of P3.p, P4.p, and P8.p again expressed high levels of *rom-1::nls::gfp* after they had fused with hyp7 ([Figure 3](#pbio-0020334-g003){ref-type="fig"}E and [3](#pbio-0020334-g003){ref-type="fig"}F). Expression of *rom-1::nls::gfp* was observed in the AC and other cells of the somatic gonad only beginning in the L4 stage, before the AC fused with the uterine seam cell and persisting after fusion ([Figure 3](#pbio-0020334-g003){ref-type="fig"}G and [3](#pbio-0020334-g003){ref-type="fig"}H) ([@pbio-0020334-Sulston1]; [@pbio-0020334-Newman1]). To test whether the inductive AC signal is required for the elevated *rom-1::nls::gfp* expression in the proximal VPCs, we ablated in *zhIs5* animals the precursors of the somatic gonad Z1 and Z4 ([@pbio-0020334-Kimble1]). Uniformly low *rom-1::nls::gfp* expression was found in all six VPCs of gonad-ablated *zhIs5* animals at the late L2 to early L3 stage, before the descendants of the 3° VPCs had fused to hyp7 ([Figure 3](#pbio-0020334-g003){ref-type="fig"}J and [3](#pbio-0020334-g003){ref-type="fig"}K, *n* = 20). To test whether *rom-1::nls::gfp* expression depends on RTK/RAS/MAPK signaling in the VPCs, we introduced the *zhIs5* transgene into *lin-7(e1413)* mutants that exhibit a penetrant Vul phenotype due to reduced LET-23 EGFR activity ([@pbio-0020334-Simske2]). In *lin-7(e1413); zhIs5* animals, the up-regulation of *rom-1::nls::gfp* occurred less frequently (in 13%, 33%, and 7% of the cases in P5.p, P6.p, and P7.p, respectively, *n* = 15). Thus, the AC signal up-regulates *rom-1::nls::gfp* expression in the VPCs that adopt vulval cell fates.
::: {#pbio-0020334-g003 .fig}
Figure 3
::: {.caption}
###### Expression Pattern of *rom-1::nls::gfp*
Expression pattern of the *zhIs5\[rom-1::nls::gfprom-1::\]* transcriptional reporter during vulval development. Images on the left (A, C, E, G, and I) show the corresponding Nomarski pictures with the arrows pointing at the Pn.p cell nuclei and the arrowhead indicating the position of the AC nucleus.
\(B) A mid L2 larva before vulval induction with uniform *rom-1::nls::gfp* expression in all the Pn.p cells.
\(D) An early L3 larva in which *rom-1::nls::gfp* expression was decreased in all VPCs except P6.p (see text for a quantification of the expression pattern). Note that the nuclei of hyp7 and the Pn.p cells that had fused to hyp7 displayed strong *rom-1::nls::gfp* expression (P1.p, P2.p, P3.p and P9.p in the example shown).
\(F) A mid to late L3 larva in which P6.p had generated four descendants. Expression of *rom-1::nls::gfp* occurred only in the 3° descendants of P.4.p and P8.p after they fused to hyp7.
\(H) An L4 larva during vulval invagination. No *rom-1::nls::gfp* was detectable in the 1° and 2° descendants of P5.p, P6.p, and P7.p, but the AC and the surrounding uterine cells displayed strong *rom-1::nls::gfp* expression.
\(K) A late L2 to early L3 larva following the ablation of the precursors of the somatic gonad. No up-regulation of *rom-1::nls::gfp* in P5.p, P6.p, or P7.p was observed. The scale bar in (K) is 10 μm.
:::
:::
ROM-1 Acts in an AC-Independent Pathway that Promotes Vulval Induction {#s2g}
----------------------------------------------------------------------
To examine whether ROM-1 acts in cells other than the AC (which is part of the somatic gonad), we tested the effect of loss of *rom-1(+)* function on vulval induction in gonad-ablated animals. If ROM-1 acts exclusively in the AC, then the *rom-1(0)* mutation should not affect vulval induction in gonad-ablated animals. On the other hand, if ROM-1 acts in cells other than the AC, then the *rom-1(0)* mutation should suppress vulval induction even in the absence of the AC. Since the inductive AC signal is absolutely required to initiate vulval development ([@pbio-0020334-Kimble1]), we performed the gonad ablation experiments in *let-60(gf)* or *hs::mpk-1* animals that exhibit a hyperactive EGFR/RAS/MAPK signaling pathway causing AC-independent vulval induction ([Table 2](#pbio-0020334-t002){ref-type="table"}, rows 5 and 8) ([@pbio-0020334-Beitel1]; [@pbio-0020334-Lackner1]; [@pbio-0020334-Chang2]). In addition, we examined *lin-3(+)* animals because, as reported previously by [@pbio-0020334-Hill1], in animals that overexpress wild-type *lin-3* under control of its own promoter, some vulval differentiation could still be observed in the absence of the AC, pointing at an additional source of LIN-3 from the transgene in cells outside of the gonad ([Table 2](#pbio-0020334-t002){ref-type="table"}, row 2). Loss of *rom-1* function in gonad-ablated *lin-3(+), let-60(gf),* or *hs::mpk-1* animals caused a strong further reduction in vulval induction ([Table 2](#pbio-0020334-t002){ref-type="table"}, compare rows 2 with 3, 5 with 6, and 8 with 9). In contrast, vulval induction in gonad-ablated *lin-15(rf)* animals that exhibit *lin-3* independent vulval differentiation was not affected by the *rom-1(0)* mutation (Table2, rows 13 and 14).
::: {#pbio-0020334-t002 .table-wrap}
Table 2
::: {.caption}
###### Gonad-Independent Function of *rom-1* and *lin-3*
:::
Vulval induction was scored as described in the legend to [Table 1](#pbio-0020334-t001){ref-type="table"}. See [Table 1](#pbio-0020334-t001){ref-type="table"} legend for key to abbreviations and terminology. Alleles used: *rom-1(zh18), let-60(n1046gf), gaIs36\[hs::mpk-1, D-mek-2(gf)\]*, *lin-3(n1049null)* \[the sterile Dpy nonUnc progeny segregated by *dpy-20(e1282) lin-3(n1049)/ unc-44(e362) unc24(e138); gaIs36* mothers was examined\], *lin-15(n309), zhEx22\[lin-3(+),* and *sur-5::gfp, unc-119(+)\].*
^a^ The gonad precursors Z1 through Z4 were ablated in L1 larvae where indicated
^b^ L2 larvae were heat-shocked for 30 min at 33 °C and grown at 25 °C until L4
:::
Analogous results were obtained by examining the *egl-17::cfp* expression pattern after removal of the AC. In gonad-ablated animals, residual *egl-17::cfp* expression was observed in all VPCs ([Figure 2](#pbio-0020334-g002){ref-type="fig"}E and [2](#pbio-0020334-g002){ref-type="fig"}F). In many cases, P6.p expressed higher levels of the reporter than did the other VPCs despite the absence of the AC. Loss of *rom-1* function in gonad-ablated animals caused a further decrease in *egl-17::cfp* expression in all VPCs ([Figure 2](#pbio-0020334-g002){ref-type="fig"}G and [2](#pbio-0020334-g002){ref-type="fig"}H). Thus, ROM-1 acts in cells outside of the somatic gonad to promote vulval induction.
An AC-Independent Activity of LIN-3 EGF {#s2h}
---------------------------------------
Next, we used an analogous strategy to test whether endogenous LIN-3 acts with ROM-1 in an AC-independent pathway. The decrease in vulval induction in *hs::mpk-1* animals that was caused by the *lin-3(n1049)* loss-of-function mutation *\[lin-3(0)\]* was much stronger than the decrease observed in gonad-ablated *lin-3(+); hs::mpk-1* animals ([Table 2](#pbio-0020334-t002){ref-type="table"}, compare rows 8 and 10; the L1 larval lethal phenotype caused by the *lin-3(0)* mutation was suppressed by the *hs::mpk-1* transgene). Vulval induction in *lin-3(0); hs::mpk-1* animals was not affected by gonad ablation since the *lin-3(0)* allele eliminated *lin-3* function in the AC ([Table 2](#pbio-0020334-t002){ref-type="table"}, compare rows 10 and 11). Thus, a complete loss of *lin-3* function had a more severe effect on vulval induction than did just the removal of the AC. Likewise, the *lin-3(e1417)* reduction-of-function mutation almost completely abolished the expression of the *egl-17::cfp* marker ([Figure 2](#pbio-0020334-g002){ref-type="fig"}I and [2](#pbio-0020334-g002){ref-type="fig"}J). Thus, LIN-3 is also necessary for the AC-independent *egl-17::cfp* expression in the VPCs. Loss of *rom-1* function in a *lin-3(0); hs::mpk-1* background caused no further decrease in vulval induction, suggesting that ROM-1 does not affect vulval development in the absence of LIN-3 ([Table 2](#pbio-0020334-t002){ref-type="table"}, compare rows 10 and 12).
Taken together, these experiments indicate that not only the AC but also cells outside of the gonad produce LIN-3 to promote vulval fate specification. This AC-independent activity of LIN-3 requires ROM-1 function.
ROM-1 Can Act in the Pn.p Cells {#s2i}
-------------------------------
The absence of detectable *rom-1::nls::gfp* expression in the AC around the time of vulval induction and the AC-independent function of *rom-1* and *lin-3* suggested that *rom-1* may act cell-autonomously in the VPCs. To test this hypothesis, we expressed *rom-1* under control of the Pn.p cell-specific *lin-31* promoter *(lin-31::rom-1)* ([@pbio-0020334-Tan1]). The *lin-31::rom-1* transgene restored vulval induction in *rom-1(0); let-60(gf)* and *rom-1(0); hs::mpk-1* double mutants to levels comparable to those found in *let-60(gf)* and *hs::mpk-1* single mutants ([Table 3](#pbio-0020334-t003){ref-type="table"}, rows 1--3 and 8--10). A transgene encoding bacterial Cre recombinase under control of the *lin-31* promoter *(lin-31::cre)* that was used as a negative control had no effect on vulval induction ([Table 3](#pbio-0020334-t003){ref-type="table"}, rows 4 and 11) ([@pbio-0020334-Hoier1]). Consistent with a function of *rom-1* in an AC-independent pathway, the *lin-31::rom-1* transgene also increased induction in gonad-ablated *rom-1(0); let-60(gf)* animals ([Table 3](#pbio-0020334-t003){ref-type="table"}, rows 5--7). Finally, we expressed *rom-1* in the AC under control of the AC-specific enhancer (ACEL) *(ACEL::rom-1),* which is located in the third intron of the *lin-3* locus ([@pbio-0020334-Hwang1]). In contrast to *lin-31::rom-1,* the *ACEL::rom-1* transgene did not rescue the suppression of the *let-60(gf)* Muv phenotype by *rom-1(0)* ([Table 3](#pbio-0020334-t003){ref-type="table"}, rows 12 and 13). Thus, the tissue-specific expression of ROM-1 in the Pn.p cells efficiently rescues a loss of *rom-1* function.
::: {#pbio-0020334-t003 .table-wrap}
Table 3
::: {.caption}
###### Expression of *rom-1* in the Pn.p Cells but Not in the AC Rescues the *rom-1(0)* Phenotype
:::
Vulval induction was scored as described in the legend to [Table 1](#pbio-0020334-t001){ref-type="table"}. See [Table 1](#pbio-0020334-t001){ref-type="table"} legend for key to abbreviations and terminology. Alleles used: *rom-1(zh18), let-60(n1046gf), gaIs36\[hs::mpk-1, D-mek-2(gf)\], zhEx66\[lin-31::rom-1, unc-119(+), sur-5::gfp\], zhEx81\[lin- zhEx81\[lin-31::cre, unc-119(+), myo-3::gfp\],* and *zhEx89\[ACEL::rom-1, sur-5::gfp\].*
^a^ The gonad precursor cells Z1 through Z4 were ablated in L1 larvae where indicated
^b^ All three independent transgenic lines examined increased the induction index of *rom-1(0); let-60(gf)* animals to 4.2--4.5
^c^ L2 larvae were heat-shocked for 30 min at 33 °C and grown at 25 °C until L4
^d^ Two independent transgenic lines examined displayed an induction index in *rom-1(0); let-60(gf)* animals of 3.3 and 3.5
:::
LIN-3 EGF from the Pn.p Cells Amplifies the AC Signal {#s2j}
-----------------------------------------------------
To examine whether the VPCs or their descendants are the source of the AC-independent LIN-3 signal, we expressed *lin-3* dsRNA in the Pn.p cells in order to down-regulate by RNAi any possible *lin-3* expression in the VPCs ([@pbio-0020334-Timmons1]). For this purpose, a vector consisting of an inverted repeat of a 921-bp *lin-3* cDNA fragment under control of the same Pn.p cell-specific *lin-31* promoter used above *(lin-31::lin-3i)* was introduced into wild-type animals ([@pbio-0020334-Tan1]). Vulval induction occurred normally in *lin-31::lin-3i* animals ([Table 4](#pbio-0020334-t004){ref-type="table"}, row 1), although the adult animals displayed an 80% penetrant egg-laying defective (Egl) phenotype due to a defect in vulval morphogenesis (*n* = 122). In wild-type L4 larvae, the 1° descendants of P6.p in the vulF toroid ring (P6.papl/r and P6.ppal/r,), secrete LIN-3 to specify the ventral uterine (uv1) cell fate in the somatic gonad ([@pbio-0020334-Chang1]). If LIN-3 expression in the F cells is blocked through a mutation in the *egl-38 pax* transcription factor, then the uv1 cell adopts a uterine seam fate, resulting in an Egl phenotype. Thus, *lin-31::lin-3i* appeared to efficiently reduce LIN-3 expression in the vulval F cells without reducing the activity of LIN-3 in the AC. To further authenticate the efficiency of this approach, we crossed animals carrying the *lin-31::lin-3i* transgene to animals expressing the short splice variant of *lin-3* cDNA in the Pn.p cells under control of the *lin-31* promoter (*lin-31::lin-3S,* see below). The *lin-31::lin-3i* transgene almost completely suppressed the Muv phenotype caused by the *lin-31::lin-3S* transgene, while the *lin-31::cre* transgene that was used as negative control had no effect ([Table 4](#pbio-0020334-t004){ref-type="table"}, rows 2--4). Furthermore, the *lin-31::lin-3i* transgene significantly reduced vulval induction in *lin-3S* animals that carry a *lin-3* minigene encoding the short splice variant ([Figure 4](#pbio-0020334-g004){ref-type="fig"}A), as well as in *let-60 ras(gf)* and *hs::mpk-1* animals ([Table 4](#pbio-0020334-t004){ref-type="table"}, rows 5--14)*.* Consistent with an AC-independent function of LIN-3 in the VPCs, the *lin-31::lin-3i* transgene also affected vulval induction in *let-60(gf)* animals lacking a gonad ([Table 4](#pbio-0020334-t004){ref-type="table"}, rows 11 and 12).
::: {#pbio-0020334-g004 .fig}
Figure 4
::: {.caption}
###### Alternative Splicing of *lin-3* mRNA
\(A) RT-PCR amplification of *lin-3* mRNA from mixed-stage N2 cDNA before (left) and after (right) size fractionation by preparative agarose gel electrophoresis. The lowest band corresponding to LIN-3S is most prominent, and the two upper bands correspond to LIN-3L and LIN-3XL.
\(B) Intron-exon structure of the *lin-3* locus. The *lin-3L* splice variant is generated by the usage of an alternative (more 3′ located) splice donor in exon 6a. The *lin-3XL* variant contains the additional exon 6b inserted between exons 6a and 7. The regions encoding the EGF repeat in exon 5 and part of 6a and the transmembrane domain in exon 7 are outlined, and the positions of the PstI sites used for the construction of the minigenes are indicated (see [Materials and Methods](#s4){ref-type="sec"}). The structure of the *lin-3S* and *lin-3L* minigenes is shown in the lower part of the graphic.
\(C) Sequence alignment of the alternatively spliced region in LIN-3 with the corresponding region in *Drosophila* Spitz. The 15 and 41 amino acids in LIN-3L and LIN-3XL, respectively, in the juxtamembrane region break the alignment of LIN-3 with Spitz. The C-terminal end of the EGF domain is underlined with a horizontally hatched bar, and the beginning of the transmembrane domain is underlined by a diagonally hatched line.
:::
:::
::: {#pbio-0020334-t004 .table-wrap}
Table 4
::: {.caption}
###### Pn.p Cell-Specific Function of *lin-3*
:::
Vulval induction was scored as described in the legend to [Table 1](#pbio-0020334-t001){ref-type="table"}. See [Table 1](#pbio-0020334-t001){ref-type="table"} legend for key to abbreviations and terminology. Alleles used: *let-60(n1046gf), egl-38(n578), gaIs36\[hs::mpk-1, D-mek-2(gf)\], zhEx72\[lin-31::lin-3S, unc-119(+), sur-5::gfp\], zhEx68\[lin-3S, unc-119(+), sur-5::gfp\], zhEx88\[lin-31::lin-3i, unc-119(+), myo-3::gfp\],*and *zhEx81\[lin-31::cre, unc-119(+), myo-3::gfp\].*
^a^ The gonad precursor cells Z1 through Z4 were ablated in L1 larvae where indicated
^b^ Three independent transgenic lines displayed a penetrant Egl phenotype and suppressed the *let-60(gf)* phenotype to induction indices L1 ranging from 3.1 to 3.3, and one line was used for further analysis. Two lines displayed no Egl phenotype and did not suppress the *let-60(gf)* phenotype (induction index 4.2 and 4.3). All five lines exhibited normal vulval induction in a wild-type background
^c^ L1 and L2 larvae were heat-shocked for 30 min at 33 °C and grown at 25 °C until L4
:::
As an independent test to determine if a reduction of LIN-3 expression in the vulval cell lineage affects induction, we used the *n578* reduction-of-function mutation in the *egl-38 pax* transcription factor, because this *egl-38* allele has been shown to eliminate LIN-3 expression in the 1° cell lineage ([@pbio-0020334-Chang1]). Although *egl-38(rf)* single mutants exhibited wild-type levels of vulval induction, the *egl-38(rf)* mutation reduced the Muv phenotype of *hs::mpk-1* animals to a similar degree as the *rom-1(0)* mutation or the *lin-31::lin-3i* transgene ([Table 4](#pbio-0020334-t004){ref-type="table"}, rows 15 and 16). Thus, EGL-38 is necessary for the AC-independent function of LIN-3.
In summary, these experiments indicated that, during the process of vulval cell fate specification, some of the Pn.p cells (probably the VPCs) produce LIN-3 to amplify the inductive signal.
Three LIN-3 EGF Splice Variants that Differ in the Juxtamembrane Domain {#s2k}
-----------------------------------------------------------------------
The *lin-3* locus encodes two splice variants termed LIN-3S (short) and LIN-3L (long) that are generated by the differential choice of the splice donor of exon 6 ([Figure 4](#pbio-0020334-g004){ref-type="fig"}B) ([@pbio-0020334-Hill1]). While performing RT-PCR experiments using a primer pair flanking the differentially spliced exons, we discovered a third splice variant, termed LIN-3XL, that is generated by the insertion of an additional exon (6b) between exons 6 and 7 ([Figure 4](#pbio-0020334-g004){ref-type="fig"}A and [4](#pbio-0020334-g004){ref-type="fig"}B). The LIN-3XL splice variant was independently isolated from the yk1053b07EST clone. LIN-3XL contains a 41 amino acid insert, and LIN-3L contains a 15 amino acid insert, in the region between the EGF repeat and the transmembrane domain, when compared to LIN-3S ([Figure 4](#pbio-0020334-g004){ref-type="fig"}C). Since the analogous region in *Drosophila* Spitz EGF is required for the proteolytic processing of Spitz by Rhomboid ([@pbio-0020334-Bang1]; [@pbio-0020334-Lee1]; [@pbio-0020334-Urban2]), we sought to determine which of the LIN-3 splice variants depend on ROM-1 activity. To address this question, we first constructed *lin-3* minigenes by replacing the differentially spliced exons with cDNA fragments encoding either of the splice forms (see [Figure 4](#pbio-0020334-g004){ref-type="fig"}B). Both *lin-3L* and *lin-3S* minigenes were capable of inducing a Muv phenotype, but we observed a marked difference in the dosages required to elicit this phenotype. All (12 out of 12) transgenic lines generated by injection of a relatively low (1 ng/μl) or high (100 ng/μl) concentration of the *lin-3S* minigene exhibited a strong Muv phenotype (with induction indices ranging from 4.1 to 5.6). In contrast, the *lin-3L* construct caused a Muv phenotype only when injected at a high concentration. (None of the seven *lin-3L* lines obtained by injecting 1 ng/μl exhibited a Muv phenotype, while all nine lines obtained by injecting 100 ng/μl exhibited a Muv phenotype, with induction indices ranging from 4.2 to 5.0). For the *lin-3XL* construct, we obtained variable results; some lines exhibited a weak Muv and others no or even a Vul phenotype (unpublished data). Since we failed to observe a consistent phenotype with this minigene construct, we did not further pursue the analysis of the *lin-3XL* minigene.
ROM-1 Is Necessary for the Activation of the Long LIN-3 Splice Variant {#s2l}
----------------------------------------------------------------------
To investigate the genetic interactions between *rom-1* and the *lin-3* splice variants, we compared one line for each of the *lin-3S* and *lin-3L* minigenes that displayed a similar degree of vulval induction ([Table 5](#pbio-0020334-t005){ref-type="table"}, rows 1 and 4). Since the presence of endogenous LIN-3 might mask a specific requirement of either LIN-3 splice variant, we introduced the two minigenes into a *lin-3(0)* background. The *lin-3S* and *lin-3L* transgenes both rescued the larval lethality of *lin-3(0)* mutants, yielding adult Muv animals ([Table 5](#pbio-0020334-t005){ref-type="table"}, rows 2 and 5 and [Table 6](#pbio-0020334-t006){ref-type="table"}, rows 1 and 3). Since we used multicopy arrays that are silenced in the germ cells and LIN-3 is required in the oocytes to induce ovulation ([@pbio-0020334-Clandinin1]), the rescued *lin-3(0); lin-3S* and *lin-3(0); lin-3L* animals were sterile. Loss of *rom-1* function did not affect the viability or the Muv phenotype of *lin-3(0); lin-3S* animals ([Table 5](#pbio-0020334-t005){ref-type="table"}, rows 2 and 3 and [Table 6](#pbio-0020334-t006){ref-type="table"}, row 2). In contrast, the efficiency of the *lin-3L* transgene in rescuing the larval lethality of *lin-3(0)* mutants was reduced by loss of *rom-1* function ([Table 6](#pbio-0020334-t006){ref-type="table"}, row 4). Moreover, the rare *rom-1(0), lin-3(0); lin-3L* animals that escaped the larval lethality exhibited a weaker Muv phenotype than *lin-3(0); lin-3L* animals, suggesting that the function of LIN-3L during vulval induction partially depends on ROM-1 activity ([Table 5](#pbio-0020334-t005){ref-type="table"}, rows 5 and 6).
::: {#pbio-0020334-t005 .table-wrap}
Table 5
::: {.caption}
###### The *lin-3L* Splice Form Depends on *rom-1* Activity
:::
Vulval induction was scored as described in the legend to [Table 1](#pbio-0020334-t001){ref-type="table"}. See [Table 1](#pbio-0020334-t001){ref-type="table"} legend for key to abbreviations and terminology. Alleles used: *rom-1(zh18), lin-3(n1049null)* \[the sterile Dpy nonUnc progeny segregated by *dpy-20(e1282) lin-3(n1049)/ unc24(e138) unc-unc-44(e362)* mothers were examined\], *zhEx68\[lin-3S, sur-5::gfp, unc-119(+)\], zhEx69\[lin-3L, sur-5::gfp, unc-119(+)\], zhEx72\[lin-31::lin-3S, unc-119(+), sur-5::gfp\],* and *zhEx73\[lin-31::lin-3L, unc-119(+) sur-5::gfp\]*
^a^ The gonad precursor cells Z1 through Z4 were ablated in L1 larvae where indicated
:::
::: {#pbio-0020334-t006 .table-wrap}
Table 6
::: {.caption}
###### Rescue of the Larval Lethality in *lin-3(0)* Mutants by the *lin-3S* and *lin-3L* Minigenes
:::
See [Table 1](#pbio-0020334-t001){ref-type="table"} legend for key to abbreviations and terminology. To confirm that the viable Dpy nonUnc animals were the rescued *lin-3(0)* homozygotes and not recombinants between *dpy-20* and *lin-3,* they were scored for fertility 4--5 d later. All animals counted for this table developed into sterile adults due to the silencing of the rescuing transgenes in the germline. In contrast, all viable Dpy nonUnc progeny segregated by *dpy-20(e1282) lin-3(n1049)/ unc-44(e362) unc24(e138)* mothers lacking a *lin-3* minigene developed into fertile adults, indicating recombination between *dpy-20* and *lin-3*. (Seven recombinants were found among 1,000 F1 progeny animals.) Alleles used: *rom-1(zh18), lin-3(n1049)*, *dpy-20(1282), unc24(e138), unc-44(e362), zhEx68\[lin-3S, sur-5::gfp, unc-119(+)\],* and *zhEx69\[lin-3L,sur- sur-5::gfp, unc-119(+)\].*
^a^ To score viability, 100--200 GFP-positive embryos segregated by *dpy-20(e1282) lin-3(n1049)/ unc24(e138) unc-44(e262)* mothers carrying the indicated minigenes were placed on NGM plates. After 24 and 48 h, the viable Dpy nonUnc larvae representing the rescued *lin-3(0)* animals and the dead larvae were counted, and the % viability was calculated as 100× \[Dpy nonUncs/(Dpy nonUncs+ dead larvae)\]
:::
To specifically test the function of the LIN-3 splice variants in the Pn.p cells, we cloned full-length cDNAs encoding the LIN-3S and LIN-3L splice variants under control of the Pn.p cell-specific *lin-31* promoter *(lin-31::lin-3S* and *lin-31::lin-3L)*. The *lin-31::lin-3S* and *lin-31::lin-3L* transgenes both caused a strong Muv phenotype in the presence and absence of the AC ([Table 5](#pbio-0020334-t005){ref-type="table"}, rows 7, 9, 11, and 13). Loss of *rom-1* function did not change the phenotype of *lin-31::lin-3S* animals ([Table 5](#pbio-0020334-t005){ref-type="table"}, rows 8--10), but it strongly suppressed the Muv phenotype of *lin-31::lin-3L* animals ([Table 5](#pbio-0020334-t005){ref-type="table"}, rows 12 and 14). Thus, ROM-1 is required for the activity of the LIN-3L splice variant in the Pn.p cells, while LIN-3S functions independently of ROM-1.
Discussion {#s3}
==========
ROM-1 Positively Regulates LIN-3 EGF Mediated Vulval Induction {#s3a}
--------------------------------------------------------------
Of the five Rhomboid proteins predicted by the complete C. elegans genome sequence, only ROM-1, the closest homolog of *Drosophila* Rhomboid-1, possesses the hallmarks of a serine protease with an intact catalytic center ([@pbio-0020334-Urban3]). Here, we show that ROM-1 acts as a positive regulator of the EGFR/RAS/MAPK signaling pathway during vulval induction, as loss of *rom-1* function partially suppresses ectopic vulval induction caused by hyperactivation of the EGFR/RAS/MAPK pathway. Our epistasis analysis points at a role of ROM-1 in activating LIN-3 EGF. The activity of a soluble form of LIN-3 lacking the transmembrane and intracellular domains is completely independent of ROM-1 activity, but the activity of full-length LIN-3 EGF is sensitive to loss of ROM-1 function. Moreover, a mutation in *lin-15,* which renders vulval induction independent of LIN-3 activity, is not suppressed by loss of *rom-1* function, but mutations in LET-23 or downstream components of the EGFR/RAS/MAPK pathway efficiently suppress the *lin-15* Muv phenotype ([@pbio-0020334-Clark1]; [@pbio-0020334-Huang1]). Although ROM-1 enhances the activity of the inductive LIN-3 EGF signal, ROM-1 is not required for vulval induction under normal growth conditions. Loss of *rom-1* function does not enhance the Vul phenotype caused by mutations that reduce RTK/RAS/MAPK signaling in the proximal VPCs, indicating that ROM-1 is not required for the induction of the proximal VPCs by the AC. These observations point at the existence of another, yet unidentified protease that mediates the release of LIN-3 from the AC. Like vertebrate TGF-α, and unlike *Drosophila* Spitz, which absolutely depends on Rhomboid function, membrane-bound LIN-3 might be cleaved at the surface of the AC by an ADAM family metalloprotease ([@pbio-0020334-Peschon1]). Another possibility our experiments have not ruled out is that in *rom-1(0)* mutants an unprocessed, membrane-bound form of LIN-3 that is retained on the plasma membrane of the AC induces the 1° fate in the adjacent VPC P6.p through juxtacrine signaling ([@pbio-0020334-Anklesaria1]). Once the AC has induced the 1° cell fate in P6.p, the 2° cell fate specification in the neighboring VPCs P5.p and P7.p can occur exclusively through lateral LIN-12 NOTCH signaling, resulting in a wild-type vulva ([@pbio-0020334-Greenwald1]; [@pbio-0020334-Kenyon1]; [@pbio-0020334-Simske1]). However, the AC is separated from the VPCs by two adjacent basal laminas that dissolve only after the vulval cell fates have been induced ([@pbio-0020334-Sherwood1]). It is therefore difficult to predict whether LIN-3 anchored in the plasma membrane of the AC could reach its receptor LET-23 EGFR on the basolateral surface of P6.p.
ROM-1 Is Required for LIN-3 EGF Activity in the Pn.p Cells {#s3b}
----------------------------------------------------------
Three lines of evidence indicate that ROM-1 functions in the signal-receiving VPCs rather than the signal-sending AC. First, a *rom-1::nls::gfp* transcriptional reporter is expressed in the VPCs but not in the AC around the time of vulval induction. The *rom-1* gene appears to be a transcriptional target of the EGFR/RAS/MAPK pathway, as *rom-1::nls::gfp* expression is up-regulated in the induced VPCs in response to AC signaling. Second, the expression of *rom-1* in the Pn.p cells rescues loss of *rom-1* function. Third, loss of *rom-1* function in animals lacking an AC results in a further suppression of vulval induction and reduction of *egl-17::cfp* expression, indicating that the main, if not the only, focus of *rom-1* action is outside of the gonad. On the other hand, our epistasis analysis and the biochemical experiments done with *Drosophila* Rhomboid-1 ([@pbio-0020334-Bang1]; [@pbio-0020334-Lee1]; [@pbio-0020334-Urban2]) suggest that ROM-1 is required cell-autonomously for the activation of a membrane-bound LIN-3 precursor. This apparent discrepancy can be explained by the previously published observation of residual *lin-3* activity in the absence of the gonad ([@pbio-0020334-Hill1]) and by the additional experiments presented in this paper that uncovered an AC-independent function of LIN-3 during vulval induction. The most likely source of LIN-3 besides the AC are the VPCs, as reducing *lin-3* function in the Pn.p cells by tissue-specific RNAi or a mutation in the *egl-38* gene, which is required for *lin-3* expression in vulval cells ([@pbio-0020334-Chang1]), had essentially the same effect as loss of *rom-1* function. Using transcriptional reporter constructs, *lin-3* expression has been observed in vulval cells of the 1° lineage beginning in the early L4 stage ([@pbio-0020334-Chang1]), and occasionally we observed weak *lin-3* expression in the VPCs or their daughter cells (unpublished data). It is possible that the reporter constructs used were lacking some of the regulatory sequences necessary to drive strong *lin-3* expression in the VPC lineage. Other potential sources of LIN-3 may be the posterior ectoderm or the excretory system in the head. However, it seems unlikely that LIN-3 secreted from cells at the anterior or posterior end of the animal influences vulval induction, since we did not observe a bias favoring the induction of anterior or posterior VPCs in the absence of the AC.
A Relay Model for Vulval Induction {#s3c}
----------------------------------
Expression levels of *rom-1::nls::gfp* are highest in the proximal VPCs (P5.p, P6.p, and P7.p) that adopt 1° and 2° vulval cell fates, suggesting that the proximal VPCs are competent to secrete LIN-3 in response to the inductive AC signal. LIN-3 from the proximal VPCs may facilitate the induction of the more distally located VPCs by paracrine signaling ([Figure 5](#pbio-0020334-g005){ref-type="fig"}). Such a relay model is reminiscent of the EGF signaling during *Drosophila* oogenesis ([@pbio-0020334-Freeman2]; [@pbio-0020334-Wasserman1]). The Gurken growth factor produced by the *Drosophila* oocyte initially activates the EGFR/RAS/MAPK pathway in the adjacent epithelial follicle cells on the dorsal side of the oocyte independently of Rhomboid. In response to the Gurken signal, the dorsal follicle cells secrete Spitz in a Rhomboid-dependent manner and activate the EGFR in the neighboring follicle cells by paracrine signaling, allowing the signal to spread along the dorsal follicle cell layer. In contrast to *Drosophila* oogenesis, signal spreading is not necessary for the development of a wild-type C. elegans vulva. The AC needs to induce only the nearest VPC, P6.p, since a 1° cell can specify the 2° fate in the neighboring cells exclusively through lateral LIN-12 NOTCH signaling ([@pbio-0020334-Greenwald1]; [@pbio-0020334-Simske1]). On the other hand, dosage experiments have indicated that low levels of inductive LIN-3 signal can directly specify the 2° cell fate in the absence of lateral signaling ([@pbio-0020334-Katz1]). It is therefore possible that the relay signal generated by ROM-1 and LIN-3 in P6.p contributes to the specification of the 2° cell fate in the neighboring VPCs in combination with the lateral LIN-12 NOTCH signal. LIN-3 secreted from the proximal VPCs could initially serve to maintain the competence of all VPCs, while at a later phase of induction the AC and lateral signals would seal the 1° fate of P6.p and the 2° fate of P5.p and P7.p, respectively. A similar two-step model of vulval induction has been proposed for other rhabditid nematode species such as *Oscheius* sp. ([@pbio-0020334-Felix1]). In *C. elegans,* ROM-1 is dispensable for the induction of the proximal VPCs, and the relay mechanism mediated by LIN-3 and ROM-1 only becomes apparent in a sensitized genetic background in which distal VPCs adopt induced cell fates. It is interesting to note in this context that in *Mesorhabditis* and *Teratorhabditis,* in which the vulva develops in the posterior body region, induction occurs without a signal from an AC or any other gonad cell ([@pbio-0020334-Sommer1]). In these posterior-vulva Rhabditidae, the VPCs are not equivalent, because only P5.p and P6.p are competent to adopt the 1° fate. The mechanism that generates this intrinsic difference among the VPCs is unknown. It is possible that in these nematodes the specification of the VPC cell fates occurs in a cell-autonomous manner that could involve EGF signaling between the VPCs. The AC in C. elegans serves to position the vulva in the central body region, and the function of an AC appears to be absent in the posterior-vulva *Rhabditidae*.
::: {#pbio-0020334-g005 .fig}
Figure 5
::: {.caption}
###### A Relay Model for Vulval Induction
The AC initiates vulval development by secreting the LIN-3 growth factor independently of ROM-1. In response to the AC signal, the proximal VPCs up-regulate ROM-1 expression and start secreting LIN-3 in a ROM-1-dependent manner to relay the AC signal.
:::
:::
Splice Variant-Specific Action of ROM-1 {#s3d}
---------------------------------------
The two previously identified LIN-3 splice forms (LIN-3S and LIN-3L) as well as the newly identified longer variant (LIN-3XL) differ by 15 and 41 amino acid insertions in the juxtamembrane region just prior to the predicted Rhomboid cleavage site at the start of the transmembrane domain ([@pbio-0020334-Hill1]). Our experiments with LIN-3 minigenes indicate that the activity of the shortest splice form (LIN-3S) is completely independent of ROM-1 function. LIN-3S is expressed at all stages of development, and the LIN-3S minigene rescued all phenotypes caused by the *lin-3(0)* mutation, including the ovulation defects (unpublished data). This may explain why loss of *rom-1* function causes neither the larval lethality nor the sterility observed in *lin-3* mutants. Furthermore, our data indicate that LIN-3L function in the VPCs almost completely depends on ROM-1 activity. It seems improbable that the 15 amino acid insertion in LIN-3L could change the substrate specificity toward the ROM-1 protease. A more likely explanation for the inherent difference in the dependence of the LIN-3 splice variants on ROM-1 is suggested by the experiments performed with *Drosophila* Spitz ([@pbio-0020334-Lee1]; [@pbio-0020334-Tsruya1]). When expressed in mammalian cells that lack Rhomboid activity, Spitz is retained in the Golgi apparatus. Introducing functional Rhomboid into these cells allows the cleavage and release of Spitz from the Golgi apparatus, resulting in the secretion of the extracellular portion of Spitz. In analogy to Spitz, the small insert in LIN-3L could cause the retention of this LIN-3 isoform in the Golgi apparatus, thus rendering LIN-3L dependent on ROM-1 mediated processing. The tissue distribution of the LIN-3 splice variants is unknown, although all three forms can be detected by RT-PCR in L2 and L3 larvae around the time of vulval induction (unpublished data). In view of the relay model discussed above ([Figure 5](#pbio-0020334-g005){ref-type="fig"}), tissue-specific splicing may account for the distinct functions of LIN-3. The roles of the two *Drosophila* EGF-like growth factors Gurken and Spitz may be fulfilled in C. elegans by the splice variants LIN-3S and LIN-3L, respectively. In this model, the AC uses the ROM-1-independent isoform LIN-3S to induce vulval development, and the proximal VPCs relay the AC signal to the distal VPCs by secreting LIN-3L. Alternative splicing has also been reported for the Neuregulin family of EGF-like ligands in vertebrates ([@pbio-0020334-Chang3]). Different Neuregulin isoforms elicit distinct responses by activating different EGFRs ([@pbio-0020334-Meyer1]). The tissue-specific expression of Rhomboid family proteases could determine which isoforms a particular cell type can secrete, thus adding another level of regulation.
Materials and Methods {#s4}
=====================
{#s4a}
### General methods and strains used {#s4a1}
Standard methods were used for maintaining and manipulating Caenorhabditis elegans ([@pbio-0020334-Brenner1]). The C. elegans Bristol strain, variety N2, was used as the wild-type reference strain in all experiments. Unless noted otherwise, the mutations used have been described in [@pbio-0020334-Riddle1] and are listed below by their linkage group: LGI: *pry-1(mu38)* ([@pbio-0020334-Gleason1]); LGIII: *dpy-19(e1259), lin-12(n137gf), rom-1(zh18)* (this study), *rom-2(ok966)* (C. elegans Gene Knockout Consortium), and *unc-119(e2498);* LGIV: *let-60(n1046)* ([@pbio-0020334-Beitel1]), *lin-3(n1049), unc-5(e53), unc-44(362), lin-45(sy96), unc-24(e138), mec-3(e1338), dpy-20(e1282), egl-38(n578),* and *mec-3(n3197);* LGX: *sem-5(n2019)* and *lin-15(n309);* extrachromosomal and integrated arrays: *zhEx22\[lin-3(+), sur-5::gfp, unc-119(+)\], zhE66\[lin-31::rom-1, unc-119(+), sur-5::gfp\], zhEx72\[lin-31::lin-3S, unc-119(+), sur-5::gfp\], zhEx68\[lin-3S, unc-119(+), sur-5::gfp\], zhEx69\[lin-3L, sur-5::gfp, unc-119(+)\],zhEx73\[lin-31::lin- zhEx73\[lin-31::lin-3L, unc-119(+) sur-5::gfp\], zhEx78\[ACEL::*Δ*pes-10::nls::gfp, unc-119(+)\], zhEx81\[lin-31::cre, unc-119(+), myo-3::gfp\], zhE88\[lin-31::lin-3i, unc-119(+), myo-3::gfp\], zhEx89\[ACEL::rom-1, sur-5::gfp\], syIs12\[hs::lin-3extra\]* ([@pbio-0020334-Katz1]), *zhIs5\[rom-1::nls::gfp, unc-119(+)\]*, *huIs7\[hs::bar-1*Δ*NT, dpy-20(+)\]* ([@pbio-0020334-Gleason1]), *gaIs36\[hs-mpk-1, IF1alpha-Dmek-2\]* ([@pbio-0020334-Lackner1]), and *arIs92\[egl-17::cfp\]* ([@pbio-0020334-Yoo1]). Unless noted in the table legends, all experiments were conducted at 20 °C. Transgenic lines were generated by injecting the experimental DNA at a concentration of 100 ng/μl or at the concentrations indicated in the text into both arms of the syncytial gonad as described ([@pbio-0020334-Mello1]).The constructs pUnc-119 (20 ng/μl), pPD93.97 (*myo-3::gfp*, 40 ng/μl), and pTG96 (*sur-5::gfp*, 100 ng/μl) were used as a cotransformation markers ([@pbio-0020334-Maduro1]; [@pbio-0020334-Yochem1]). The extrachromosomal array *zhEx\[rom-1::nls::gfprom-1::gfp; unc-119(+)\]* was integrated in the genome animals following γ-irradiation with 3,000 Rad to generate the array *zhIs5* and backcrossed six times before analysis. Double and triple mutants were constructed using standard genetic methods. Where cis-linked markers were used they are indicated in the table legends.
### Plasmid constructs {#s4a2}
The transcriptional *rom-1::nls::gfp* reporter construct (pRH2) was generated by ligating a HindIII-NheI--restricted 6,998-bp genomic fragment spanning the entire 5′ upstream region of F26F4.3 isolated by PCR amplification with the primers OAD49 (5′-GGAAGCTTGCATGCCCAACGAAATCGATA-3′) and OAD59 (5′-GGGCTAGCCATGTTGTGGAGAAGGAGAAC-3′) into the HindIII-XbaI site of pPD96.04. The *rom-1::gfp* translational reporter construct (pAD31) was generated by PCR amplification of a 3,146-bp genomic fragment containing 1,849 bp of 5′ sequences and the entire *rom-1* ORF using the primers OAD47 (5′-GACTCTAGAGTTGTCAAAAGGTCACGGG-3′) and OAD51 (5′-ATCCTCTAGAGTTGAGCAATTTTCGTTGTTCCAC-3′\') followed by XbaI restriction and ligation to XbaI-digested vector pPD95.75. The upstream promoter region of this construct was further extended by replacing a 420-bp PstI fragment with a 2,099-bp PstI genomic fragment corresponding to positions --1,432 and --3,531 relative to the predicted translation start codon of F26F4.3. The *lin-31::rom-1* construct (pAD16) was generated by ligating a 1,601-bp SalI-NotI fragment spanning the entire *rom-1* coding sequence amplified with the primers OAD44 (5′-TTTTGGTCGACCTCCTTCTCCACAAC-3′) and OAD45 (5′-TTTGGCGGCCGCCTATGAGCAATTTTCG-3′) into the SalI-NotI site of the pB253 vector ([@pbio-0020334-Tan1]). To generate the *ACEL::rom-1* construct, a 2.3-kb SalI genomic *lin-3* fragment encompassing the third intron, which contains the ACEL ([@pbio-0020334-Hwang1]), was cloned into the SalI site of the pTB11 plasmid, which consists of an *nls::gfp* reporter cassette under control of the truncated *pes-10* minimal promoter ([@pbio-0020334-Berset1]). Transgenic animals carrying the resulting *ACEL::*Δ*pes-10::nls::gfp* construct (pAH67) showed strong and specific GFP expression in the AC beginning in the mid L2 stage as reported ([@pbio-0020334-Hwang1]). The KpnI-EcoRI fragment encoding the *nls::gfp* cassette was then replaced with a 1.6-kb KpnI-NotI *rom-1* fragment isolated from the *lin-31::rom-1* plasmid described above to yield the *ACEL::rom-1* construct. For the *lin-31::lin-3* splice variant constructs, partial cDNAs covering the differentially spliced region in the *lin-3* mRNA were amplified with the primers OAD31 (5′-CCCTTCGTGGTTTCGTCAAGAACGTAGTGC-3′) and OAD32 (5′-CGTATCTGCAGAATCCAACTCGATATTAATTAC-3′) using first-strand cDNA synthesized from mixed-stage total RNA as template. The PCR-amplified products were size-fractionated by agarose gel electrophoresis, cloned into the pGEMT vector (Promega), and sequenced to identify clones encoding individual splice variants. To obtain full-length *lin-3* cDNA construct (pAD27), a 1,996-bp XhoI fragment from the EST clone yk1053b07 (confirmed to encode full-length *lin-3XL* cDNA by DNA sequencing) was first subcloned into the XhoI site of a modified pBluescriptSK (Stratagene, La Jolla, California, United States) vector (pAD23) in which the PstI site had been destroyed by restriction with EcoRV and SmaI and religation of the resulting blunt ends. To generate full-length *lin-3S* and *lin-3L* cDNA constructs (pAD25 and pAD26, respectively), 1,065-bp and 1,110-bp PstI fragments specific for each splice variant isolated from the partial cDNA clones described above were used to replace the 1,188-bp PstI fragment in the full-length *lin-3XL* cDNA construct (pAD27). The *lin-31::lin-3S* and *lin-31::lin-3L* constructs were generated by cloning the 1,133-bp and 1,178-bp XhoI cDNA fragments of the S and L splice variants into the SalI site of pB253 ([@pbio-0020334-Tan1]). The *lin-3* splice variant minigene constructs (pAH63, pAH64, and pAH65 for *lin-3S, lin-3L,* and *lin-3XL,* respectively) were generated by cloning a 6.1-kb genomic fragment spanning the entire ORF of *lin-3* and 574 bp of 5′ and 236 bp of 3′ sequences amplified with the primers OAH137 (5′-CCAGAAAGTTCATGTGAATCAT-3′) and OAH138 (5′-TCACAGGAACTGAGAGGGAGAGTG-3′) into the pGEMT vector. From this construct, a 6,206-bp ApaI-SacI fragment was subcloned into pAD23 to obtain pAH62. The minigenes encoding each of the splice variants were obtained by replacing the 2,728-bp *lin-3* genomic PstI fragment with 1,065-, 1,110-, and 1,188-bp PstI fragments isolated from cDNAs of the different splice variants. To construct the *lin-31::lin-3* hairpin plasmid (pAD35), a 964-bp NdeI-HindIII *lin-3S cDNA* fragment from pAD25 was cloned into NdeI-HindIII--digested pAD27 using the recA^--^ E. coli SURE strain as host to obtain pAD32. The resulting 1,918-bp *lin-3* hairpin fragment was excised with XhoI from pAD32 and subcloned in E. coli SURE into the SalI site of the pB253 vector to obtain pAD35.
### RNA interference {#s4a3}
The dsRNA to interfere with *rom-1* function was generated by in vitro transcription using a 350-bp *rom-1* cDNA fragment corresponding to the nucleotides --17 to 725 relative to the predicted start codon of the ORF inserted into pGEM-T (Stratagene) as template. Transcripts were prepared using T7 and Sp6 RNA polymerase and annealed prior to injection as described ([@pbio-0020334-Fire1]). Progeny of the injected animals were assayed at 20 °C. RNAi of *rom-2* and *rom-3* was done by feeding the animals dsRNA-producing E. coli at 20 °C as described ([@pbio-0020334-Kamath1]).
### Isolation of the *rom-1(zh18)* deletion allele {#s4a4}
The *rom-1(zh18)* deletion mutant was isolated from an ethyl methanesulfonate--mutagenized library consisting of approximately 10^6^ haploid genomes as previously described ([@pbio-0020334-Jansen1]; [@pbio-0020334-Berset1]). DNA pools were screened by nested PCR with primers Rho13 (5′-GAGACCGGGGACCGTATTCTGGCAC-3′) and Rho10 (5′-GAGAGCATAAACTCCTGCGGAAGCACC-3′) in a first PCR reaction, and Rho35 (5′-GGGAATCCGACGGTGGTAGAAGC-3′) and Rho10 (5′-GAGAGCATAAACTCCTGCGGAAGCACC-3′) in a second PCR reaction. The *zh18* deletion removes 1,556 bp including 384 bp of 5′ upstream sequences and 618 bp of the *rom-1* ORF (positions 4906804--4908360 in the cosmid F26F4). The mutant strain was backcrossed six times against N2 before further experiments were done.
### Vulval induction assay {#s4a5}
Vulval induction was scored by examining worms at the L4 stage under Nomarski optics as described ([@pbio-0020334-Sternberg3]). The number of VPCs that adopted a 1° or 2° vulval fate was counted for each animal as described ([@pbio-0020334-Sternberg3]), and the induction index was calculated by dividing the number of 1° or 2° induced cells by the number of animals scored. Statistical analysis was performed using a t-test for independent samples. To remove the AC, the nuclei of the Z1 to Z4 gonadal precursor cells were ablated in early L1 larvae with a laser microbeam as described ([@pbio-0020334-Sulston2]; [@pbio-0020334-Kimble1]). The operated animals were allowed to develop until the L4 stage. Only those animals in which neither gonad arm developed and no residual gonadal cells survived were scored.
Supporting Information {#s5}
======================
Accession Numbers {#s5a1}
-----------------
The GenBank (<http://www.ncbi.nlm.nih.gov/>) accession numbers of the Rhomboid genes discussed in this paper are C.e. ROM-1 (AAA91218), C.e. ROM-2 (CAA82377), C.e. ROM-3 (CAB55154), C.e. ROM-4 (CAB55122), C.e. ROM-5 (AAF60768), D.m. Rho-1 (CAA36692), D.m. Rho-2 (AAK06752), D.m. Rho-3 (AAK06753), D.m. Rho-4 (AAK06754), D.m. Rho-6 (NP\_523557), H.s. Rho-1 (CAA76629).
We wish to thank all the members of our group for fruitful discussion and input into this work. We are grateful to Ernst Hafen and Michael Hengartner for their critical comments on the manuscript, to Andy Fire for GFP vectors (including pPD 95.75 and pPD96.04), and to the C. elegans Genetics Center, Stuart Kim, Iva Greenwald, and Paul Sternberg for providing some of the strains used. The yk1053b07EST clone was a gift of Y. Kohara. The *rom-2* deletion mutant was kindly provided by the C. elegans Gene Knockout Consortium. This research was supported by the Swiss National Science Foundation and the Kanton of Zürich.
**Conflicts of interest.** The authors have declared that no conflicts of interest exist.
**Author contributions.** AD and AH conceived and designed the experiments. AD performed the experiments. AD and AH analyzed the data. SC and EFH contributed reagents/materials/analysis tools. AD and AH wrote the paper.
Academic Editor: Julie Ahringer, University of Cambridge
¤Current address: Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
Citation: Dutt A, Canevascini S, Froehli-Hoier E, Hajnal A (2004) EGF signal propagation during C. elegans vulval development mediated by ROM-1 rhomboid. PLoS Biol 2(11): e334.
AC
: anchor cell
ACEL
: AC-specific enhancer
ADAM
: a disintegrin and metalloprotease
EGF
: epidermal growth factor
EGFR
: EGF receptor
Egl
: egg-laying defective
GFP
: green fluorescent protein
hyp7
: hypodermal syncytium
L\[N\]
: larval stage \[N\]
MAPK
: mitogen-activated protein kinase
Muv
: multivulva
NLS
: nuclear localization signal
ORF
: open reading frame
1°
: primary
RNAi
: RNA interference
RTK
: receptor tyrosine kinase
2°
: secondary
3°
: tertiary
TGF
: transforming growth factor
VPC
: vulval precursor cell
Vul
: vulvaless
|
PubMed Central
|
2024-06-05T03:55:47.968887
|
2004-9-28
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519001/",
"journal": "PLoS Biol. 2004 Nov 28; 2(11):e334",
"authors": [
{
"first": "Amit",
"last": "Dutt"
},
{
"first": "Stefano",
"last": "Canevascini"
},
{
"first": "Erika",
"last": "Froehli-Hoier"
},
{
"first": "Alex",
"last": "Hajnal"
}
]
}
|
PMC519002
|
Introduction {#s1}
============
For over a hundred years, it has been recognized that chromatin is distributed non-randomly within the interphase nucleus ([@pbio-0020342-Rabl1]; [@pbio-0020342-Boveri1]). More recently, three-dimensional fluorescence microscopy studies have established that chromosomes are organized into distinct, evolutionarily conserved subnuclear territories (reviewed by [@pbio-0020342-Cockell1]; [@pbio-0020342-Isogai1]). However, DNA is mobile and can move between these domains (reviewed in [@pbio-0020342-Gasser1]). Recent studies suggest that the subnuclear localization of genes can have dramatic effects on their chromatin state, rate of recombination, and transcription ([@pbio-0020342-Cockell1]; [@pbio-0020342-Isogai1]; [@pbio-0020342-Bressan1]). Heterochromatin, for example, is generally found concentrated in close proximity to the nuclear envelope. Several genes conditionally colocalize with heterochromatin under conditions in which they are repressed. The transcriptional regulator Ikaros, for example, interacts both with regulatory sequences upstream of target genes and with repeats enriched at centromeric heterochromatin. When repressed, these genes become colocalized with heterochromatin, suggesting that Ikaros promotes repression by directly recruiting target genes into close proximity with heterochromatin ([@pbio-0020342-Brown2], [@pbio-0020342-Brown1]; [@pbio-0020342-Cobb1]). Consistent with this view, euchromatic sequences that become colocalized with heterochromatin are transcriptionally silenced ([@pbio-0020342-Csink1]; [@pbio-0020342-Dernburg1]).
In *Saccharomyces cerevisiae,* genes localized in proximity to telomeres are similarly transcriptionally silenced ([@pbio-0020342-Gottschling1]). Silencing is due to Rap1-dependent recruitment of Sir proteins to telomeres ([@pbio-0020342-Gotta1]), which promotes local histone deacetylation and changes in chromatin structure (reviewed in [@pbio-0020342-Rusche1]). Physical tethering of telomeres at the nuclear periphery through interactions with the nuclear pore is required for silencing ([@pbio-0020342-Gotta1]; [@pbio-0020342-Laroche1]; [@pbio-0020342-Galy1]; [@pbio-0020342-Feuerbach1]). When a reporter gene flanked by silencer motifs was relocated more than 200 kb away from a telomere, silencing was lost ([@pbio-0020342-Maillet1]). Silencing was restored to this gene by overexpression of *SIR* genes. Therefore it is thought that tethering serves to promote efficient recruitment of Sir proteins, which are enriched at the nuclear periphery and limiting elsewhere ([@pbio-0020342-Maillet1]). Another example of gene silencing at the nuclear periphery comes from experiments in which defects in the silencer of the *HMR* locus could be suppressed by artificially tethering this locus to the nuclear membrane ([@pbio-0020342-Andrulis1]). Thus, localization of chromatin to the nuclear periphery has been proposed to play a major role in transcriptional repression.
By contrast, we report here that dynamic recruitment of genes to the nuclear membrane can have profound effects on their activation. The gene under study here is *INO1,* a target gene of the unfolded protein response (UPR), which encodes inositol 1-phosphate synthase. The UPR is an intracellular signaling pathway that is activated by the accumulation of unfolded proteins in the endoplasmic reticulum (ER), which can be stimulated by treatment with drugs that block protein folding or modification or, in yeast, by starvation for inositol ([@pbio-0020342-Cox3]). These conditions activate Ire1, a transmembrane ER kinase/endoribonuclease ([@pbio-0020342-Cox2]; [@pbio-0020342-Mori1]), which, through its endonuclease activity, initiates nonconventional splicing of the mRNA encoding the transcription activator Hac1 ([@pbio-0020342-Cox1]; [@pbio-0020342-Shamu1]; [@pbio-0020342-Kawahara1]; [@pbio-0020342-Sidrauski1]). Only spliced *HAC1* mRNA is translated to produce the transcription factor; the Ire1-mediated splicing reaction, therefore, constitutes the key switch step in the UPR ([@pbio-0020342-Sidrauski2]; [@pbio-0020342-Ruegsegger1]).
Hac1 is a basic-leucine zipper transcription factor that binds directly to unfolded protein response elements (UPREs) in the promoters of most target genes to promote transcriptional activation ([@pbio-0020342-Cox1]; [@pbio-0020342-Travers1]; [@pbio-0020342-Patil1]). However, a subset of UPR target genes uses a different mode of activation. Transcriptional activation of these genes, including *INO1,* depends on Hac1 and Ire1. These target genes contain an upstream activating sequence that is regulated by the availability of inositol, the UAS[INO]{.smallcaps} element, in their promoters that is repressed by Opi1 under non-UPR conditions ([@pbio-0020342-Greenberg1]; [@pbio-0020342-Cox3]). Opi1 repression is relieved in a Hac1-dependent manner upon induction of the UPR ([@pbio-0020342-Cox3]). Positively acting transcription factors Ino2 and Ino4 then promote transcription from UAS[INO]{.smallcaps}-containing promoters ([@pbio-0020342-Loewy1]; [@pbio-0020342-Ambroziak1]; [@pbio-0020342-Schwank2]). Our previous work established that the production of Hac1 by UPR induction functions upstream of Opi1, suggesting that the role of the UPR is to counteract Opi1-mediated repression ([@pbio-0020342-Cox3]).
To understand the regulation of UAS[INO]{.smallcaps}-controlled genes by the UPR, we have examined the molecular events leading to the activation of *INO1*. We find that Scs2, an integral protein of the nuclear and ER membrane that was recently shown to play a role in telomeric silencing ([@pbio-0020342-Craven1]; [@pbio-0020342-Cuperus1]), is required to activate *INO1*. We observe dynamic *INO1* recruitment to the nuclear membrane under activating conditions. Importantly, we find that recruitment requires Hac1 and is opposed by Opi1. Furthermore, we show that artificial recruitment of *INO1* to the nuclear membrane can bypass the requirement for Scs2. Gene recruitment to the nuclear membrane therefore plays an instrumental role in *INO1* activation.
Results {#s2}
=======
Abundance and Localization of the Transcriptional Regulators Ino2, Ino4, and Opi1 Are Unaffected by UPR Induction {#s2a}
-----------------------------------------------------------------------------------------------------------------
To characterize the molecular basis of transcriptional activation of *INO1,* we first asked whether the steady-state levels of the known transcriptional regulators---the activators Ino2 and Ino4 and the repressor Opi1---were affected by induction of the UPR. To this end, we monitored the levels of *myc*-tagged proteins by Western blotting after UPR induction by inositol starvation ([Figure 1](#pbio-0020342-g001){ref-type="fig"}A). Induction of the UPR did not result in a significant change of the abundance of any of the proteins. Thus, in contrast to what has been suggested in previous studies ([@pbio-0020342-Ashburner1], [@pbio-0020342-Ashburner2]; [@pbio-0020342-Cox3]; [@pbio-0020342-Schwank1]; [@pbio-0020342-Wagner1]), *INO1* transcription is not regulated through adjustment of the abundance of these regulators.
::: {#pbio-0020342-g001 .fig}
Figure 1
::: {.caption}
###### Scs2 Regulates the Function of Opi1 on the Nuclear Membrane
\(A) Steady state protein levels and localization of Opi1, Ino2, and Ino4 under repressing and activating conditions. Strains expressing *myc*-tagged Opi1, Ino2, or Ino4 ([@pbio-0020342-Longtine1]) were grown in the presence (*INO1* repressing condition) or absence (*INO1* activating condition) of *myo*-inositol for 4.5 h. Tagged proteins were analyzed by Western blotting (size-fractionated blots on the left, designated Opi1, Ino2, and Ino4) and indirect immunofluorescence (photomicrographs on the right). For Western blot analysis, 25 μg of crude lysates were immunoblotted using monoclonal antibodies against either the *myc* epitope (top bands in each set) or, as a loading control, Pgk1 (bottom bands in each set; indicated with an asterisk). Immunofluorescence experiments were carried out using anti-*myc* antibodies and anti-mouse Alexafluor 488. Bright-field (BF) and indirect fluorescent (IF) images for a single z slice through the center of the cell were collected by confocal microscopy.
\(B) Ino2 and Ino4 heterodimerize under both repressing and activating conditions. Cells expressing either HA-tagged Ino4 (negative control) or HA-tagged Ino4 and *myc*-tagged Ino2 were grown in the presence or absence of 1 μg/ml tunicamycin (Tm; an inhibitor of protein glycosylation that induces protein misfolding in the ER) for 4.5 h and lysed. Proteins were immunoprecipitated using the anti-*myc* monoclonal antibody. Immunoprecipitates were size-fractionated by SDS-PAGE and immunoblotted using the anti-HA monoclonal antibody. (Continued on next page)
\(C) Coimmunoprecipitation of Scs2 with Opi1. Detergent-solubilized microsomal membranes from either an untagged control strain (lane C) or duplicate preparations from the Opi1-*myc* tagged strain (*myc* lanes, 1 and 2) were subjected to immunoprecipitation using monoclonal anti-*myc* agarose. Immunoprecipitated proteins were size-fractionated by SDS-PAGE and stained with colloidal blue. Opi1-*myc* and the band that was excised and identified by mass spectrometry as Scs2 are indicated. IgG heavy and light chain bands are indicated with an asterisk.
\(D) Coimmunoprecipitation with tagged proteins. Immunoprecipitation analysis was carried out on strains expressing either Scs2-HA alone (lanes 1--3) or Scs2-HA together with Opi1p-*myc* (lanes 4--6). Equal fractions of the total (T), supernatant (S), and bound (B) fractions were size-fractionated by SDS-PAGE and immunoblotted using anti-*myc* or anti-HA monoclonal antibodies.
\(E) Epistasis analysis. Haploid progeny from an *OPI1/opi1*Δ*SCS2/scs2*Δ double heterozygous diploid strain having the indicated genotypes were streaked onto minimal medium with (+ inositol) or without (-- inositol) 100 μg/ml *myo*-inositol and incubated for 2 d at 37 °C.
:::
:::
Next, we tested whether the subcellular localization of these regulators is modulated. We examined the localization of *myc*-tagged Opi1, Ino2, and Ino4 by indirect immunofluorescence ([Figure 1](#pbio-0020342-g001){ref-type="fig"}A). Again, we observed no significant change upon UPR induction: Ino2 and Ino4 localized to the nucleus under both repressing and activating conditions. Localization of Opi1 also showed no change. Like Ino2 and Ino4, Opi1 localized to the nucleus under both conditions. However, in agreement with recent data by [@pbio-0020342-Loewen1], we found that Opi1 was concentrated at the nuclear membrane and diffusely distributed throughout the nucleoplasm ([Figure 1](#pbio-0020342-g001){ref-type="fig"}A). Furthermore, coimmunoprecipitation experiments showed that Ino2 and Ino4 heterodimerize under both conditions, suggesting that this interaction is not regulated ([Figure 1](#pbio-0020342-g001){ref-type="fig"}B). Taken together, these observations therefore pose an interesting puzzle: How is regulation achieved when the localization and abundance of all three regulators is unchanged between activating and repressing conditions?
Opi1 Is Regulated by an Integral ER/Nuclear Membrane Protein {#s2b}
------------------------------------------------------------
To begin to explore a possible functional significance of Opi1\'s unusual localization pattern at the nuclear membrane, we sought to identify binding partners that might tether Opi1 to the membrane. To this end, we immunoprecipitated *myc*-tagged Opi1 under nondenaturing conditions from mildly detergent-solubilized microsomal membranes. Bands that were enriched in the immunoprecipitated fraction from the *myc*-tagged strain were identified by matrix-assisted laser desorption ionization mass spectrometry ([Figure 1](#pbio-0020342-g001){ref-type="fig"}C). This procedure identified Scs2, a bona fide integral membrane protein known to reside in nuclear membranes and ER ([@pbio-0020342-Nikawa1]; [@pbio-0020342-Kagiwada2]; [@pbio-0020342-Kagiwada1]). To confirm that Scs2 and Opi1 interact, we performed coimmunoprecipitation analysis from extracts of strains expressing *myc*-tagged Opi1 and hemagglutinin (HA)-tagged Scs2. We observed specific recovery of Scs2-HA in Opi1-*myc* immunoprecipitates ([Figure 1](#pbio-0020342-g001){ref-type="fig"}D). Recent results from a genome-wide immunoprecipitation study ([@pbio-0020342-Gavin1]) and in vitro peptide binding studies ([@pbio-0020342-Loewen1]) corroborate the interaction between Opi1 and Scs2.
In contrast to Opi1, the transcriptional repressor Scs2 has been implicated in the activation of *INO1* transcription: Overexpression of *SCS2* suppresses the Ino^--^ growth phenotype in cells that cannot activate the UPR ([@pbio-0020342-Nikawa1]), and loss of Scs2 impairs activation of *INO1* ([@pbio-0020342-Kagiwada2]; [@pbio-0020342-Kagiwada1]). Therefore, either Scs2 is the downstream target of Opi1-mediated repression, or Scs2 functions upstream to relieve Opi1-mediated repression. To distinguish between these possibilities, we analyzed the growth of the double mutant in the absence of inositol. As shown in [Figure 1](#pbio-0020342-g001){ref-type="fig"}E, *opi1*Δ cells grew in absence of inositol because *INO1* is constitutively expressed. In contrast, *scs2*Δ cells did not grow under these conditions. Double mutant *opi1*Δ *scs2*Δ cells grew in the absence of inositol, indicating that Scs2 functions to regulate Opi1 and is dispensable in the absence of Opi1. Given that Scs2 is an integral membrane protein, these data suggest that regulation of Opi1 occurs at the nuclear membrane.
Ino2 and Ino4 Bind to the *INO1* Promoter Constitutively {#s2c}
--------------------------------------------------------
Ino2 and Ino4 have been shown by gel-shift analysis of yeast extracts to bind directly to the UAS[INO]{.smallcaps} in the *INO1* promoter ([@pbio-0020342-Lopes1]; [@pbio-0020342-Ambroziak1]; [@pbio-0020342-Bachhawat1]; [@pbio-0020342-Schwank2]). Binding was observed in extracts from cells grown under repressing or activating conditions, and was increased in the absence of Opi1 ([@pbio-0020342-Wagner1]). To monitor the interaction of Ino2 and Ino4 with the *INO1* promoter in vivo, we used chromatin immunoprecipitation (ChIP) ([@pbio-0020342-Solomon1]; [@pbio-0020342-Dedon1]). Consistent with the gel-shift experiments, we found that Ino2-HA and Ino4-HA bound to the *INO1* promoter under both repressing and activating conditions ([Figure 2](#pbio-0020342-g002){ref-type="fig"}A). Real-time quantitative PCR analysis of immunoprecipitated DNA confirmed that both Ino2 and Ino4 associated with the *INO1* promoter constitutively ([Figure 2](#pbio-0020342-g002){ref-type="fig"}B). Although we observed an increase in the association of Ino2 with the *INO1* promoter under inducing conditions compared with repressing conditions, these results argue that occupancy of the promoter by Ino2/Ino4 is not sufficient for activation but that it must be a subsequent step in the activation process that is regulated by the UPR.
::: {#pbio-0020342-g002 .fig}
Figure 2
::: {.caption}
###### Ino2/Ino4 Bind to the *INO1* Promoter Constitutively
\(A) Untagged control cells (upper images), or cells in which the endogenous copies of *INO2* and *INO4* were replaced with HA-tagged Ino2 (center images) or HA-tagged Ino4 (lower images) were harvested in mid-logarithmic phase and washed into medium with or without *myo*-inositol. After 4.5 h, about 1.5 × 10^8^ cells were harvested and processed for Northern blot analysis (light images with dark bands, right). Northern blots were probed against both *INO1* and *ACT1* (loading control) mRNA. The remaining cells were fixed with formaldehyde and lysed. Chromatin was sheared by sonication and then subjected to immunoprecipitation with anti-HA agarose. Input DNA (In) and immunoprecipitated DNA (IP) were analyzed by PCR using primers to amplify the *INO1* promoter and the *URA3* gene. Amplified DNA was size-fractionated by electrophoresis on ethidium bromide-stained agarose gels (dark images with light bands, left).
\(B) Quantitative PCR analysis. Input and IP fractions were analyzed by real-time quantitative PCR. The ratio of *INO1* promoter to *URA3* template in the reaction is shown. Error bars represent the standard error of the mean (SEM) between experiments.
:::
:::
The molecular mechanism by which Opi1 represses transcription is not understood. In particular, it is not clear whether Opi1 binds to the *INO1* promoter directly. Early gel-shift experiments using yeast lysates suggested that Opi1 might interact with DNA ([@pbio-0020342-Lopes1]). However, this association has not been confirmed, and its significance is unknown. We used ChIP analysis and real-time quantitative PCR to assess the interaction of Opi1 with the *INO1* promoter in vivo. We observed specific enrichment of the *INO1* promoter by immunoprecipitation of Opi1 from cells grown in the presence of inositol (repressing condition) but no significant enrichment of the *INO1* promoter by immunoprecipitation of Opi1 from cells starved for inositol (activating condition; [Figure 3](#pbio-0020342-g003){ref-type="fig"}). By contrast, when we performed the immunoprecipitations from either *hac1*Δ or *scs2*Δ strains, we observed greater enrichment of the *INO1* promoter sequences from cells grown under both activating and repressing conditions. These results are consistent with the notion that Opi1 binds to chromatin at the *INO1* promoter and that the function of Hac1 and Scs2 is to promote Opi1 dissociation.
::: {#pbio-0020342-g003 .fig}
Figure 3
::: {.caption}
###### UPR-Dependent Dissociation of Opi1 from Chromatin
\(A) Chromatin-associated Opi1 dissociates upon activation of the UPR. Cells of the indicated genotypes were harvested after growth for 4.5 h with or without *myo*-inositol, fixed, and processed as in [Figure 2](#pbio-0020342-g002){ref-type="fig"}. The *scs2*Δ mutant was transformed with pRS315-Opi1-*myc*, a *CEN ARS* plasmid that expresses Opi1-*myc* at endogenous levels. Input DNA (In) and immunoprecipitated DNA (IP) were analyzed by PCR using primers to amplify the *INO1* promoter and the *URA3* gene. Amplified DNA was separated by electrophoresis on ethidium bromide--stained agarose gels.
\(B) Quantitative PCR analysis. Input and IP fractions were analyzed by real-time quantitative PCR. The ratio of *INO1* promoter to *URA3* template in the reaction is shown. Error bars represent the SEM between experiments.
:::
:::
In contrast to immunoprecipitation of Ino2 and Ino4, which specifically recovered the *INO1* promoter and not the control *URA3* sequences (see [Figure 2](#pbio-0020342-g002){ref-type="fig"}), immunoprecipitates of Opi1 recovered significant amounts of *URA3* sequences as well ([Figure 3](#pbio-0020342-g003){ref-type="fig"}A, upper bands). It is clear from the quantitative PCR analysis that Opi1 binding to the *INO1* promoter is specific ([Figure 3](#pbio-0020342-g003){ref-type="fig"}B). The different conditions used in the qualitative gel analysis (measuring PCR products after many cycles) and the quantitative PCR (measuring PCR products in the linear range of amplification) are likely to account for this difference.
The *INO1* Gene Relocalizes within the Nucleus upon UPR Activation {#s2d}
------------------------------------------------------------------
Since Opi1 dissociation from the *INO1* promoter correlates with activation and requires Hac1 and Scs2, an integral nuclear membrane protein, we wondered whether activation might occur at the nuclear periphery and thus might be dependent on the subnuclear positioning of the gene. Consistent with this hypothesis, we found that a form of Scs2 (Scs2ΔTMD) lacking the transmembrane domain, which was localized throughout the cell and was not excluded from the nucleus ([Figure 4](#pbio-0020342-g004){ref-type="fig"}A, compare cytosolic protein Rps2 to Scs2ΔTMD for colocalization with 4′,6′-diamidino-2-phenylindole), and was nonfunctional, rendering cells inositol auxotrophs, despite being expressed at levels comparable to full length Scs2 ([Figure 4](#pbio-0020342-g004){ref-type="fig"}B and [4](#pbio-0020342-g004){ref-type="fig"}C).
::: {#pbio-0020342-g004 .fig}
Figure 4
::: {.caption}
###### Membrane Association Is Essential for Scs2 Function
The carboxyl-terminal transmembrane domain of Scs2 was removed by replacement with three copies of the HA epitope (Scs2ΔTMD-HA; [@pbio-0020342-Longtine1]).
\(A) Scs2ΔTMD localization. Ribosomal protein S2 (Rps2-HA), Scs2-HA, and Scs2ΔTMD-HA were localized by immunofluorescence against the HA epitope. DNA was stained with 4′,6′-diamidino-2-phenylindole. Images were collected in a single z-plane (≤ 0.7 μm thick) by confocal microscopy. Unlike Rps2-HA, which was excluded from the nucleus (indicated with white arrows), Scs2ΔTMD-HA staining was uniform and evident in the nucleoplasm.
\(B) Scs2ΔTMD steady-state levels. Equal amounts of whole cell extract from cells expressing either Scs2-HA or Scs2ΔTMD-HA were analyzed by immunoblotting.
\(C) Scs2ΔTMD is nonfunctional. Strains expressing the indicated forms of Scs2 were streaked onto medium with or without *myo*-inositol and incubated for 2 d at 37 °C.
:::
:::
If *INO1* were regulated at the nuclear periphery, then the *INO1* locus should colocalize with the nuclear membrane under activating conditions. To test this idea, we constructed a strain in which an array of Lac operator (Lac O in [Figure 5](#pbio-0020342-g005){ref-type="fig"}) binding sites was integrated adjacent to the *INO1* locus ([@pbio-0020342-Robinett1]). The strain also expressed a green fluorescent protein (GFP)-Lac repressor fusion protein (GFP-Lac I in [Figures 5](#pbio-0020342-g005){ref-type="fig"} and [6](#pbio-0020342-g006){ref-type="fig"}) that binds to the Lac operator array to allow localization of the *INO1* gene. In a control strain, we integrated the same Lac operator array adjacent to the *URA3* locus. Cells were fixed and GFP was visualized by indirect immunofluorescence. Most cells showed a single intranuclear spot localizing the tagged gene; the remaining cells showed two spots due to their post-replication state in the cell cycle. In both the tagged *INO1* and the tagged *URA3* strains, we simultaneously visualized the ER and nuclear membrane by indirect immunofluorescence against Sec63-*myc* using a different fluorophore ([Figure 5](#pbio-0020342-g005){ref-type="fig"}A).
::: {#pbio-0020342-g005 .fig}
Figure 5
::: {.caption}
###### The *INO1* Gene Is Recruited to the Nuclear Membrane upon Activation
An array of Lac operator repeats was integrated at *INO1* or *URA3* in strains expressing GFP-Lac repressor and *myc*-tagged Sec63. GFP-Lac repressor and Sec63-*myc* were localized in fixed cells by indirect immunofluorescence. Data were collected from single z sections representing the maximal, most focused signal from the Lac repressor.
\(A) Two classes of subnuclear localization. Shown are five representative examples of localization patterns that were scored as membrane-associated (photomicrographs and plots on left) or nucleoplasmic (right). For each image, the fluorescence intensity was plotted for each channel along a line that intersects both the Lac repressor spot and the center of the nucleus.
\(B) *INO1* is recruited to the nuclear membrane upon activation. The fraction of cells that scored as membrane-associated is plotted for each strain grown in the presence (+) or absence (--) of inositol. The site of integration of the Lac operator (Lac O), the version of the GFP-Lac repressor (GFP-Lac I; either wild-type or having the FFAT membrane-targeting signal) expressed, and the relevant genotype of each strain is indicated. The dashed line represents the mean membrane association of the *URA3* gene. The vertical arrow indicates the frequency of membrane association in the wild-type strain under activating conditions. Error bars represent the SEM between separate experiments. Each experiment scored at least 30 cells. The total number of cells (and experiments) scored for each column were: bar 1, 70 (2); bar 2, 66 (2); bar 3, 39 (1); bar 4, 71 (2); bar 5, 140 (4); bar 6, 88 (2); bar 7, 88 (2); bar 8, 92 (3); bar 9, 74 (2); and bar 10, 38 (1).
:::
:::
::: {#pbio-0020342-g006 .fig}
Figure 6
::: {.caption}
###### Artificial Relocalization of *INO1* Bypasses the Requirement for Scs2
\(A) Northern blot analysis of membrane-targeted *INO1*. Strains of the indicated genotypes having the Lac operator array integrated at *INO1* and expressing either the wild-type GFP-Lac repressor or GFP-FFAT-Lac repressor were grown in the presence or absence of 1 μg/ml tunicamycin (Tm) for 4.5 h, harvested, and analyzed by Northern blot. Blots were probed for either *INO1* or *ACT1* (as a loading control) mRNA. The wild-type strain CRY1, lacking both the Lac operator array and the Lac repressor, was included in the first two lanes for comparison.
\(B) Wild-type or *scs2*Δ mutant strains in which the Lac operator had been integrated at *INO1* were transformed with either GFP-Lac repressor or GFP-FFAT-Lac repressor. The resulting transformants were serially diluted (tenfold between wells) and spotted onto medium lacking inositol, uracil, and histidine, and incubated for 2 d at 37 °C.
\(C) Wild-type and *scs2*Δ mutant strains transformed with either GFP-Lac repressor or GFP-FFAT-Lac repressor, but lacking the Lac operator, were streaked onto medium lacking inositol and histidine and incubated for 2 d at 37 °C.
:::
:::
To ask whether *INO1* associates with the nuclear membrane, we developed stringent criteria for scoring *INO1* localization ([Figure 5](#pbio-0020342-g005){ref-type="fig"}A). Using confocal microscopy, we collected a single z slice through each cell that captured the brightest, most focused point of the GFP-visualized Lac operator array. Images in which this slice traversed the nucleus (i.e., cells that showed a clear nuclear membrane ring staining with a \"hole\" of nucleoplasm), were binned into two groups: Cells in which the peak of the spot corresponding to the tagged gene coincided with nuclear membrane staining were scored as membrane-associated, and cells in which the peak of the spot corresponding to the tagged gene was offset from nuclear membrane staining were scored as nucleoplasmic. This procedure allowed us to determine the fraction of cells in a given population in which the tagged gene colocalized with the membrane, thus providing a quantitative measure for membrane association. Five examples of each group, with fluorescence intensity plotted along a line bisecting the nucleus and the spot, are shown in [Figure 5](#pbio-0020342-g005){ref-type="fig"}A.
To confirm that our scoring criterion would identify nuclear membrane association in a meaningful way, we applied it to two controls. As a control for membrane association, we localized *INO1* in a strain expressing GFP-Lac repressor fused to a peptide motif from Opi1 containing two phenylalanines in an acidic tract (FFAT motif), which serves as a nuclear membrane--targeting signal ([@pbio-0020342-Loewen1]). This motif was shown to bind to Scs2 and to be required for Opi1 targeting to the nuclear envelope ([@pbio-0020342-Loewen1]). Importantly, targeting of Opi1 to the nuclear membrane still occurred in the absence of Scs2 in an FFAT-dependent manner ([@pbio-0020342-Loewen1]), indicating that, in addition to Scs2, there must exist another, yet-unidentified receptor for FFAT in the nuclear membrane. As shown in [Figure 5](#pbio-0020342-g005){ref-type="fig"}B, the localization of *INO1* scored as 85% membrane-associated ([Figure 5](#pbio-0020342-g005){ref-type="fig"}B, bar 1), confirming both our scoring criteria and the previous result that FFAT indeed promotes nuclear membrane targeting.
As a control for random distribution, we localized *URA3* in a strain expressing GFP-Lac repressor without the FFAT targeting signal. *URA3* scored as 23% membrane-associated ([Figure 5](#pbio-0020342-g005){ref-type="fig"}B, bar 3). Induction of the UPR after depletion of inositol had no effect on the localization of either FFAT-tagged *INO1* or *URA3* in these strains ([Figure 5](#pbio-0020342-g005){ref-type="fig"}B, bars 2 and 4). Given that 25% of the volume of the nucleus is contained in the outer shell represented by only 10% of the radius, this level of background is consistent with a random distribution of the *URA3* gene throughout the nuclear volume. Based on the spatial resolution of our data ([Figure 5](#pbio-0020342-g005){ref-type="fig"}A), a spot only 10% of the radius distant from the membrane signal would have been scored as membrane-associated. We therefore defined the mean frequency of membrane-association of the *URA3* control between these two conditions (25% ± 3%) as the baseline for subsequent comparisons ([Figure 5](#pbio-0020342-g005){ref-type="fig"}B, dashed line).
We next compared the membrane association of *INO1* under repressing and activating conditions. Under repressing conditions, the membrane association of *INO1* was only slightly greater than the baseline (32% ± 3%; [Figure 5](#pbio-0020342-g005){ref-type="fig"}B, bar 5). In striking contrast, when *INO1* was activated, the frequency of membrane association of *INO1* increased significantly over baseline (52% ± 3%; [Figure 5](#pbio-0020342-g005){ref-type="fig"}B, bar 6). Thus, we conclude that, in a significant portion of cells, the *INO1* gene became associated with the nuclear membrane under UPR-inducing conditions.
To confirm that the observed recruitment was indeed due to UPR induction, we compared the membrane association of *INO1* under repressing or activating conditions in the *hac1*Δ mutant. Because Hac1 is required for activation of *INO1,* we predicted that membrane association would be prevented in this mutant. Indeed, *INO1* failed to become membrane associated in *hac1*Δ mutants starved for inositol ([Figure 5](#pbio-0020342-g005){ref-type="fig"}B, bars 7 and 8). Our earlier experiments suggested that Hac1 functions to promote dissociation of Opi1 from the *INO1* promoter. We therefore tested next whether the presence of Opi1 prevents membrane association. To this end, we determined *INO1* localization in the *opi1*Δ strain, in which *INO1* is constitutively transcribed ([@pbio-0020342-Cox3]). Indeed, we observed a high degree of membrane association, both in the presence and absence of inositol (68% ± 5%; [Figure 5](#pbio-0020342-g005){ref-type="fig"}B, bars 9 and 10).
Artificial Recruitment of *INO1* Suppresses the *scs2*Δ Ino^--^ Phenotype {#s2e}
-------------------------------------------------------------------------
The experiments described above indicate that there is a correlation between membrane association of *INO1* and its transcriptional activation. To establish causality, we examined the effect of artificially targeting *INO1* to the nuclear membrane. In an otherwise wild-type background, artificial targeting of *INO1* to the nuclear membrane via FFAT-Lac repressor binding (same strain as in [Figure 5](#pbio-0020342-g005){ref-type="fig"}B, bars 1 and 2) had no effect on *INO1* expression as assessed by Northern blot analysis ([Figure 6](#pbio-0020342-g006){ref-type="fig"}A) or on the growth of the wild-type strain in the absence of inositol ([Figure 6](#pbio-0020342-g006){ref-type="fig"}B; compare top two panels). This result suggests that membrane targeting per se is not sufficient to cause activation. In contrast, in the *scs2*Δ mutant we observed that the inositol-requiring growth phenotype of the strain was suppressed by expression of the membrane-targeted FFAT-Lac repressor ([Figure 6](#pbio-0020342-g006){ref-type="fig"}B; compare bottom two panels). This effect was strictly dependent on having the Lac operator array integrated at the *INO1* locus; expressing GFP-FFAT-Lac repressor in the absence of the array ([Figure 6](#pbio-0020342-g006){ref-type="fig"}C)---or if the array was integrated at the *URA3* locus (unpublished data)---did not improve the growth of the *scs2*Δ mutant in the absence of inositol. Consistent with the previous report that FFAT does not require Scs2 to promote nuclear membrane targeting, we observed approximately 50% membrane association of *INO1* in the strain expressing the FFAT-Lac repressor (78 cells counted, unpublished data). Thus, the defect in transcription of *INO1* in the *scs2*Δ mutant could be rescued, at least partially, through artificial targeting of *INO1* to the nuclear membrane. This result demonstrates that nuclear membrane association is functionally important for achieving *INO1* transcriptional activation.
Discussion {#s3}
==========
It is becoming increasingly clear that the spatial arrangement of chromosomes within the nucleus is important for controlling the reactions that occur on DNA and might be regulated (reviewed in [@pbio-0020342-Cockell1]; [@pbio-0020342-Isogai1]). Here we have shown that activation of *INO1* occurs at the nuclear membrane and requires the integral membrane protein Scs2. Moreover, artificial recruitment of *INO1* to the nuclear membrane permits activation in the absence of Scs2, indicating that the precise intranuclear localization of a gene can profoundly influence its activation. Most importantly, we have shown that the localization of *INO1* depends on its activation state; gene recruitment therefore is a dynamic process and appears to play an important regulatory role.
Regulation of Gene Localization {#s3a}
-------------------------------
The nucleoplasm is bounded by the inner nuclear membrane, which provides a template that is likely to play a major role in organizing the genome. It is clear from numerous microscopic and biochemical studies that chromatin interacts with nuclear membrane proteins, associated proteins such as filamentous lamins, and nuclear pore complexes (DuPraw, 1965; Murray and Davies, 1979; Paddy, 1990; Worman et al., 1990; Belmont et al., 1993; Glass et al., 1993; Foisner and Gerace, 1993; [@pbio-0020342-Sukegawa1]; Luderus et al., 1994; [@pbio-0020342-Dernburg1]). Indeed, several transcriptionally regulated genes have been shown to colocalize with heterochromatin at the nuclear periphery when repressed ([@pbio-0020342-Csink1]; [@pbio-0020342-Dernburg1]; [@pbio-0020342-Brown2], [@pbio-0020342-Brown1]). Likewise, silencing of genes near telomeres requires physical tethering of telomeres to nuclear pore complexes at the nuclear periphery ([@pbio-0020342-Gotta1]; [@pbio-0020342-Maillet1]; [@pbio-0020342-Andrulis1]; [@pbio-0020342-Laroche1]; [@pbio-0020342-Galy1]; [@pbio-0020342-Andrulis2]; [@pbio-0020342-Feuerbach1]).
Thus, the nuclear periphery has been generally regarded as a transcriptionally repressive environment ([@pbio-0020342-Gotta1]; [@pbio-0020342-Maillet1]; [@pbio-0020342-Andrulis1]; [@pbio-0020342-Laroche1]; [@pbio-0020342-Galy1]; [@pbio-0020342-Andrulis2]; [@pbio-0020342-Feuerbach1]). In contrast, the work presented here shows that gene recruitment to the nuclear periphery can be important for transcriptional activation. This conclusion is supported by a recent study published while this manuscript was in preparation ([@pbio-0020342-Casolari1]). These authors found that a subset of actively transcribed genes associates with components of nuclear pore complexes and that activation of *GAL* genes correlates with their recruitment from the nucleoplasm to the nuclear periphery and pore-complex protein association ([@pbio-0020342-Casolari1]). The results presented here argue that recruitment of genes to the nuclear periphery is controlled by transcriptional regulators and is important for achieving transcriptional activation. Thus, together, the work by [@pbio-0020342-Casolari1] and the work presented here demonstrate that gene recruitment to the nuclear periphery can have a general role in activating transcription.
This notion is consistent with the "gene gating hypothesis" put forward by [@pbio-0020342-Blobel1]. As proposed in this hypothesis, transcription of certain genes may be obligatorily coupled to mRNA export through a particular nuclear pore complex. It remains to be shown for *INO1,* however, whether gene recruitment to the nuclear periphery involves interaction with nuclear pore complex components. Several other scenarios could explain why *INO1* activation might require gene recruitment to the nuclear periphery. First, *INO1* transcriptional activation requires the SAGA histone acetylase, and both the SWI/SNF and INO80 chromatin remodeling complexes ([@pbio-0020342-Kodaki1]; [@pbio-0020342-Pollard1]; [@pbio-0020342-Ebbert1]; [@pbio-0020342-Shen1]; [@pbio-0020342-Dietz1]). Conversely, repression requires the Sin3/Rpd3 histone deacetylase and the ISW chromatin remodeling complex ([@pbio-0020342-Hudak1]; [@pbio-0020342-Sugiyama1]). Thus, if these factors have distinct subnuclear distributions, then the localization of genes regulated by them might influence their transcriptional state. Consistent with this notion, the SAGA complex interacts with nuclear pore complexes, and therefore might be concentrated at the nuclear periphery, where *INO1* activation occurs ([@pbio-0020342-Rodriguez-Navarro1]). Second, because *INO1* and many other UAS[INO]{.smallcaps}-regulated genes are involved in the biosynthesis of phospholipids, it is possible that the state of the membrane itself plays a role, perhaps sensed by Scs2, in activating transcription. It has been shown that defects in phospholipids biosynthesis can disrupt regulation of *INO1,* although the mechanism of this regulation remains unknown ([@pbio-0020342-Greenberg1]; [@pbio-0020342-McGraw1]; [@pbio-0020342-Griac2]; [@pbio-0020342-Griac1]; [@pbio-0020342-Shirra1]). Third, inositol polyphosphates have been shown to regulate SWI/SNF-catalyzed chromatin remodeling, and it is possible that their production is spatially restricted ([@pbio-0020342-Shen2]; [@pbio-0020342-Steger1]).
Role of Factors Regulating *INO1* Activation {#s3b}
--------------------------------------------
Our current understanding of *INO1* activation is summarized in a model in [Figure 7](#pbio-0020342-g007){ref-type="fig"}. The positive transcription activators Ino2 and Ino4 constitutively associate with the *INO1* promoter, which is kept transcriptionally repressed by Opi1. We do not currently understand the mechanism by which Opi1 prevents activation. Activation of the UPR leads to the production of Hac1, which, by an unknown mechanism, promotes Opi1 dissociation from chromatin. We propose that Scs2 at the nuclear membrane binds to Opi1 released from the DNA and thus keeps Opi1 sequestered and prevented from rebinding. Indeed, overproduction of Scs2 bypasses the requirement for Hac1 in activation of *INO1* transcription and allows *hac1*Δ cells to grow in the absence of inositol ([@pbio-0020342-Nikawa1]), supporting the role of Scs2 as a sink for Opi1 and suggesting that Opi1 may cycle between chromatin-bound and free states.
::: {#pbio-0020342-g007 .fig}
Figure 7
::: {.caption}
###### Model for *INO1* Gene Recruitment and Transcriptional Activation
Ino2 and Ino4 bind constitutively to the *INO1* promoter. Under repressing conditions, Opi1 associates with chromatin to prevent activation, and the *INO1* locus localizes to the nucleoplasm. Hac1 synthesis under UPR-inducing conditions promotes dissociation of Opi1 from chromatin. Scs2 binds to Opi1 at the nuclear membrane to stabilize the non-chromatin-bound state. Dissociation is coupled to recruitment of *INO1* to the nuclear membrane, where transcriptional activation occurs.
:::
:::
Both Hac1 ([@pbio-0020342-Cox3]) and Scs2 (see [Figure 1](#pbio-0020342-g001){ref-type="fig"}) are dispensable for *INO1* activation in the absence of Opi1, suggesting that their role is to relieve Opi1 repression. However, our data suggest that Hac1 and Scs2 have distinct functions: While the absence of either protein prevents the dissociation of Opi1 from chromatin and the activation of *INO1,* we propose that the role of Hac1 is to promote dissociation and that of Scs2 is to prevent reassociation. This model explains why artificially tethering *INO1* to the nuclear membrane suppresses the absence of Scs2 but not the absence of Hac1 (unpublished data): We propose that the environment of membrane-tethered *INO1* promotes late steps in the transcription activation---such as chromatin remodeling, discussed above---permitting *INO1* to be expressed upon transient Hac1-induced Opi1 dissociation. Therefore, we envision that dissociation of Opi1 from the *INO1* promoter is coupled to the delivery of the gene to an environment near the nuclear membrane that is permissive for its activation.
The mechanistic role of Scs2 is currently not known. Its recently discovered function in promoting telomeric silencing ([@pbio-0020342-Craven1]; [@pbio-0020342-Cuperus1]) suggests that Scs2 may play a more global role in the regulation of transcription at the nuclear membrane. Scs2 contains a major sperm protein domain, named after a homologous protein in Ascaris suum sperm that forms a cytoskeletal structure and confers motility to sperm cells. It is thus tempting to speculate that Scs2 might similarly self-associate in the plane of the nuclear membrane, perhaps providing a two-dimensional matrix on which membrane-associated reactions could be organized. One suggestion from our data is that Scs2 may function as a local sink for Opi1. But it is also clear that other nuclear membrane components are likely to participate in the reaction. Opi1, for example, still localizes to nuclear membranes even in *scs2*Δ cells, indicating that another, yet-unidentified Opi1 binding partner must exist ([@pbio-0020342-Loewen1]; unpublished data). Similarly, artificial *INO1* recruitment to the membrane via the FFAT motif suppresses the *scs2*Δ phenotype (see [Figure 6](#pbio-0020342-g006){ref-type="fig"})---i.e., it is sufficient to position *INO1* in an environment permissive for its induction---yet the FFAT binding protein and the molecular nature of the permissive environment remain unknown.
Upon inducing the UPR, only 52% of the cells scored *INO1* as membrane-associated (see [Figure 5](#pbio-0020342-g005){ref-type="fig"}). Thus, under activating conditions, two types of cells are present in the population at any one time: those in which the *INO1* gene is recruited to the membrane, and those in which the *INO1* gene is dispersed throughout the nucleoplasm. This score correlated with the level of *INO1* transcription; *INO1* was membrane-associated in 68% of the cells in the *opi1* mutant, which exhibits a correspondingly higher degree of activation than that observed in the wild-type strain. A quantitatively similar nuclear peripheral-nucleoplasmic distribution was observed upon activation of *GAL* genes ([@pbio-0020342-Casolari1]), suggesting that it may be a general feature of gene recruitment. There are at least two possible interpretations for the observed bimodal distributions. First, the distribution profiles might represent heterogeneity in the activation of *INO1* among cells. In this case, activation of *INO1* would be variable in individual cells exposed to identical conditions. Gene recruitment thus would stably trap *INO1* in a permissive environment for activation, and the localization of *INO1* would strictly correlate with its activation state. Alternatively, gene recruitment might alter the balance between two rapidly exchanging states; that is, stable membrane recruitment would not be required for activation. In this case, the observed distributions would represent snapshots of transient colocalization of *INO1* with the nuclear membrane within a population of cells that are uniformly activating transcription. Dynamic measurements of gene recruitment and single cell activity assays will need to be developed to distinguish between these possibilities. But no matter which of these possibilities proves to be correct, gene recruitment emerges as a new mechanism regulating eukaryotic gene expression and may be crucial to the regulation of many genes.
Materials and Methods {#s4}
=====================
{#s4a}
### Antibodies and reagents {#s4a1}
Monoclonal anti- HA antibody HA11 was obtained from Babco (Berkeley, California, United States). Monoclonal anti-*myc*, anti-*myc* agarose and anti-HA agarose were from Santa Cruz Biotechnology (Santa Cruz, California, United States). Monoclonal anti-Pgk1, rabbit polyclonal anti-GFP, goat anti mouse IgG-Alexafluor 594, and goat anti-rabbit IgG Alexafluor 488 were from Molecular Probes (Eugene, Oregon, United States).
All restriction endonucleases and DNA modification enzymes were from New England Biolabs (Beverly, Massachusetts, United States). Unless indicated otherwise, all other chemicals and reagents were from Sigma (St. Louis, Missouri, United States).
### Strains and plasmids {#s4a2}
All yeast strains used in this study were derived from wild-type strain CRY1 *(ade2--1 can1--100 his3--11,15 leu2--3,112 trp1--1 ura3--1 MAT*a*)*. Tags and disruptions marked with either the *kan^r^* gene from E. coli or the *His5* gene from S. pombe were introduced by recombination at the genomic loci as described ([@pbio-0020342-Longtine1]). Strains used in this study, with relevant differences indicated are JBY345 *(OPI1--13myc::kan^r^),* JBY350-r1 *(scs2*Δ*:: kan^r^),* JBY359 *(SCS2-HA:: kan^r^),* JBY356--1A *(opi1*Δ*::LEU2),* JBY356--1B *(opi1*Δ*::LEU2 scs2*Δ*:: kan^r^ ),* JBY356--1C *(scs2*Δ*:: kan^r^),* JBY356--1D (wild-type control), JBY361 *(scs2*Δ*TMD-HA:: kan^r^),* JBY370*(INO2-HA3::His5+),* JBY371 *(INO4-HA3::His5+),* JBY393 *(INO4-myc::His5+ MAT*a*),* JBY397 *(SEC63--13myc:: kan^r^ INO1:LacO128:URA3 HIS3:LacI-GFP),* JBY399 *(SEC63--13myc::Kan\^r INO1:LacO128:URA3 HIS3:LacI-FFAT-GFP),* JBY401 *(ino4*Δ*::LEU2 SEC63--13myc::Kan^r^ INO1:LacO128:URA3 HIS3:LacI-GFP MATα),* JBY404 *(opi1*Δ*::LEU2 SEC63--13myc::Kan^r^ INO1:LacO128:URA3 HIS3:LacI-GFP),* JBY406 *(opi1*Δ*::LEU2 SEC63--13myc::Kan^r^ INO1:LacO128:URA3 HIS3:LacI-FFAT-GFP),* JBY409 *(SEC63--13myc::Kan^r^ URA3:LacO128:URA3 HIS3:LacI-GFP),* JBY412 *(INO2-myc::His5+),* JBY 416 *(hac1*Δ*::URA3 SEC63--13myc::Kan^r^ LacO128:INO1 HIS3:LacI-GFP)*.
Plasmid pRS315-Opi1-*myc* was created by first amplifying the *OPI1-myc* coding sequence and 686 bp upstream from the translational start site from strain JBY345 using the following primers: OPI1 promoter Up (5′-GGGAGATACAAACCATGAAG-3′) and OPI1 down (5′-ACTATACCTGAGAAAGCAACCTGACCTACAGG-3′). The resulting fragment was cloned into pCR2.1 using the Invitrogen (Carlsbad, California, United States) TOPO TA cloning kit. The *OPI1-myc* locus was then cloned into pRS315 as a HindIII-NotI fragment. Plasmid pASF144 expressing *GFP-lacI* has been described ([@pbio-0020342-Straight1]). Plasmid pGFP-FFAT-LacI was constructed by digesting pASF144 with EcoRI and ligating the fragment to the following hybridized oligonucleotides, encoding the FFAT motif from *OPI1:* LacI\_FFAT1 (5′-AATTGGACGATGAGGAGTTTTTTGATGCCTCAGAGG-3′) and LacI\_FFAT2 (5′-AATTCCTCTGAGGCATCAAAAAACTCCTCATCGTCC-3′). The orientation of the insert was confirmed by DNA sequencing. Both pAFS144 and pGFP-FFAT-LacI were digested with NheI, which cuts within the *HIS3* gene, and transformed into yeast.
Plasmid p6INO1LacO128 was constructed as follows. The *INO1* coding sequence, with 437 bp upstream and 758 bp downstream, was amplified from yeast genomic DNA using the following primers: INO1\_promoter\_Up (5′-GATGAGGCCGGTGCC-3′) and INO1\_3′down (5′-AAGATTTCCTTCTTGGGCGC-3′), and cloned into pCR2.1 using the Invitrogen TOPO TA cloning kit, to produce pCR2.1-INO1. *INO1* was moved from pCR2.1 into pRS306 as a KpnI fragment, to produce pRS306-INO1. The Lac operator array was then cloned from pAFS52 into pRS306-INO1 as a HindIII-XhoI fragment, to produce plasmid 10.2. Because the Lac operator fragment was smaller than had been reported (2.5 kb instead of 10 kb), presumably reflecting loss of Lac operator repeats by recombination, the Lac operator array was duplicated by digesting plasmid 10.2 with HindIII and SalI and introducing a second copy of the 2.5-kb HindIII-XhoI fragment, as described ([@pbio-0020342-Robinett1]). The resulting plasmid, p6INO1LacO128, has a 5-kb Lac operator array, corresponding to approximately 128 repeats of the *lac* operator. To integrate this plasmid at *INO1,* p6INO1LacO128 was digested with BglII, which cuts within the *INO1* gene, and transformed into yeast.
The *INO1* gene was removed from this plasmid to generate p6LacO128. This plasmid was used to integrate the Lac operator array at *URA3* by digestion with StuI and transformation into yeast.
### Immunoprecipitations {#s4a3}
Cells were lysed using glass beads in IP buffer (50 mM Hepes-KOH pH 6.8, 150 mM potassium acetate, 2 mM magnesium acetate, and Complete Protease Inhibitors \[Roche, Indianapolis, Indiana, United States\]). The whole cell extract was used for coimmunoprecipitation of Ino2-*myc* and Ino4-HA. For immunoprecipitation of Opi1-*myc*, microsomes were pelleted by centrifugation for 10 min at 21,000 × *g* and resuspended in IP buffer. Triton X-100 was then added to either whole cell extract (Ino2-*myc*; final concentration of 1%) or the microsomal fraction (Opi1-*myc*; final concentration of 3%) and incubated for 30 min at 4 °C; detergent-insoluble material was then removed by centrifugation at 21,000 × *g*, 10 min. Anti-*myc* agarose was added to the supernatant and incubated 4 h at 4 °C, while rotating. For the experiment in [Figure 1](#pbio-0020342-g001){ref-type="fig"}D, a fraction of the total was collected after antibody incubation. After agarose beads were pelleted, an equal fraction of the supernatant was collected. Beads were washed either five (see [Figure 1](#pbio-0020342-g001){ref-type="fig"}B and [1](#pbio-0020342-g001){ref-type="fig"}D) or ten times (see [Figure 1](#pbio-0020342-g001){ref-type="fig"}C) with IP buffer. A fraction of the final wash equal to the pellet fraction in [Figure 1](#pbio-0020342-g001){ref-type="fig"}D was collected. After the final wash, proteins were eluted from the beads by heating in sample buffer and separating by SDS-PAGE (see [Figure 1](#pbio-0020342-g001){ref-type="fig"}B and [1](#pbio-0020342-g001){ref-type="fig"}D). Trypsin digestion, gel extraction, and mass spectrometry of proteins that coimmunoprecipitated with Opi1 were performed by the HHMI Mass Spectrometry facility (University of California, Berkeley, United States).
### Immunoblot and Northern blot analysis {#s4a4}
For immunoblot analysis, 25 μg of crude protein, prepared using urea denaturing lysis buffer ([@pbio-0020342-Ruegsegger1]), was separated on Invitrogen NuPage polyacrylamide gels, transferred to nitrocellulose, and immunoblotted. RNA preparation, electrophoresis, and labeling of probes for Northern blot analysis has been described ([@pbio-0020342-Ruegsegger1])**.**
### Immunofluorescence {#s4a5}
Immunofluorescence was carried out as described ([@pbio-0020342-Redding1]), except that cells were harvested and fixed by incubation in 100% methanol at --20 °C for 20 min. Fixed, spheroplasted, detergent-extracted cells were probed with 1:200 monoclonal anti-*myc* (see [Figures 1](#pbio-0020342-g001){ref-type="fig"} and [5](#pbio-0020342-g005){ref-type="fig"}), 1:200 monoclonal anti-HA (see [Figure 4](#pbio-0020342-g004){ref-type="fig"}), or 1:1000 rabbit polyclonal anti-GFP (see [Figure 5](#pbio-0020342-g005){ref-type="fig"}). Secondary antibodies were diluted 1:200. Vectashield mounting medium (Vector Laboratories, Burlingame, California, United States) was applied to cells before sealing slides and visualizing using a Leica TCS NT confocal microscope (Leica, Wetzlar, Germany). For experiments localizing the GFP-Lac repressor, we first collected a single z slice through each cell that captured the brightest, most focused point of the GFP-visualized Lac operator array. This z slice was picked blind with respect to the nuclear membrane staining. Images in which this slice showed a clear nuclear membrane ring staining with a \"hole\" of nucleoplasm were then scored as follows: Cells in which the peak of the GFP-Lac repressor spot coincided with Sec63-*myc* nuclear membrane staining were scored as membrane-associated, and cells in which the peak of this spot was offset from nuclear membrane staining were scored as nucleoplasmic.
### Chromatin immunoprecipitation {#s4a6}
Chromatin immunoprecipitation was carried out on strains expressing endogenous levels of tagged Ino2, Ino4, and Opi1 as described ([@pbio-0020342-Strahl-Bolsinger1]), with the following modifications. The time of formaldehyde fixation was specific for each tagged protein. Strains expressing Ino2-HA were fixed for 15 min, strains expressing Ino4-HA were fixed for 60 min, and strains expressing Opi1-*myc* were fixed for 30 min. After lysis, cells were sonicated 15 times for 10 s at 30% power using a microtip on a Vibracell VCX 600 Watt sonicator (Sonics and Materials, Newtown, Connecticut, United States). After sonication, lysates were centrifuged 10 min at 21,000 × *g* to remove insoluble material and incubated for 4 h with anti-HA agarose or anti-*myc* agarose. After elution of immunoprecipitated DNA and reversal of crosslinks by heating to 65 °C for 8 h, DNA was recovered using Qiaquick columns from Qiagen (Alameda, California, United States). Eluted samples were analyzed by PCR using the following primers against the *INO1* promoter or the *URA3* gene: INO1\_proUp2 (5′-GGAATCGAAAGTGTTGAATG-3′), INO1\_proDown (5′-CCCGACAACAGAACAAGCC-3′), URAup (5′- GGGAGACGCATTGGGTCAAC-3′), and URADown (5′-GTTCTTTGGAGTTCAATGCGTCC-3′).
### Real time quantitative PCR analysis {#s4a7}
PCR reactions were carried out as described ([@pbio-0020342-Rogatsky1]) using a DNA Engine Opiticon 2 Real-Time PCR machine (MJ Research, Waltham, Massachusetts, United States), using 1/25 of the immunoprecipitation fraction and an equal volume of a 1:400 dilution of the input fraction as template. Primers used were: INO1up3 5′-ATTGCCTTTTTCTTCGTTCC-3′), INO1down2 (5′-CATTCAACACTTTCGATTCC-3′), URAup2 (5′-AGACGCATTGGGTCAAC-3′), and URAdown2 (5′-CTTCCCTTTGCAAATAGTCC-3′). Dilution of the input fraction from 1:25 to 1:12,800 in fourfold steps demonstrated that reactions were within the linear range of template. This dilution series was used as a standard curve of C(T) values versus relative template concentration for both primer sets. The concentration of the *INO1* promoter and the *URA3* gene were calculated using this standard curve. The ratio of *INO1* promoter to *URA3* was corrected for each sample to make the input ratio equal to 1.0.
Supporting Information {#s5}
======================
Accession Numbers {#s5a1}
-----------------
The GenBank accession numbers of the genes and proteins discussed in this paper are Ire1 (NP\_116622), *INO1* (NP\_012382), Trl1 (NP\_012448), Opi1 (NP\_011843), Hac1 (NP\_011946), Ino2 (NP\_010408), Ino4 (NP\_014533), Scs2 (NP\_009461), Rap1 (NP\_014183), *URA3* (NP\_010893), *SSS1* (NP\_010371), Pgk1 (NP\_009938) *lacI* (NP\_414879), and Ikaros (Q03267).
The authors are very grateful to all the members of the Walter lab, in particular Gustavo Pesce, Tobias Walther, Jess Leber, and Tomas Aragon, for helpful discussions and inspiration; Isabella Halama for help with immunofluorescence; Hans Lueke for help with ChIP experiments and real time quantitative PCR; Doris Fortin for help with confocal microscopy; Joel Credle for technical assistance; John Sedat for providing the Lac operator and the GFP-Lac repressor plasmids; and Keith Yamamoto for helpful comments on the manuscript. This work was supported by a Helen Hay Whitney Postdoctoral Fellowship (JHB), by the Sandler Family Opportunity Fund, and by grants from the National Institutes of Health to PW. PW is an Investigator of the Howard Hughes Medical Institute.
**Conflicts of interest.** The authors have declared that no conflicts of interest exist.
**Author contributions.** JHB and PW conceived of the experiments. JHB performed the experiments. JHB and PW wrote the paper.
Academic Editor: Tom Misteli, National Cancer Institute
Citation: Brickner JH, Walter P (2004) Gene recruitment of the activated *INO1* locus to the nuclear membrane. PLoS Biol 2(11): e342.
ChIP
: chromatin immunoprecipitation
ER
: endoplasmic reticulum
FFAT
: ER/nuclear membrane targeting motif containing two phenylalanines in an acidic tract
GFP
: green fluorescent protein
HA
: hemagglutinin
SEM
: standard error of the mean
UAS[INO]{.smallcaps}
: upstream activating sequence responsive to inositol
UPR
: unfolded protein response
|
PubMed Central
|
2024-06-05T03:55:47.975329
|
2004-9-28
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519002/",
"journal": "PLoS Biol. 2004 Nov 28; 2(11):e342",
"authors": [
{
"first": "Jason H",
"last": "Brickner"
},
{
"first": "Peter",
"last": "Walter"
}
]
}
|
PMC519003
|
A developing organism captured on time-lapse video is a wonder to behold. If you\'re watching a chick embryo, by day 3, you\'ll see millions of cells engaged in a frenzy of activity, as rapidly dividing cells migrate to new positions, acquire the characteristics of specialized cells, and craft well-defined tissues, organs, and limbs in just under two weeks. In addition to the cells destined for specialization is another important group, stem cells, whose progeny have two very different fates. They can either "self renew"---that is, make identical copies of themselves---or generate intermediate progenitor cells that give rise to mature, differentiated cells.
Both differentiation and self renewal are guided by an elaborately regulated genetic program, which transforms embryonic stem cells into the many different cell types that make up the body. Adult stem cells share the hallmark trait of self renewal, but are relatively rare: in bone marrow, the source of hematopoietic, or blood-forming, only an estimated one in 10,000--15,000 cells is an adult hematopoietic stem cell (HSC).
Studies that have compared the gene expression profiles of different types of stem cells to identify genetic signatures of "stemness" have found only a limited number of signature genes. And the molecular mechanisms that regulate this so-called potency and the self renewal process have remained obscure. Now, focusing on HSCs, Margaret Goodell and colleagues have undertaken a systematic evaluation of HSC renewal. The study identifies molecular signatures associated with discrete stages of the HSC self renewal cycle and proposes a molecular model of the process.
HSC renewal passes through three stages: quiescence, activation and proliferation, and a return to the dormant state. HSCs give rise to both red blood cells, which carry oxygen and carbon dioxide, and white blood cells, which fight infection. Certain stressors---including blood-cell-inhibiting chemotherapy and bone marrow transplants---trigger HSC activation, which induces rapid proliferation, generating both progenitors to deal with the threat and new stem cells that return to quiescence. Once activated by a trigger, dormant HSCs engage a regulatory program that rapidly churns out billions of cells, then puts the brakes on cell division, prompting the return to a nondividing, quiescent state.
To understand the genetic programs underlying this process, Goodell and colleagues induced proliferation in HSCs (with the chemotherapeutic drug, 5-fluorouracil, or 5FU), then allowed the cells to return to quiescence, so they could characterize the changes in gene expression that occurred during each stage. They compared these time-specific patterns to the gene expression profiles of naturally proliferating fetal mouse HSCs (which undergo massive proliferation) and quiescent adult mouse HSCs (which hardly divide at all) to find genes associated with the two different states.
Genes were grouped into proliferating or quiescent groups based on when they were expressed after 5FU treatment, and these groupings were refined based on comparisons to previously published HSC gene expression data. Functional analysis of these genes found a bias toward genes involved in cell division processes in the proliferation stage and toward cell division inhibitors in the quiescent stage, supporting the logic of the groupings. To understand the activation process at a global level, the authors employed some novel analysis strategies, including the "Gene Ontology" (GO) system for classifying genes.
With these results, Goodell and colleagues constructed a model of the HSC self renewal cycle: quiescent HSCs maintain a "state of readiness," molecularly speaking, that allows a quick response to environmental triggers. A stressor (like the chemotherapy mentioned above) triggers a "prepare to proliferate" state---a kind of pregnant pause---and then the proliferation machinery kicks in, going through an early and late phase before quiescence returns. By shedding light on the molecular mechanisms of stem cell renewal, this study will aid efforts to develop stem-cell-based clinical therapies, which depend on replicating the HSC self renewal cycle to replenish diseased or damaged tissue, and will ultimately guide efforts to grow stem cell colonies outside the body, a long-standing goal that would have many clinical applications. The authors suggest their findings may also be relevant to studies of cancer stem cells, tumor cells with self renewal properties.
|
PubMed Central
|
2024-06-05T03:55:47.980161
|
2004-9-28
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519003/",
"journal": "PLoS Biol. 2004 Oct 28; 2(10):e349",
"authors": []
}
|
PMC519004
|
In this issue of *PLoS Biology,* [@pbio-0020354-Hebert2] have set out to test the resolution and performance of "DNA barcoding," using a single mtDNA gene, cytochrome *c* oxidase I (COI), for a sample of North American birds. Before turning to details of this study, it is useful as context to consider the following questions: What is DNA barcoding, and what does it promise? What is new about it? Why is it controversial? What are the potential pitfalls?
Put simply, the intent of DNA barcoding is to use large-scale screening of one or a few reference genes in order to (i) assign unknown individuals to species, and (ii) enhance discovery of new species ([@pbio-0020354-Hebert1]; [@pbio-0020354-Stoeckle1]). Proponents envisage development of a comprehensive database of sequences, preferably associated with voucher specimens representing described species, against which sequences from sampled individuals can be compared. Given the long history of use of molecular markers (e.g., allozymes, rDNA, and mtDNA) for these purposes ([@pbio-0020354-Avise2]), there is nothing fundamentally new in the DNA barcoding concept, except increased scale and proposed standardization. The former is inevitable. Standardization, i.e., the selection of one or more reference genes, is of proven value in the microbial community and in stimulating large-scale phylogenetic analyses, but whether "one gene fits all" is open to debate.
Why, then, all the fuss? Initial reactions to the DNA barcoding concept have ranged from unbridled enthusiasm, especially from ecologists ([@pbio-0020354-Janzen1]), to outright condemnation, largely from taxonomists (e.g., see the February 2003 issue of *Trends in Ecology and Evolution*). The former view reflects a real need to connect different life history stages and to increase the precision and efficiency of field studies involving diverse and difficult-to-identify taxa. The criticisms are mainly in response to the view that single-gene sequences should be the primary identifier for species ("DNA taxonomy"; [@pbio-0020354-Tautz1]; see also [@pbio-0020354-Blaxter1]). At least for the macrobiota, the DNA barcoding community has moved away from this to emphasize the importance of embedding any large-scale sequence database within the existing framework and practice of systematics, including the importance of voucher specimens and of integrating molecular with morphological characters. Another point of contention---that DNA barcodes have limited phylogenetic resolution---arises from confusion about the scope of inference. At best, single-gene assays can hope to identify an individual to species or reveal inconsistencies between molecular variation and current perceptions of species boundaries. DNA barcoding should not be confused with efforts to resolve the "tree of life." It should connect with and benefit from such projects, but resolving phylogeny at scales from species to major eukaryotic clades requires a very different strategy for selecting genes. Indeed, the very characteristic that makes the COI gene a candidate for high-throughput DNA barcoding---highly constrained amino acid sequence and thus broad applicability of primers ([@pbio-0020354-Hebert1])---also limits its information content at deeper phylogenetic levels (e.g., [@pbio-0020354-Russo1]; [@pbio-0020354-Zardoya1]; [@pbio-0020354-Naylor1]). Finally, while superficially appealing, the very term DNA barcoding is unfortunate, as it implies that each species has a fixed and invariant characteristic---like a barcode on a supermarket product. As evolutionary biologists, we should question this analogy.
In evaluating the promise and pitfalls of DNA barcoding, we need to separate the two areas of application: molecular diagnostics of individuals relative to described taxa, and DNA-led discovery of new species. Both are inherently phylogenetic and rely on a solid taxonomic foundation, including adequate sampling of variation within species and inclusion of all previously described extant species within a given genus. Accurate diagnosis depends on low intraspecific variation compared with that between species, such that a short DNA sequence will allow precise allocation of an individual to a described taxon. The extensive literature on mtDNA phylogeography ([@pbio-0020354-Avise1]) indicates that this condition often holds, although there are exceptions. Furthermore, within many species there is sufficient structure that it will be possible to allocate an individual to a particular geographic population. Such identifications should be accompanied by a statement of confidence---e.g., node support in a phylogenetic analysis and caveats in relation to the breath of sampling in the reference database (e.g., whale forensics; [@pbio-0020354-Palumbi1]).
DNA-led species discovery is more contentious, but again is not new. In animals, inclusion of mtDNA evidence in biogeographic and systematic analyses often reveals unexpected diversity or discordance with morphology, which then prompts re-evaluation of morphological and ecological characteristics and, if warranted, taxonomic revision. But, despite recent proposals ([@pbio-0020354-Wiens1]; [@pbio-0020354-Hebert2]), it does not follow that mtDNA divergence should be a primary criterion for recognizing species boundaries (see also [@pbio-0020354-Sites1]). Potential limitations of using mtDNA to infer species boundaries include retention of ancestral polymorphism, male-biased gene flow, selection on any mtDNA nucleotide (as the whole genome is one linkage group), introgression following hybridization, and paralogy resulting from transfer of mtDNA gene copies to the nucleus. These are acknowledged by [@pbio-0020354-Hebert2] and well documented in the literature ([@pbio-0020354-Bensasson1]; [@pbio-0020354-Ballard1]), including that on birds ([@pbio-0020354-Degnan1]; [@pbio-0020354-Quinn1]; [@pbio-0020354-Lovette1]; [@pbio-0020354-Weckstein1]). More specifically, using some level of mtDNA divergence as a yardstick for species boundaries ignores the low precision with which coalescence of mtDNA predicts phylogenetic divergence at nuclear genes ([@pbio-0020354-Hudson1]). An additional problem with focusing on mtDNA (or any other molecular) divergence as a primary criterion for recognizing species is that it will lead us to overlook new or rapidly diverged species, such as might arise through divergent selection or polyploidy, and thus to conclude that speciation requires long-term isolation. For example, a recent mtDNA analysis of North American birds ([@pbio-0020354-Johnson2]) showed that numerous avian species have low divergences and that speciation can occur relatively rapidly under certain circumstances. We contend, therefore, that whereas divergent or discordant mtDNA sequences might stimulate taxonomic reassessment based on nuclear genes as well as morphology, ecology, or behavior, mtDNA divergence is neither necessary nor sufficient as a criterion for delineating species. This view accords with existing practice: taxonomic splits in North American birds typically are based on multiple lines of biological evidence, e.g., morphological and vocal differences as well as genetic data ([@pbio-0020354-AOU1]).
We turn now to the core of Hebert et al.\'s paper---COI sequencing of a substantial sample of North American birds (260 of 667 species) and its validity as a test of the barcoding concept. Their aim is to test "the correspondence between species boundaries signaled by COI barcodes and those established by prior taxonomic research." North American birds are an interesting choice because their species-level taxonomy is relatively well resolved and there has been extensive previous analysis of levels of mtDNA sequence divergence within and among described species ([@pbio-0020354-Klicka1]; [@pbio-0020354-Avise3]; [@pbio-0020354-Johnson2]). [@pbio-0020354-Hebert2] found differences in COI sequences "between closely related species" that were 19--24 times greater in magnitude than the differences within species (7.05%--7.93% versus 0.27%--0.43%, respectively). From these data, they conclude that most North American bird species can be discriminated via molecular diagnosis of individuals and propose a "standard sequence threshold" of ten times the mean intraspecific variation (yielding a 2.7% threshold in birds) to flag genetically divergent taxa as "provisional species." Thus, their analysis seeks to address both potential applications of DNA barcoding.
Although Herbert et al. sampled a large number of species, a true test of the precision of mtDNA barcodes to assign individuals to species would include comparisons with sister species---the most closely related extant relatives. This would require that all members of a genus be examined, rather than a random sample of imprecisely defined close relatives, and that taxa be included from more than one geographic region. [@pbio-0020354-Johnson2] showed the importance of comparing sister species when examining genetic divergence values in North American birds, with results that contrast strongly with those of Hebert et al. as well as previous studies (e.g., [@pbio-0020354-Klicka1]). For 39 pairs of avian sister species, mtDNA sequence divergences ranged from 0.0% to 8.2%, with an average of 1.9% (cf. 7% to 8% among closely related species in Hebert et al.). Of these, 29 pairs (74%) are at or below the 2.7% threshold proposed by Herbert et al. and thus would not be recognized as species despite biological differences. Moreover, although only a few of these 39 pairs (see Table 1 in [@pbio-0020354-Johnson2]) had sufficient sampling to assess intraspecific variation in mtDNA sequences, these typically showed paraphyly in mtDNA haplotypes. Therefore, there are still too few cases with adequate sampling of intraspecific diversity for sister species pairs to know how common paraphyly is, although a recent meta-analysis found that 17% of bird species deviated from mtDNA monophyly ([@pbio-0020354-Funk1]). Collectively, these observations cast doubt on the precision of DNA barcoding for allocating individuals to previously described avian species.
Empidonax flycatchers, which are renowned for their morphological similarity and could thereby benefit from DNA-based identification tools, provide an example of the importance of a more detailed analysis. A complete molecular phylogeny for this group ([@pbio-0020354-Johnson1]) yielded distances between four pairs of sister species that ranged from 0.7% (E. difficilis versus E. occidentalis) to 4.6% (E. traillii versus E. alnorum); notably, the genetic distance between mainland and island populations of E. difficilis (E. d. difficilis and E. d. insulicola, 0.9%) was greater than that between sister species ([@pbio-0020354-Johnson1]). Herbert et al.\'s analysis included only two species of Empidonax (E. traillii and E. virescens), which are not sisters but members of divergent clades. Because E. virescens is genetically distant from all other species of Empidonax (10.3% to 12.5% uncorrected distance; [@pbio-0020354-Johnson1]), its comparison with E. trailli therefore inflates estimates of interspecific distances within the genus.
Another key point of Hebert et al.\'s analysis was to estimate levels of intraspecific diversity. For 130 species of the 260 examined, more than two individuals were sequenced (*n* = 2 to 12 individuals per species, mean = 2.4), and pooled pairwise genetic distances were found to be uncorrelated with geographic distances, leading Hebert et al. to conclude that "high levels of intraspecific divergence in COI in North American birds appear uncommon." However, this makes the assumption that there is a common underlying pattern of phylogeographic structure, which is unlikely for North American birds ([@pbio-0020354-Zink1], [@pbio-0020354-Zink2]). If there is significant variation, assessment of intraspecific diversity can be based on a small sample of individuals only if individuals are sampled across existing population subdivisions for which geography and phenotypic variation are reasonable initial surrogates.
The analyses presented by Hebert et al. will certainly stimulate further debate (a reply by Hebert et al. to the present letter is posted at <http://www.barcodinglife.com>), but, for the reasons outlined here, they are not yet a definitive test of the utility of DNA barcoding for either diagnosis of individuals or discovery of species. We also question whether the results for North American birds can be extrapolated to the tropics, where DNA barcoding could have maximum value. In general, among-population sequence divergence increases with decreasing latitude, even excluding previously glaciated regions ([@pbio-0020354-Martin1]), and studies of intraspecific genetic diversity in Neotropical birds have revealed a higher level of phylogeographic subdivision compared to temperate species ([@pbio-0020354-Remsen1], [@pbio-0020354-Lovette1]). Thus, the general utility of mtDNA barcoding across different biogeographic regions---and between resident versus migratory taxa---requires further scrutiny.
There is little doubt that large-scale and standardized sequencing, when integrated with existing taxonomic practice, can contribute significantly to the challenges of identifying individuals and increasing the rate of discovering biological diversity. But to determine when and where this approach is applicable, we now need to discover the boundary conditions. The real challenge lies with tropical taxa and those with limited dispersal and thus substantial phylogeographic structure. Such analyses need to be taxonomically broad and need to extend beyond the focal geographic region to ensure that potential sister taxa are evaluated and can be discriminated. There is also the need to examine groups with frequent (possibly cryptic) hybridization, recent radiations, and high rates of gene transfer from mtDNA to the nucleus. Only then will the skeptics be satisfied.
Academic Editor: Charles Godfray, Imperial College
Craig Moritz and Carla Cicero are at the Museum of Vertebrate Zoology, University of California, Berkeley, California, United States of America.
COI
: cytochrome *c* oxidase I
|
PubMed Central
|
2024-06-05T03:55:47.980731
|
2004-9-28
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519004/",
"journal": "PLoS Biol. 2004 Oct 28; 2(10):e354",
"authors": [
{
"first": "Craig",
"last": "Moritz"
},
{
"first": "Carla",
"last": "Cicero"
}
]
}
|
PMC519005
|
One hundred years before Darwin returned from his voyage on the *H. M. S. Beagle* "struck with certain facts" that "seemed to throw some light on the origin of species," Linnaeus published the first systematic taxonomy of life. In *Systema Naturae,* the Swedish botanist divided organisms into plants, animals, and minerals, eventually assigning scientific names to 7,700 plant and 4,400 animal species, and popularizing the binomial system---as in Homo sapiens---of naming species.
In the 1700s and 1800s, naturalists classified organisms based on morphology, devoting their careers to naming newfound plants and animals. Today biologists still use Linnaean taxonomy as the foundation of scientific classification. But with just a fraction of the estimated 5--30 million species on the planet already named and too few specialists to do the job, biologists are looking for high-throughput tools that can rapidly and accurately identify both individuals of a species and entirely new species. That\'s what some scientists say the DNA barcode will do. The DNA barcode, as the name implies, uses genes to identify species much like supermarket barcodes identify products. The idea is that a short stretch of genetic code from a reference gene is unique enough to one species to distinguish it from every other species, and that comparisons of sequence variations in that stretch of gene can reveal evolutionary relationships among species.
Such technology could radically advance biologists\' attempts to achieve the long-standing goal of cataloging life on earth, but the approach is controversial, with critics questioning both the method and its applications. (For more on the debate, see "DNA Barcoding: Promise and Pitfalls," also in this issue.) Paul Hebert and colleagues offer a proof of the utility of the DNA barcoding concept, using a 648-basepair region of a mitochondrial gene (cytochrome *c* oxidase I, or COI) in a study of 260 North American bird species.
Mitochondria---the cell\'s power generators---contain their own DNA, and mitochondrial DNA (mtDNA) evolves much faster than nuclear DNA. It evolves so quickly, in fact, that mtDNA sequence variation has been found not just between closely related, or sister, species but also within species. Still, the variation is much greater among than within species, which is why mtDNA divergences have become a tool for identifying species.
Hebert and colleagues tested the effectiveness of the mtDNA COI barcode by matching bird species flagged by the COI barcode against those already established by taxonomic methods. The litmus test for DNA barcoding is absence of COI sequence overlap between species. Beyond that, differences within species should be significantly fewer than those between species. And that\'s what the researchers found. All 260 species had unique COI barcodes, with differences between species for the most part much more frequent---on average, 18 times more common---than those within species. In the 130 species represented by two or more individuals, COI sequences were either identical or closest to other sequences within that species. For these 260 bird species (of the 667 bird species that breed in North America), the authors report, the COI barcodes "separate individuals into the categories that taxonomists call species."
The COI barcode, the authors propose, could help resolve problematic classifications based on morphology, as arise when populations of a single species acquire distinct characteristics after geographic barriers prevent their interbreeding. For example, the similar COI sequences found in American and black oystercatchers here support taxonomic studies suggesting that they are actually color morphs of one species. And conversely, highly divergent COI sequences might bolster taxonomic studies indicating that lineages of uncertain status are indeed distinct species.
Future studies will have to determine whether these results can be generalized to animals in other climes and ecosystems, but the authors argue that constructing a comprehensive library of barcodes will facilitate such efforts. Hebert and colleagues conclude that the success of DNA barcoding depends not only on such a repository---with sequences pegged to well-characterized species exemplars---but also on the expertise of trained taxonomists. The hope is that large-scale, standardized testing based on a uniform barcode sequence could go a long way toward finishing what Linnaeus started: a full classification of all plant and animal life. To E. O. Wilson, every species is "a masterpiece of evolution, offering a vast source of useful scientific knowledge because it is so thoroughly adapted to the environment in which it lives." Faced with what Wilson calls the "worst wave of extinction since the dinosaurs died," the need for a fast and easy way to identify species has never been greater.
|
PubMed Central
|
2024-06-05T03:55:47.982619
|
2004-9-28
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519005/",
"journal": "PLoS Biol. 2004 Oct 28; 2(10):e357",
"authors": []
}
|
PMC519006
|
Whether a person inherits a defective gene or acquires genetic damage by chance, two types of genes typically play a role in transforming a healthy cell into a cancer cell. Oncogenes and tumor suppressor genes are normally involved in cell growth, development, and cell differentiation. Both functions can be appropriated to ill effect by mutations. Single mutations in these genes rarely cause cancer on their own, but they predispose cells to additional insults that precipitate malignant transformation.
Susceptibility to cancer depends, among other things, on age. Though cancer in children is rare, the most common childhood cancers strike the hematopoietic system (leukemia), nervous system, and skeletal muscle system, while solid tumors of the lung, breast, prostate, and colon are more common in adults. This age differential suggests that an oncogene\'s ability to cause cancer in a particular cell type might depend on that cell\'s developmental stage. (A cell\'s gene expression profile differs with type and age; breast cells express different genes than liver cells, and immature cells express different genes than fully differentiated cells.) In a new study, Dean Felsher and colleagues show that age matters: activating oncogenes at different developmental time points in mouse liver cells produces different results.
Typically, once a cell is transformed, it stays in its "differentiative" state, that is, it stays in whatever developmental stage it was in when it became a tumor cell. But in a previous study, Felsher and colleagues found that turning off oncogenes in tumor cells allowed them to differentiate; these mature cells did not resume tumorigenesis after the oncogenes were reactivated. In this study, Felsher and colleagues show that the ability of the *MYC* oncogene to initiate liver cancer (hepatocellular carcinoma) in a transgenic mouse model varies with the age of the mouse.
::: {#pbio-0020375-g001 .fig}
::: {.caption}
###### Developmental consequences of MYC overexpression
:::
:::
To study the consequences of *MYC* overexpression in the liver cells of embryonic, neonatal, and adult mice, the authors used a biotech trick (called the Tet system) that controls gene expression dose and timing with a drug. The system relies on the interplay of two elements: a gene (in this case, *MYC*) fused to a regulatory enhancer, and a transcription factor that binds to the enhancer and activates the gene. Administering a tetracycline-like drug (in this case, doxycycline) prevents the transcriptional activation of the gene.
Overexpressing the *MYC* oncogene in mice during embryonic development or at birth occasioned their demise fairly quickly (ten days and eight weeks after birth, respectively). In contrast, overexpression of *MYC* in adult mice resulted in tumorigenesis only after a long latency period. When the authors evaluated the cellular effects of *MYC* overexpression, they found that hepatocytes from neonatal transgenic mice showed evidence of increased proliferation (replicated DNA content) compared to normal hepatocytes, while transgenic adult hepatocytes showed increased cell and nuclear growth (some nuclei had as many as twelve genome copies instead of two) without dividing. Since these adult cells eventually developed into tumors, some clearly acquired the ability to divide, which the authors show is facilitated, among other events, by the loss of the p53 tumor suppressor.
Altogether these results suggest that whether oncogene activation can support tumor growth depends on the age of the host, which in turn suggests the role of genetically distinct pathways in young and adult mice. The consequences of *MYC* activation, Felsher and colleagues conclude, depend on the cell\'s developmental program, which determines whether a cell can grow and divide, or simply grow. In adult hepatocytes---which are normally quiescent---*MYC* requires additional genetic events to induce cell division and tumorigenesis; in immature hepatocytes---which are already committed to a program of cellular proliferation---*MYC* activation alone is sufficient. The next step will be to identify the epigenetic developmental factors, both internal and external, that lead to tumor formation, and how to prevent it.
|
PubMed Central
|
2024-06-05T03:55:47.983376
|
2004-9-28
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519006/",
"journal": "PLoS Biol. 2004 Nov 28; 2(11):e375",
"authors": []
}
|
PMC519007
|
A fundamental question in developmental biology is, how does a multicellular organism develop from a single cell? It\'s clear that one cell begets two, two beget four, and so on, but how do the newly created cells know which developmental fate to pick? Major insights into this question have come from identifying genes, molecules, and intercellular signaling pathways involved in a wide range of developmental processes. Operating in labyrinthine, often overlapping pathways, intercellular signals determine whether a cell divides, differentiates, migrates, and even lives or dies.
Scientists prefer to work out such problems in organisms with a manageable number of cells for obvious reasons, making the 959-cell soil nematode Caenorhabditis elegans a popular developmental model. C. elegans can exist as either a male or a hermaphrodite, and for some biologists, the hermaphrodite vulva---which consists of just 22 cells---is the perfect system for working out key aspects of intercellular signaling and cell fate.
In a new study, Alex Hajnal and colleagues challenge conventional thinking about vulval cell specification by identifying an enzyme that can amplify a signal\'s range and help turn three non-vulval precursors into vulval cells. Surprisingly, the enzyme, called ROM-1, accomplishes this feat by acting in the signal-receiving vulval precursor cells, rather than in the signal-sending cell that instructs the vulval cell fates.
The worm vulva forms a bridge between its gonad and the opening to the outer epidermal layer, called the cuticle. In the current model of vulval formation, a group of twelve epidermal cells, called Pn.p cells, lines the ventral surface of the worm. Six of these cells, P3.p--P8.p, the vulval precursor cells (VPCs), have the potential to become vulval cells. During postembryonic development, the anchor cell in the larval gonad secretes an epidermal growth factor (called LIN-3) that activates the EGFR/RAS/MAPK signaling pathway and induces just three of the precursors to differentiate into vulval cells. The VPC closest to the anchor cell, P6.p receives most of the signal, and differentiates into eight vulval cells that form the tube linking the uterus to the gonad. Positioned on either side of P6.p, P5.p and P7.p receive a slightly attenuated signal, which, combined with a lateral signal from P6.p, gives rise to seven vulval cells that form vulval structures. The other three vulval precursors, P3.p, P4.p, and P8.p, it was thought, are too far away to receive the vulval induction signal and fuse into the surrounding epidermis.
::: {#pbio-0020376-g001 .fig}
::: {.caption}
###### Vulval precursor cells in C. elegans
:::
:::
The LIN-3 epidermal growth factors sit nestled within the cell membrane and must be "processed" to become active, prompting Hajnal and colleagues to look for candidate enzymes that could be doing the processing. They investigated the Rhomboid family of proteases, which are known activators of epidermal growth factor transmembrane proteins, and found one, ROM-1, with the amino acid profile required for catalytic protease activity. After showing that *rom* genes were not required for normal vulval development, the authors had a closer look at their role in vulval cell fate specification. Since loss of ROM-1 reduces the severity of a defect (in this case, multiple vulvas) caused by hyperactivation of the EGFR/RAS/MAPK pathway but has no effect on the precursors closest to the anchor cell, the authors conclude that ROM-1 enhances the EGFR/RAS/MAPK pathway, allowing it to reach the distant P3.p, P4.p, and P8.p precursors.
LIN-3 exists in two variant forms of different lengths, the longer one carrying a stretch of 15 extra amino acids in the region that is cleaved off to yield an active growth factor. Hajnal and colleagues show that ROM-1 only acts on the longer form to regulate the EGFR/RAS/MAPK pathway---and that the ROM-1/LIN-3 interaction occurs in the VPCs, independently of the anchor cell. They go on to propose a two-step model of vulval cell specification in which ROM-1 "extends the range" of the anchor signal, relaying it from the proximal to the more distant precursor cells by promoting the secretion of the long version of LIN-3. In normal development, LIN-3 secretion by the VPCs may serve initially to maintain the differentiation potential of all the precursors, while the anchor cell signal may seal their fates at a later phase.
|
PubMed Central
|
2024-06-05T03:55:47.984153
|
2004-9-28
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519007/",
"journal": "PLoS Biol. 2004 Nov 28; 2(11):e376",
"authors": []
}
|
PMC519008
|
Multicellular organisms contain a complete set of genes in nearly all of their cells, each cell harboring the potential to make nearly any protein in their genome. The same holds true for a single-celled bacterium or yeast. Yet a cell activates only a fraction of its genes at any given time, calling on a number of different mechanisms to activate the right genes at the right time. To metabolize sugar, for example, a cell needs to synthesize proteins involved in sugar metabolism, not protein repair, and vice versa. In a new study, Jason Brickner and Peter Walter report a mechanism for gene activation that depends on shuttling DNA to a particular location within the nucleus.
In organisms whose cells have nuclei (eukaryotes), genomes lie within the nucleus (called the nucleoplasm) but also interact with the inner nuclear membrane. Transcription factors activate gene expression by binding to a promoter sequence in the gene\'s DNA. The physical structure of DNA---which is packaged with proteins into chromatin---affects gene expression by controlling access to DNA. Where chromatin exists in the nucleus also influences gene expression. Heterochromatin---stretches of highly condensed chromatin---typically lines the nuclear periphery, and genes bundled into heterochromatin are typically silent. Active transcription generally occurs in the less condensed euchromatic regions. But since euchromatic regions are also silenced when they associate with heterochromatin along the membrane, it is thought that delivering chromatin to the nuclear periphery regulates transcriptional repression. Brickner and Walter, however, found evidence of the opposite effect---recruiting genes to the nuclear periphery can promote their activation---suggesting that nuclear membrane recruitment plays a much broader role than previously suspected in gene regulation.
::: {#pbio-0020381-g001 .fig}
::: {.caption}
###### The INO1 gene (green) is recruited to the nuclear membrane (red) upon activation
:::
:::
To explore the consequences of chromatin location, the authors focused on a yeast gene called *INO1,* which encodes inositol 1-phosphate synthase, an enzyme involved in phospholipid (fat) biosynthesis. *INO1* is also a target gene of the "unfolded protein response," which is triggered when unfolded proteins accumulate in the endoplasmic reticulum, a subcellular organelle where secreted proteins are folded. The *INO1* gene contains a regulatory element (called UASINO) within its promoter region that responds to inositol availability. Genes under the control of this element are transcriptionally repressed by a repressor, Opi1, and activated by two transcription factors, Ino2 and Ino4. The presence of unfolded proteins sets off a chain of events to relieve Opi1 repression and allow activation of *INO1*.
Through a series of genetic and biochemical studies, Bricker and Walter show that Ino2 and Ino4 are always bound to the *INO1* promoter. Opi1 associates with the chromatin, restricting the *INO1* locus to the nucleoplasm and repressing transcription. Induction of the unfolded protein response bumps Opi1 off the chromatin and, with Opi1 out of the way, *INO1* travels to the membrane and transcription proceeds. Crucially, the authors show that artificial recruitment of *INO1* to the nuclear membrane can be enough to activate the gene. There are several mechanistic aspects of this model to figure out still, but Brickner and Walter argue that for *INO1,* gene recruitment to the nuclear membrane promotes its activation. In light of other recent work, this phenomenon may be emerging as a more general mechanism for regulating eukaryotic gene expression.
|
PubMed Central
|
2024-06-05T03:55:47.984786
|
2004-9-28
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519008/",
"journal": "PLoS Biol. 2004 Nov 28; 2(11):e381",
"authors": []
}
|
PMC519021
|
Background
==========
The exponential growth of the lymphatic filariasis elimination program has highlighted the need for tools that can be used to monitor progress toward programmatic endpoints (e.g. when to stop mass treatment) as well as to conduct surveillance to detect any potential resumption of transmission. Measurement of microfilaremia, the recognized gold standard for demonstrating the impact of community-wide interventions, is not an optimal monitoring or surveillance tool because of the requirement for nocturnal blood collection in much of the world and because it is a relatively insensitive test for infection \[[@B1]\]. For *Wuchereria bancrofti*, assessment of antigenemia offers the convenience of daytime testing and greater sensitivity than testing for microfilaremia; however, both microfilaremia and antigenemia develop from months to years after exposure, reducing their utility for detection of low levels of infection or recrudescence of transmission \[[@B2]-[@B6]\]. Entomologic methods can be used to monitor filarial infection in mosquitoes and to provide point estimates of transmission intensity; however, as infection levels decline, it may become more difficult to collect sufficient numbers of mosquitoes to demonstrate with confidence that infection is absent \[[@B7]\]. By providing a cumulative measure of exposure to filarial infection, antibody assays may circumvent many of the limitations of methods based on direct detection of the parasite, its antigens or its DNA.
Antibody detection has served as the basis for diagnostic assays for filariasis for many decades. The best of these assays are sensitive for infection but are not specific, both because they cannot distinguish current infection from past infection or exposure to the parasite and because there is some degree of cross-reactivity with other helminth infections. On the positive side, prior studies have shown that virtually all residents of filariasis-endemic areas mount antifilarial antibody responses within the first few years of life. Thus, prevalence rates of antifilarial antibodies in children may be a useful index for assessing changes in transmission of the infection \[[@B8],[@B9]\].
Antibody assays based on crude filarial extracts are limited by cross-reactions with other nematode antigens \[[@B10]\]. Recombinant filarial antigens should, in principle, be more useful as the basis of diagnostic or exposure assays because of their greater specificity. As a first step in the development and validation of such assays, we conducted a multicenter evaluation of antibody-based diagnostic assays using 3 recombinant antigens, Bm14, WbSXP and BmR1.
Bm14 and WbSXP belong to a family of related genes that encode proteins that are strong immunogens in many parasitic nematode infections \[[@B11]\]. SXP and Bm14 were originally isolated from cDNA libraries based on their strong recognition by antibodies from microfilaremic persons, and both have been developed as candidates for diagnostic assays \[[@B12],[@B13]\]. Assays based on detection of IgG4 antibodies to Bm14 have sensitivities of 85--90% when serum specimens from microfilaremic persons are tested \[[@B14],[@B15]\]. This antigen is reported to be equally sensitive for sera from patients infected with *Brugia malayi*or *Wuchereria bancrofti*. Comparable results have been reported with assays for SXP \[[@B11],[@B16],[@B17]\]. BmR1 encodes a secreted antigen selected from a *B. malayi*cDNA library by antibody screening \[[@B18],[@B19]\]. ELISA and dipstick formats of BmR1 assays have been reported to have a sensitivity of \>90% when serum specimens from persons with *B. malayi*or *B. timori*microfilaremia were tested \[[@B18]-[@B22]\].
The present study was designed to compare objectively the performance of antibody assays for filariasis based on recombinant antigens Bm14, WbSXP, and BmR1. We report here the results of this multicenter evaluation.
Materials and Methods
=====================
Serum Specimens
---------------
Serum specimens from patients of known infection status (see Table [1](#T1){ref-type="table"}) were sent to the U.S. Centers for Disease Control and Prevention (CDC). For persons with filariasis, infection was diagnosed by detection of microfilariae. Each specimen was assigned a code number and aliquotted into 5 tubes (100 -- 200 μl per tube). A panel of coded serum samples was sent to each of the five participating laboratories along with antigens and assay kits for testing. Results were sent back to CDC for data analysis.
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Sensitivity and Specificity of Antibody Assays^1^
:::
Infection Bm14 ELISA Positive/Tested (%) SXP Cassette Positive/Tested (%) BmR1 ELISA Positive/Tested (%) BmR1 Dipstick Positive/Tested (%)
-------------------------------------------------------- -------------------------------- ---------------------------------- -------------------------------- -----------------------------------
W. bancrofti (n = 35)^2^ 32/35 (91%) 30/33 (2 NC) (91%) 14/31 (4 NC) (45%) 17/30 (5NC) (56.7%)
B. malayi (n = 28)^3^ 27/28 (96%) 7/18 (10 NC) (39%) 28/28 (100%) 27/27 (1NC) (100%)
O. volvulus (n = 20)^4^ 11/16 (4 NC) (69%) 9/15 (5 NC) (60%) 0/20 (0%) 1/20 (5%)
Loa (n = 10)^5^ 7/9 (1 NC) (78%) 3/7 (3 NC) (43%) 0/10 (0%) 0/9 (1 NC) (0%)
Other (incl. S*trongyloides, Echinococcus*; n = 20)^6^ 0/19 (1 NC) (0%) 0/19 (1 NC) (0%) 0/20 (0%) 0/20 (0%)
^1^Specimens were collected from persons with documented infections with the listed parasites; for patients with filarial infections, microfilariae were detected. Abbreviations: NC, no consensus; specimens with a no consensus result were not included in the denominators for calculations.
^2^Geographic source of specimens provided in Table 2.
^3^Geographic source of specimens provided in Table 2.
^4^Ten specimens were from Guatemala and 10 were from Ecuador.
^5^Specimens were collected from patients in Benin.
^6^*Echinococcus*specimens were collected in Kenya; *Strongyloides*specimens were from several settings where lymphatic filariasis was not endemic.
:::
Assay formats
-------------
The Bm14 and BmR1 tests included in the evaluation are based on the detection of antifilarial IgG4 antibodies. The Bm14 assays were performed according to procedures described by Weil et al. \[[@B15]\]. Three different assay formats were used to test for BmR1: an ELISA \[[@B18]\], a dipstick \[[@B20]\] and cassette. All were produced by Malaysian Bio-Diagnostics, Research, Sdn, Bhd. A rapid cassette test for IgG antibody to WbSXP was produced by Span Diagnostics, Ltd (Sachin, India). All participating labs followed assay instructions provided by the assay or kit supplier.
Analysis of Results
-------------------
Results of ELISA assays were determined using cut offs defined by the assay developer. For qualitative tests, each laboratory determined whether the appropriate band or spot was visible. To collate results for a given assay with a specific serum sample, a consensus result (either positive or negative) was defined on the basis of agreement among at least 4 of 5 labs. If only 3 of 5 labs obtained the same result or if 3 did and one of the two remaining laboratories did not obtain an interpretable result, this was considered to represent a lack of consensus (recorded as \'NC\' or no consensus in Tables [1](#T1){ref-type="table"} and [2](#T2){ref-type="table"}). Only two labs used the BmR1 cassette to test the specimens. Achieving consensus required two identical results for this test. Inter-laboratory agreement was assessed with Kappa coefficients, a measure of pair-wise agreement among observers making categorical judgments. For Bm14 and BmR1 ELISA, categorical assignments of positive or negative results were based on criteria established by the test developers.
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Regional Differences in Antigen Recognition
:::
Infection Location (serum source) Bm14 ELISA SXP Cassette BmR1 ELISA
----------------------------------- ------------ -------------- ------------
W. bancrofti
Cook Is. 10/10 9/9 (1 NC) 4/8 (2 NC)
PNG 9/10 9/9 (1 NC) 6/10
India 9/10 9/10 4/8 (2 NC)
Kenya 2/3 1/3 0/3
Haiti 2/2 2/2 0/2
B. malayi
Indonesia 10/10 0/5 (5 NC) 10/10
India 7/7 4/6 (1NC) 7/7
Malaysia 10/11 3/7 (4 NC) 11/11
:::
Results
=======
The Bm14 ELISA displayed comparable sensitivity for both *W. bancrofti*(91%) and Brugia (96%) infections, while the other two tests performed better with specimens from the homologous infections (Table [1](#T1){ref-type="table"}). For example, the BmR1 ELISA was positive for 100% of the samples from *Brugia*patients, but displayed only modest sensitivity (45%) in terms of its performance with *W. bancrofti*samples. Results were comparable for both the BmR1 dipstick and cassette (data not shown). Similarly, the WbSXP assay was positive for 30 of 33 (91%) serum specimens from *W. bancrofti*patients, but only 39% of *Brugia*cases.
BmR1 assays were remarkably specific for *Wuchereria*and *Brugia*infections, and there was little reactivity with specimens from persons with *O. volvulus*, *Loa loa*or other helminths (e.g. *Strongyloides*)*.*The Bm14 assay, and to a lesser extent, the WbSXP assay, appeared to function as a \'pan-filaria\' assay, showing reactivity with the specimens from persons with *W. bancrofti*, *B. malayi*, *L. loa*and *O. volvulus*. None of the assays demonstrated reactivity with specimens from persons with non-filarial helminth infections (Table [1](#T1){ref-type="table"}) or with hyper-IgE syndrome (data not shown).
When the geographic source of the serum specimens was considered, additional heterogeneity in responsiveness was noted. For example, although only a limited number of specimens were available for testing, 4 of 6 serum specimens from persons from India infected with *B. malayi*were positive using the WbSXP cassette; however, none of those from Indonesia were positive with this assay (Table [2](#T2){ref-type="table"}).
Inter-laboratory categorical agreement for the ELISA assays was quite good (Table [3](#T3){ref-type="table"}). Rapid format tests, though convenient, often presented problems of interpretation, independent of the test. Some labs reported the presence of weak bands or dots with control sera. This resulted in a significant number of \'no consensus\' results (Table [1](#T1){ref-type="table"}) as well as the lower kappa scores associated with the rapid tests (Table [3](#T3){ref-type="table"}).
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Inter-lab Agreement for the Different Diagnostic Tests
:::
Assay Range of Kappa statistics Mean
--------------- --------------------------- ------
Bm14 ELISA 0.690 -- 1.00 0.88
SXP Cassette 0.612 -- 0.912 0.73
BmR1 ELISA 0.878 -- 0.982 0.93
BmR1 Dipstick 0.817 -- 0.965 0.87
BmR1 Cassette 0.546 -- 1.00 0.80
Kappa statistics were derived from 10 pair-wise inter-lab comparisons.
:::
Discussion
==========
Assays based on Bm14, WbSXP, or BmR1 demonstrate adequate sensitivity for field use. The Bm14 assay appeared to function as a \'pan-filaria\' assay, demonstrating antibody reactivity in the sera from patients with *W. bancrofti*, *B. malayi*, *L. loa*and *O. volvulus*. Although this cross reactivity makes the Bm14 assays useful for monitoring either bancroftian or brugian filariasis, cross reactivity with *O. volvulus*and *L. loa*may limit its utility in some areas of sub-Saharan Africa. The BmR1 assays were sensitive for *B. malayi*infection but relatively insensitive for *W. bancrofti*infection. They showed excellent specificity for *Brugia*and *Wuchereria*, with little reactivity with sera from persons infected with other parasites, including *L. loa*and *O. volvulus*. These results suggest that it may be useful to study the *W. bancrofti*homologue of BmR1 to determine if it is as specific for *W. bancrofti*as BmR1 is for *Brugia*. Unfortunately, recent work suggests that this is not the case \[[@B23]\].
For mapping the distribution of lymphatic filariasis, rapid antibody tests may provide acceptable sensitivity, depending on the geographic area where the mapping is to be done, but the potential for problems with specificity (both in distinguishing past exposure from present infection as well as differentiating filarial from non-filarial infection) still remains. For mapping *W. bancrofti*, there is minimal value in using antibody tests instead of the antigen tests that are currently used, but because there is no antigen test for *Brugia*, antibody tests might be an alternative for mapping the distribution of these infections. In *Brugia*-endemic areas, it will be important to demonstrate, however, the relationship between prevalence rates for microfilaremia and antibodies to validate the assay as a useful tool for programmatic decisions. At this point, it is not clear what antibody prevalence should be considered an indication to initiate mass treatment; no attempt was made in this study to distinguish between antibody responses associated with active infection and those triggered by exposure \[[@B24],[@B25]\].
Antibody assays almost certainly will find other uses in the context of lymphatic filariasis (LF) elimination programs. For example, antifilarial antibody tests may be sensitive markers of transmission intensity or provide evidence of ongoing exposure to filarial infection long before the development of antigenemia or microfilaremia. Primates develop antibody responses to Bm14 within 4--8 weeks following *B. malayi*infection \[[@B26]\]. In a longitudinal study in Egypt, microfilaria-negative persons who were positive for Bm14 antibody at baseline were more likely to be microfilaria-positive after one year than were Bm14-negative persons \[[@B15]\]. Less is known about the kinetics of antibody responses to BmR1. Since antibody responses provide an early indicator of infection, assays for antifilarial antibodies should be useful for surveillance following initiation of LF elimination programs.
As LF programs reach their planned end point (5 or more years of \> 80% drug coverage in targeted populations), it will be necessary to determine whether or not transmission has been interrupted and whether mass drug administration can be stopped. Parasitologic testing, whether for microfilaremia or antigenemia, will require testing of thousands of persons to demonstrate that infection levels are below 0.1%, the level established by the Global Program as the end point for defining the elimination of LF. Since antibody responses develop in the absence of demonstrable infection, detecting incident antibody responses should provide a more sensitive measure of transmission than microfilaria or antigen detection. Children born following the cessation of transmission should be antibody-negative, while older children and adults may have evidence of residual antibody reactivity \[[@B8],[@B9],[@B27]\]. A testing strategy based on screening of children could be exploited for ongoing surveillance in the aftermath of LF programs and may not require screening of as many children as called for by current testing guidelines. The absence of antibody in appropriately chosen populations would strongly suggest that transmission has been interrupted. Additional studies are needed to test the value of antibody testing as a tool for certifying the elimination of filariasis transmission.
Operational use of antibody assays requires far more practical experience with the assays than we now have. Of greatest concern is the specificity of the tests employed. For example, ELISA tests often use a statistical approach to establish cutoff values for positive results. A test that is 99% specific will predictably have some false positive results if large numbers of samples are tested. Further work will be needed to establish rates of antibody positivity that exceed the number that are likely to occur by chance. In addition, it will be necessary to develop and validate algorithms for confirming the presence of infection or ongoing transmission in situations where low antibody prevalence rates are detected. Despite these caveats, we believe that antibody tests based on antigens like Bm14, BmR1, and Wb-SXP will prove to be useful tools that can be used to facilitate decision making by program managers in the context of filariasis elimination programs.
Competing Interests
===================
GW, RN, and PK have relationships with companies interested in developing commercial applications of the Bm14, BmR1 and WbSXP assays, respectively.
Authors\' Contributions
=======================
GW, RN, PK, and VBL were responsible for the initial development of the assays. All of the authors participated in the planning of this multicenter study. DG was responsible for coordinating specimen shipment and database management. Participating labs included PL and DG from CDC, RN from the Universiti Sains Malaysia, PK and VBL from Anna Center for Biotechnology, CS from NIH and GW from Washington University School of Medicine. PL and EO were responsible for coordinating the study. PL wrote the first draft of the manuscript, but all of the authors participated in the editing of subsequent versions.
Acknowledgments
===============
We thank Drs Amy Klion, Tania Supali, Chris King and R.K. Shenoy for providing serum specimens for testing Jacquelin M. Roberts for assistance with statistical analysis, and all of the participants in the Denver meeting for their valuable support. Funding for the BmR1 tests was provided by European Commission grant No: ICA4-CT-2001-10081 and Malaysian Bio-Diagnostic Research Sdn. Bhd.
|
PubMed Central
|
2024-06-05T03:55:47.985621
|
2004-9-3
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519021/",
"journal": "Filaria J. 2004 Sep 3; 3:9",
"authors": [
{
"first": "Patrick J",
"last": "Lammie"
},
{
"first": "Gary",
"last": "Weil"
},
{
"first": "Rahmah",
"last": "Noordin"
},
{
"first": "Perumal",
"last": "Kaliraj"
},
{
"first": "Cathy",
"last": "Steel"
},
{
"first": "David",
"last": "Goodman"
},
{
"first": "Vijaya B",
"last": "Lakshmikanthan"
},
{
"first": "Eric",
"last": "Ottesen"
}
]
}
|
PMC519022
|
Background
==========
Garlic (*Allium sativum*) has been cultivated since ancient times and used as a spice and condiment for many centuries \[[@B1]\]. During the past years, there has been a growing awareness of the potential medicinal uses of garlic \[[@B2]-[@B5]\]. The antioxidant properties of garlic are well documented \[[@B6]-[@B8]\]. In particular, aqueous garlic extract \[[@B9]\] and aged garlic extract \[[@B10]-[@B12]\] are able to prevent Cu^2+^-induced low density lipoprotein (LDL) oxidation. In addition, Ide *et al*. \[[@B10]\] and Ho *et al*. \[[@B13]\] have shown that some garlic compounds such as S-allylcysteine, N-acetyl-S-allylcysteine, S-allylmercaptocysteine, alliin, and allixin, are also able to prevent Cu^2+^-induced LDL oxidation. Ou *et al*. \[[@B14]\] showed that the garlic compounds S-ethylcysteine, N-acetylcysteine, diallyl sulfide, and diallyl disulfide inhibit amphotericin- and Cu^2+^-induced LDL oxidation. Huang *et al*. \[[@B15]\] showed that diallyl sulfide, diallyl disulfide, S-allylcysteine, S-ethylcysteine, S-methylcysteine, and S-propylcysteine are able to prevent glucose-induced lipid oxidation in isolated LDL. The protective effect of aged garlic extract \[[@B10],[@B11]\] and S-ethylcysteine, N-acetylcysteine, diallyl sulfide, and diallyl disulfide \[[@B14]\] on Cu^2+^-induced LDL oxidation may be explained, at least in part, for their ability to chelate Cu^2+^. Interestingly, the diethyl ether extract of aged garlic extract, which also inhibits Cu^2+^-induced LDL oxidation, is unable to chelate Cu^2+^\[[@B11]\] indicating that its ability to prevent LDL oxidation is unrelated to Cu^2+^-chelation.
On the other hand, 95% of the sulfur in intact garlic cloves is found in two classes of compounds in similar abundance: the S-alkylcysteine sulfoxides and the γ-glutamyl-S-alkylcysteines \[[@B16]\]. The most abundant sulfur compound in garlic is alliin (S-allylcysteine sulfoxide), which is present at 10 mg/g fresh garlic or 30 mg/g dry weight \[[@B16]\]. When garlic cloves are cut, crushed, or chopped (or when the powder of dried cloves becomes wet in a non-acid solution), the cysteine sulfoxides, which are odorless, are very rapidly converted to a new class of compounds, the thiosulfinates which are responsible for the odor of freshly chopped garlic. The formation of thiosulfinates takes place when the cysteine sulfoxides, which are located only in the clove mesophyll storage cells, come in contact with the enzyme allinase or alliin lyase (E.C. 4.4.1.4), which is located only in the vascular bundle sheath cells. Allinase is active at pH 4--5.8, but is immediately inhibited at acidic pH values below 3.5 or by cooking. Furthermore, microwave heating destroys allinase activity in 1 min \[[@B17]\]. Due to the abundance of alliin, the main thiosulfinate formed upon crushing garlic is allicin \[[@B16]\]. The half-life of allicin at room temperature is 2--16 hours; however, in crushed garlic (or in garlic juice) it is 2.4 days \[[@B16]\].
Several studies have been performed to test the effect of heating on several garlic properties. It has been shown that the boiling of garlic cloves by 15 min impairs significantly its ability to inhibit cyclooxygenase activity \[[@B18]\] and thromboxane B~2~synthesis \[[@B19]\]. In addition, heating of garlic cloves by 60 seconds in microwave reduces its anticancer properties \[[@B17]\]. Interestingly when microwave heating was applied 10 minutes after garlic crushing the anticancer properties were preserved indicating that allinase activation is necessary to generate anticancer compounds which are heat stable \[[@B17]\]. In a similar way, the hydroxyl scavenging properties of garlic were essentially preserved when garlic extracts were heated at 100°C by 20, 40 or 60 min \[[@B20]\]. In contrast, heating of garlic extracts by 10 min at 100°C reduced the bactericidal activity against *Helicobacter pylori*\[[@B21]\] and the ability to inhibit platelet aggregation \[[@B22]\]. However, to our knowledge, there are no studies exploring if the heating of garlic cloves or aqueous extract of raw garlic or garlic powder are able to inhibit Cu^2+^-induced lipoprotein oxidation in human serum. In the present paper we studied if the ability of aqueous garlic extracts to inhibit *in vitro*Cu^2+^-induced lipoprotein oxidation in human serum is altered in the following aqueous preparations: (a) heated extract of garlic powder, (b) heated extract of raw garlic, (c) extract of boiled garlic cloves, (d) extract of microwave-treated garlic cloves, and (e) extract of pickled garlic. In addition it was studied if the above mentioned preparations are able to chelate Cu^2+^.
It was found that (a) the heating of garlic extracts or garlic cloves had no influence on the ability of garlic extracts to prevent *in vitro*Cu^2+^-induced lipoprotein oxidation in human serum, and (b) this protective effect was unrelated to Cu^2+^-chelation.
Methods
=======
Materials and reagents
----------------------
Bulbs of garlic were from a local market. Garlic powder was from McCormick (Mexico City, Mexico). Copper sulfate, Na~2~EDTA, Na~2~CO~3~, KH~2~PO~4~, and Na~2~HPO~4~were from JT Baker (Mexico City, Mexico). Copper sulfate was dissolved in distilled water. Xanthine oxidase, xanthine, and nitroblue tetrazolium (NBT) were from Sigma Chemical Co. (St. Louis, MO., USA).
Preparation of aqueous extracts of garlic
-----------------------------------------
### Extract of garlic powder (GP)
Garlic powder was weighted (0.6 g), dissolved, and stirred with 6 mL of distilled water for 20 min. This solution was centrifuged at 20,124 × g for 5 min at 4°C. The supernatant was recovered and used at the final concentration of 0.05, 0.075, 0.10, and 0.25 mg/mL.
### Heated extract of garlic powder (HGP)
The procedure was similar to the previous one except that the mixture was boiled for 20 min before the centrifugation. The supernatant was recovered and used at the final concentration of 0.05 and 0.10 mg/mL.
### Extract of raw garlic (RG)
Garlic cloves were peeled off, weighted, chopped, and homogenized with distilled water in a Polytron (Model PT2000, Brinkmann, Switzerland). This homogenate was centrifuged at 1,277 × g for 10 min and the supernatant was centrifuged at 20,124 × g for 5 min at 4°C. The supernatant was recovered and used at the final concentration of 0.125, 0.25, 0.5, and 0.75 mg/mL.
### Heated extract of raw garlic (HRG)
The procedure was similar to the previous one except that the homogenate was boiled for 20 min before the second centrifugation step. The amount of water evaporated was replaced at the end of the heating. The supernatant was recovered and used at the final concentration of 0.25 and 0.5 mg/mL.
### Extract of boiled garlic (BG)
Unpeeled garlic cloves were boiled in water for 10 min. After this time, garlic cloves were peeled off and the aqueous extract was prepared as described before (extract of raw garlic). The supernatant was recovered and used at the final concentration of 0.25 and 0.5 mg/mL.
### Extract of garlic cloves submitted to microwave heating (MG)
Unpeeled garlic cloves were submitted to microwave heating for 1 min (1100 watts). After this time, garlic cloves were peeled off and the aqueous extract was prepared as described before (extract of raw garlic). When allinase is inactivated by heating, the cascade of thiosulfinate formation is blocked from alliin, and allicin and its derivates can not be formed. It has been shown that as little as 60 seconds of microwave heating can totally destroy allinase enzyme activity whereas microwave heating for 30 seconds inhibits 90% of allinase activity compared with unheated garlic \[[@B17]\]. The supernatant was recovered and used at the final concentration of 0.25 and 0.5 mg/mL.
### Preparation of pickled garlic (PG)
Garlic cloves were peeled off carefully to avoid allinase activation and put in an aqueous solution of vinegar (1:1, v/v) and then heated to the boiling point for 30 min. Garlic cloves were put into jars with same solution and then pasteurized for 5 min at 72°C. The jars were closed immediately and stored at 4°C. The experiments with pickled garlic were performed five weeks after. The aqueous extract was prepared as described before (extract of raw garlic). The supernatant was recovered and used at the final concentration of 0.25 and 0.5 mg/mL.
### Blood collection
Blood samples were obtained from 2 male and 3 female healthy volunteers aged 24 to 46 years. The experimental protocol is in compliance with the Helsinki Declaration and written informed consent was obtained from all subjects. A fasting blood sample was drawn from the antecubital fossa vein into glass tubes, allowed to clot, and then centrifuged at 2,000 × g for 10 min. The serum removed was aliquoted and frozen at -80°C until assayed. The concentration of glucose, cholesterol and triglycerides in serum was measured by an autoanalyzer (Hitachi 917 Automatic Analyzer, Boheringer Mannheim Corporation, Indianapolis, IN, USA).
### Cu^2+^-induced lipoprotein oxidation in human serum
A modification of the serum oxidation method described by Regnstrom *et al*. \[[@B23]\] was used. This method provides an indication of conjugated dienes formation in lipoprotein fatty acids present in serum exposed to Cu^2+^, assessed by measuring changes in absorbance at 234 nm. The formation of conjugated dienes in lipoprotein deficient serum exposed to Cu^2+^is absent, indicating that diene formation in lipoprotein fatty acids is primarily responsible for the increase in absorbance \[[@B23]\]. The oxidation curves have three phases: lag, propagation, and decomposition. This method has been used previously by others \[[@B24]-[@B28]\]. Serum was diluted to a final concentration of 0.67% in 20 mM phosphate buffer, pH 7.4 and saturated with O~2~. Oxidation was initiated by the addition of CuSO~4~to a final concentration of 0.0125 mM. The formation of conjugated dienes was followed by monitoring the change in absorbance at 234 nm at 37°C on a Beckman DU-64 spectrophotometer equipped with a six position automatic sample changer (Fullerton, CA, USA). Absorbance readings were taken every 10 min over 240 min. The aqueous garlic extracts were added at the indicated concentrations (ranging from 0.05 to 0.75 mg/mL). Control tubes consisted of identical assays conditions but without the garlic extract. Since the transition from lag phase to propagation phase was continuous, lag time was defined as the intercept of the tangents of the propagation and lag phases and expressed in minutes.
### Determination of Cu^2+^chelation of garlic extracts
The Cu^2+^chelating properties of aqueous garlic extracts were assessed using an approach based upon restoring the activity of xanthine oxidase described previously \[[@B11]\]. This enzyme is inhibited in the presence of 0.050 mM CuSO~4~\[[@B29]\]. The activity of xanthine oxidase can be assessed by monitoring either the production of superoxide anion or the formation of uric acid. Xanthine oxidase activity would be restored if garlic extracts were able to chelate Cu^2+^.
Xanthine oxidase activity was measured by NBT reduction and uric acid production. The following concentrated solutions were prepared in distilled water: xanthine oxidase 168 U/L, xanthine 0.30 mM, NBT 0.15 mM, and Na~2~CO~3~0.4 M. Superoxide anions were generated in a reaction volume of 1 mL containing in a final concentration: xanthine 0.087 mM, Na~2~CO~3~15 mM, NBT 0.022 mM, and 50 mM phosphate buffer pH 7.4 or garlic extract in a volume of 0.1 mL for control or experimental tube, respectively. In additional tubes with or without garlic extract, CuSO~4~was added in a final concentration of 0.050 mM. The reaction was initiated by the addition of 0.025 U of xanthine oxidase, and superoxide anion production was monitored at 560 nm. In the same experiment, xanthine oxidase activity was measured by following the uric acid production at 295 nm \[[@B30]\]. Absorbance at 560 and 295 nm was obtained every minute for 3 minutes and the results were expressed as change of absorbance/min. The garlic extracts were added at the higher concentration used in the experiments for Cu^2+^-induced lipoprotein oxidation along with (+CuSO~4~) or without (-CuSO~4~) 0.050 mM CuSO~4~. Control tubes contained all the reagents but without garlic extracts and they considered as 100% production of uric acid and superoxide anion. In a separate tube with 0.050 mM CuSO~4~, 0.060 mM EDTA was added as an additional control in which was expected the restoration of xanthine oxidase since EDTA is a metal-chelating agent.
Statistics
----------
Data are expressed as mean ± SEM of five determinations using different serum samples. The variables used to describe the difference between the oxidation curves were lag time, area under the oxidation curve (AUC), and slope of the propagation phase. These parameters were obtained using the GraphPad Prism software v. 3.02 (San Diego, CA, USA). All parameters were compared using either one way analyses of variance followed by Bonferroni\'s t test or Kruskall-Wallis analysis of variance followed by Dunn\'s test. p \< 0.05 was considered significant.
Results
=======
Glucose, cholesterol, and triglycerides in human serum
------------------------------------------------------
The concentration, in mmol/L, of glucose, cholesterol, and triglycerides in serum, of the subjects involved in this study was 4.56 ± 0.15, 4.24 ± 0.42, and 1.05 ± 0.11, respectively. These data show that the human beings from whom the blood serum samples were obtained for this study had no alterations in the circulating levels of glucose, cholesterol, and triglycerides.
Effect of garlic extracts on Cu^2+^-induced lipoprotein oxidation in human serum
--------------------------------------------------------------------------------
Unheated garlic extracts from raw garlic or from garlic powder inhibited lipoprotein oxidation in a dose-dependent way. Figure [1](#F1){ref-type="fig"} shows a representative graph obtained from a single subject. Panel A shows the effect of increasing concentrations of garlic powder extract (0.05 to 0.25 mg/mL) and panel B shows the effect of increasing concentrations of raw garlic extract (0.125 to 0.75 mg/mL) on Cu^2+^-induced lipoprotein oxidation in human serum. The increasing concentrations of garlic extracts displaced the curve to the right, compared to the control curve obtained without garlic extract, indicating that the inhibition of Cu^2+^-induced lipoprotein oxidation is dose-dependent. Lag time, AUC, and slope were obtained from these oxidation curves. Figure [2](#F2){ref-type="fig"} shows the lag time (panels A and C) and AUC (panels B and D) and Table [1](#T1){ref-type="table"} shows the slopes of the propagation phase from the five subjects studied. Panels A and B show the effect of garlic powder extract and panels C and D show the effect of raw garlic extract. It can be seen that garlic extracts dose-dependently increased lag time and decreased AUC and slopes. Based on these curves the concentrations of all the extracts studied were chosen: 0.25 and 0.5 mg/mL for HRG, BG, MG, and PG; and 0.05 and 0.1 mg/mL for GP and HGP.
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Representative curves showing the effect of aqueous garlic extracts on Cu^2+^-induced lipoprotein oxidation in human serum. Panel A shows the effect of garlic powder extract and panel B shows the effect of raw garlic extract. Cu^2+^-induced oxidation was followed at 234 nm. Readings were taken every 10 min. Oxidation was started by the addition of CuSO~4~at a final concentration of 0.0125 mM in 20 mM phosphate buffer, pH 7.4 saturated with O~2~and the readings were followed by 240 min at 37°C.
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Dose-dependent effect of aqueous garlic extracts on lag time and AUC. Panels A and B shows the effect of garlic powder extract and panels C and D shows the effect of raw garlic extract. Lag time is shown in panels A and C and AUC is shown on panels B and D. ^a^p \< 0.01 (panel A) and p \< 0.001 (panels B, C, and D) vs. 0 mg/mL. Data are mean ± SEM of five determinations using independent samples.
:::
:::
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Effect of extract of garlic powder (GP) and raw garlic (RG) on the slopes of oxidation curves.
:::
GP, \[mg/mL\] 0 0.05 0.075 0.1 0.25
--------------- ----------------- ----------------- ----------------- -------------------- ---------------------
slope 0.0025 ± 0.0002 0.0017 ± 0.0003 0.0014 ± 0.0002 0.0009 ± 0.0003 0.0003 ± 0.00003^a^
RG, \[mg/mL\] 0 0.125 0.25 0.5 0.75
slope 0.0027 ± 0.0002 0.0018 ± 0.0002 0.0022 ± 0.0002 0.0017 ± 0.0002^b^ 0.0007 ± 0.0003^a^
Data are mean ± SEM of five determinations using independent samples. ^a^p \< 0.001, ^b^p \< 0.05 vs. 0 mg/mL.
:::
Effect of different treatments of garlic on Cu^2+^-induced lipoprotein oxidation in human serum
-----------------------------------------------------------------------------------------------
The effect of HGP, HRG, BG, MG, and PG on the lag time and AUC is shown on Figs. [3](#F3){ref-type="fig"},[4](#F4){ref-type="fig"},[5](#F5){ref-type="fig"},[6](#F6){ref-type="fig"},[7](#F7){ref-type="fig"} respectively. The effects of these extracts on the slopes of oxidation curves are shown in Tables [2](#T2){ref-type="table"} and [3](#T3){ref-type="table"}. GP and HGP were studied at 0.05 and 0.1 mg/mL and HRG, BG, MG, and PG were studied at 0.25 and 0.5 mg/mL. The data of HGP and HRG were compared with those of unheated extracts, GP and RG, respectively (Figs. [3](#F3){ref-type="fig"} and [4](#F4){ref-type="fig"} and Tables [2](#T2){ref-type="table"} and [3](#T3){ref-type="table"}). The data of BG, MG, and PG were compared with those of RG (Figs. [5](#F5){ref-type="fig"},[6](#F6){ref-type="fig"},[7](#F7){ref-type="fig"} and Table [3](#T3){ref-type="table"}). It can be seen that the extracts increased lag time and decreased AUC at both concentrations studied indicating that they inhibit Cu^2+^-induced lipoprotein oxidation. The decrease in the slope was significant only at the higher concentration for GP and HGP (Table [2](#T2){ref-type="table"}) and for RG and HRG, BG, and MG (Table [3](#T3){ref-type="table"}). The decrease in the slope in PG was not significant (Table [3](#T3){ref-type="table"}). Interestingly, the treatments (heating of extracts of garlic powder or raw garlic or heating garlic cloves by boiling, microwave or pickling) had no significative effect on lag time, AUC, and slope. All the comparisons between unheated and heated extracts were not different. Our data show that the antioxidant ability of garlic on Cu^2+^-induced lipoprotein oxidation in human serum is not significantly affected by the above mentioned treatments.
::: {#F3 .fig}
Figure 3
::: {.caption}
######
Effect of heated extract of garlic powder (HGP) on lag time and AUC. Aqueous extract of garlic powder was heated at 100°C by 10 min. Aqueous extracts of unheated (GP) and HGP were added to the system at two concentrations (0.25 and 0.5 mg/mL). Cu^2+^-induced oxidation was followed at 234 nm. Readings were taken every 10 min. Oxidation was started by the addition of Cu^2+^at a final concentration of 0.0125 mM in 20 mM phosphate buffer, pH 7.4 saturated with O~2~and the readings were followed by 240 min at 37°C. ^a^p \< 0.001, ^b^p \< 0.01, and ^c^p \< 0.05 vs. 0 mg/mL. Δ= HGP. Data are mean ± SEM of five determinations using independent samples.
:::
:::
::: {#F4 .fig}
Figure 4
::: {.caption}
######
Effect of heated extract of raw garlic (HRG) on lag time and AUC. Aqueous extract of raw garlic was heated at 100°C by 10 min. Aqueous extracts of unheated (RG) or HRG were added to the system at two concentrations (0.25 and 0.5 mg/mL). Cu^2+^-induced oxidation was followed at 234 nm. Readings were taken every 10 min. Oxidation was started by the addition of Cu^2+^at a final concentration of 0.0125 mM in 20 mM phosphate buffer, pH 7.4 saturated with O~2~and the readings were followed by 240 min at 37°C. ^a^p \< 0.05 vs. 0 mg/mL. Δ= HRG. Data are mean ± SEM of five determinations using independent samples.
:::
:::
::: {#F5 .fig}
Figure 5
::: {.caption}
######
Effect of aqueous extract of boiled garlic (BG) cloves on lag time and AUC. Comparison was made with aqueous extract of raw garlic (RG). Aqueous extracts of BG and RG were added to the system at two concentrations (0.25 and 0.5 mg/mL). Cu^2+^-induced oxidation was followed at 234 nm. Readings were taken every 10 min. Oxidation was started by the addition of Cu^2+^at a final concentration of 0.0125 mM in 20 mM phosphate buffer, pH 7.4 saturated with O~2~and the readings were followed by 240 min at 37°C. ^a^p \< 0.001, ^b^p \< 0.01, and ^c^p \< 0.05 vs. 0 mg/mL. Δ= BG cloves. Data are mean ± SEM of five determinations using independent samples.
:::
:::
::: {#F6 .fig}
Figure 6
::: {.caption}
######
Effect of aqueous extract of garlic cloves submitted to microwave heating (MG) on lag time and AUC. Comparison was made with aqueous extract of raw garlic (RG). Aqueous extracts of microwave-treated garlic cloves (MG) and RG were added to the system at two concentrations (0.25 and 0.5 mg/mL). Cu^2+^-induced oxidation was followed at 234 nm. Readings were taken every 10 min. Oxidation was started by the addition of Cu^2+^at a final concentration of 0.0125 mM in 20 mM phosphate buffer, pH 7.4 saturated with O~2~and the readings were followed by 240 min at 37°C. ^a^p \< 0.001 and ^b^p \< 0.01 vs. 0 mg/mL. Δ= MG. Data are mean ± SEM of five determinations using independent samples.
:::
:::
::: {#F7 .fig}
Figure 7
::: {.caption}
######
Effect of aqueous extract of pickled garlic (PG) on lag time and AUC. Comparison was made with aqueous extract of raw garlic (RG). Aqueous extracts of PG and RG were added to the system at two concentrations (0.25 and 0.5 mg/mL). Cu^2+^-induced oxidation was followed at 234 nm. Readings were taken every 10 min. Oxidation was started by the addition of Cu^2+^at a final concentration of 0.0125 mM in 20 mM phosphate buffer, pH 7.4 saturated with O~2~and the readings were followed by 240 min at 37°C. ^a^p \< 0.05, ^b^p \< 0.001 (panel A), and ^a^p \< 0.01 (panel B) vs. 0 mg/mL. Δ= PG. Data are mean ± SEM of five determinations using independent samples.
:::
:::
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Effect of extract of garlic powder (GP) and heated garlic powder (HGP) on the slopes of oxidation curves.
:::
Extract \[mg/mL\] 0 0.05 0.05 Δ 0.1 0.1 Δ
------------------- ----------------- ----------------- ----------------- -------------------- --------------------
GP or HGP 0.0024 ± 0.0002 0.0017 ± 0.0002 0.0018 ± 0.0002 0.0013 ± 0.0001^a^ 0.0013 ± 0.0001^a^
Data are mean ± SEM of five determinations using independent samples. ^a^p \< 0.01 vs. 0 mg/mL. Δ = HGP.
:::
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Effect of different extracts of garlic on the slopes of oxidation curves.
:::
Extract, \[mg/mL\] 0 0.25 0.25 Δ 0.5 0.5 Δ
-------------------- ----------------- ----------------- -------------------- -------------------- --------------------
RG or HRG 0.0023 ± 0.0003 0.0020 ± 0.0001 0.0014 ± 0.0001^a^ 0.0013 ± 0.002^b^ 0.0011 ± 0.0002^b^
RG or BG 0.0021 ± 0.0001 0.0016 ± 0.0002 0.0008 ± 0.0002^c^ 0.0007 ± 0.0004^c^ 0.0005 ± 0.0001^c^
RG or MG 0.0024 ± 0.0002 0.0018 ± 0.0002 0.0015 ± 0.0002 0.0011 ± 0.0003^b^ 0.0005 ± 0.0002^c^
RG or PG 0.0026 ± 0.0002 0.0023 ± 0.0004 0.0021 ± 0.0004 0.0016 ± 0.0003 0.0019 ± 0.0003
Data are mean ± SEM of five determinations using independent samples. ^a^p \< 0.05, ^b^p \< 0.01, ^c^p \< 0.001, vs. 0 mg/mL. Δ = HRG, BG, MG or PG.
:::
Cu^2+^-chelation studies
------------------------
To investigate if the ability of garlic extracts to inhibit Cu^2+^-induced lipoprotein oxidation in human serum was secondary to Cu^2+^-chelation, these extracts were tested in an *in vitro*system (see material and methods) to know if they were able to chelate Cu^2+^. The results for each extract at the higher concentration are presented in Fig. [8](#F8){ref-type="fig"}. Panel A shows uric acid production measured at 295 nm and panel B shows superoxide production measured by the NBT reduction at 560 nm. Cu^2+^-induced a decrease in xanthine oxidase activity measured both by uric acid production at 295 nm which decreased 71% and by NBT reduction at 560 nm which decreased 96% (Fig. [8](#F8){ref-type="fig"}). Uric acid production and NBT reduction were restored by EDTA. The extracts were added at the following concentrations: GP and HGP = 0.1 mg/mL, and RG, HRG, BG, MG, and PG = 0.5 mg/mL. We have previously shown that at these concentrations, the extracts increased lag time and decreased AUC indicating that they were able to inhibit Cu^2+^-induced lipoprotein oxidation (Figs. [3](#F3){ref-type="fig"},[4](#F4){ref-type="fig"},[5](#F5){ref-type="fig"},[6](#F6){ref-type="fig"}). In absence of Cu^2+^(-CuSO~4~) the extracts were unable to modify uric acid production indicating that they were unable to modify xanthine oxidase activity. In absence of Cu^2+^, NBT reduction was decreased significantly by RG indicating that this extract quenched superoxide anion. In presence of Cu^2+^(+CuSO~4~) the extracts were unable to restore (a) uric acid production (p \> 0.05 vs. CT without Cu^2+^), with the exception of RG which was able to restore it partially (p \< 0.05 vs. CT without Cu^2+^), and (b) NBT reduction (p \> 0.05 vs. CT without Cu^2+^). In summary, the extracts were unable to restore xanthine oxidase activity indicating that they do not chelate Cu^2+^. Only RG showed a weak Cu^2+^-chelating activity.
::: {#F8 .fig}
Figure 8
::: {.caption}
######
The Cu^2+^-chelating properties of aqueous garlic extracts were assessed using an approach based upon restoring the activity of xanthine oxidase which has been inhibited in the presence of 0.050 mM CuSO~4~. The activity of xanthine oxidase can be assessed by monitoring either the production of superoxide anion (measuring the reduction of NBT at 560 nm) or the formation of uric acid (following absorbance at 295 nm). Xanthine oxidase activity would be restored if the garlic extracts were able to chelate Cu^2+^. Panel A shows xanthine oxidase activity measuring uric acid production at 295 nm. ^a^p \< 0.0001 vs. CT (-Cu^2+^), ^b^p \< 0.0001 vs. CT (+Cu^2+^), ^c^p \< 0.0001 vs. its respective group without Cu^2+^. Panel B shows xanthine oxidase activity measuring superoxide production by NBT reduction at 560 nm. ^a^p \< 0.0001 vs. CT (-Cu^2+^); ^b^p \< 0.0001 and ^c^p \< 0.05 vs. CT (+Cu^2+^); ^d^p \< 0.05 vs. its respective group without Cu^2+^. CT = Control (-Cu^2+^, +Cu^2+^), GP = aqueous extracts of garlic powder, HGP = heated aqueous extracts of garlic powder, RG = aqueous extracts of raw garlic, HRG = heated aqueous extracts of raw garlic, BG = aqueous extracts of boiled garlic, MG = aqueous extracts of microwave-treated garlic, and PG = aqueous extracts of pickled garlic. GP and HGP = 0.1 mg/mL, RG, HRG, BG, MG, and PG = 0.5 mg/mL. Data are mean ± SEM of 3 determinations, except for both CT groups and EDTA group in which n = 7.
:::
:::
Discussion
==========
Garlic has been used for millennia in folk medicine of many cultures to treat cardiovascular diseases and other disorders \[[@B1]-[@B8]\]. It has been shown in many cases that the protective effect of garlic is associated with its antioxidant properties \[[@B7],[@B8]\]. The antioxidant properties of some garlic extracts used in this work have been studied. It has been found that aqueous extract of raw garlic scavenges hydroxyl radicals \[[@B20],[@B31],[@B32]\] and superoxide anion \[[@B32]\], inhibits lipid peroxidation \[[@B20]\], LDL oxidation \[[@B9]\], the formation of lipid hydroperoxides \[[@B20],[@B31],[@B32]\], and *in vivo*enhances endogenous antioxidant system \[[@B33]\] and prevents oxidative stress to the heart \[[@B34],[@B35]\]. Chronic administration of raw garlic homogenate increases catalase and superoxide dismutase in rat heart \[[@B33]\] and protects heart against oxidative damage induced by adriamycin \[[@B34]\] or ischemia and reperfusion \[[@B35]\]. Aqueous extract of garlic powder are also able to scavenge hydroxyl radicals \[[@B36]\] and superoxide anion \[[@B37]\]. The heated aqueous extract of garlic powder maintains its ability to scavenge hydroxyl radicals \[[@B20]\]. In addition the ability of the aqueous extracts from boiled garlic cloves to scavenge hydroxyl radicals, superoxide anion, and hydrogen peroxide is not altered (unpublished results from our group). To our knowledge, additional antioxidant properties of the extracts from microwave-treated garlic cloves or from pickled garlic have not been studied.
Furthermore, the antioxidant properties of some isolated garlic compounds also have been studied. Allicin, the main component in aqueous extract from raw garlic and garlic powder, scavenges hydroxyl radicals and inhibit lipid peroxidation \[[@B38]\] and prevents the lung damage induced by ischemia-reperfusion \[[@B39]\]. The antioxidant properties of allicin may explain, at least in part, the ability of these extracts (from raw garlic or garlic powder) to inhibit Cu^2+^-induced lipoprotein oxidation in human serum. Alliin, the main component in extracts from boiled garlic cloves, microwave-treated garlic cloves and pickled garlic, scavenges hydroxyl radicals \[[@B40]\], hydrogen peroxide \[[@B41]\], and inhibits lipid peroxidation \[[@B41]\] and LDL oxidation \[[@B42]\]. This may explain, at least in part, the ability of boiled garlic, microwave-treated garlic, or picked garlic to inhibit Cu^2+^-induced lipoprotein oxidation in human serum. Interestingly, it has been shown that another garlic compounds such as S-allylcysteine \[[@B10],[@B13]\], N-acetyl-S-allylcysteine \[[@B10]\], S-allylmercaptocysteine \[[@B10]\], alliin \[[@B10]\], allixin \[[@B10]\], and S-ethylcysteine, N-acetylcysteine, diallyl sulfide, and diallyl disulfide \[[@B14]\] are able to inhibit Cu^2+^-induced LDL oxidation. The antioxidant properties of S-allylcysteine \[[@B43]\], S-allylmercaptocysteine \[[@B44]\], diallyl sulfide \[[@B45]\], and diallyl disulfide \[[@B46]\] also have been seen *in vivo*in an experimental model of nephrotoxicity induced by gentamicin.
Our data strongly suggest that the ability of garlic to prevent Cu^2+^-induced lipoprotein oxidation in human serum is preserved in spite of inactivation of allinase by boiling, microwave or pickling or by the heating of garlic extracts and that the compound(s) involved in the inhibition of Cu^2+^-induced lipoprotein oxidation are heat stable. Our data are in contrast with previous studies in the literature showing that the heating may impair significantly several garlic properties. For example, microwave-treatment for 1 min impaired the anticancer properties of garlic \[[@B17]\] and the heating of garlic cloves by 15 min impairs significantly its ability to inhibit thromboxane B~2~synthesis \[[@B19]\], and platelet aggregation \[[@B22]\], and the cyclooxygenase activity \[[@B18]\]. The heating by 10 min at 100°C reduced the bactericidal activity against *Helicobacter pylori*\[[@B21]\]. Interestingly, Kasuga *et al*. \[[@B47]\] have found that garlic extracts, prepared from boiled cloves, show efficacy in the following three experimental models: testicular hypogonadism induced by warm water treatment, intoxication of acetaldehyde, and growth of inoculated tumor cells, and Prasad *et al*. \[[@B20]\] found that the heating did not modify the ability of garlic extract to scavenge hydroxyl radicals. The data from Prasad *et al*. \[[@B20]\] and Kasuga *et al*. \[[@B47]\] strongly suggest that some garlic properties may remain unmodified after heating. Our data are in agreement with those of Prasad *et al*. \[[@B20]\] suggesting that the ability to inhibit Cu^2+^-induced lipoprotein oxidation is also preserved after the heating of garlic.
In addition, it was found that the garlic extracts used in our study were unable to chelate Cu^2+^suggesting that the ability of these extracts to inhibit Cu^2+^-induced lipoprotein oxidation is not secondary to Cu^2+^-chelation. Only RG showed a weak Cu^2+^-chelation activity, which was more evident at 295 nm. Based on previous data with aged garlic extracts \[[@B11]\] and some individual garlic compounds such as S-ethylcysteine, N-acetylcysteine, diallyl sulfide, and diallyl disulfide \[[@B14]\], we expected that our garlic extracts had Cu^2+^-chelating activity. The discrepancy with our data may simply reflect differences in composition in each garlic extract. This is additionally supported by the fact that the diethyl ether extract from aged garlic extract has no Cu^2+^-chelating activity \[[@B11]\]. The precise mechanism by which our extracts inhibit Cu^2+^-induced lipoprotein oxidation remains to be studied.
Conclusions
===========
\(a) the heating of aqueous extracts of raw garlic or garlic powder or the heating of garlic cloves by boiling, microwave or pickling do not affect garlic\'s ability to inhibit Cu^2+^-induced lipoprotein oxidation in human serum, and (b) this ability is not secondary to Cu^2+^-chelation.
Authors\'s contributions
========================
JPCH conceived, designed and coordinated the study and drafted the manuscript. MGO performed the studies on Cu^2+^-chelation and studied the effect of boiled garlic, picked garlic and garlic submitted to microwave heating on Cu^2+^-induced lipoprotein oxidation in human serum. GA developed in our laboratory the method to oxidize lipoproteins by Cu^2+^and performed studies with garlic extracts of raw garlic and garlic powder. LBE participated in the studies on Cu^2+^-chelation. MM participated in the blood obtention and clinical chemistry analyses of blood serum. ONMC participated in the statistical analyses and developed the method to analyze the Cu^2+^chelating properties of garlic extracts. All authors read and approved the final manuscript.
Competing interests
===================
None declared.
Acknowledgements
================
Financial support. This work was supported by CONACYT (Grant No. 40009-M).
|
PubMed Central
|
2024-06-05T03:55:47.987618
|
2004-9-1
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519022/",
"journal": "Nutr J. 2004 Sep 1; 3:10",
"authors": [
{
"first": "José",
"last": "Pedraza-Chaverrí"
},
{
"first": "Mariana",
"last": "Gil-Ortiz"
},
{
"first": "Gabriela",
"last": "Albarrán"
},
{
"first": "Laura",
"last": "Barbachano-Esparza"
},
{
"first": "Marta",
"last": "Menjívar"
},
{
"first": "Omar N",
"last": "Medina-Campos"
}
]
}
|
PMC519023
|
Background
==========
Diet has an effect on mood and cognitive function \[[@B1]\]. There is some evidence that deficiency or supplementation of nutrients can affect not only mood, but also behavioral patterns.
A double-blind placebo-controlled trial with 30 patients showed that omega-3 essential fatty acid supplements alleviated symptoms in patients with bipolar disorder \[[@B2]\]. In a recent double-blind, placebo-controlled trial on 231 young adult prisoners, by comparing the number of their disciplinary offences before and during the supplementation, antisocial behavior was reduced by the supplementation of vitamins, minerals and essential fatty acids \[[@B3]\]. Vitamin D supplementation during winter was reported to improve mood in a double-blind, placebo-controlled trial on 44 healthy volunteers \[[@B4]\].
A number of studies have shown that acute tryptophan depletion produces depressive symptoms and results in worsening of mood \[[@B5]\]. Folic acid deficiency may also correlate with depression, and it has particular effects on mood, cognitive as well as social functioning \[[@B6]\]. Recently, it have been reported that low levels of dietary folic acid are associated with elevated depressive symptoms in middle-aged men \[[@B7]\].
In general, a low-fat diet may have negative effects on mood \[[@B8]\], and altered dietary fat intake can lead to acute behavioral effects such as drowsiness, independent of energy consumption \[[@B9]\]. A high intake of proteins also seems to increase alertness \[[@B1]\]. Increased dietary serine and lysine may be linked to the pathogenesis of major depressive disorder \[[@B10]\]. Apart from specific nutrients or vitamins, certain foods may have an effect on mental wellbeing. Warm milk, for instance, has been traditionally used as self-medication for insomnia. Individuals drinking regular coffee with caffeine have reported to have decreased total sleep time and sleep quality, and increased sleep latency \[[@B11]\]. It has been reported that people with a high consumption of fish appear to have a lower prevalence of major depressive disorder \[[@B12],[@B13]\]. Recently, it has been also reported that increased fish intake in people without depressive symptoms had no substantial effect on mood \[[@B14]\].
Depressed subjects tend to consume more carbohydrates in their diets than non-depressed individuals \[[@B15]\], and they show heightened preference for sweet carbohydrate or fat rich foods during depressive episodes \[[@B16]\]. High carbohydrate intakes increase brain uptake of tryptophan, which in turn stimulates the synthesis of serotonin \[[@B1]\]. At present, there are some studies focusing on the use of dietary supplements in individuals with mental disorders, but there is a lack of consistent data concerning the impact of nutrition, diet and eating habits on mental health.
Aims
====
We set out to study whether food consumption and intake of nutrients in subjects with depressed mood, anxiety and insomnia differed from those in subjects without any such symptoms.
Methods
=======
This study was based on the cohort of a randomized, double-blind, placebo-controlled primary prevention trial testing the hypothesis that daily supplementation with α-tocopherol or β-carotene reduces the incidence of lung and other cancers \[[@B17]\]. The study participants were recruited between 1985 and 1988 from the total male population 50--69 years of age, residing in southwestern Finland (n = 290,406). These men were sent a questionnaire on current smoking status and willingness to participate in the trial. Smokers of at least five cigarettes per day and who were willing to participate were then invited to visit their local study center for further evaluation of their eligibility. A previous cancer diagnosis, current severe angina with exertion, chronic renal insufficiency, cirrhosis of the liver, alcohol dependence, or a disorder limiting participation in the long-term trial, such as mental disorder or physical disability, were reasons for exclusion. A total of 29,133 men were randomly assigned to receive supplements of either α-tocopherol, β-carotene, both, or placebo, in a 2 × 2 factorial design. The ethics review boards of the participating institutions approved the study, and all subjects provided written informed consent prior to randomization.
At baseline, subjects completed a questionnaire on their background and medical history, including three questions on mental wellbeing. These items concerned anxiety, depressed mood and insomnia experienced in the past four months. Height and weight were also measured, and a blood sample was drawn for determining total and high-density lipoprotein (HDL) cholesterol concentrations. Diet and alcohol consumption was assessed from a self-administered dietary history questionnaire \[[@B18]\], which asked the frequency of consumption and the usual portion size of 276 food items during the past year, using a color picture booklet as a guide for portion size. Complete dietary data were available for 27,111 participants.
Dietary nutrient data were analyzed by linking the questionnaire data to the food composition database of the National Public Health Institute, Finland. For analysis, we considered three main groups: principal nutrients, specific nutrients selected on the basis of a priori hypotheses, and certain foods. The principal nutrients were energy, carbohydrates, proteins and fats. The hypothesis-based nutrients were omega-3 and omega-6 fatty acids, lysine, serine, tryptophan, and two vitamins, vitamin D and folic acid. Omega-3 fatty acids from fish consist of long-chain fatty acids, while the omega-3 fatty acids in vegetables are shorter-chain molecules. The food items included were fish, milk, meat, vegetables, margarine, coffee and alcohol. We also evaluated the total energy intake.
The trial involved three follow-up visits annually. At each follow-up visit the participants were asked whether they had felt anxiety, depression, or insomnia since the preceding visit (Have you felt feelings of depression in last three months? Have you felt feelings of anxiety in last three months? Have you had insomnia in last three months?). To identify subjects who suffered chronically from these symptoms we took into account the symptoms reported throughout the first follow-up year, i.e. at baseline and the three follow-up visits (at baseline, 4 months, 8 months and 12 months). Men reporting anxiety, depression, insomnia, or all these symptoms at all four visits were included in these analyses.
Statistics
----------
As potential risk factors, baseline age, body-mass index (BMI), energy intake, alcohol consumption, education level, marital status and smoking were entered into regression models as covariates. Dietary factors were adjusted for energy intake in the models \[[@B19]\].
Results
=======
At study entry, 4314 (16%) men reported depressed mood in the past four months, 6498 (24%) feelings of anxiety, and 5550 (21%) insomnia. The mean intake of energy was 1 to 3% greater and consumption of alcohol 30 to 33% greater in subjects with any such symptoms, compared with symptom-free individuals (Table [1](#T1){ref-type="table"}). Men reporting all three symptoms consumed as much as 47% more alcohol than those without any symptoms. Subjects with insomnia consumed 7% less coffee than symptom-free individuals, whereas those with depressed mood or anxiety consumed only about 2% less coffee (Table [2](#T2){ref-type="table"}).
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Baseline characteristics of subjects with self-reported depressed mood, anxiety or insomnia, and subjects with all three or none of the symptoms.
:::
Depressed mood Anxiety Insomnia All three symptoms No symptoms
---------------------------------- ---------------- --------- ---------- -------------------- ------------- ------ ------ ------ ------ ------
Age (years) 57.2 4.9 57.0 4.8 57.8 5.1 56.9 4.8 57.8 5.1
Energy (kcal/day) 2877 813 2888 801 2828 818 2886 863 2793 777
Alcohol consumption (g/day) 21.7 26.2 21.5 25.1 22.0 25.4 24.3 28.5 16.5 19.8
BMI (kg/m^2^) 26.3 3.9 26.2 3.9 26.1 3.9 26.1 3.8 26.3 3.7
Total serum cholesterol (mmol/l) 6.16 1.19 6.22 1.18 6.15 1.19 6.13 1.21 6.26 1.16
Serum HDL-cholesterol (mmol/l) 1.24 0.36 1.26 0.36 1.27 0.37 1.27 0.38 1.23 0.34
:::
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Baseline daily food consumption and nutrient intake of subjects self-reporting depression, anxiety or insomnia, and all three or none of the symptoms.
:::
----------------------------------------------------------------------------------------------------------------------------------------------------------------
Depressed mood\ Anxiety\ Insomnia\ All three symptoms\ No symptoms\
(n = 4314) (n = 6498) (n = 5550) (n = 1670) (n = 19116)
------------------------------------------- ----------------- ------------ ------------ --------------------- -------------- ------ ------- ------ ------ ------
Fish (g) 39.3 30.2 39.9 30.2 40.1 30.3 40.3 32.9 39.3 29.8
Milk (g) 212 315 203 316 226 321 219 325 220 322
Coffee (ml) 595 374 601 372 567 364 583 382 609 349
Meat (g) 78.0 38.4 80.2 38.8 77.6 38.6 78.0 37.8 78.6 37.2
Vegetables (g) 256 103 264 104 253 104 255 106 263 101
Margarine (g) 11.5 21.1 11.5 20.8 10.7 20.3 11.8 21.3 10.2 19.8
Carbohydrate (g) 308 97.7 309 96.8 300 96.7 304 97.6 303 94.0
Protein (g) 105 30.6 105 30.2 103 31.2 105 31.6 103 28.9
Fat (g) 125 41.8 125 41.8 123 42.2 125 43.4 122 40.6
Sugar (g) 38.5 27.5 38.3 28.0 36.9 26.7 37.7 27.6 38.1 26.5
Lysine (g) 6.42 1.97 6.44 1.95 6.37 2.01 6.44 2.04 6.30 1.86
Serine (g) 4.12 1.31 4.27 1.30 4.22 1.33 4.28 1.35 4.18 1.24
Tryptophan (g) 1.28 0.38 1.29 0.38 1.27 0.39 1.29 0.40 1.26 0.36
Omega-3 fatty acids (total) (g) 2.21 0.93 2.24 0.92 2.16 0.92 2.23 0.97 2.14 0.87
Omega-3 fatty acids (from fish) (g) 0.47 0.28 0.48 0.29 0.48 2.89 0.49 0.30 0.46 0.28
Omega-3 fatty acids (from vegetables) (g) 1.77 0.82 1.79 0.80 1.70 0.80 1.77 0.86 1.70 0.77
Omega-6 fatty acids (g) 10.12 6.82 10.14 6.70 9.70 6.65 10.17 7.05 9.44 6.31
Omega-6/omega-3 ratio 4.47 2.00 4.45 2.01 4.41 2.03 4.50 2.30 4.34 1.85
Folic acid (μg) 342 106 344 105 335 106 340 107 336 103
Vitamin D (μg) 5.59 3.21 5.65 3.18 5.60 3.18 5.72 3.23 5.45 3.08
----------------------------------------------------------------------------------------------------------------------------------------------------------------
:::
In subjects with depressed mood, the mean intake of omega-6 fatty acids was 7% greater than in symptom-free subjects. In individuals with anxiety, the mean intake of omega-6 fatty acids was 7% greater and that of omega-3 fatty acids from vegetables 5% greater than in subjects with no symptoms. Intake of fish or omega-3 fatty acids from fish were not associated with anxiety or depressed mood.
When the symptoms reported during the first trial follow-up year were taken into analysis, 782 men reported depressed mood, 1237 feelings of anxiety, 1234 insomnia, and 166 men all three symptoms on all four occasions. The mean intake of energy was 7% greater in subjects reporting all three symptoms repeatedly compared with symptom-free individuals. Subjects with insomnia consumed 11% less coffee but 10% more milk than those with no insomnia. Both in subjects with depressed mood and with anxiety, the mean intake of total omega-3 fatty acids was 9% greater and that of omega-3 fatty acids from vegetables 6% greater than in respective symptom-free subjects, whereas the mean intake of omega-6 fatty acids was 6% greater in subjects with depressed mood and 9% greater in subjects with anxiety.
Discussion
==========
Our subjects reporting anxiety had higher intakes of omega-3 and omega-6 fatty acids, but omega-3 fatty acids from fish were not linked to anxiety. Margarine was the main source of both omega-3 fatty acids from vegetables and omega-6 fatty acids. Subjects with depressed mood also had a higher intake of omega-6 fatty acids. Because 3138 (73%) subjects with depressed mood also had feelings of anxiety, it may be that anxiety is the dominant symptom, and the greater intake of omega-3 and omega-6 fatty acids is primarily related to feelings of anxiety.
Previously, it has been suggested that omega-3 fatty acids may alleviate the effects of depressive symptoms but not those of mania \[[@B20]\]. Recently, we have reported that the low dietary intake of omega-3 fatty acids is not associated with depression \[[@B21]\]. Our present results show now that individuals suffering from symptoms of depressed mood have higher intakes of omega-6 and omega-3 fatty acids. More investigation is needed to elucidate the specific effects of omega-3 fatty acids on mood.
Subjects with any or all of the symptoms consumed more alcohol than the symptom-free subjects. Subjects with all three symptoms consumed most alcohol of all, and they received 6% of their total energy from alcohol, compared with 4% in subjects with no symptoms. Energy from alcohol, however, did not explain the differences in the mean intake of energy between groups. Body-mass index was lower, despite a higher caloric intake, in subjects with any of the symptoms compared with symptom-free subjects.
Subjects reporting insomnia drank more milk than symptom-free subjects, but less coffee. Warm milk has long been taken as a self-medication for insomnia, and our finding among those with insomnia accords with this traditional habit. In addition, they avoided consuming large amounts of coffee, which is known to have impact of sleep. We also found that subjects reporting depressed mood consumed more carbohydrates than subjects with no symptoms. This finding is consistent with the attempt by depressed subjects to alleviate the carbohydrate craving associated with symptoms of depression.
Tryptophan intake showed no association with mental wellbeing in our study population. Interestingly, a number of negative studies has been published recently, suggesting that the effects of tryptophan depletion on mood are inconsistent \[[@B22]-[@B24]\], and the rationale for augmentation has now been challenged \[[@B25]\]. The intakes of vitamin D and folic acid exceeded the daily recommendations and showed no association with mental wellbeing. Neither did the consumption of fish, milk, meat or vegetables.
Limitations
===========
There are some limitations in our study. Our study was a cross-sectional study, and it cannot provide causal evidence on the association between the diet and symptoms of depression, anxiety or insomnia. The study participants included only men, aged 50 to 69 years, and all were smokers. Our exclusion criteria limit the generalization of our findings, but the study still provides valid and reliable data on a community-based, homogenous sample of older men.
Dietary intake and alcohol consumption were assessed with a validated food use questionnaire to measure the habitual dietary intake over the previous year as completely as possible. For most nutrients, both the reproducibility and the validity of this method are 0.6 to 0.7 \[[@B18]\]. For example, they are 0.66 and 0.73 for energy intake, 0.88 and 0.85 for alcohol, 0.70 and 0.75 for carbohydrates, and 0.70 and 0.64 for vitamin D, respectively.
The assessment of self-reported depression was based on a single item only that might have compromised the specificity, but not sensitivity. For example, two questions only may be as effective as more detailed screening instruments in detecting probable cases of major depression \[[@B26]\]. One of these questions (\"During the past month, have you often been bothered by feeling down, depressed, or hopeless?\") is rather similar to the item that we applied for being indicative of depressed mood.
Conclusion
==========
The scientific examination of relationships between nutrition and mental wellbeing is a relatively new area of study. Most of the studies focus on the use of dietary supplements, which provide more concentrated amounts of specific nutrients than most food sources. There are few data evaluating food consumption and nutrient intake among subjects with compromised mental health. Our main finding was that we did not find any association between omega-3 fatty acids from fish and mental wellbeing. In general, more attention need to be paid to the intake of nutrients in patients suffering from symptoms of depression, anxiety or insomnia. Further studies are needed to clarify complex associations between the diet and mental wellbeing, and to elucidate their mechanisms of action.
Acknowledgments
===============
The authors thank Ms Satu Männistö, Ph.D., from the Department of Epidemiology and Health Promotion, National Public Health Institute, Finland for her expertise, help and support. The ATBC Study was supported by Public Health Service contracts (N01-CN-45165 and N01-RC-45035) with the National Cancer Institute, National Institutes of Health, Department of Health and Human Services, USA.
|
PubMed Central
|
2024-06-05T03:55:47.990219
|
2004-9-13
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519023/",
"journal": "Nutr J. 2004 Sep 13; 3:14",
"authors": [
{
"first": "Reeta",
"last": "Hakkarainen"
},
{
"first": "Timo",
"last": "Partonen"
},
{
"first": "Jari",
"last": "Haukka"
},
{
"first": "Jarmo",
"last": "Virtamo"
},
{
"first": "Demetrius",
"last": "Albanes"
},
{
"first": "Jouko",
"last": "Lönnqvist"
}
]
}
|
PMC519024
|
Background
==========
Following partial hepatectomy (PHx) the remaining liver is transfused by normal blood volume, thereby exposing liver sinusoidal endothelial cells (LECs) to excess hemodynamic forces. These forces have been noted as an early event leading to liver restoration in rats \[[@B1]-[@B3]\]; however, the idea that quality of the blood rather than quantity has been the accepted dogma \[[@B4],[@B5]\]. Based on time-scale events, shear stress inflicted on liver cells precedes the expression of factors some of which are expressed within minutes. Studies conducted in recent years indicate that shear stress induced NO leads to the expression of genes participating in liver regeneration including c-fos \[[@B6]-[@B8]\]. There is evidence demonstrating that increase of c-fos in PHx or portal branch ligation models is inhibited by N-nitro-L-arginine methyl ester, which blocks NO synthase \[[@B8]\]. The present study was undertaken to examine the molecular and ultrastructural effects of hemodynamic forces on LECs. We have chosen to focus on vascular endothelial cell growth factor (VEGF) receptors (VEGFRs), as these are present on endothelial cells and have been demonstrated not only to have a role in liver regeneration, but also to be affected by shear stress conditions. Following PHx \[[@B9]\], VEGF is expressed in periportal regions demonstrating lobular heterogeneity \[[@B10],[@B11]\]. VEGFR-1 and VEGFR-2, as well as Tie 1, Tie 2 and platelet-derived growth factor, are all shown to increase in endothelial cells following PHx \[[@B12]\]. We have demonstrated the stimulatory effects of both VEGF-165 and VEGF-121 on liver cell proliferation following PHx \[[@B13],[@B14]\]. In a recent study \[[@B15]\], it was shown that shear stress causes the induction and translocation of VEGFR-2 to the nucleus in bovine aortic endothelial cells. In addition, it promotes the formation of a complex comprising VEGFR-2, VE-cadherin and β-catenin. It is postulated that the complex acts as a shear stress receptor, mediating signals into the cells. Here, we describe the relationship between elevated blood flow to the liver following PHx and the morphology alterations associated with lining endothelial cells. We also provide evidence demonstrating that shear stress imposed on LECs *in vitro*is accompanied by a significant increases in VEGFR-1, VEGFR-2 and neuropilin-1 mRNA levels. Furthermore, following shear stress both receptors alternate from perinuclear and faint cytoplamic orientation to adhere to cytoskeletal components and cell membrane. These changes coincide with the behavior of the adherence junction proteins VE-cadherin and β-catenin.
Results
=======
Portal blood flow following liver hepatectomy
---------------------------------------------
Seventy percent of PHx is associated with cell proliferation and a gradual increase in liver mass (data not shown). Nine days post-hepatectomy close to 80% of the original liver weight was restored. PCNA labeling index peaked at 48 hrs thereby returning to preoperative values. Concomitant with liver resection an immediate increase in blood flow to the remnant liver was evident, reaching a maximum of 2.5 fold at 24 hrs (Fig. [1](#F1){ref-type="fig"}). Elevated values remained for as long as 72 hrs. Ten days following partial hepatectomy blood flow returned to normal. Values recorded earlier than 20 minutes are subject to technical difficulties; therefore, they are not presented.
::: {#F1 .fig}
Figure 1
::: {.caption}
######
**Portal blood flow in normal and 70% partially hepatectomized rats.**At the designated time following partial hepatectomy rats were anesthetized and placed on a temperature controlled table. Following tracheotomy and saline infusion an ultrasound sensor was fixed to the portal vein. Blood flow was monitored by ultrasonic flowmetry. Results represent an average of 5 rats + 2 × SD.
:::
:::
LEC Ultrastructure following partial hepatectomy
------------------------------------------------
The effects of partial hepatectomy and the associated shear stress developing as a result of excessive blood flow to the remnant liver were evaluated with the aid of scanning electron microscopy. Special emphasis was given to the influence of these forces on the surface of liver sinusoids and intactness of the endothelial lining.
Under normal conditions, liver lobule sinusoids show an intact endothelial lining, consisting of LECs with flattened processes perforated by small fenestrae. These fenestrae measure 0.15--0.2 μm in diameter and are arranged in groups, sieve plates (Fig. [2a](#F2){ref-type="fig"}). As early as ten minutes post hepatectomy, endothelial changes were already noted in the form of fused fenestrae (gaps), ranging in size between 0.3 μm and 2 μm (Fig. [2b](#F2){ref-type="fig"}). These gaps were more prominent in periportal than pericentral areas (Table [1](#T1){ref-type="table"}). Increasing values were noted in subsequent times, 24 (Fig. [2c](#F2){ref-type="fig"}), 72 (Fig. [2d](#F2){ref-type="fig"}) and 168 hrs (Fig. [2e](#F2){ref-type="fig"}) post-surgery in both areas. Ten days after hepatectomy, the morphology of the endothelial lining (Fig. [2f](#F2){ref-type="fig"}) and number of gaps returned to preoperative conditions (Table [1](#T1){ref-type="table"}).
::: {#F2 .fig}
Figure 2
::: {.caption}
######
**Scanning electron micrographs of liver periportal sinusoids.**(a) control, (b-f) following partial hepatectomy; control liver (a) demonstrates an intact fenestrated wall (arrow) and undisrupted bordering parenchymal cells (Pc). Inset depicts fenestrae (arrowhead). (b) Numerous gaps (arrow) are observed as early as ten minutes after PHx. Inset shows a detailed image of gaps (arrow) and fenestrae (arrowhead). (c) 24 hrs after PHx, gaps (arrow) are still present. Note the protruding microvilli from the underlying parenchymal cell surface (arrowhead). Small structures (\*), probably platelets, could be noticed adhering to endothelial wall. 72 hrs (d) and 168 hrs (e) after PHx, depicting features similar to those seen in (c). (f) Ten days after PHx an intact endothelial lining (arrow) and fenestrae (arrowhead) could be observed. Scale bars: 2 μm; Insets: 0.5 μm.
:::
:::
Transmission electron microscopy was used to study in great detail the above alterations. (Fig. [3](#F3){ref-type="fig"}). Control tissue showed an intact relationship between LECs and neighboring liver parenchymal cells (Fig. [3a](#F3){ref-type="fig"}). The sinusoid was patent and empty; the wall of the sinusoid was composed of a thin layer of fenestrated endothelium covering the space of Disse, filled by microvilli extending from the parenchymal cell surface. These parenchymal cells contained glycogen, a few lipid vesicles, and numerous organelles in their cytoplasm (Fig. [3a](#F3){ref-type="fig"}). Ten minutes after hepatectomy, many blood platelets adhered to the endothelial lining. In addition, the endothelial lining became disrupted as represented by the occurrence of gaps and microvilli, which were facing directly toward the sinusoidal lumen (Fig. [3b](#F3){ref-type="fig"}). These morphological alterations were still present 24, 72 and 168 hrs after PHx. Lipid accumulation in the form of droplets could be observed in the cytoplasm of parenchymal cells 10 hrs (data not shown) after partial hepatectomy, persisting until day 3 (Fig. [3d](#F3){ref-type="fig"}). To avoid any possible effect caused by the procedure and anesthetic reagents used, a sham operation was conducted (time 0).
::: {#F3 .fig}
Figure 3
::: {.caption}
######
**Transmission electron micrographs of liver periportal areas.**(a), control, (b-d), after partial hepatectomy; (a) illustrates an intact histological relationship between liver sinusoidal endothelium (Ec) and neighboring liver parenchymal cells (Pc). Note the patent lumen (L). Inset depicts the intact cytoplasmic processes of endothelial cells bearing fenestrae (arrow). (b) Ten minutes after PHx, the surface area of the sinusoidal lumen (L) decreases and severe damage of the endothelial lining in the form of gaps is noted (arrow). Blood platelets (arrowhead) adhere to the damaged sinusoidal lumen. Inset shows a detailed image of blood platelets. (c) 24 hrs after PHx. Fat droplets (arrow) are evident in the cytoplasm of parenchymal cells. Gaps are still present (arrowhead). (d) 72 hrs after PHx reveals endothelial damage (arrowhead) and large fat droplets (arrow) within the parenchymal cells (compare with Figure 3c for the difference). Scale bars: 2 μm; Insets: 0.5 μm.
:::
:::
Effect of laminar shear stress on the expression and distribution of VEGF receptors in liver endothelial cells
--------------------------------------------------------------------------------------------------------------
Purified LECs grown in culture retained their characteristic sieve plates (data not shown). Following 4 hrs of incubation at 37°C and extensive washing, the cells demonstrated nuclear localization of NFκb suggesting an active state. To avoid activation, purified LECs were grown in feeding medium containing 0.25% FCS for 4 hrs, extensively washed and left for 12 hrs before further used. Under these conditions, more than 94% of the cells exhibited cytoplasmic NFκb which was re-localized to the nucleus following shear stress (data not shown). LECs displayed perinuclear and cytoplasmic localization of VEGFR-2 and neuropilin 1 (Fig. [4](#F4){ref-type="fig"}). Following exposure to shear stress conditions (10 dynes/cm^2^/15 minutes), a strong cytoplasmic presence was evident, with a clear tendency to adhere to cytoskeletal components. VEGFR-1 displayed nuclear localization, which was unchanged when shear stress was applied.
::: {#F4 .fig}
Figure 4
::: {.caption}
######
**Immunofluoresence of LECs before and after shear stress.**LECs were reacted with anti VEGFR-1, VEGFR-2 and neuropilin-1 before and after exposure to laminar shear forces (10 dynes/cm^2^/15 minutes). Cy2 conjugated labeled second antibodies were used to visualize the binding of the appropriate antibody. Scale bars: 2 μm.
:::
:::
Owing to the tendency of VE-cadherin and β-catenin to react with cytoskeletal proteins under hemodynamic forces, both were followed in LECs under static conditions and shear stress. Co-staining analysis of both suggests the formation of a complex demonstrating a strong tendency to the membrane (data not shown). Co-staining of VE-cadherin and VEGFR-2 (Fig. [5](#F5){ref-type="fig"}) exhibits similar profile, pointing to the existence of a possible complex, composed of the two proteins.
::: {#F5 .fig}
Figure 5
::: {.caption}
######
**Immunofluoresence of LECs before and after shear stress.**LECs were reacted with anti VE-cadherin and VEGFR-2 alone and in conjunction before and after exposure to laminar shear forces (10 dynes/cm^2^/5 minutes). Cy2 and rhodamine (TRITC) conjugated labeled second antibodies were used to visualize the binding of the appropriate antibody. Scale bars: 2 μm.
:::
:::
Real time RT-PCR was used to quantify the amount of mRNA of all receptors before and after shear stress (Fig. [6](#F6){ref-type="fig"}). The results shown represent pooled RNA isolated from six animals. It is evident that VEGFR-1, VEGFR-2 and neuropilin-1 levels increase following shear stress conditions.
::: {#F6 .fig}
Figure 6
::: {.caption}
######
**Real time PCR of VEGFR-1, VEGFR-2 and neuropilin-1 before and after exposure of LECs to laminar shear stress.**Pooled RNA from six different experiments was isolated from LECs subjected to laminar shear stress forces (10 dynes/cm^2^/15 minutes) and used to measure mRNA levels of the respective receptors.
:::
:::
Discussion
==========
Liver regeneration is associated with an increased expression of a diverse number of genes including immediate early genes, delayed genes, cell cycle and DNA replication and mitosis genes \[[@B4],[@B5]\]. Some of these genes increase within moments after PHx; others increase hours post-surgery. Regardless of the timeframe, the most obvious change occurring immediately after PHx is an elevated in hemodynamic forces imposed on liver cells. Those changes are the result of an increase in the ratio of blood flow to liver weight. We documented a 2.5 fold increase in portal blood flow following 70% PHx. These changes occur immediately and persist for a number of days.
Endothelial cells lining liver sinusoids are likely to be the first to sense changes in shear stress. Those cells are unique as they have no typical basal lamina. Moreover, the cells are fenestrated allowing free passage of chylomicrons, lipoproteins, hormones, growth factors and proteases \[[@B16]\]. The size and density of these fenestrae are affected by physical factors, such as portal pressure and shear stress, as well as soluble factors \[[@B17]-[@B20]\].
Exploring the effects of shear stress on LECs *in vivo*is, at the moment, beyond our reach. Therefore, the present study examines the effects of increased blood flow following PHx on the morphology of LECs. We also follow the gene expression and protein distribution in LECs exposed to controlled shear stress *in vitro*. These forces mimic to the best of our ability physiological conditions.
Following 70% PHx an immediate ultrastructural change was noted in the form of fused fenestrae and gaps. Their number increased significantly in both periportal and pericentral areas (Fig. [2](#F2){ref-type="fig"}); yet, expressed differently in both zones (Table [1](#T1){ref-type="table"}). This observation is not surprising in light of other zonation gradients reported for many liver functions \[[@B16],[@B21]-[@B23]\], like fenestration pattern, differential expression of receptors, hepatocyte metabolism, and ECM-distribution in the space of Disse. Different high-resolution microscopic methods have shown that gaps may originate from the fusion of several fenestrae \[[@B24],[@B25]\]. In fact, gaps along the endothelial lining have been noted when different sample preparation methods were applied \[[@B16],[@B24],[@B26]\] or be induced by hepatotoxins \[[@B27]\] and high-perfusion pressure \[[@B28]\]. In accordance with our observation, Wack et al. \[[@B29]\] reported a gradient behavior in porosity between periportal and pericentral areas following 70% PHx, surprisingly though the gradient described by those authors persists only at 5 minutes and 24 hrs post-surgery. In this study, diameter determinations on gaps were omitted making full comparison difficult. In our experiments, we could not detect statistical variations in the size of gaps between the two zonal areas (our unpublished data). This could be explained by the fact that the size of gaps varied between 0.3 μm and 2 μm and mean values with large standard errors were obtained, excluding therefore valuable statistical analysis.
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Number of gaps along the sinusoidal endothelial lining following partial hepatectomy
:::
**Time** **Periportal (zone 1) n gaps / 10 μm**^2^ **Pericentral (zone 3) n gaps / 10 μm**^2^
---------- ------------------------------------------- --------------------------------------------
Control 0.10 (0.14) 0.06 (0.12)
10 min 1.57 (0.74)\* 0.33 (0.13)^§^
24 hrs 1.47 (0.66)\* 0.47 (0.32)^§^
72 hrs 2.18 (0.91)\* 0.84 (0.65)^§^
168 hrs 2.28 (0.88)\* 0.79 (0.55)^§^
240 hrs 0.09 (0.05) 0.07 (0.05)
Morphometric analysis evaluating the number of gaps per area along the sinusoidal endothelial lining, studied by SEM. Results are expressed as mean (standard deviation) and significance was determined with the Mann Whitney two-sided U-test. The symbols \* and ^§^denote significant differences between control and respective time points (p ≤ 0.05). Significant differences (p ≤ 0.05) between the number of gaps in the periportal and pericentral zones were also noted at all time points following partial hepatectomy except day 10 and control. For every group, n = 3.
:::
In our experiments (Fig. [1](#F1){ref-type="fig"}), maximal values of blood flow per mg of liver were determined at 24 hrs thereby returning to baseline levels. The inconsistency between the number of gaps and the ratio of blood flow per mg of liver tissue, at later time, points may either reflect the time lapse required for liver tissue to recover or that portal pressure is not the only factor influencing lining endothelial cells. Consistent with the increased permeability in zone 1 and zone 2 following PHx, accumulation of lipid droplets was evident 10 hrs post surgery, persisting until day three. At the completion of liver regeneration, lipid content returns to normal values \[[@B18]\]. Increased lipid uptake seems to correlate with the change in barrier competence presented by sinusoidal endothelial cells; however, the role it has in the regenerating liver is still to be elucidated.
Given the increase in blood flow to the liver immediately after PHx, it is likely that the \"damage\" caused to LECs is the result of excessive shear stress to which the cells are exposed. Interestingly, injections of large volume at a short time, hydrodynamic injections \[[@B30]\] inflict periportal and pericentral damage in the form of large (fused) fenestra (our data to be published).
Shear stress conditions can artificially be applied using the cone and plate apparatus \[[@B31]\]. We have chosen to limit our observation to VEGF receptors as those were shown to be expressed on endothelial cells and their level changed during liver regeneration. Owing to the fact that neuropilin-1 acts as VEGF co-receptor, we have looked at neuropilin-1 expression following shear stress as well.
LECs exhibited nuclear staining of VEGFR-1. This localization was not affected by shear stress conditions. VEGFR-2 and neuropilin-1 present a similar pattern of perinuclear and faint cytoplasmic presence. Following shear stress conditions the two receptors seemed to adhere to membrane and cytoskeletal components.
Neuropilin-1 is an isoform specific receptor for VEGF-165 \[[@B32]\], VEGF-E \[[@B33]\], PLGF152 \[[@B34]\] and VEGF-B \[[@B35]\]. Recent studies have demonstrated a complex dependent signaling involving VEGF-165, neuropilin-1 and VEGFR-2 \[[@B36]\]. Such a complex was shown to exist on the surface of endothelial cells or between tumor cells and endothelial cells. Activation of VEGFR-2 has been shown to be involved in the formation of complexes with various cytoplasmic proteins including adherence junction proteins \[[@B37],[@B38]\]. Furthermore, nuclear translocation of VEGFR-2 along with caveolin-1 and eNOS was reported to occur following VEGF treatment \[[@B39]\]. Consistent with data recently presented \[[@B15]\], VEGFR-2 co-stains with VE-cadherin following exposure to shear stress. Our preliminary data point to the possibility of a large complex consisting of VEGFR-2, neuropilin-1 and the adherence junction proteins VE-cadherin and β-catenin; nonetheless, additional experiments need to be done before any conclusion can be reached. Coinciding with the intense staining of the above following exposure to shear stress are the increased mRNA levels of all three as detected by real time PCR.
Hemodynamic forces play a major role in restructuring blood vessels by modulating endothelial structure and functions such as increased permeability to macromolecules or damage to endothelial cells \[[@B40]\]. Therefore, a key question in liver regeneration is how these forces imposed during the early steps following resection are translated into gene expression, DNA synthesis and cell proliferation. Shear forces dependent signaling is presumably based on cytoskeletal components, which act as a mechano-transducer. Indeed, tyrosine phosphorylation of the endothelial cell adhesion molecule PECAM-1 is observed in response to flow \[[@B40]\].
Conclusions
===========
In summary, the present study documents an increase in blood flow to remnant liver following PHx. This change is associated with an elevated number of endothelial cell gaps in both periportal and pericentral areas. Shear stress *in vitro*induces in endothelial cells membrane translocation of VEGFR-2 and neuropilin-1. It is conceivable that under shear stress conditions a complex consisting of VEGFR-2/neuropilin-1 and adhesion molecules forms. Such a complex may well be formed following the elevated blood flow associated with partial hepatectomy, playing a role in the early signals leading to liver regeneration.
Methods
=======
Animals and surgical procedures
-------------------------------
Male Sprague-Dawley rats weighing 300--325 g were used. PHx was performed on 5 animals under light anesthesia by removing the right lateral and median lobes\[[@B41]\]. At different time intervals animals were exsanguinated, the liver removed and tissue samples were prepared for immunostaining and RNA extraction. Animals undergoing PHx and analyzed by electron microscopy were anesthetized first by Ketamine and Xylasine followed by intubation with isoflurane 1.5%. Animals received humane care according to the criteria outlined in the \"Guide for the care and use of laboratory animals\" NIH publication.
Monitoring liver regeneration
-----------------------------
Liver regeneration was monitored using liver mass and PCNA. Liver mass was calculated by weighing the removed lobes following surgery and the regenerating liver at the indicated time point. For PCNA immunostaining, specimens were fixed in paraformaldehyde, embedded in paraffin and sliced. Sections were incubated with anti-PCNA followed by biotin conjugated secondary antibody. The binding of anti-PCNA was monitored using avidin-peroxidase and amino ethyl carbazol as a substrate (Zymed, San Francisco, CA).
Blood flow
----------
Five rats were anesthetized and placed on a temperature-controlled table. Following tracheotomy and saline infusion an ultrasound sensor was fixed to the portal vein. Portal blood flow was monitored by ultrasound flowmetry and automatically recorded (Ultrasonic System Inc. model T206, Ithaca, N.Y).
Preparation of liver tissue for electron microscopy
---------------------------------------------------
Tissue samples were prepared according to standard protocols \[[@B16]\]. Briefly, samples were cut into 1 mm^3^blocks in 1.5% glutaraldehyde, in 0.12 M sodium cacodylate buffer. Following fixation, blocks were submerged in 1% osmium tetroxide, dehydrated in ethanol and embedded in Epon. Semithin (1 μm) sections were cut and stained with 1% toluidine blue solution. For detailed EM-study, 50--80 nm ultrathin sections were stained first with uranyl acetate and then with lead citrate. For SEM, dehydrated blocks were dried with hexamethyldisilazane and subsequently broken in liquid nitrogen, mounted on stubs and sputter coated with a thin layer of 20 nm gold \[[@B24]\]. Morphometric analysis was performed on randomly acquired digitized SEM images at magnifications ×5,000 or ×20,000, as previously described \[[@B42]\]. The UTHSCSA Image Tool 2.0 software was used to determine the number of liver sinusoidal endothelial gaps. Gaps, an empty area, a hole with a maximum diameter of ≤ 0.3 μm and ≤ 2 μm, were discriminated from fenestrae based on morphology and size \[[@B16],[@B24],[@B27]\]. For each experimental variable, 10 images in the periportal and pericentral zones (regions up to 100 μm in diameter) were randomly selected and captured at both magnifications. Three animals were tested at each time point. All experiments were repeated three times and data were expressed as mean (plus standard deviation of the mean).
Isolation of liver endothelial cells (LECs)
-------------------------------------------
LECs were isolated using a modification of the procedure described by Braet et al. \[[@B42]\] and Smedsrod and Pertoft \[[@B43]\]. Briefly, the liver was washed and perfused through the portal vein with balanced salt solution and 0.05% collagenase A. Following excision and mincing, the cells were filtered and centrifuged. Enriched liver sinusoidal cells were then layered on a two-step percoll gradient (25/50%) and centrifuged for 20 minutes at 900 g. The intermediate, 25/50% zone is enriched with LECs and Kupffer cells. Following selective adherence of Kupffer cells, LECs were spread on collagen coated plastic slides for 4 hrs and extensively washed. Based on EM such cultures are estimated to be 95% pure.
*In vitro*shear stress
----------------------
LECs grown on plastic collagen-coated slides were subjected to shear stress forces produced between a stationary base plate and a rotating cone \[[@B31]\]. High-level shear stress forces of 10 dynes/cm^2^were enforced for 5 or 15 minutes at which time the cells were washed and either used for immunofluorescence or RNA extraction.
Immunofluorescence
------------------
Cells were fixed in 2% paraformaldehyde followed by 1% triton paraformaldehyde solution. The slides were then immersed in blocking solution and stained with either anti VEGFR-1, VEGFR-2, neuropilin-1, VE-cadherin, β-catenin or NFκb. Cy2 or rhodamine (TRITC) conjugated secondary antibodies were used.
RNA extraction
--------------
RNA was extracted from LECs by the RNAeasy kit (Qiagen, Chatsworth, CA) according to manufacturer\'s protocol and treated with DNase.
Real time RT-PCR
----------------
RNA samples were reversed transcribed and amplified using the QuantiTect SYBR Green RT-PCR kit (Qiagen) and appropriate primers at concentrations of 90 nM to 125 nM. The one-step RT-PCR was carried out at a Rotor-Gene 2000 real time cycler (Corbett Research, Australia). The thermal cycling conditions included 95°C for 15\' followed by 45 cycles of amplification at 94°C 20\", 60°C 15--30\", 72°C 15\". Samples were monitored after elongation by SYBR Green dye binding to the amplified double stranded DNA at 72°C--78°C. All samples were amplified in duplicates and each experiment was repeated twice. Quantitation was carried out using a standard curve. The Rotor-Gene analysis software was used for the calculation of the amount of each RNA sample.
Statistical analysis
--------------------
Significance was determined with the Mann Whitney two-sided U-test. Differences were considered significant when when p ≤ 0.05.
Authors\' contributions
=======================
FB and GS conceived the design and coordination of the study and drafted the manuscript and assessed LEC ultrastructure, MS carried out cell isolation, shear stress experiments and immunofluorescence. MP carried out Real time PCR and participated in animal procedures and drafting the paper. SB carried out portal blood flow evaluation. NK participated in animal procedures, NR participated in design and coordination. All authors read and approved the final manuscript.
Acknowledgments
===============
Israel Science Foundation 537/01, Chief Scientist\'s Office of the Israel Ministry of Health 5002, Mars-Pittsburgh Foundation for Medical Research 182-012, Rappaport Family Institute Fund. This research was partially supported by the \"Fund for Scientific Research-Flanders\" (grant N° 1.5.001.04N (F.B.)). F.B. is a postdoctoral researcher of the \"Fund for Scientific Research-Flanders\".
|
PubMed Central
|
2024-06-05T03:55:47.992703
|
2004-9-1
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519024/",
"journal": "Comp Hepatol. 2004 Sep 1; 3:7",
"authors": [
{
"first": "Filip",
"last": "Braet"
},
{
"first": "Maria",
"last": "Shleper"
},
{
"first": "Melia",
"last": "Paizi"
},
{
"first": "Sergey",
"last": "Brodsky"
},
{
"first": "Natalia",
"last": "Kopeiko"
},
{
"first": "Nitzan",
"last": "Resnick"
},
{
"first": "Gadi",
"last": "Spira"
}
]
}
|
PMC519025
|
1. Type I Restriction-Modification enzymes
==========================================
Type I R-M enzymes are multifunctional, multisubunit enzymes that provide bacteria with protection against infection by DNA-based bacteriophage \[[@B5]\] They accomplish this through a complex restriction activity that cuts the DNA at random locations, which can be extremely distal (\>20 kbp) from the enzyme\'s recognition sequence. In fact, the enzyme is capable of two opposing functions (restriction and modification), which are controlled enzymatically through an allosteric effector (ATP) and temporally through the assembly of the holoenzyme. In addition, the R-M enzyme has a powerful ATPase activity, which is associated with DNA translocation prior to cleavage; it is this translocation process that leads to random cleavage sites. Therefore, these enzymes are unusual molecular motors that bind specifically to DNA and then move the rest of the DNA through this bound complex (Fig [1](#F1){ref-type="fig"}).
::: {#F1 .fig}
Figure 1
::: {.caption}
######
DNA Translocation by TypeI Restriction-Modification enzyme. The yellow block represents the recognition sequence for the enzyme. The enzyme binds at this site and upon addition of ATP, DNA translocation begins. During translocation, an expanding loop is produced.
:::
:::
Type I R-M enzymes fall into families based on complementation grouping, protein sequence similarities, gene order and related biochemical characteristics \[[@B6]-[@B8]\]. Within one sub-type (the IC family) there are three well-described members, including EcoR124I, which is the focus of our interest. This enzyme recognises the DNA sequence GAAnnnnnnRTCG \[[@B9]\] and is comprised of three subunits (HsdR,M,S) in a stoichiometric ratio of R~2~M~2~S \[[@B10],[@B11]\], (Fig [2](#F2){ref-type="fig"}). However, Janscák *et al*. also showed that the *Eco*R124I R-M holoenzyme exists in equilibrium with a sub-assembly complex of stoichiometry R~1~M~2~S \[[@B11]\] which is unable to cleave DNA, but retains the ATPase and motor activity \[[@B12]\]. The HsdS subunit is responsible for DNA specificity; HsdM is required for DNA methylation (modification activity) and together they can produce an independent DNA methyltransferase (M~2~S) \[[@B13],[@B14]\]. HsdR, along with the core MTase is absolutely required for DNA cleavage (restriction activity) and is also responsible for ATP-binding and subsequent DNA translocation. Therefore, the HsdR subunit is the motor subunit of the enzyme and this subunit is associated with helicase activity \[[@B15]-[@B18]\]. However, the precise mechanism of DNA translocation is uncertain and the true nature of the motor function has yet to be fully determined but a number of important functional units -- nuclease, helicase and assembly domains have been identified within the HsdR subunit \[[@B19]\].
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Schematic of the motor subunits. HsdS denotes the DNA binding subunit; HsdM -- is the subunit responsible for DNA methylation and HsdR subunit, together with the core enzyme acts to restrict DNA.
:::
:::
2. A versatile molecular motor
==============================
The motor activity of Type I R-M enzymes is the mechanism through which random DNA cleavage is accomplished. Szczelkun *et al*. \[[@B20]\] showed that cleavage only occurs in a *cis*fashion indicating that the motor component of the HsdR subunit is able to \'grasp\' adjacent DNA and pull this DNA through the enzyme-DNA-bound complex. According to the Studier model \[[@B21]\] cleavage occurs when two translocating enzymes collide (Fig [3](#F3){ref-type="fig"}). However, highly efficient cleavage of circular DNA carrying only a single recognition sites for the enzyme suggests collision-based cleavage is not the whole story \[[@B20],[@B22]\].
::: {#F3 .fig}
Figure 3
::: {.caption}
######
Mechanism of DNA cleavage. The enzyme subunits are represented by: green ellipse -- M2S complex, green box -- HsdR subunit (with ATPase and restrictase activities; C denoting cleavage site). The black line represents DNA with the yellow box denoting the recognition sequence. Arrow shows direction of DNA translocation. For more details see text.
:::
:::
DNA translocation has been assayed in bulk solution using protein-directed displacement of a DNA triplex and the kinetics of one-dimensional motion determined. The data shows processive DNA translocation followed by collision with the triplex and oligonucleotide displacement. A linear relationship between lag duration and inter-site distance gives a translocation velocity of 400 ± 32 bp/s at 20°C. Furthermore, this can only be explained by bi-directional translocation. An endonuclease with only one of the two HsdR subunits responsible for motion could still catalyse translocation. The reaction is less processive, but can \'reset\' in either direction whenever the DNA is released (Fig [4](#F4){ref-type="fig"}).
::: {#F4 .fig}
Figure 4
::: {.caption}
######
Motor activity of type I R-M Enzyme. (a) The yellow block represents the DNA-binding (recognition) site of the enzyme, which is represented by the green object approaching from the top of the diagram and about to dock onto the recognition sequence. (b) The motor is bound to the DNA at the recognition site and begins to attach to adjacent DNA sequences. (c) The motor begins to translocate the adjacent DNA sequences through the motor/DNA complex, which remains tightly bound to the recognition sequence. (d) Translocation produces an expanding loop of positively supercoiled DNA. The motor follows the helical thread of the DNA resulting in spinning of the DNA end (illustrated by the rotation of the yellow cube). (e) When translocation reaches the end of the linear DNA it stops, resets and then the process begins again.
:::
:::
As previously mentioned, the final step of the subunit assembly pathway of the Type I Restriction-Modification enzyme EcoR124I produces a weak endonuclease complex of stoichiometry R~2~M~2~S~1~. We have produced a hybrid HsdR subunit combining elements of the HsdR subunits of the EcoR124I and EcoprrI \[[@B23]-[@B25]\] Type I Restriction-Modification enzymes. This subunit has been shown to assemble with the EcoR124I DNA methyltransferase (MTase) to produce an active complex with low-level restriction activity. We have also assembled a hybrid REase and the data obtained show that the hybrid endonuclease (REase) containing only HsdR(prrI) is an extremely weak complex, producing primarily R~1~-complex. The availability of the hybrid REase produced from core MTase(R124I) and HsdR(prrI), which provides a stable R~1~-complex, also gives a useful molecular motor that will not cleave the DNA that it translocates.
3. Sub-cellular localisation of R-M enzymes
===========================================
As can be seen from the above, DNA cleavage by Type I restriction enzymes occurs by means of a very unusual, and highly energy-dependent, mechanism. Therefore, these enzymes are believed to be involved not only as a defence mechanism for the bacterial cell, but also in some types of specialised recombination system controlling the flow of genes between bacterial strains \[[@B26],[@B27]\]. A periplasmic location would be well adapted for the restriction activity of R-M enzymes, but recombination requires a cytoplasmic location. Restriction enzymes protect the cells by cutting foreign DNA and could be assumed to be located at the cell periphery. Using immunoblotting to analyse subcellular fractions, Holubova *et al.*\[[@B28]\] detected that the subunits of the R-M enzyme were predominantly in the spheroplast extract. The HsdR and HsdM subunits were found in the membrane fraction only when co-produced with HsdS and, therefore, part of a complex enzyme, either methylase or endonuclease. Further studies have shown that the R-M enzyme is bound to the membrane *via*the HsdS subunit and that for some enzymes this may involve DNA \[[@B29]\].
4. Uses of the EcoR124I molecular motor: polymer-protein conjugates in nanobiotechnology
========================================================================================
One of the major obstacles for the practical application of single molecule devices is the absence of control methods in biological media, where substrates or energy sources (such as ATP) are ubiquitous. Synthetic polymers offer a robust and highly flexible means by which devices based on single biological molecules can be controlled. They can also be used to link individual biomacromolecules to surfaces, package them or to control their specific functions, thus expanding the applicability of the natural molecules outside conventional biological environments.
Moreover, a number of synthetic polymers have been recently developed that can potentially perform nanoscale operations in a manner identical to natural and engineered biopolymers. A key property of these materials is \'smart\' behaviour, especially the ability to undergo conformational or phase changes in response to variations in temperature and/or pH. Synthetic polymers with these properties are being developed for applications ranging from microfluidic device formation, \[[@B30]\] through to pulsatile drug release \[[@B31]-[@B34]\], control of cell-surface interactions \[[@B35]-[@B39]\], as actuators \[[@B40]\] and, increasingly, as nanotechnology devices \[[@B41]\].
In the context of bio-nanotechnology we focus here on the uses of one particular subclass of smart materials, i.e. substituted polyacrylamides, but it should be noted that there are many more examples of synthetic polymers and engineered/modified biopolymers that exhibit responsive behaviour and new types and applications of smart materials are constantly being reported.
Poly(N-isopropylacrylamide) (PNIPAm) is the prototypical smart polymer and is both readily available and of well-understood properties \[[@B42]\]. PNIPAm undergoes a sharp coil-globule transition in water at 32 °C, being hydrophilic below this temperature and hydrophobic above it. This temperature (the Lower Critical Solution Temperature or LCST) corresponds to the region in the phase diagram at which the enthalpic contribution of water hydrogen-bonded to the polymer chain becomes less than the entropic gain of the system as a whole and thus is largely dependent on the hydrogen-bonding capabilities of the constituent monomer units (Fig [5](#F5){ref-type="fig"}). Accordingly, the LCST of a given polymer can in principle be \"tuned\" as desired by variation in hydrophilic or hydrophobic co-monomer content.
::: {#F5 .fig}
Figure 5
::: {.caption}
######
Inverse temperature solubility behavior of responsive polymers at the Lower Critical Solution Temperature (LCST). Left hand side shows hydrated polymer below LCST with entropic loss of water and chain collapse above LCST (right hand side).
:::
:::
4.1 Soluble PNIPAm-biopolymer conjugates
----------------------------------------
Covalent attachment of single or multiple responsive polymer chains to biopolymers offers the possibility of exerting control over their biological activity as, in theory at least, the properties of the resultant polymer-biopolymer conjugate should be a simple additive function of those of the individual components. This principle is now being widely exploited in pharmaceutical development, as covalent attachment of, for example, PEG chains to therapeutic proteins has been shown to stabilize the proteins without losing their biological function \[[@B43]-[@B48]\]. Polymer-biopolymer conjugates can be prepared as monodisperse single units, or as self-assembling ensembles depending on the chemistries used for attaching the synthetic component and on the associative properties of the polymer and/or biopolymer. Furthermore, by altering the response stimulus of the synthetic polymer, and how and where it is attached to the biopolymer, the activity of the overall conjugate can be very closely regulated. These chimeric systems can thus be considered as true molecular-scale devices.
Pioneering work in this area has been carried out by Hoffman, Stayton and co-workers, who engineered a mutant of cytochrome b5 such that a single cysteine introduced *via*site-directed mutagenesis was accessible for reaction with maleimide end-functionalised PNIPAm \[[@B49]\]. Since the native cytochrome b5 does not contain any cysteine residues this substitution provided a unique attachment point for the polymer. The resultant polymer-protein conjugate displayed LCST behaviour and could be reversibly precipitated from solution by variation in temperature. This approach has proved to be very versatile and a large number of polymer-biopolymer conjugates have now been prepared, incorporating biological components as diverse as antibodies, protein A, streptavidin, proteases and hydrolases \[[@B50],[@B51],[@B50],[@B51]\]. The biological functions or activities of these conjugate systems were all similar to their native counterparts, but were switched on or off as a result of thermally induced polymer phase transitions. Of especial note have been the recent reports of a temperature and photochemically switchable endoglucanase, which displayed varying and opposite activities depending on whether temperature or UV/Vis illumination was used as the switch \[[@B52]\].
4.2. Controllable DNA packaging and compartmentalization devices
----------------------------------------------------------------
We are currently developing responsive polymers as a switch to control the EcoR124I motor function and are investigating this polymer-motor conjugate as part of an active drug delivery system. We aim for the practical demonstration of a nano-scale DNA packaging/separation and delivery system uniting the optimal features of both natural and synthetic molecules. In essence, we assemble a supramolecular device containing the molecular motor capable of binding and directionally translocating DNA through an impermeable barrier. To control the process of translocation in biological systems, where a constant supply of ATP is present, we have added to the motor subunit of EcoR124I the thermoresponsive poly(N-isopropylacrylamide) (PNIPAm), which, through its coil-globule transition, acts as a temperature-dependent switch controlling motor activity.
PNIPAm copolymers with reactive end-groups are being attached to a preformed R subunit of the motor *via*coupling of a maleimide-tipped linker on the synthetic polymer terminus to a cysteine residue. This residue has been selected, as it is both accessible and located close to the active centre on the R subunit of the motor. The protein-polymer conjugates are stable to extensive purification and, when combined with M2S complex, the activity of this conjugate motor system is similar to the native counterpart, but can be switched on or off as a result of thermally induced polymer phase transitions \[[@B53],[@B54]\].
Thus the conjugation of the responsive polymer to the molecular motor generates a nano-scale, switchable device (Fig [6](#F6){ref-type="fig"}), which can translocate DNA under one set of conditions (i.e. into a protective capsule or into a compartment). Conversely, in another environment (e.g. inside cells), in response to changed conditions (e.g. changed temperature, pH) the polymer switch will change its conformation, allowing ATP to power the motor, releasing DNA from capsules or compartments.
::: {#F6 .fig}
Figure 6
::: {.caption}
######
Schematic representation of the molecular motor function controlled by a thermoresponsive polymer switch. R, M and S denote the specific motor subunits. Chain-extension of the polymer below LCST provides a steric shield blocking the active site. Chain collapse (above LCST) enables access to the active site and restoration of enzyme function. For more details see text.
:::
:::
The conjugation of the motor with synthetic polymers brings additional advantages. One such benefit arises from the ability to functionalise the polymer side chains or terminus in a way that allows attachment of the entire complex to surfaces for sensing and device applications.
Therefore, although our hybrid polymer-protein conjugate was originally aimed at gene targeting (as it has the potential to increase the delivery of intact DNA to cell nuclei and thereby increase gene expression) this system may also be used in building automated nano-chip sensors, therapeutic and diagnostic devices, where DNA itself would be a target, or where DNA might be used as a \'conveyor-belt\' for attached molecules. The strength of the molecular motor has proven sufficient to disrupt most protein-DNA interactions and thus numerous processes and applications where highly localised force is required can also be envisaged.
5. Conclusions
==============
The use of synthetic polymers offers a number of possibilities, which otherwise could not be exploited or would be difficult to take advantage of, if purely biological systems were used. Moreover, the combination of the properties of molecular motors with \"smart\" polymers has hitherto been unexplored and represents a novel concept in nanotechnology, which could ultimately lead to a wholly new class of molecular devices. Nanoscale control of molecular transport *in vitro*and especially *in vivo*opens up a whole host of possibilities in medicine, including drug or DNA delivery (e.g. gene therapy), but also where protection of a therapeutic is required under one biological regime and release in another (e.g. prodrugs conjugated to DNA which can be released by nuclease-mediated degradation at the site of action). In addition, this system may allow the generation of switchable nanodevices and actuators, controllable by changes in the synthetic copolymer structure as well as ATP-mediated DNA motion and may pave the way for biofeedback-responsive nanosystems. It can be used for nano-scale isolation of various biochemical processes in separate compartments connected *via*a tightly controlled shuttle device.
In essence, this concept bridges the disciplines of chemistry and biology by using a biological motor to control chemistry and a synthetic polymer to regulate biological processes.
Author\'s contributions
=======================
KF conceived the idea of using the modified R-M enzyme as a molecular motor and carried out, with co-workers, the molecular studies of the motor components, SSP carried out the polymer synthesis, polymer-motor conjugations and functional studies, CA designed and participated in the synthesis of smart polymers and DCG conceived of the study. All authors participated in study design and coordination as well as the reading and approval of the final manuscript
Acknowledgements
================
This work is supported by a Wellcome Trust Showcase grant (Grant Reference 067484) and Institute of Biomedical and Biomolecular Sciences, University of Portsmouth.
|
PubMed Central
|
2024-06-05T03:55:47.995232
|
2004-9-6
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519025/",
"journal": "J Nanobiotechnology. 2004 Sep 6; 2:8",
"authors": [
{
"first": "Sivanand S",
"last": "Pennadam"
},
{
"first": "Keith",
"last": "Firman"
},
{
"first": "Cameron",
"last": "Alexander"
},
{
"first": "Dariusz C",
"last": "Górecki"
}
]
}
|
PMC519026
|
Background
==========
For most people who are able to access and tolerate highly active antiretroviral therapy (HAART), HIV/AIDS has become a chronic condition characterized by cycles of illness and wellness. People live longer lives, but with physical, psychological and social challenges that affect quality of life \[[@B1]-[@B3]\]. Evidence of this phenomenon may be found in qualitative studies describing the ways in which improved health has also brought about different and unforeseen social, psychological and physical challenges for many people who had previously been facing end-stage disease.
For instance, Brashers et al (1999) identified four categories of \"uncertainties\" resulting from the experience of \"revival\" brought about by HAART, including (a) renegotiating feelings of hope and future orientation in the face of questionable durability of immune restoration; (b) fear about social roles and identities, in the transition from a person who is dying to a person living with a chronic illness; (c) concerns with interpersonal relations, including the potential of stigmatizing reactions from employers and co-workers; and, (d) reconsidering the quality of their lives, captured in this quote from one participant, \'The good news is you\'re going to live, the bad news is you\'re not going to enjoy the rest of your life\' \[[@B1]\].
Sowell et al. (1998) used in-depth interviews to explore the psychological changes and care delivery issues experienced by HIV-positive men who were facing end-stage disease but had experienced dramatic physical improvements \[[@B4]\]. Key findings included themes around protease inhibitors as a reprieve from death, shifting perspectives on roles and relationships, and a renewed need for advocacy related to care, treatment and support. Others have examined particular aspects of living with HIV in the post-HAART era, such as challenges related to income and employment \[[@B5]\]. Along with qualitative literature, the HIV communities themselves have responded with a wave of community-based studies, publications and programming to address challenges related to living with the ups and downs of life on combination therapies \[[@B6]-[@B9]\].
Quantitative studies exploring the life-and health-related consequences of living with HIV are limited. An exception is the HIV Cost and Services Utilization Survey in the United States, which described physical and social role restrictions in a nationally representative sample \[[@B10]\]; however, no similar work exists in Canada. The American study was undertaken during the early years of HAART, and so the majority of participants were not yet on protease inhibitors. As such, there is a gap in the literature in terms of studies that systematically quantify the prevalence of life-and health-related challenges associated with living with HIV since the advent of HAART.
The International Classification of Functioning, Disability and Health (WHO, 2001) offers a useful framework for studying disablement and health-related consequences of disease based on the following three concepts: impairments, activity limitations and participation restrictions \[[@B11]\]. Impairments are understood to be problems with physiological functioning or anatomical (e.g., organs, limbs) structure of the body. Activity limitations are defined as difficulties in executing a task or action. Finally, participation restrictions are problems relating to involvement in life situations. This classification system and its precursor, the International Classification of Impairments, Disabilities and Handicaps (WHO, 1980), have been used to frame a plethora of studies on a diverse array of diseases and conditions \[[@B12]-[@B15]\]. Furthermore, this framework has been used to conceptualize HIV \[[@B16]\], and informs the policy, research and advocacy work of organizations such as the Canadian Working Group on HIV and Rehabilitation \[[@B17]\].
This article addresses this gap in the literature by reporting on the results of a quantitative investigation into the prevalence of and associations among impairments, activity limitations and participation restrictions experienced by people living with HIV in British Columbia.
Methods
=======
Data sources
------------
Individuals living with HIV were involved in all stages of this project, from identification of the research question to data collection and analysis. A lead partner was the British Columbia Persons With AIDS Society (BCPWA), an organization of more than 3,600 HIV positive individuals living in British Columbia, which was created to provide support, information and advocacy for its members.
From May to September of 2002, the BCPWA in conjunction with the British Columbia Centre for Excellence in HIV/AIDS conducted a survey of HIV positive individuals living in British Columbia. The anonymous self-administered questionnaire was mailed to the 1508 HIV positive individuals registered with the BCPWA who had consented to receive mailings.
Definition of disability
------------------------
A section of the survey on diagnosed conditions asked participants to indicate if a doctor had ever in their lifetime diagnosed them with any conditions from a list of thirteen, including depression, schizophrenia, bipolar disorder and post-traumatic stress disorder, as well as a space to indicate any diagnoses that was not present in the list.
Participants identified their experiences during the past month using check-lists of impairments, activity limitations and participation restrictions that included space to identify unlisted items.
Participants were asked: \"Within the last month have you experienced any of the following\...\" after which they were able to check off symptoms from a list of twenty-two, including a space for unlisted items. The list of impairments was categorized into mental, internal system, sensory and neuromusculoskeletal groups based on the International Classification of Functioning, Disability and Health \[[@B12]\]. Mental impairments included reduced libido, poor concentration, poor appetite, chronic fatigue, decreased endurance, decreased memory, impaired cognition and aphasia. Internal impairments included diarrhea, gastric reflux, shortness of breath, constipation, wasting, weakness, vomiting and incontinence. Sensory impairments included headaches, altered sensations, nausea, mouth pain and decreased vision. Neuromusculoskeletal impairments included altered muscle tone, stiff joints, seizures, hemiparesis and paraparesis. This section was followed by a question which asked participants how much HIV-related pain they had experienced in the past month, with categorical options including none, a little bit, mild or infrequent, moderate, severe or persistent and don\'t know. Participants were also asked to pinpoint the location(s) of their HIV related pain.
Activity limitations were addressed by asking the participants \" \[h\]ow well can you manage these typical daily activities?\" with an indication to circle the response which best describes their experience in the past month. A fifteen-item list including ability to walk one block, eat, shower, and dress followed. For each item, participants indicated whether they were (a) completely able, (b) somewhat limited or (c) unable to perform the activity. Overall prevalence of activity limitations was calculated by including anyone indicating (b) or (c) for any one of the fifteen items.
In the same way, participants were asked \" \[h\]as your health limited your usual \[role/participation\]\" in any of a number of categorical activities and functions. Participants were indicated to choose the response that came closest to the way they had been feeling during the past month. A ten-item list was used to assess levels of restriction in social, student, and cultural roles. Participants indicated whether they were (a) not limited, (b) somewhat limited or (c) very limited with respect to their ability to function in these roles. Overall prevalence of participation restrictions was calculated by including anyone indicating (b) or (c) for any one of the ten items.
Statistical analysis
--------------------
Rates of impairments, activity limitations and participation restrictions among the participants were compared across three categories of CD4 cell counts (≤ 200 cells/mm3, 201 to 500 cells/mm3 and \> 500 cells/mm3) using a chi-squared test for categorical variables and the Kruskal-Wallis test for continuous variables. Bonferroni corrections for multiple comparisons were done for each item and those which remained significant are indicated in bold.
To test the hypothesis that social role restrictions would be more strongly associated with mental function impairments and personal care and mobility limitations, a series of logistic regression models were tested with each category of impairment and limitation. A dichotomous outcome was used, collapsing \"somewhat\" and \"very much\" social role restriction into any social restriction. Likewise, specific activity limitations were dichotomized into \"no limitations\" vs. \"some effort\" required or \"unable\" to accomplish the activity. Associations of social restriction with impairment categories and specific activity limitations were examined univariately and in adjusted models accounting for age, sex, income, depression, pain, risk category (men who have sex with men, injecting drug users, heterosexual contact, combination) and number of symptoms for activity limitation models.
A scoring system was then used to develop categories of activity limitation and participation restriction. If a participant indicated an activity limitation item at the highest level (\"unable\" to accomplish) or a participatory role restriction at the highest level (\"very much\" restricted), two points were received, while participants indicating an activity limitation item at moderate level (requiring \"effort\" to accomplish) or a participation restriction item at a moderate level (\"somewhat\" restricted), one point was received. Overall scores for participation restriction and activity limitation were therefore dependent on both the severity and total number of challenges in activities or participatory roles.
The participation restriction score, with an overall maximum of 20, was then categorized into three levels: 0 to 5 points, 6 to 10 points and \> 10 points, based on the population distribution of the score. Likewise, the activity limitation score, with an overall maximum of 28, was also categorized based on distribution as follows: 0, 1 to 5 points, and \> 5 points. The higher the score, the greater the disablement.
An overall model examined the associations of increasing participation restriction level with number of impairments and activity limitation scores, testing the hypothesis that impairments may account for some of the associations seen between activity limitations and participation restrictions, but that both of the former would have independent associations with the latter. Ordinal logistic regression was implemented, using the three-level participation restriction outcome and testing number of symptoms, categorical limited activity score, pain and mental diagnoses as explanatory variables. All models were stratified on CD4 levels, with separate models built for individuals with counts below 200 cells/mm3, and adjusted for age, gender, employment, years since diagnosis and risk category.
Results
=======
Population characteristics
--------------------------
Of the 762 people living with HIV who completed the survey, 614 provided information about their CD4 levels and were included in this analysis. The population answering the BCPWA survey was comprised mainly of white (88.7%), sexual-minority males (76.6%) between the ages of 30 to 49 (63.9%). The 148 respondents who were not included in the analysis because they did not provide CD4 information were in a lower income bracket (42.5% vs 19.9%; p-value \< 0.001), were more likely to be current IDUs (11.3% vs 4.3%; p-value \< 0.001) and more likely to be First Nations/Inuit/Metis (17.6% vs. 6.5%; p-value \< 0.001).
A comparison of all BCPWA members who received the survey and the subset who responded found a similar distribution of age and a similar proportion identifying as Aboriginal (7.1% vs. 8.7%). The proportion of females was higher among the total BCPWA population than among the subset of respondents (13.5% vs.10.2%; p = 0.001).
Prevalence of impairments, activity limitations and participation restrictions
------------------------------------------------------------------------------
Table [1](#T1){ref-type="table"} describes levels of diagnoses, impairments, activity limitations and participation restrictions among participants. Mental health diagnoses were reported by 62.9% (N = 479) of the participants. The most prevalent diagnosis was depression with an overall prevalence of 58.1%. Among those listing one or more diagnoses, 92.5% experienced depression as one of their diagnoses. While the overall number of participants with depression appeared lower among those with CD4 ≤ 200 cells/ml, the percent of those listing depression out of those with any diagnosis remained close to 92.5% across all strata.
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Prevalence of diagnosed conditions, impairments and pain, activity limitations and participation restrictions experienced by BCPWA participants by CD4 cell counts
:::
**CD4 \< 200** **CD4 201 to 500** **CD4 \> 500** **p-value**
------------------------------------------------------- ---------------- -------------------- ---------------- -------------
**Diagnosed conditions**
Depression 64 (52.0) 183 (59.2) 110 (61.5) 0.238
General Anxiety 11 (8.9) 34 (11.0) 14 (7.8) 0.488
Post traumatic Stress 6 (4.9) 18 (5.8) 13 (7.3) 0.677
Panic Disorder 8 (6.5) 35 (11.4) 12 (6.7) 0.124
**Median number of impairments (IQR)** **9 (5, 13)** **7 (2.5, 12)** **7 (3, 12)** **0.006**
**% With any impairment** 120 (97.6) 285 (92.5) 161 (89.9) 0.041
**Pain**
None 25 (20.7) 82 (29.4) 48 (28.4) 0.079
Little/mild 35 (28.9) 89 (31.9) 62 (36.7)
Moderate/severe 61 (50.4) 108 (38.7) 59 (34.9)
**Median number of activity limitations (IQR)** 3 (1, 7) 3 (1, 7) 2 (1, 5) 0.015
**% With any Activity Limitation** 108 (87.8) 236 (77.4) 137 (76.5) 0.031
**Median number of Participation Restrictions (IQR)** 7 (4, 9) 7 (3, 9) 7 (3, 9) 0.251
**% With any Participation Restrictions** 121 (98.4) 278 (91.5) 161 (89.9) 0.017
**Bold**print indicates comparison that remained significant at the p = 0.016 level after Bonferroni correction for multiple comparisons.
:::
The presence of multiple impairments among the participants was also high, with a median of 7 (3,12) impairments and approximately one third of the participants experiencing more than ten impairments. At least one impairment was reported by 91.5% (N = 697). There was a significant difference in the distribution of impairments across CD4 categories, which remained after Bonferroni correction (CD4 ≤ 200 cells/ml vs CD4 \> 500 cells/ml, p-value= 0.002; CD4 ≤ 200 cells/ml vs CD4 between 200 and 500 cells/ml, p-value = 0.017). Mental impairment was reported by 78.2% (N = 596), sensory impairment by 71.9% (N = 548), neuromuscular impairment by 49.5% (N = 377), and internal impairment by 81.0% (N = 617) of the participants.
Pain was reported by over half of the participants, and by over three quarters of the participants with CD4 ≤ 200 cells/ml. Approximately one-third reported little or mild pain and 37.1% reported moderate or severe pain. For participants with lower CD4 counts, more people reported moderate and severe pain (50.4% vs. 38.7% vs. 34.9%; p-value 0.08), although comparisons of each CD4 category to the others showed no significant differences.
Activity limitations were reported by 80.6% (N = 607) of the participants. The median number of activity limitations reported by an individual was 3 (1, 7). Six hundred and ninety-nine individuals (93.2%) reported some level of participation restriction. The median number of participatory roles in which individuals felt somewhat or highly restricted was 7 (3, 9). Although distributions of activity limitations and participation restrictions were significantly different, adjustment for multiple comparisons across the CD4 categories resulted in no significant difference in prevalence.
Figures [1](#F1){ref-type="fig"},[2](#F2){ref-type="fig"},[3](#F3){ref-type="fig"} summarize the prevalence of impairments, activity limitations and participation restrictions, respectively. The most prevalent impairments experienced by participants included diarrhea (57.1%), reduced libido (55.8%), general weakness (48.2%), poor concentration (47.0%), headaches (46.9%) and chronic fatigue (46.6%). Vigorous and moderate activities, sexual activities and household chores were the most frequently reported limitations. The level of participation restrictions was high for all CD4 categories, with sexual roles, student/employee roles and financial roles being the most prevalent.
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Prevalence of specific impairments for participants with CD4 counts ≤ 200 cells/mm3 (speckled bars), 201 to 500 cells/mm3 (downward diagonally-striped bars) and \> 500 cells/mm3 (horizontally-striped bars). Significant p-value from chi-square test across CD4 categories.
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Prevalence of specific activity limitations for participants with CD4 counts ≤ 200 cells/mm3 (speckled bars), 201 to 500 cells/mm3 (downward diagonally-striped bars) and \> 500 cells/mm3 (horizontally-striped bars). Significant p-value from chi-square test across CD4 categories.
:::
:::
::: {#F3 .fig}
Figure 3
::: {.caption}
######
Prevalence of specific participation restrictions for participants with CD4 counts ≤ 200 cells/mm3 (speckled bars), 201 to 500 cells/mm3 (downward diagonally-striped bars) and \> 500 cells/mm3 (horizontally-striped bars). Significant p-value from chi-square test across CD4 categories.
:::
:::
Univariate associations of impairments and activity limitations on social role restrictions
-------------------------------------------------------------------------------------------
Table [2](#T2){ref-type="table"} describes the univariate odds ratios for presence of social role restriction (yes vs. no) based on impairment categories and type of activity limitation. All impairments and activity limitations were significantly associated with social role restriction. Social role restriction was most strongly associated with limitations in using the toilet, (OR: 18.5 for toilet difficulties vs. no toilet difficulties; 95%CI: 4.5 -- 76.3), followed by banking, (OR: 11.3 for banking difficulties vs. no banking difficulties; 95%CI: 5.4 -- 23.5). Social role restriction had the weakest association with getting out of bed, (OR: 3.6 for difficulties getting out of bed vs. no difficulties; 95%CI: 2.3 -- 5.6). With respect to impairment categories, social role restriction was most strongly associated with mental impairments (OR 7.0 for mental impairments vs. no mental impairments; 95% CI 4.7--10.4) although the other three impairment categories had odds ratios higher than four.
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Univariate and adjusted odds ratios for social role restriction given each activity limitation and prevalence of these limitations in this population
:::
**Activity** **Prevalence (%)** **Odds Ratio (95% CI)** **Adjusted Odds Ratio (95% CI)\***
----------------------------------- -------------------- ------------------------- ------------------------------------ ----------------------------
≤ 200 cells/ml \> 200 cells/ml
Getting dressed 8.9 (54) 4.03 (2.03 -- 8.00) 7.90\*\* (0.45 -- 137) 1.60 (0.47 -- 5.44)
Using the toilet 6.3 (38) 18.47 (4.47 -- 76.3) 9.14\*\* (0.52 -- 159) **37.7\*\* (2.29 -- 620)**
Showering 10.2 (62) 6.62 (3.15 -- 13.91) 3.38 (0.41 -- 28) 2.30 (0.57 -- 9.18)
Walking one block 13.2 (80) 5.33 (2.86 -- 9.91) 3.33 (0.54 -- 20) 3.40 (0.72 -- 16)
Banking 16.4 (99) 11.27 (5.42 -- 23.45) 3.78 (0.33 -- 42) **3.30 (1.09 -- 10)**
Getting out of bed 20.8 (125) 3.63 (2.34 -- 5.63) 1.15 (0.31 -- 4.14) 1.89 (0.79 -- 4.54)
Driving 21.5 (121) 3.51 (2.25 -- 5.47) 1.59 (0.45 -- 5.49) 1.93 (0.87 -- 4.31)
Eating 20.1 (122) 4.66 (2.89 -- 7.53) 0.87 (0.26 -- 2.94) **3.17 (1.07 -- 9.37)**
Public Transportation 25.2 (148) 6.75 (4.19 -- 10.86) 4.36 (0.91 -- 21) **3.29 (1.32 -- 8.20)**
Laundry 28.1 (171) 7.53 (4.73 -- 11.98) **8.41 (1.32 -- 54)** **3.26 (1.41 -- 7.52)**
Groceries 32.6 (198) 8.43 (5.38 -- 13.21) **3.97 (1.21 -- 13)** **2.97 (1.37 -- 6.43)**
Household chores 39.6 (241) 6.89 (4.72 -- 10.06) **5.12 (1.62 -- 16.2)** **3.11 (1.59 -- 6.10)**
Moderate activity 42.4 (258) 5.87 (4.11 -- 8.37) 2.10 (0.76 -- 5.77) **3.10 (1.62 -- 5.93)**
Sexual activity 46.6 (283) 5.33 (3.81 -- 7.47) 2.56 (1.00 -- 6.57) **2.06 (1.16 -- 3.68)**
Vigorous activity 71.9 (437) 5.09 (3.61 -- 7.19) 2.69 (0.97 -- 7.48) **2.60 (1.37 -- 4.96)**
**Impairment Category**
Mental functioning 78.7 (481) 7.02 (4.73 -- 10.4) **18.71 (2.31 -- 151)** **4.32 (2.20 -- 8.51)**
Neuro-musculoskeletal functioning 49.3 (301) 4.12 (2.98 -- 5.69) 1.77 (0.67 -- 4.68) **1.76 (1.03 -- 3.00)**
Sensory functioning 72.3 (442) 4.12 (2.94 -- 5.78) 0.85 (0.27 -- 2.65) **2.17 (1.20 -- 3.93)**
Internal functioning 81.4 (500) 4.15 (2.82 -- 6.12) 2.48 (0.69 -- 8.91) 1.84 (0.96 -- 3.51)
\*Adjusted for age, gender, income, number of impairments (for activity limitation models), pain, risk category and doctor-diagnosed depression
**\*\***Small sample size; analysis stratified on CD4 but not adjusted due to zero cells.
:::
Adjusted odds ratios stratified by CD4 counts remained significant for getting groceries, doing laundry, household chores, and mental functioning, regardless of CD4 levels, although the estimates were higher for participants with counts under 200 cells/mm3. For those with CD4 counts above 200 cells/mm3, difficulties with eating, public transportation, moderate or vigorous activities, sexual activities, neuromuscular functioning and sensory functioning also remained significantly associated with social restrictions. Adjusted odds ratios for using the toilet and getting dressed were unable to be estimated as these were co-linear with the outcome. Stratified, unadjusted estimates of 9-fold and 37-fold increases in social restriction were seen with limitations in toileting.
Stratification by CD4 levels indicated a general effect modification across activity limitations and impairment categories, with greater, although more unstable, associations with social restrictions being found among participants with \< 200 cells/mm3.
Multivariate associations of impairments and activity limitations with participation restriction levels
-------------------------------------------------------------------------------------------------------
Table [3](#T3){ref-type="table"} describes the ordinal logistic regression model examining associations with a three-category measure of participation restriction level, stratified by CD4 cell counts. Among those with CD4 counts under 200 cells/mm3, being in a higher category of participation restriction was strongly associated with having activity limitation scores above ten, and was marginally inversely associated with being on antiretrovirals. Increasing number of impairments did not show any significant association.
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Ordinal logistic regression estimating the probability of being in a higher category of the three level participation restriction score based on levels of impairment, limited activity scores and pain.
:::
**CD4 ≤ 200**
---------------------------- --------------- --------------
**Limited Activity score**
None 1
1--5 3.58 0.91 -- 14.2
\> 5 24.7 4.85 -- 125
**Number of impairments** 1.01 0.94 -- 1.12
**Antiretroviral use** 0.28 0.08 -- 0.93
CD4 \> 200
**OR\*** **95% CI**
**Limited Activity score**
None 1
1--5 2.67 1.40 -- 5.12
\> 5 8.56 3.90 -- 18.8
**Number of impairments** 1.19 1.12 -- 1.25
**Pain**
None 1
Some/mild 1.31 0.71 -- 2.44
Mod/severe 1.78 0.85 -- 3.75
**Antiretroviral use** 1.39 0.83 -- 2.35
\*adjusted for age, gender, employment, education, years since diagnosis and risk category
:::
Among participants with CD4 counts above 200 cells/mm3, being in a higher category of participation restriction was associated with increasing levels of limited activity \[(OR: 2.7 for limited activity scores of 4--10 vs. scores \< 4; 95%CI: 1.4--5.1) and (OR: 8.6 for limited activity scores \> 10 vs. scores \< 4; 95%CI: 3.9--18.8)\]. A higher participation restriction category was also significantly associated with increasing number of impairments, with a 19% increase in the odds with additional impairment. Increased participation restriction level was only marginally significantly associated with moderate or severe pain; however, point estimates for the pain categories suggested a dose response relationship, as did the inclusion of pain as a continuous variable (p-value 0.066).
Discussion
==========
This study has demonstrated that a population-based sample of people living with HIV in British Columbia have been experiencing strikingly high levels of depression, body impairments, activity limitations and participation restrictions. The latter two categories were higher among this population than a national survey of HIV positive persons in the United States\[[@B10]\]. However, the American study was conducted prior to HAART availability, underscoring the importance of examining quality of life issues faced in the post-HAART era. In a study examining similar concepts of activity limitation among cancer patients, the percent experiencing any difficulties ranged from 18.0 to 70.0%, depending on the type of cancer, but was only 30.0% overall \[[@B18]\]. Another study of cancer survivors found a similar prevalence to that seen in the present study (80.0%) when including all ambulatory difficulties, not just activities of daily living \[[@B19]\]. The elevated levels of limitation among the BCPWA population were also emphasized in a comparison with the general population and with those identifying as suffering from a chronic illness, where the least difference showed a five-fold increase \[[@B20]\].
The level of depression among this population was extremely high. Nearly 60.0% of the participants reported ever having been diagnosed with depression by a doctor. Levels of depression among HIV positive persons reported in the literature range from 5.0% to 40.0%, although among HIV positive women, 60.0% prevalence has been reported \[[@B21],[@B22]\]. Depression is generally found to be higher, regardless of HIV status, among women and men who have sex with men \[[@B21]\]. Studies conducted among MSM have found prevalence of major depression to range from 23.0 to 37.0%, while Aboriginal populations in general, and Aboriginal MSM in particular, have been shown to have higher depression scores \[[@B23]-[@B25]\]. Likewise, depression among IDU populations has been seen to be as high as 47.0% \[[@B24]\]. Some study scales may capture current depression but may miss the experience of people with recurrent episodes who feel well at the time of testing. The high level of depression recorded in this study may be the result of a large percentage of men who have sex with men in the sample as well as the survey\'s ability to capture more cumulative measures of depression. The high prevalence may be due in part to the self-report of the diagnosis as well, which may result in recall bias and increased reporting of non-diagnosed depression. Regardless, this common experience of depression demands consideration by researchers, policy-makers and care providers concerned with the quality of life of people living with HIV.
The prevalence of impairments was also high, with diarrhea at the top of the list, followed by problems with fatigue and endurance. Furthermore, challenges with daily activities and social roles were extremely common, at greater than 80.0 and 90.0%, respectively. The high proportion of individuals experiencing impairments, activity limitations and participation restrictions sheds light on the spectrum of challenges related to living with HIV. Even among those with relatively high CD4 counts, the impact of HIV on disability and health is not trivial.
Of note, the differences experienced between people according to categories of CD4 levels were less and less apparent going from impairments (problems at the level of organ or body part) to activity limitations to participation restrictions (problems with social roles). This draws attention to the variety of influences affecting a person\'s ability to perform daily tasks and participate in regular societal roles above and beyond his/her clinical measures of disease status.
All types of activity limitation were associated with the experiencing of social role restrictions. After accounting for impairments, depression and pain levels, there remained significant associations between household upkeep, including laundry and groceries, and social role participation. Although it was hypothesized that personal care issues would have stronger associations, this was not the case. This may be because the severity of personal care limitations (dressing, eating, showering) is such that among those experiencing these limitations, the presence of pain or numerous impairments overshadows any independent association between the limitation and social restriction.
Household chores, getting groceries and doing laundry as well as moderate and vigorous activities had significant associations with social role restrictions and had the highest prevalence in this population. Therefore, interventions that target these types of limitations may provide the most benefit at a population level. Whether or not these interventions would have any impact on an individual\'s feelings of participatory restriction remains to be seen; however, coordinating these types of simple interventions might offer contact with people in need of social support.
Mental impairments were the most prevalent of the four impairment categories and were found to have a significant association with participation restrictions. These results mirror a study describing disability among a national sample of people living with HIV in the United States which reported a correlation between general fatigue and increased limitations in both physical and role functions \[[@B10]\]. Other reports have also found relationships among neuropsychological performance, depression, stress levels and perceived disability \[[@B26]\]. It is suggested that increased social support networks can result in improved mental health, which may indicate that the association between the presence of mental impairment and the ability to interact in social and community roles is not unidirectional.
The adjusted models (Table [3](#T3){ref-type="table"}) indicate that both impairments and activity limitations remain associated with participation restrictions independent of one another for people with high CD4 counts. The use of antiretrovirals among those with low CD4 counts is associated with lower participation restriction levels. Since this cannot be accounted for through a lessening of impairments or limitations among those on antiretrovirals, it is more likely a reflection of the type of support and interaction with the health care system among those who are able to access antiretrovirals.
Limitations of the study
------------------------
Limitations of the study include the somewhat homogeneous nature of the participants, which affects the generalizability of these findings to other populations. The participants were mainly white, sexual-minority males with moderate yearly incomes and stable housing. The under-representation of people who are homeless, injection drug users, female and Aboriginals becomes apparent when comparing the low proportions seen amongst the BCPWA membership to the higher proportions seen in incident cases reported by the British Columbia Centre for Disease Control \[[@B27]\].
The survey was sent to BCPWA members consenting to receive mail. Individuals who did not consent were more likely to reside in the Greater Vancouver region, suggesting a greater geographical representation from outside of this urban area. Non-consenting BCPWA members were also more likely to be female (15.8% vs 11.9%) and more likely to be First Nations, Inuit or Metis (27.1% vs 8.4%). Furthermore, because the survey was anonymous and self-reported, there are issues with missing data and incomplete records. For example, almost 20.0% of the sample, again representing a high proportion of women and First Nations, were excluded because of missing CD4 information. While the exclusion of this population may have affected the power and generalizability of the study, one may argue that challenges reported in this study may be an underestimation of the restrictions in this population due to compounding social inequity issues.
Lastly, there are limitations in the nature of self-reported diagnoses. Participants may have trouble recalling the presence or absence of impairments, limitations or restrictions over the past month. Although there was no direct incentive, participants may be biased towards increased reporting of problems as they may feel that this would be beneficial for program funding and support.
Despite these limitations, this survey represents a large provincial sample and is one of few attempts to collect information from a population-based sample on this scale. Furthermore, this is one of the first studies to systematically quantify levels of disablement among persons living with HIV.
Conclusions
===========
This study revealed a strikingly high prevalence of impairments, activity limitations and participation restrictions among a population-based sample of people living with HIV in British Columbia. The complicated interplay among these categories requires further study, but it is clear that interventions designed to help overcome activity limitations and social support programs are required, especially those addressing mental impairments and depression. While impairments and limitations are not always reversible, innovative programs that help people living with HIV address these challenges may help to decrease the subsequent high rates of participatory restrictions experienced. Antiretroviral treatments have enabled the prolongation of the lives of people who are HIV-infected; now we need to give due attention to optimizing the quality of these extended lives.
Authors\' Contributions
=======================
MR and KC carried out the statistical analyses; SN and AS participated in the design of the study and the development of the study instrument; PB participated in the conceptualization of the study and the interpretation of the results; RH participated in the conceptualization and design of the study. All authors read and approved the final manuscript.
Acknowledgments
===============
This work was supported by the Canadian Working Group on HIV and Rehabilitation (CWGHR), by the Michael Smith Foundation for Health Research through a Senior Scholar Award to Dr. Robert Hogg, a Doctoral Scholar Award to Paula Braitstein and a Training award to Melanie Rusch, as well as by the Canadian Institutes for Health Research through a Fellowship to Stephanie Nixon.
Special thanks to Ruth Marzetti and Ryan Kyle from the BCPWA society. The authors are indebted to all the members of the British Columbia PWA society who participated in this survey.
|
PubMed Central
|
2024-06-05T03:55:47.997326
|
2004-9-6
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519026/",
"journal": "Health Qual Life Outcomes. 2004 Sep 6; 2:46",
"authors": [
{
"first": "Melanie",
"last": "Rusch"
},
{
"first": "Stephanie",
"last": "Nixon"
},
{
"first": "Arn",
"last": "Schilder"
},
{
"first": "Paula",
"last": "Braitstein"
},
{
"first": "Keith",
"last": "Chan"
},
{
"first": "Robert S",
"last": "Hogg"
}
]
}
|
PMC519027
|
Background
==========
Comorbid chronic diseases are increasingly recognized as a significant factor in declining health. Of the 125 million Americans with chronic diseases, 48% are estimated to have at least one comorbidity, and 62% of persons over the age of 65 have two or more chronic illnesses.\[[@B1],[@B2]\] Approximately 25% of persons with chronic illness have some limitation in activity and the percent of persons with disability increases with increasing numbers of coexisting conditions.\[[@B2],[@B3]\] As the population in the United States ages, the number of persons with comorbid chronic disease will increase substantially. Primary care physicians will both provide and coordinate much of the care for this population \[[@B4]\].
Primary care for persons with chronic medical conditions differs from specialist care for these same conditions in the need to see both the forest and the trees: to address disease-specific issues and outcomes in the context of both coexisting medical conditions and the patient\'s psychosocial environment. To this end, practice guidelines developed from randomized controlled trials with strict inclusion criteria may not generalize well to the heterogeneity of primary care practice or the complex individual patient.
In the environment of competing demands that characterizes medicine in general, and primary care in particular; information on health outcomes that can be inferred from the medical record problem list may be particularly relevant in clinical decision making for persons with multiple chronic conditions. We chose to investigate the health outcome of physical well being for several reasons: It is relevant to both clinical and quality-of-life decision making; and previous findings have demonstrated that different combinations of chronic medical conditions have been shown to be associated with type and/or severity of disability \[[@B5],[@B6]\].
Longitudinal studies suggest that the cumulative effect of comorbid conditions is not simply additive: certain combinations of diseases may have a greater effect on outcomes than others. Combinations of diabetes plus obesity or heart disease \[[@B7]\], and arthritis plus diabetes, pulmonary disease or obesity \[[@B8]\] were significantly more detrimental to measures of health outcomes than either condition alone or in combination with other comorbidities. In a review of multiple longitudinal studies on comorbidity, Gijsen et al. found comorbidity to be a predictor of higher mortality, worse functional status, decreased quality of life, and increased health care utilization \[[@B9]\]. It is impractical for the primary care physician to maintain an awareness of specific combinations of chronic conditions that may characterize patients at risk for functional decline. However recognizing certain chronic medical conditions as potential \'red flags\' for further investigation would be useful.
We hypothesized that certain chronic diseases that often occur as comorbidities may have a greater impact than others on functional status outcomes over time. To explore this question, we analyzed data from the Medical Outcomes Study (MOS), a longitudinal study focusing on the care and medical outcomes of patients with specific common chronic conditions \[[@B10]\]. The MOS data have been previously used to study comparative effects of chronic conditions on physical well being over time \[[@B11]-[@B14]\]. These investigations have included analyses of the effects of anxiety disorder, varying levels of physical activity, and depression on health outcomes in the context of multiple chronic diseases.\[[@B12],[@B15],[@B16]\] We used this important data set to further explore the complexities of long-term health outcomes in a heterogeneous group of patients with comorbid chronic disease.
Our study used MOS data to investigate the relative effect of six different common chronic conditions (diabetes, coronary artery disease (CAD), congestive heart failure (CHF), chronic respiratory disease, musculoskeletal disease and depression) on measures of physical well being over the course of four years in patients with comorbidities. This data base is comprised of information from respondents with certain chronic medical conditions. There is no information on \'healthy\' respondents without any chronic conditions. Therefore we examined the relative effects of selected conditions relative to hypertension alone. We examined the presence of a specified level of decline in physical well being that had been verified to be clinically significant, rather than a change in the PCS score that might be statistically significant but of limited practical importance to patients. In addition, we analyzed the effect of specific diagnoses in the context of the total disease burden in an effort to identify possible \'sentinel\' conditions that may specifically contribute to functional decline for patients with multiple comorbidities.
Methods
=======
Study design
------------
The MOS was a four-year observational study that included assessment of health outcomes of chronically ill patients. Details of the study including design, sampling, site selection and clinician recruitment have been previously published\[[@B10],[@B16]-[@B18]\]
Study setting
-------------
MOS study sites were selected from three cities (Boston, MA, Chicago, IL and Los Angeles, CA), from both primary care (family practice and internal medicine) and specialty (endocrinology, cardiology and mental health) practices, and from both managed care and fee-for-service payment plans.
Sample and data collection
--------------------------
The original study sample consisted of patients with one or more of five chronic \"tracer\" conditions (hypertension, adult onset diabetes, myocardial infarction within the past six months, congestive heart failure or depression) approached during a visit with an MOS clinician during a two-week period in 1986. Of the 28,257 patients originally approached, 20,232 agreed to participate. From this group, patients were selected for follow up on the basis of diagnosis and completion of baseline data collection, as described elsewhere \[[@B18],[@B19]\]. Of the 3589 patients selected for follow-up, 2708 completed a baseline assessment, and 2235 were randomly selected for follow-up. Four-year follow-up data were obtained for 1574 of these 2235 (70%). For the current study, the chronic conditions of interest (diabetes, CAD, CHF, chronic respiratory disease, musculoskeletal conditions, and depression) were defined by combining the original tracer diagnoses with additional diagnoses determined by a structured medical history interview conducted by a trained clinician \[[@B17]\]. For example our category of CAD consists of persons with the original tracer condition of myocardial infarction within the past 6 months plus those with a history of angina, current symptoms of angina, and myocardial infarction more than one year ago. If information about a condition was missing, an independently derived probability of each diagnosis was substituted if the probability was at least 90%. The components of each of the main diagnoses are listed in Table [1](#T1){ref-type="table"}. We chose to analyze these conditions based on their high prevalence as well as frequent assessment in the literature on comorbidity and chronic disease management.
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Components of main disease categories
:::
**Main Disease** **Number (percent)^a^**
----------------------------------------------- -------------------------
**Diabetes** **359**
Type 2 diabetes mellitus 319 (88.9)
Type 1 diabetes mellitus 40 (11.1)
**CAD** **425**
Myocardial infarction within past 6 months 76 (17.9)
History of angina 104 (24.5)
Current angina 233 (54.8)
Myocardial infarction more than one year ago 135 (31.8)
**CHF** **159**
**Respiratory disease** **133**
Asthma 42 (31.6)
Chronic obstructive pulmonary disease 95 (71.4)
Other lung disease 23 (17.3)
**Musculoskeletal disease** **684**
Back pain 446 (65.2)
Musculoskeletal complaints 277 (40.5)
Hip impairment 55 (8.0)
Osteoarthritis 145 (21.2)
Rheumatoid arthritis 30 (4.4)
**Depression** **555**
Diagnosed depression 260 (46.8)
Symptoms of depression 295 (53.2)
a\) May sum to more than 100% due to coexisting conditions.
:::
The final sample included patients who had complete baseline and four-year follow-up information (including deaths), had completed a medical history questionnaire, and had definitive diagnostic information on their original tracer condition \[[@B17]\]. Patients from the longitudinal sample who were lost to follow-up did not have significant differences in initial health status from those who remained in the sample, however patients lost to follow-up tended to be younger and had lower income than those remaining \[[@B17]\].
Outcome measures
----------------
We analyzed categorical change (worse versus same/better) in SF-36^®^Health Survey (SF-36) physical component summary (PCS) scores over four years. We chose this dichotomous outcome to emphasize the clinical importance of anticipating functional decline in patients with chronic medical conditions. Categorical change was defined as a decrease of 6.5 or more points in PCS. This was based on standards for PCS scores in which a change of 6.5 points is outside the 95% confidence interval for PCS scores. Longitudinal change norms for PCS classify patients with +/- two standard errors of measurement (SEM) as \"better\" or \"worse\" and those within two SEM as \"staying the same\" \[[@B17],[@B20]\]. Changes of 6.5 points or more in PCS over time are clinically significant and correlate with changes in health and mortality \[[@B17],[@B20]\]. We also assessed linear change in PCS scores over the four-year period.
Statistical analysis
--------------------
Based on published sample sizes specifically calculated to detect differences in PCS between two groups using repeated measures over time, our sample size was adequate to detect a difference of five points in PCS with 80% power (alpha = 0.05, two tailed test with an intertemporal correlation of 0.70) \[[@B20]\]. As these published sample size calculations were designed to detect a slightly smaller difference in PCS than we chose to examine (5.0 versus 6.5 points), our sample sizes should be more than adequate.
We used logistic regression to analyze the independent effect of each main chronic disease on categorical change (worse vs. same/better) in PCS relative to hypertension alone adjusting for the effect of the other main diseases. Logistic regression was again used to assess change in PCS over four years in patients with one, two, three or four or more of the main chronic conditions relative to those with hypertension alone.
Due to the selection criteria for the original MOS study \[[@B10]\], the MOS data set does not include \'healthy\' participants without any chronic conditions. Therefore we used persons with hypertension alone, but none of the other main chronic conditions, as the referent group for the analysis. In one analysis, hypertension alone had an effect on PCS that was comparable to the effect of aging in a \'healthy\' population.\[[@B21],[@B22]\] However another longitudinal analysis has shown slightly increased odds of a decline in health status over 2 years in patients with hypertension alone relative to those with no chronic conditions. This effect diminished with age \[[@B7]\].
We completed separate regressions to determine the effect on PCS due to each of the main chronic conditions of interest. In these models, the study population was divided into those with hypertension alone (referent group), those with the main chronic disease of interest (with and without other conditions), and those with any other of the main chronic conditions *other than*the condition of interest. Using similar modeling, linear regression analysis was used to assess the relative contributions of the explanatory variables. There were no significant interactions between each of the main conditions and the total number of conditions. As age has been shown to be associated with functional outcomes in persons with comorbidities \[[@B23]\], we assessed categorical change in PCS by number of comorbid conditions relative to hypertension alone for older and younger age groups (under 65 years vs. 65 and over). Four-year change in PCS relative to hypertension was comparable in both age groups, therefore the final analysis was not stratified by age.
Analyses were additionally adjusted for age, a count from a list of 16 additional chronic conditions (in addition to adjustments for main diseases as mentioned above), poverty level, gender, race, educational level, employment status, and marital status. Subjects who died during the course of the study were assigned a four-year PCS score of zero and included in the \'worse\' category. Assignment of a zero PCS sore to participants who died during the course of the study has been discussed by Diehr et al. as a reasonable approach for analyses in which a decline in health is the outcome of interest \[[@B17],[@B24]\]. Failure to incorporate these subjects could substantially bias the results by limiting the assessment of outcomes to \'healthier\' subjects. To partially account for level of physical well being at baseline, the analyses also adjusted for starting PCS score relative to age/gender norms.
Results
=======
Of a total of 1574 subjects, 281 individuals carried a diagnosis of hypertension exclusive of any of the other major comorbid conditions, and were defined as the referent population for this analysis. (As participants in the original MOS study were selected on the basis of chronic medical diagnoses, the study population did not include a referent \'disease-free\' population.) The remaining 1293 subjects had either one or more of the six comorbid conditions of diabetes, CAD, CHF, respiratory disease, musculoskeletal disease and depression with or without hypertension. In this heterogeneous population, subjects with the main conditions of interest had, on average, 1.8 of the main conditions and 0.8 from a list of 16 additional conditions. Referent subjects with hypertension and no other main conditions of interest had 0.3 additional conditions. The majority of all respondents had starting PCS scores within 1 standard deviation of age/gender norms, with an additional 10% above and 26% below age gender norms. Table [2](#T2){ref-type="table"} describes the characteristics of the study population.
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Characteristics of study population
:::
**N** **1574**
------------------------------------------------------------------- ---------------
Age (mean) +/- SD 57.6 +/- 15.4
Male 41.3%
Married 58.3%
Employed 46.4%
At or below 200% of poverty level 19.3%
White (vs. non-white) 82.5%
**Education**
Education less than high school 14.6%
High School graduate 28.5%
Greater than high school 28.5%
College graduate 12.1%
Greater than college 16.3%
Mean number of main diseases\* 1.5
Hypertension alone (referent group) 0
Remaining subjects 1.8
Mean number of additional diseases\*\* 0.7
Hypertension alone (referent group) 0.3
Remaining subjects 0.8
**PCS Scores**
Baseline PCS score \> 1 standard deviation above age/gender norms 10.0%
Within 1 standard deviation of age/gender norms 63.7%
\>1 standard deviation below age/gender norms 17.9%
\>2 standard deviation below age/gender norms 8.5%
\* Diabetes, coronary artery disease, congestive heart failure, musculoskeletal disease, respiratory disease and depression.
\*\* From a list of 16 additional conditions.
:::
Subjects with CHF, diabetes or chronic respiratory disease had increased odds of a clinically significant decline in PCS over 4 years. These odds ratios (confidence intervals) were 2.9 (1.7, 5.0), 2.1 (1.5, 2.9) and 1.7 (1.1, 2.8) respectively (Table [3](#T3){ref-type="table"}). Subjects with diagnoses of CAD, musculoskeletal disease, or depression did not show a significant change in physical well being over 4 years relative to the referent population. The effects of these main conditions on physical well being over 4 years were confirmed by the linear model in which subjects with diagnoses of CHF, diabetes or respiratory disease had adjusted 4-year declines in PCS scores of -10.0, -3.2 and -3.1 points (p \< = 0.05 for all).
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Adjusted odds of a decline in PCS attributable to presence vs. absence of each main chronic disease^a^(Total N = 1574)
:::
**Disease** **N^b^** **Adjusted odds ratio**
-------------------------- ---------- -------------------------
Hypertension 281 1.0
Diabetes 249 **2.1 (1.5, 2.9)**
Coronary Artery Disease 364 1.1 (0.8, 1.5)
Congestive Heart Failure 137 **2.9 (1.7, 5.0)**
Respiratory Disease 125 **1.7 (1.1, 2.8)**
Musculoskeletal Disease 514 0.9 (0.7, 1.2)
Depression 319 1.3 (0.9, 1.8)
a\) Adjusted for number of main conditions, number of additional comorbid conditions, poverty level, gender, race, educational level, employment status, marital status.
b\) Sum to more than 100% due to coexisting conditions
:::
An absolute decrease in PCS of 6.5 points *per subject*was used as criteria for a *clinically*significant decline in PCS over time based on previous analyses of the MOS data and on validation of the SF-36^®^survey instrument \[[@B17]\]. The linear regression model presents changes in PCS for the *population*of subjects adjusted for characteristics of that population. Therefore the statistically significant changes in PCS scores over time resulting from the linear regression analysis may not necessarily be greater than 6.5 points
Little increase in the odds of functional decline was evident in individuals with 1,2, or 3 of the main chronic conditions. However having 4 or more of these conditions predicted a decline in PCS (OR 2.8; CI 1.3, 5.9) (Table [4](#T4){ref-type="table"} and Figure [1](#F1){ref-type="fig"}). The effect on PCS of the number of chronic diseases was similar in older and younger age groups.
::: {#T4 .table-wrap}
Table 4
::: {.caption}
######
Number of main chronic conditions as predictors of a decline in physical well being over four years
:::
**Number of main chronic conditions** **N** **Adjusted odds of a decine in PCS^ab^(N = 1574)**
--------------------------------------- ------- ----------------------------------------------------
Hypertension alone 281 1.0
One main chronic disease^c^ 607 1.1 (0.8, 1.4)
Two main chronic diseases^c^ 423 1.2 (0.8, 1.7)
Three main chronic diseases^c^ 197 1.4 (0.9, 2.2)
Four or more chronic diseases^c^ 66 **2.8 (1.3, 5.9)**
a\) Adjusted for age, number of additional comorbid conditions, poverty level, gender, race, educational level, employment status, marital status.
b\) Number of main chronic diseases as a predictor of a decrease in PCS is statistically significant at p \< = .05
c\) Subjects with one, two, three or four or more of the following: DM, CAD, CHF, musculoskeletal disease, respiratory disease, or depression. May also include hypertension.
:::
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Change in PCS relative to hypertension alone by number of main chronic diseases.
:::
:::
Discussion
==========
Physical well being is particularly relevant for persons with chronic conditions and the clinicians who care for them. Declines in physical well being may have significant social, emotional and economic repercussions, as they correlate with job loss, high health care utilization and increased mortality \[[@B20]\]. Based on this analysis of a heterogeneous population from the MOS; persons with CHF, diabetes and/or chronic respiratory disease are at particular risk. Primary care providers are in an ideal position to help prevent, delay or proactively manage potential declines in physical functioning for these patients.
In this analysis of change in physical well being over time in persons with a variety of chronic medical conditions, we found that specific diagnoses of CHF, diabetes and/or chronic respiratory disease; or the presence of 4 or more chronic conditions, were predictive of a clinically significant decline in PCS. We hypothesize that our findings reflect the different clinical courses of each of these conditions as well as the varying potential for therapeutic interventions in each case. The natural history of CHF, diabetes and some respiratory disease is progressive. Treatment of these conditions is aimed at optimizing long-term health outcomes. Ongoing management involves self-care that is replete with complex concepts and tasks. In contrast, management of CAD and musculoskeletal disease may include the potential for surgical intervention and protocol-driven rehabilitation programs. While some sub-populations of patients with these latter conditions may develop increasing disability, others may experience significant improvement in physical well being over time. For example, increases in PCS scores associated with hip replacement and therapy for low back pain can be in the range of 9.5 and 7.6 respectively \[[@B20]\]. We have no specific information on such interventions in our study population and therefore were unable to incorporate treatment interventions into our analysis.
Disease management programs have been successful in improving health outcomes for persons with these and other chronic conditions \[[@B25],[@B26]\]. However these programs are often disease specific \[[@B4],[@B27],[@B28]\]. As this study population illustrates, many chronic conditions do not occur in isolation. This may make disease-specific programs less beneficial for many patients. Some components of successful disease-management programs that are particularly relevant to persons managing multiple medical conditions include: guidance in problem solving, decision making, confidence building, self-management support, and systematic support of the disease management process \[[@B29]-[@B31]\].
In considering the issue of functional decline, any \'clinically significant change\' over time is not only a function the starting and ending levels of functional status. It also is determined by the individual for whom the change has meaning, the instrument used to assess the change, and population norms that provide the context for the observed change \[[@B32],[@B33]\]. Population-based studies (including ours) address parts of this equation, but do not address the most important dependent variable in the equation: the implications of a change in function to the individual. It is up to the provider and the patient to interpret the \'data\' in the context of the individual and consider any subsequent recommendations in that same context.
Our findings on depression deserve special mention. Depression in particular and mental health in general are well known to affect the management and outcomes of several chronic medical conditions \[[@B34]-[@B36]\]. Furthermore there is a high prevalence of coexisting depression in persons with chronic disease \[[@B37]\]. In this analysis, we found that depression did not predict a decline in physical functioning over time. We hypothesize that this is partly due to the natural history of the disease: Depression has a waxing and waning course, and disease symptoms that are subject to significant environmental and social effects. Therefore the effect of depression on physical functioning in this patient population may have varied significantly within the population over time. Our findings are also consistent with previous findings on depression in this data set: When MOS subjects with depression were followed over two years \[[@B12]\], they were noted to have similar or improved scores of physical functioning at the end of two years relative to those at baseline. It is possible that this trend continued in our sub-sample and accounted for the non-significant change in PCS score for subjects with depression as a comorbid condition.
The study of comorbidity is, by definition, the study of inter-relationships: between different diseases and between diseases and age or other health-related sociodemographic variables. Caring for persons with chronic illness is, similarly, the care of heterogeneous populations of individuals with multidimensional medical, psychological and social issues. The heterogeneity of this study population may be relevant to the provider willing to sacrifice some internal validity in hopes of generalizing the findings to his or her patient population.
Limitations
===========
Our sample size precluded stratification to investigate the relative contributions of different medical conditions to physical well being in sub-populations defined by specific combinations of conditions, smaller age groups, socioeconomic status or other demographic criteria that might further clarify the interactive nature of the comorbid chronic disease process. It is likely that the effect of CHF, diabetes, chronic respiratory disease or other conditions on measures of health related quality of life differs within different subpopulations. Specifically, vulnerable populations may be more at risk of poor health outcomes due to socioeconomic status or process of care factors than specific disease states \[[@B17],[@B38]\]. In addition, there may be additional psychological and sociodemographic factors (e.g. levels of self-efficacy and social support systems) that we were unable to incorporate in our model, which affect outcomes in persons with comorbid conditions. In the original MOS cross-sectional analysis of functional status and well being, most of the variance in outcomes measured (including PCS scores) was not attributable to the diseases studied the same is true of our longitudinal analysis \[[@B16]\].
Due to the nature of the MOS data base, we compared the effect of selected chronic conditions on physical well being to a referent group with hypertension alone. While the effect of hypertension alone on physical well being over 4 years may be minimal ; it is possible that there is a synergistic effect between hypertension and certain conditions such as CAD and CHF on physical well being over time. If so, the effect of CAD or CHF on PCS scores for persons with these conditions may have been slightly magnified. It is unlikely that this bias would change the overall significance of the results of our analysis.
We were unable to directly account for severity of illness for all main chronic conditions either at baseline or follow-up. However statistical adjustments for starting PCS score relative to age/gender norms and the inclusion of patients who died in the final analysis should indirectly account for some degree of severity of illness throughout the study population.
As in all investigations, the conclusions reflect the population studied: primarily Caucasian, with a majority above 200% of the federal poverty level, relatively well educated and specifically selected for inclusion on the basis of certain medical diagnoses. Results from this study may not be generalizable to populations with different demographic characteristics and different constellations of comorbid conditions.
Conclusions
===========
This analysis suggests that long term physical well being in persons with multiple chronic diseases is a function of both the number and type of medical conditions. Relative to persons with hypertension alone, those who carry diagnoses of CHF, diabetes and chronic respiratory disease have an increased risk of a decline in physical well being over 4 years. The presence of CAD, musculoskeletal disease or depression does not predict a similar decline.
For the primary care physician for whom \'comorbidity\' implies an exponentially increasing ratio of items on the problem list to available time during the office visit, the specific diagnoses of CHF, diabetes and chronic respiratory disease may serve as triggers for management decisions. Clinicians who care for patients with these common conditions should be alert to the possibility that a proactive approach incorporating generalizable principles of disease management may either attenuate this loss of function or help the patient and family anticipate future needs.
Authors\' contributions
=======================
EB participated in the design of the investigation, performed analysis and drafted the manuscript. MB participated in the design of the investigation, performed additional analysis, data management, and manuscript revision. JW supervised the original data collection and MOS investigations and assisted in manuscript revision. JS participated in the design of the investigation, advised on the analysis and assisted in manuscript revision. All authors read and approved the final manuscript.
Acknowledgements
================
This project was completed while Dr. Bayliss was a primary care research fellow at the University of Colorado Health Sciences Center and funded by the NRSA training grant \# HP-10006-09 5T32 Health Resources Services Administration.
Portions of this manuscript were presented in poster format at the North American Primary Care Research Group meeting, October 13--16, 2001, Halifax, Nova Scotia.
|
PubMed Central
|
2024-06-05T03:55:48.000496
|
2004-9-7
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519027/",
"journal": "Health Qual Life Outcomes. 2004 Sep 7; 2:47",
"authors": [
{
"first": "Elizabeth A",
"last": "Bayliss"
},
{
"first": "Martha S",
"last": "Bayliss"
},
{
"first": "John E",
"last": "Ware"
},
{
"first": "John F",
"last": "Steiner"
}
]
}
|
PMC519028
|
Background
==========
Neurofibromatosis type-1 (NF-1) is a common autosomal dominant disorder characterized by multiple neurofibromas, *café-au-lait*spots, freckling of the inguinal or axillary regions, gliomas, iris hamartomas, and malignant peripheral nerve sheath tumors \[[@B1],[@B2]\]. Neurofibromas are typically well-delineated and are composed of an admixture of various cell types, such as Schwann cells, fibroblasts and perineural-like cells and cells showing intermediate features \[[@B1],[@B2]\]. Although as outlined above, multiple neurofibromas are characteristic of patients with NF-1, however, most cases of neurofibroma which are diagnosed in general are sporadic in nature. The vast majority of neurofibromas are cutaneous and less commonly are intraneural, within the soft tissues or viscera. Presacral neurofibromas or neurofibromas with presacral involvement are uncommon in patients without NF-1, and have been the subject of sporadic case reports over the past half-century \[[@B3]-[@B16]\]. Likewise, spitzoid melanoma or melanomas showing spitzoid-like features form only a small percentage of all malignant melanomas. This diagnosis is based on the rare finding that some melanomas displays cytologic features that are similar to those identified in the benign Spitz nevus \[[@B17]\]. The controversy associated with this lesion stems from the fact that some dermatopathologists do not believe in its existence and prefer to designate melanocytic proliferations meeting traditional criteria for malignancy as malignant melanomas, irrespective of the Spitzoid features \[[@B18]\]. To our knowledge, a synchronous presacral neurofibroma and cutaneous spitzoid melanoma have never been reported in a patient without neurofibromatosis. More importantly, the absence of NF-1 in our patient may have implications for the potential association between malignant melanoma and NF-1.
Case presentation
=================
In September 2000, a 35-year-old female without any history or clinical stigmata of NF-1 presented to her primary physician with complaints of a dull, localized left upper leg pain of several months\' duration. An abdominal mass was palpated during a physical examination. Magnetic resonance imaging (MRI) as well as a computed tomographic (CT) scan of the abdomen and pelvis showed a large well-defined, near spherical mass in the left false pelvis which enhanced heterogeneously at a mean Hounsfield value of 44 units (Figure [1](#F1){ref-type="fig"}). The mass displaced the external iliac vein medially and psoas muscle laterally. It also abutted the upper surface of the left ovary without truly invading any of these or other surrounding structures. However, the mass was believed to be in the course of the left genitofemoral nerve and lumbar plexus. The decision was made to resect the mass. Intraoperatively, the tumor\'s capsule was found to be densely adhered medially to the external iliac vessels, with at least 10 external venous branches directly supplying the tumor. The tumor was carefully marsupialized out of the retroperitoneal area and the decision was made to leave the residual capsule, since an attempt at its removal would have entailed a highly morbid procedure that was not felt to be justified based on the histopathologic appearance of the tumor on frozen sections. Intraoperatively, a pigmented macular lesion with faintly irregular edges was noted in the left upper thigh, which was biopsied. Pathologic examination showed a malignant melanoma with spitzoid features. The precise circumstances regarding the duration of the lesion and whether there had been any increase in its size was unclear. She subsequently underwent a wide local excision (4 × 12 cm skin ellipse was removed) and sentinel lymph node biopsy, both of which showed no residual melanoma. The patient\'s postoperative course over the subsequent 2 years was remarkable for a relatively slow but progressive improvements in the neurologic symptoms related to her surgery. However, she showed no evidence of either tumor recurrence at last follow-up, 26 months postoperatively.
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Computed tomographic scan of the pelvis showing a large, well-circumscribed presacral mass
:::
:::
Pathologic findings
===================
The resected mass was spherical, weighed 270 grams and measured 8.5 × 7 cm × 7 cm (figure [2](#F2){ref-type="fig"}). The specimen was sectioned to reveal a myxoid tan-yellow cut surface (figure [3](#F3){ref-type="fig"}). Microscopically, the specimen was uniformly hypocellular, and showed a haphazard admixture of wavy Schwann cells and collagen fibers dispersed in a mucopolysaccharide matrix (figure [4](#F4){ref-type="fig"}). No increased cellularity, nuclear pleomorphism, increased mitotic activity or tumor coagulative cell necrosis was identified. On immunohistochemistry the tumor was positive for S100, Neurofilament, vimentin, and negative for epithelial membrane antigen, in combination with the morphological features a diagnosis of neurofibroma was made. Pathologic examination of the skin lesion showed a malignant melanoma (6 mm in diameter) with spitzoid features: epithelioid and spindle atypical melanocytes growing in a solid, asymmetric, non-maturing pattern with deep mitotic figures (up to 3 mitotic figures/mm^2^). The individual cells displayed nuclear pleomorphism with prominent nucleoli and the epithelioid forms showed abundant cytoplasm (Figures [5](#F5){ref-type="fig"}, [6](#F6){ref-type="fig"}, [7](#F7){ref-type="fig"}, [8](#F8){ref-type="fig"}). Immunohistochemically, both the spindle and epithelioid cells showed strong and diffuse immunoreactivity for S100 and HMB-45. The proliferative index of the tumor was 30--40% as assessed with the immunohistochemical marker ki-67. This lesion was at a Clark\'s level IV and at a depth of 2.1 mm. Growth phase was vertical and ulceration was absent. A few tumor-infiltrating lymphocytes were present and there was no definitive evidence of regression.
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Macroscopic appearance of the external surface of the presacral mass
:::
:::
::: {#F3 .fig}
Figure 3
::: {.caption}
######
The cut surface of the presacral mass showing glistening myxoid, tan-yellow appearance
:::
:::
::: {#F4 .fig}
Figure 4
::: {.caption}
######
Microscopic appearance of the presacral mass showing a haphazard admixture of wavy Schwann cells and collagen fibers dispersed in a mucopolysaccharide matrix (Hematoxylin and Eosin, 20×)
:::
:::
::: {#F5 .fig}
Figure 5
::: {.caption}
######
Photomicrographic panoramic view of the patient\'s cutaneous biopsy showing an asymmetric lesion with a basal confluent growth (Hematoxylin and Eosin 2×)
:::
:::
::: {#F6 .fig}
Figure 6
::: {.caption}
######
Photomicrograph of the junctional component of the tumor showing Spitzoid features of the lesional cells. Note that the junctional nests do not display a uniform vertical orientation towards the epidermis, as is expected in most Spitz nevi. (Hematoxylin and Eosin 40×)
:::
:::
::: {#F7 .fig}
Figure 7
::: {.caption}
######
Interemediate-power view of the cutaneous lesional cells, showing the admixture of spindle and epithelioid cells (Hematoxylin and Eosin 20×)
:::
:::
::: {#F8 .fig}
Figure 8
::: {.caption}
######
Photomicrograph showing the cytologic features of the lesion. Note the nuclear pleomorphism and prominent nucleoli. This focus was near the deep edge of the lesion, reflecting a lack of histological maturation (Hematoxylin and Eosin 20×)
:::
:::
Discussion
==========
The potential association between NF-1 and malignant melanoma has been the source of controversy in the medical literature. The common neural crest origin of these conditions has provided an attractive framework for this discussion. However, it is unclear whether patients with NF-1 have an inherently higher propensity to develop malignant melanomas than the general population. In a follow-up study of 70 NF-1 patients reported to the Swedish Cancer registry, 24% of the 70 patients developed 19 malignancies, only 1 of which was a melanoma \[[@B19]\]. However, the precise prevalence of melanomas in NF-1 patients is largely unknown. Most melanomas that arise in the setting of NF-1 are ocular. In a recent literature review, Honavar *et al*\[[@B20]\] identified only 19 reported cases overall. Cutaneous and anorectal melanomas have also been rarely reported in patients with NF-1 \[[@B21]-[@B27]\]. The rarity of this association given the frequency of NF-1 (1 in 3000) suggests that the probability of NF-1 patients developing malignant melanoma is no more than the general population. However, this needs to be tested in a rigorous population-based study. Ishii *et al*\[[@B21]\] recently reported a loss of heterozygosity (LOH) at the NF-1 gene in an anal melanoma occurring in an NF-1 patient. This suggests that the well-known Knudson\'s two-hit hypothesis may be operational, and that somatic loss of the second allele of the putative tumor suppressor function of the NF-1 gene causes development of this particular somatic malignancy. Again, more cases need to be studied to exclude the possibility that LOH for NF-1 occuring as a late event in the tumorigenesis of sporadic melanomas.
Our case provides another framework for the discussion of the potential association between NF-1 and malignant melanoma. Our patient has no evidence of either of the neurofibromatosis syndromes. The rarity of the clinicopathologic features of both lesions identified in this patient (the unusual presacral location of the neurofibroma and the spitzoid melanoma) suggests that their association in this patient is coincidental, even though both are neural crest derived neoplasms. This presumption contradicts the notion that in patients with NF-1, malignant melanomas that rarely develop are part of their neurocristopathy. For residents of the United States, the lifetime probability of developing cutaneous melanoma is 1 in 55--82 (approximately 1.5%) \[[@B28]\]. As previously noted, NF-1 is a relatively common condition with a prevalence of 1 in 3000. Since no more than 100 cases of melanoma (all sites combined) developing in NF-1 patients have been reported, the incidence is significantly lesser than the 1.5% that can be attributed to chance alone.
Although the patient described in this report did not have characteristic clinical features of NF-1, an important possibility that requires consideration is that she has segmental NF-1. Segmental NF-1 is thought to result from a post-zygotic mutation in the NF-1 gene resulting in a somatic mosaicism \[[@B29],[@B30]\]. In these patients, characteristic NF-1-associated diseases are limited to a localized part of the body \[[@B29],[@B30]\]. In our patient, a presacral neurofibroma was associated with an upper thigh cutaneous melanoma, putting both lesions in the general same region, albeit without true co-localization. Additionally, melanoma is not a diagnostic criteria for NF-1, as associated lesions are required to be for the definition of segmental NF-1. The location of the current patient\'s neurofibroma is also somewhat unusual for segmental NF-1. In two combined series that investigated 163 patients with segmental NF-1, there was not a single case of a retroperitoneal neurofibroma \[[@B29],[@B30]\]. In one of these series \[[@B29]\], neurofibromas alone were the most common manifestation of segmental NF-1. However, in all such cases, the neurofibromas were either dermal, on major peripheral nerve trunks or both. Although these findings argue against segmental NF-1 in the current patient, the possibility certainly remains. Thus, the findings in this case should be viewed within the context of that possibility.
In conclusion, we report here the previously unreported synchronous diagnosis of a presacral neurofibroma and a spitzoid malignant melanoma in a patient without NF-1. Furthermore, the finding of a sporadic neurofibroma and malignant melanoma occurring in a patient without NF-1 lends credence to the view that when these lesions occur in patients with NF-1, the association may be coincidental.
Competing interests
===================
None declared.
Authors\' contributions
=======================
OF and DH made substantial contributions to the intellectual content of the paper. Both co-wrote the manuscript. Both the authors have seen the final version of the manuscript and approved it for publication.
Acknowledgement
===============
Patient consent was obtained for the presentation of her records.
|
PubMed Central
|
2024-06-05T03:55:48.003573
|
2004-9-13
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519028/",
"journal": "World J Surg Oncol. 2004 Sep 13; 2:31",
"authors": [
{
"first": "Oluwole",
"last": "Fadare"
},
{
"first": "Denise",
"last": "Hileeto"
}
]
}
|
PMC519029
|
Background
==========
To meet the increasing fetal demands and maternal energy requirements of pregnancy, alterations in the partitioning and utilization of maternal nutrients must occur. These adaptations are regulated by changing blood concentrations of regulatory metabolites and hormones, together with changes in target tissue responsiveness. Of principle interest are alterations in maternal glucose metabolism during pregnancy, as glucose is a major limiting nutrient of fetal growth \[[@B1],[@B2]\]. As sheep pregnancy advances, circulating maternal insulin concentrations decline \[[@B3],[@B4]\] and the insulin response to a glucose load is significantly reduced \[[@B5],[@B6]\]. These decreased insulin concentrations during the last third of gestation and into lactation in ruminants have been postulated to be the result of the decreased response of the pancreas to insulinotropic agents \[[@B7]\]. Reducing insulin secretion during pregnancy is proposed to be beneficial to fetal well-being, through the creation of an environment which supports minimizing peripheral glucose utilization and maximizing glucose extraction of the gravid uterus \[[@B8],[@B9]\]. Additionally, the sensitivity of peripheral tissues to insulin is reduced \[[@B10],[@B11]\] and increased mobilization of adipose tissue to supply non-esterified fatty acids (NEFA) as an alternative maternal energy source occurs \[[@B12]-[@B15]\]. This pregnancy induced mobilization of adipose tissue is accompanied by a decline in lipid synthesis, and occurs as a result of alterations in insulin receptor numbers, a decreased circulating insulin concentration, as well as interactions with specific hormones of pregnancy \[[@B16],[@B17]\].
High plasma NEFA concentrations have been associated with the development of insulin resistance in the peripheral tissues and also the β-cell \[[@B18]\]. Elevated NEFAs in the muscle inhibit glucose disposal through interactions with the insulin signaling pathways, as certain lipid species act as secondary messengers (ceramide, diacylglycerol and hexosamine), inhibiting insulin signaling \[[@B19],[@B20]\]. Altered serine/threonine phosphorylation of insulin substrate-1 and direct inhibition of components such as protein kinase B, are also sites of action through which NEFAs may give rise to decreased insulin signaling \[[@B20],[@B21]\]. Several of these steps, including the insulin receptor substrate -1 association with phosphatidylinositol, are reduced in liver and muscle during pregnancy \[[@B22]\]. Furthermore, cardiac function is impaired in situations of elevated ceramide, through apoptotic pathways \[[@B23]\]. With regards to the pancreas, elevated NEFA concentrations in rats have been reported to decrease pancreatic responsiveness, resulting in a reduction in glucose stimulated insulin secretion \[[@B24]-[@B26]\]. In studies with male rat pancreas, following 48 hours of incubation with elevated NEFA concentrations, glucose-induced insulin secretion, as well as proinsulin biosynthetic responses, are reduced \[[@B24],[@B26]\]. In addition, there is a body of evidence which suggests that chronically elevated NEFA concentrations have a lipotoxic effect on the pancreas, through the formation of nitric oxide and β-cell apoptosis \[[@B18],[@B19],[@B27],[@B28]\].
Studies investigating a possible interaction between increasing NEFA concentrations and maternal pancreatic sensitivity during ovine pregnancy have not yet been reported. The following experiments were designed to examine whether the pregnancy-associated rise in NEFA concentration is associated with a reduced pancreatic sensitivity to glucose *in vivo*. Reported here are *in vivo*pregnant sheep studies of insulin responsiveness to glucose, measured using bolus injection and hyperglycemic clamp techniques.
Methods
=======
Animals and experimental design
-------------------------------
Twenty-four 3--4 year old, pen-trained Merino ewes of a known gestational age were used. The experiments were conducted adhering to the National Health and Medical Research Council (NH&MRC) guidelines as administered and approved by the University of Western Sydney, Hawkesbury Animal Care and Ethics Committee and the Commonwealth Scientific Research Organization, Division of Animal Production, Animal Care and Experimentation Ethics Committee. All animals displaying estrus following a program of synchronised mating induced by pre-treatment with intravaginal progestogen pessaries were recorded. Pregnancy was later verified by rectal ultrasound scanning at 28 dGA, and then confirmed together with litter size determination at 65 dGA, using abdominal ultrasound. Those ewes displaying estrus, but failing to conceive were used in a non-pregnant, non-lactating (NPNL) control group. A total of 15 NPNL ewes and nine pregnant ewes, three single bearing and six twin bearing, were used in this study. At 90 dGA a trial glucose bolus injection study was conducted in four ewes. At 105 dGA, all animals were studied (total n = 9), in both glucose bolus and hyperglycaemic protocols and then subsequently again at 135 dGA. At each gestational age, NPNL ewes (n = 15) were also studied under both protocols, expect at 90 dGA were only the bolus studies were conducted and only 5 NPNL animals studied.
One week prior to the commencement of the experimental period, ewes were weighed. Body weights (BW) were used to determine the glucose bolus doses to be administered at study (0.4 g glucose/kg). Animals were then individually penned under natural lighting conditions and fed 700 g/d per animal, of a 60:40 pelleted ration, consisting of 60% hammer milled lucerne and 40% hammer milled oaten chaff (92.7 ± 0.34 % dry matter (DM), 68.9 ± 1.05% digestible organic matter, and having a calculated metabolizable energy content of 10.33 ± 0.2 MJ/kg DM, crude protein content of 13.8 ± 0.5%). Water was freely available at all times.
Glucose Treatments
------------------
The ewes were subjected to an experiment protocol consisting of two procedures, 1) a bolus glucose study and 2) a hyperglycaemic clamp study. Each experimental period extended over 5 days, with 2 days in between the procedures. On the day before the commencement of the bolus glucose study, each ewe had polyvinyl jugular vein catheters inserted bilaterally under local anaesthesia. Catheters were maintained patent with daily-heparinized saline flushes (35 U heparin/ml). The bolus glucose procedure was conducted as follows. On the day of the experiment, following a 24-h fast, two pre-injection (basal concentration) blood samples were collected 15 min apart. Immediately following the second basal sample, a glucose bolus was administered. Seven two ml blood samples were collected at 5, 10, 20, 35, 55, 155 and 215 min post-injection and stored in an ice bath until centrifuged at 1,200 × g for 15 min at 4°C. A 0.5 ml aliquot of supernatant was removed for glucose determination, while the remaining plasma was frozen at -20°C for later biochemical analysis.
Two days after the bolus glucose injection study, animals were also subjected to a 120 min hyperglycaemic clamp procedure, which was imposed after a 24 h fast \[[@B29]\]. Prior to the commencement of the clamp, three pre-infusion samples were taken 15 min apart (T -30, T -15 and T 0) through the right jugular catheter. At T 0, a bolus glucose injection was administered through the left jugular catheter and then individual peristaltic pumps were activated to begin the glucose infusion through the left jugular catheter. Blood samples (3.0 ml) were then collected every 5 min from the right jugular catheter. To maintain glucose at the bolus injection level, a spot sample of blood was taken from each 5 min sample and glucose concentration determined using a Boehringer Mannheim Accutrend^®^blood glucose monitoring kit (Boehringer Germany). The pump speed setting was then adjusted to maintain the required blood glucose concentration. Samples were collected for analysis as described for the bolus protocol.
Assays and calculations
-----------------------
The plasma concentrations of insulin, growth hormone (GH) and ovine placental lactogen (oPL) were determined by double antibody radioimmunoassay as previously described \[[@B30]\]. Insulin measurements were made for every collection point, while GH and oPL were determined from the pooled pre-bolus samples. Plasma glucose and NEFA concentrations were determined as previously described \[[@B31],[@B32]\]. While glucose samples were determined at each sample point, samples for NEFA concentration during the hyperglycaemic clamp studies were collected at T -30 and T 0 and at 85 and 90 min relative to the imposition of the clamp. Inter-assay and intra-assay co-efficients of variation for low and high quality control samples for all assays are detailed. *Insulin;*Inter-assay LQC, 5.2, HQC, 3.9 and intra-assay LQC, 5.7, HQC, 7.3. *GH;*Inter-assay LQC 10.3, HQC 7.9, and intra-assay LQC 8.6, HQC 7.5.*oPL;*Inter-assay LQC 9.1, HQC 12.0, and intra-assay LQC 9.2, HQC 10.9. *Glucose;*Inter-assay LQC 10.1, HQC 9.3, and intra-assay LQC 10.3, HQC 11.9. *NEFA;*Inter-assay LQC 11.4, HQC 7.8, and intra-assay LQC 10.6, 6.7.
Data from the bolus glucose injection studies were expressed using the following parameters;
\- Area under curve (AUC), for both the glucose ((mg/ml)/min) and insulin ((ng/ml)/min) response profiles,
\- Glucose clearance rate (CLR; ml/min)
\- Glucose half life (t1/2, min)
AUC for both the glucose and the resulting insulin response profiles were calculated using the trapezoidal rule. Glucose clearance rate (CLR, ml/min) was calculated as Glucose dose /AUC. Glucose and insulin half-life was determined from the interpolated cumulative response curve. Glucose and insulin concentrations at 10 minutes were used as the peak response. In the hyperglycaemic clamp studies, in addition to AUC calculations for the whole study period, the Mean Plasma Glucose Increment (MPGI, mg/dl), Glucose Infusion Rate (GIR; g (glucose)/kg BW/min) and Mean Plasma Insulin Increment (MPII; ng/ml) were determined over the last 40 min of the clamp \[[@B29]\], during the GIR steady state period. These results were averaged for each animal, and then pooled to give group results.
Statistical analyses
--------------------
There was no significant time of experiment effect when comparing NPNL ewe data collected at each of the gestational age studied, and as a consequence NPNL data from studies at 90, 105 and 135 dGA were pooled and analysed as a single control group against each gestational age group. No differences were found between the singleton and twin bearing ewes and litter size data were pooled to give one pregnant animal group at 105 and 135 dGA (n = 9). Glucose data from the 90, 105 and 135 dGA bolus glucose and 105 and 135 dGA hyperglycaemic clamp experiments were analysed through repeated measures ANOVA with Greenhouse Geisser adjustment \[[@B33]\]. Between ewe variation was included in the ANOVA model. In the hyperglycaemic clamp studies T0 and baseline measurements were used as co-variates. Glucose and insulin AUC, peak concentrations, t1/2 and CLR data from the bolus glucose injection studies were further analysed using the following orthogonal contrasts of a), NPNL versus pregnant ewes; b) day 90 versus day 105 and day 135 ewes and c) day 105 versus day 135. Body weights, glucose doses, insulin, GH, oPL and NEFA concentrations and the derived variables of GIR, MPII and MPGI were all analysed using two sample unpaired Student\'s *t*-tests. Changes in NEFA concentrations following hyperglycaemic clamp treatment at three different physiological states, NPNL, 105 dGA and 135 dGA was analysed using 2 way ANOVA.
Results
=======
Pre experimental body weights, glucose and insulin concentrations
-----------------------------------------------------------------
There were no significant differences in body weight (Mean weight: 48.4 ± 1.8 kgs) and required glucose bolus injection (19.5 ± 0.7 g) across the physiological states studied. In the bolus glucose experiments, the basal glucose concentration was significantly lower in pregnant ewes measured on day 135 than on day 90 of gestation (p \< 0.05). Basal glucose concentrations in the clamp studies, at 105 and 135 dGA, were also significantly reduced compared to NPNL concentrations (p \< 0.05, Table [1](#T1){ref-type="table"}). The basal insulin concentrations as gestation advanced declined, and basal levels measured at 105 and 135 days gestation were significantly reduced compared to NPNL concentrations in both experimental treatments (p \< 0.05, Table [1](#T1){ref-type="table"}).
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Basal glucose (mg/dl) and insulin (ng/ml) concentrations for both bolus glucose injection and hyperglycaemic clamp studies at four gestation age groups. Within columns values with different superscripts are significantly different at p \< 0.05 and (n) = number of animals.
:::
**Glucose** **Insulin**
----------------- ---------------- --------------- ----------------- ----------------
**Bolus** **Clamp** **Bolus** **Clamp**
**NPNL (15)** 46.9 ± 1.7^a^ 51.1 ± 1.9^a^ 0.89 ± 0.13^a^ 1.09 ± 0.10^a^
**90 dGA (4)** 40.1 ± 4.8^ab^ 0.64 ± 0.05^ab^
**105 dGA (9)** 29.1 ± 4.0^bc^ 38.6 ± 3.0^b^ 0.49 ± 0.11^bc^ 0.53 ± 0.06^b^
**135 dGA (9)** 21.3± 1.9^c^ 40.6 ± 4.9^b^ 0.29 ± 0.07^c^ 0.36 ± 0.06^b^
:::
Bolus glucose studies
---------------------
Glucose injection significantly increased glucose concentrations in all groups compared to basal levels (Figure [1a](#F1){ref-type="fig"}, p \< 0.001). After co-variate adjustment for basal glucose concentration, repeated measure ANOVA of glucose concentration after bolus injection revealed no significant differences in maximal glucose concentration obtained between pregnant and NPNL ewes. There was no difference for glucose AUC between NPNL and pregnant ewes, nor did CLR and t1/2 differ between NPNL and pregnant ewes (Table [2](#T2){ref-type="table"}).
::: {#F1 .fig}
Figure 1
::: {.caption}
######
\(a) Plasma glucose (mg/dl) and (b) insulin concentrations (ng/ml) following a bolus glucose injection (0.4 g/kg) in NPNL ewes (□, n = 15) and pregnant ewes, 90 (×, n = 4), 105 (Δ, n = 9) 135 (■, n = 9) dGA.
:::
:::
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Glucose peaks (mg/dl), AUC (mg/ml)/min), clearance rate (CLR, ml/min) and half life (t1/2, min) for NPNL (n = 15) ewes and pregnant ewes, 90 (n = 4), 105 (n = 9), and 135 (n = 9) dGA following bolus glucose injection.
:::
**Glucose peak** **AUC** **CLR** **t1/2**
------------- ------------------ --------------- --------------- ------------
**NPNL** 244.9 ± 6.1 166.46 ± 10.2 129.9 ± 7.8 49.6 ± 2.9
**90 dGA** 239.3 ± 21.9 162.0 ± 18.5 124.42 ± 11.9 50.9 ± 3.8
**105 dGA** 192.5 ± 12.1 131.4 ± 9.7 149.1 ± 6.7 48.2 ± 3.2
**135 dGA** 203.4 ± 9.6 162.4 ± 11.4 123.4 ± 8.4 57.4 ± 2.5
:::
Whereas peak insulin concentrations and the insulin AUC profiles were significantly reduced in pregnant compared with NPNL ewes (Figure [1b](#F1){ref-type="fig"}, p \< 0.001 and Table [3](#T3){ref-type="table"}). Day 135 ewes had significantly reduced peak insulin responses compared to day 105 ewes (Table [3](#T3){ref-type="table"}, p \< 0.04). Ewes at 105 and 135 dGA had significantly reduced AUC when compared to day 90 ewes (Table [3](#T3){ref-type="table"}, p \< 0.001). The decline in AUC was linearly related to stage of pregnancy, whilst insulin t1/2 did not vary significantly across the groups (Table [3](#T3){ref-type="table"}).
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Peak insulin responses (ng/ml), AUC ((ng/ml)/min) and half life (t1/2, min) for NPNL (n = 15) ewes and pregnant ewes 90 (n = 4), 105 (n = 9) and 135 (n = 9) dGA following bolus glucose injection.
:::
**Peak** **AUC** **t1/2**
------------- ------------ ---------------- -------------
**NPNL** 13.5 ± 1.4 1095.3 ± 112.8 60.7 ± 4.1
**90 dGA** 6.9 ± 2.0 458.8 ± 48.9 61.9 ± 12.2
**105 dGA** 4.7 ± 0.8 277.5 ± 60.3 45.7 ± 7.2
**135 dGA** 2.5 ± 0.5 169.9 ± 24.9 68.9 ± 10.8
:::
Hyperglycaemic clamp studies
----------------------------
The bolus glucose injection, prior to the start of the clamp, significantly elevated glucose concentrations in all groups (Table [1](#T1){ref-type="table"} and Figure [2a](#F2){ref-type="fig"}, p \< 0.001). Following adjustment for basal differences, the glucose concentrations obtained were not statistically different between pregnant and NPNL ewes or between days of gestation. Pregnant ewes while having glucose concentrations not different from NPNL ewes had significantly reduced insulin responses and continued depressed insulin secretion over the 2 hours of the study (Figure [2b](#F2){ref-type="fig"}, p \< 0.001). The measured insulin AUC (ng/ml)/min), were significantly reduced over gestation in 105 dGA and 135 dGA ewes compared to NPNL ewes (NPNL; 1675 ± 110 vs. 105 dGA; 491 ± 67 and 135 dGA; 427 ± 55, p \< 0.001).
::: {#F2 .fig}
Figure 2
::: {.caption}
######
\(a) Plasma glucose (mg/dl), (b) insulin concentrations (ng/ml) and (c) glucose infusion rates (mg glucose/kg/min) during a hyperglycaemic clamp conducted on NPNL ewes (□, n = 15) and pregnant ewes at 105 (Δ, n = 9) 135 (■, n = 9) dGA.
:::
:::
Mean plasma glucose increment (MPGI), glucose infusion rate (GIR) and Mean plasma insulin increment (MPII)
----------------------------------------------------------------------------------------------------------
The MPGI did not differ significantly between the three physiological states examined (Table [4](#T4){ref-type="table"}). Despite a slight rise in glucose concentrations during the clamp, the amount of glucose required to maintain glucose concentrations constant, declined from approximately 14 to 6 mg glucose/kg/min (Figure [2c](#F2){ref-type="fig"}). A steady state infusion point was obtained in the last 40 min of the clamp. GIR during this period was constant, at approximately 5.8 mg glucose/kg/min, across all physiological states (Table [4](#T4){ref-type="table"}). Although MPII during the last 40 min of the glucose hyperglycaemic infusion was significantly greater in NPNL ewes, than in the day 105 and 135 groups (Table [4](#T4){ref-type="table"}, p \< 0.001), the glucose infusion rates necessary to maintain hyperglycemia within the groups was not significantly altered (Table [4](#T4){ref-type="table"}).
::: {#T4 .table-wrap}
Table 4
::: {.caption}
######
Mean plasma glucose increment (MPGI, mg/dl), glucose infusion rates (GIR, mg glucose/kg/min) and mean plasma insulin increments (MPII, ng/ml) during the last 40 min of hyperglycemic clamp for NPNL (n = 15) ewes and pregnant ewes at 105 (n = 9) and 135 (n = 9) dGA. Within columns values with different superscripts are significantly different at p \< 0.05.
:::
**MPGI** **GIR** **MPII**
------------- ----------------- ---------------- ----------------
**NPNL** 368.3 ± 12.5^a^ 5.58 ± 0.39^a^ 16.44 ± 1.1^a^
**105 dGA** 344.1 ± 24.8^a^ 6.03 ± 0.51^a^ 5.1 ± 0.61^b^
**135 dGA** 354.4 ± 16.2^a^ 5.66 ± 0.71^a^ 5.03 ± 0.74^b^
:::
GH, oPL and NEFA concentrations
-------------------------------
Pre-bolus pooled samples for maternal GH and oPL concentrations displayed increased concentrations with gestational age. Maternal GH concentrations increased with gestation, rising significantly from 0.78 ± 1.1 ng/ml in the NPNL state (p \< 0.05), to 2.13 ± 0.35 ng/ml at 105 dGA and 3.5 ± 0.9 ng/ml at 135 dGA. Placental lactogen concentrations were 579 ± 74 ng/ml at 105 dGA and increased to 1211 ± 144 ng/ml (p \< 0.05) by 135 dGA. Both pregnant groups displayed higher NEFA concentrations than did the NPNL control ewes following a 24-h fast (Figure [3](#F3){ref-type="fig"}). Pre-fasting, pre-clamp NEFA concentrations at day 105 were significantly greater than those of NPNL ewes (p \< 0.05, Figure [3](#F3){ref-type="fig"}). Ewes at 135 dGA displayed significantly elevated NEFA concentrations compared to NPNL NEFA concentrations (P \< 0.001, Figure [3](#F3){ref-type="fig"}), and higher concentrations than at 105 dGA (p \< 0.06). Following the 2 hour hyperglycaemic clamp, NEFA concentrations were reduced to levels 54% of pre-clamp levels in NPNL ewes, 59% in day 105, and 58% in day 135 ewes (Figure [3](#F3){ref-type="fig"}). Circulating NEFA concentrations in 105 dGA ewes following the hyperglycaemic clamp were not significantly different from NPNL concentrations, nor were they different from post clamp 135 dGA concentrations, though 135 dGA post clamp concentrations remained elevated above NPNL concentrations (p \< 0.05, Figure [3](#F3){ref-type="fig"}).
::: {#F3 .fig}
Figure 3
::: {.caption}
######
Post fast circulating NEFA concentrations (μmol/L), pre (■) and post (□) the imposition of a hyperglycaemic clamp at three physiological states, NPNL (n = 15), day 105 (n = 9) and day 135 (n = 9) ewes. Comparisons are by 2-way ANOVA compared to NPNL post fasting pre-hyperglycaemic clamp NEFA concentrations, \* p \< 0.05, \*\*p \< 0.01 and \*\*\* p \< 0.001.
:::
:::
Discussion
==========
There are two important findings of these studies. Firstly, circulating maternal insulin concentration and glucose-stimulated insulin release decrease as gestation advances. Secondly, the imposition of a two-hour hyperglycaemic clamp in pregnant ewes reduces NEFA concentrations, to concentrations not different form the pre clamp concentrations of fasted non-pregnant non-lactating ewes, though despite the reduction, insulin response to glucose remains depressed in 105 and 135 dGA ewes. These results are in agreement with the blunted insulin release during a hyperglycemic clamp treatment observed in lactating cattle, where NEFA concentrations are also elevated late in gestation, prior to a clamp \[[@B29],[@B34]\]. Glucose-stimulated insulin release over gestation in our report was assessed by the capacity of the maternal pancreas to release insulin in response to two forms of glucose challenge. Both of these challenges confirmed that by the end of the second third of gestation (105 dGA, term 147 dGA), a significant and maintained depression in insulin release in the light of elevated glucose levels was observed, which was repeated near term (135 dGA). This suppression of glucose stimulated insulin release was accompanied by increases in maternal NEFA, GH and oPL concentrations.
Lipid metabolism during pregnancy has two distinct phases. The first two thirds of pregnancy are characterised by a low lipolytic activity and the majority of maternal energy appears to be derived from dietary carbohydrate. During the later part of pregnancy and into lactation, there is an increased level of lipolytic activity resulting in increased NEFA concentrations \[[@B17]\], which serve as an alterative energy source, reducing maternal peripheral reliance upon glucose \[[@B12],[@B13]\]. Under these increasing rates of lipolysis, the whole body glycemic response to insulin changes to conserve glucose for uterine uptake and fetal growth \[[@B13]\] and maternal insulin concentrations decline \[[@B3],[@B4]\]. NEFAs are well documented to promote glucose stimulated insulin secretion \[[@B35],[@B36],[@B36]\], however, the chronic effects of elevated NEFA concentrations, specifically as occur during pregnancy, are ill defined, and may be associated with suppressed glucose stimulated insulin release \[[@B25]\]. The responsiveness of the male pancreas has been reported to be decreased following exposure to elevated NEFA concentrations for periods from 3 up to 48 hours \[[@B24]-[@B26]\]. In the pregnancy studies presented here, a two-hour hyperglycaemic clamp at two time points in the later half of gestation, reduced NEFA concentrations by approximately 50%, but maternal insulin release in response to glucose remained suppressed. This is in contrast to the same protocol in NPNL ewes, where NEFA concentrations were also reduced, though pancreatic insulin response was maintained. It is interesting to note that the NEFA concentrations before the clamp in NPNL ewes were similar to pregnant ewes\' NEFA concentrations at the end of the clamp procedure, and yet the NPNL insulin response remained unaltered and NPNL NEFA concentrations had declined by approximately 50%. In contrast, in the pregnant ewes, insulin release remained suppressed, despite a comparable depression in NEFA concentrations as generated in the NPNL ewes, similar to NPNL pre-clamp NEFA concentrations. Somewhat similar studies have been conducted in fed and fasted non-pregnant mice \[[@B36]\]. When a hyperglycaemic clamp was imposed, NEFA concentrations were reduced. While fasted animals had a normal first phase insulin release, similar to the fed animals, this response fell away and significantly reduced insulin secretion rates were observed \[[@B36]\]. The interesting differences between these mice studies and the pregnant sheep response, is that the initial insulin response is also blunted in pregnancy, suggesting other effects of fasting and or pregnancy are involved in this absolute suppression of a glucose stimulated insulin response.
These data demonstrate that the acute suppression of NEFA concentrations per se during pregnancy does not result in the restoration of a NPNL-like insulin response. This suggests that possibly other factors of pregnancy, such as the influence of lactogenic and steroid hormones, and NEFA metabolism may be acting upon the maternal pancreas to suppress the maternal insulin response during pregnancy in sheep. Placental lactogens have been documented in many mammalian species, including the sheep and human, and PL concentrations increase with advancing gestational age, reaching maximal concentrations just prior to term \[[@B37],[@B38]\], similar to what is reported in this study. Homologous studies with human placental lactogen, prolactin and growth hormone have shown significantly elevated *in vitro*secretion of insulin from pancreatic islets \[[@B39]\]. Interestingly, more recently it has been suggested that PL and placental GH act in concert to modulate maternal metabolism, resulting in an increase in the available supply of glucose and amino acids to the fetus \[[@B9]\]. Studies concerning the effect sheep PL may have on pancreatic function however, are not definitive \[[@B40]-[@B42]\]. The short-term removal of oPL by immunoneutralisation increased insulin concentration \[[@B42]\], while an acute oPL infusion failed to demonstrate any significant changes in insulin levels \[[@B41]\]. However, in the carunculectomy model of fetal growth restriction (FGR), carunculectomised ewes have increased glucose concentration, without any increase in insulin \[[@B40]\], suggesting that there may be a pregnancy-specific impairment of insulin secretion during sheep pregnancy.
Placental progesterone has also been reported to play a major role in modulating insulin release during pregnancy. In rat islet studies, progesterone counteracts lactogenic insulin stimulatory behaviour \[[@B43]\], and circulating progesterone levels in the sheep increase from approximately 50 dGA \[[@B38],[@B44]\]. Possible differential and interactive effects of ovine PL and progesterone on insulin secretion as gestation advances, as observed in the rat \[[@B43],[@B45]\], remain to be fully explored. Despite this fact, changes in adipose tissue insulin sensitivity suggest that in pregnancy, insulin resistance may develop together with a change in the pattern of substrate utilization, which occur under rising progesterone, prolactin, PL and GH concentrations \[[@B9],[@B13],[@B46]\]. Actions of GH on adipose tissue include inhibition of insulin-induced fatty acid synthesis \[[@B47]\]. Also a down-regulation of GLUT-1 and GLUT-4 *in vivo*, in rat adipocyte plasma membranes incubated with GH, has resulted in a reduced adipocyte glucose uptake \[[@B48]\], associated with a down regulation of insulin sensitivity or responsiveness. In addition, despite initial experiments reporting that GH and oPL do not modulate lipolytic activity \[[@B17]\], there is evidence to suggest PL and prolactin decrease adipocyte glucose transport \[[@B49]\] and that oPL may act in concert with GH, enhancing GH effects on the pattern of substrate utilization \[[@B9],[@B50]\].
Another candidate that presents itself as possibly regulating maternal insulin response is that of leptin. Leptin concentrations rise during pregnancy \[[@B51]\], and stimulates lipolysis in muscle tissues \[[@B52]\], and may also be involved in a unique form of lipolysis where glycerol is released instead of NEFAs \[[@B53]\]. A direct role of action upon human and rat islet cells has been demonstrated in culture and *in vivo,*through actions in the regulation of Ca^2+^influx into the β-cell \[[@B54],[@B55]\]. However, when leptin was administered to fasted mice there were no observed changes in plasma insulin or glucose concentrations \[[@B54]\], suggesting other factors in a fasted state act to regulate pancreatic insulin release in response to glucose. Leptin concentrations were not determined in the study reported here, but the relationship between elevated leptin levels during pregnancy and pancreatic responsiveness is an interesting one, and one that requires further study *in vivo*. One final possible explanation of the data reported here could be that the chronic elevation in NEFA levels, as occurs in pregnant ewes, does play a role. While the acute suppression of NEFA concentrations during pregnancy did not result in the restoration of a NPNL-like insulin response, a chronic exposure to elevated NEFAs imparts a continuous \'lipotoxic\' inhibitory effect. Increased NEFA concentrations have been associated with a lipotoxic effect on the pancreas resulting in suppressed insulin release and β-cell apoptosis, following the formation of nitric oxide \[[@B18],[@B19],[@B27],[@B28]\], possibly similar to that demonstrated to occur in myocardium \[[@B23]\]. However no studies have yet been conducted to examine this possible pathophysiological outcome in the pregnant animal.
One final aspect of the present studies was the attempt to use the hyperglycemic clamp parameters of MPGI, GIR and MPII \[[@B29],[@B34]\], to define more precisely pregnancy-induced insulin resistance in sheep. The MPGI was constant across all physiological states and MPII, as an index of the ewe\'s pancreatic responsiveness to elevated glucose concentrations, was reduced in late pregnancy, reflecting the depressed sensitivity of the pancreas throughout the hyperglycemic clamp. During the final 40 minutes of the hyperglycemic clamp, GIR achieved glucose concentrations remained similar between the groups, suggesting both NPNL ewes and pregnant ewes were utilizing and extracting available glucose at the same rate, though to obviously different sinks. This is further supported by the fact that following a fast, both NPNL and pregnant ewes had glucose clearance rates not significantly different from one another. In the present experiments, feed intakes were not different across pregnant and non-pregnant ewes and the constant infusion rates suggest similar total utilization rates, while the difference in MPII reflects different patterns of glucose utilization. Thus as pregnancy advances, the site of utilization changes, from peripheral tissues (muscle and adipose tissues) to the gravid uterus \[[@B13],[@B56]\]. If there were no mechanisms in place to suppress peripheral glucose utilization, be it insulin resistance or reduced insulin output, it should be expected that pregnant animals would show a greater GIR and an increased MPII. Therefore, as GIR was constant across groups and insulin secretion is suppressed, the peripheral glucose utilization, through the induction of peripheral insulin resistance, must be depressed in an effort to support glucose homeorhesis during pregnancy.
Conclusions
===========
Increasing NEFA concentrations as gestation advances provide the maternal compartment with a double advantage. Firstly they act to an alterative fuel source for maternal metabolism. Secondly, they act to promote the development of an insulin resistant state, which is aided through the suppression of the glucose-stimulated insulin release response. This later action is still not well defined in pregnancy, but could be the result of interactions between hormones of pregnancy and the maternal pancreas, and possibly the result of chronically elevated NEFA concentrations. Through the development of insulin resistance in maternal peripheral tissues and a reduced insulin output, glucose is \'spared\' and available for placental uptake and ultimately, fetal demands.
List of abbreviations as defined in the text
============================================
NEFA Non-esterified fatty acids
NPNL Non-pregnant, non lactating
BW Body weight
DM Dry matter
GH Growth hormone
OPL Ovine placental lactogen
AUC Area under curve
CLR Glucose clearance rate
MPGI Mean plasma glucose increment
GIR Glucose infusion rate
MPII Mean plasma insulin increment
Acknowledgements
================
The authors would like to thank the animal house staff at Commonwealth Scientific and Industrial Research Organization (CSIRO) Prospect, for their care and maintenance of the animals during the studies. In addition the expert statistical analyses of Dr George Brown and Peter Baker is gratefully acknowledged. This work was supported through a Commonwealth Scientific and Industrial Research Organization/University of Western Sydney Hawkesbury PhD scholarship to TRHR.
|
PubMed Central
|
2024-06-05T03:55:48.004793
|
2004-9-7
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519029/",
"journal": "Reprod Biol Endocrinol. 2004 Sep 7; 2:64",
"authors": [
{
"first": "Timothy RH",
"last": "Regnault"
},
{
"first": "Hutton V",
"last": "Oddy"
},
{
"first": "Colin",
"last": "Nancarrow"
},
{
"first": "Nadarajah",
"last": "Sriskandarajah"
},
{
"first": "Rex J",
"last": "Scaramuzzi"
}
]
}
|
PMC519030
|
Introduction
============
Reports that veterans of the 1991 Gulf War were suffering from unexplained signs and symptoms started to appear as early as one year after the conflict \[[@B1]\]. Veterans complained of several symptoms including myalgia, arthralgia and debilitating fatigue, but no cause could be found. Over a decade later, it remains uncertain whether or not Gulf War illness is a specific response to a specific exposure/hazard, or alternatively a non-specific response to what may be a variety of hazards/stressors and circumstances \[[@B2]\]. Factor analysis may assist this debate by determining whether or not there is a specific structure to the symptoms endorsed by Gulf War veterans that differentiates them from symptoms shown by non-Gulf veterans.
Several studies have applied factor analysis (or principal components analysis) to examine and compare the inter-relationships among symptoms reported by veterans \[[@B3]-[@B13]\]. In general, factor structures have been found to be similar in veterans deployed and not deployed to the Gulf War \[[@B3],[@B9]-[@B11]\]. Despite different symptom inventories, differences in analytical procedures, and personal choices for factor labeling, studies of Gulf War illness report between three and seven factors that represent combinations of the following domains: (a) mood, cognition, fatigue, psychological; (b) respiratory condition; (c) neurological condition; (d) musculoskeletal pain; (e) peripheral nervous system; (f) gastrointestinal disorder; and (g) mixed somatic complaints.
When symptoms are measured on a continuous scale normally distributed, linear factor analysis (e.g. common factor analysis \[[@B14]\]) can be applied. However, when symptoms are measured on a nominal (Yes/No) or binary scale (0/1), linear factor analysis may yield biased estimates of the factor structure \[[@B15],[@B16]\]. A dichotomous factor analysis model \[[@B15]\] would be more appropriate.
The objective of this report was to apply dichotomous factor analyses to binary symptom data from two studies, i.e., the UK study of Gulf War illness \[[@B11],[@B17]-[@B19]\] and the US Air Force study of Gulf War veterans \[[@B12]\], and to assess whether observed symptom patterns represented similar syndromes across nations.
Methods
=======
Sources of data
---------------
The data used in this report came from two sources: the UK Study of Gulf War illness \[[@B11],[@B17]-[@B19]\] that included three cohorts: individuals deployed to the Persian Gulf in 1991 or to Bosnia on U.N. peacekeeping operation, and Gulf War-era servicemen who were not deployed to the Gulf, and a study of US Air Force Gulf War veterans \[[@B12]\]. Briefly, the UK study was a postal survey conducted between August 1997 and November 1998 that asked veterans of the Royal Navy, Army, Royal Air Force about socio-demographic, military and health characteristics \[[@B17]-[@B19]\]. In Gulf veterans, previous work has shown that ill health was associated with rank and socio-demographic factors but it was similar across all three services \[[@B19]\]. Also, linear factor analysis and cluster analysis indicated that symptom patterns were similar across the three cohorts \[[@B11],[@B17]\]. In the US study, four Air Force units (2 in Pennsylvania and 2 in Florida) were surveyed between January and March 1995. Questionnaires were distributed to volunteers and queried about deployment to the Persian Gulf, health status, demographic and military characteristics and symptoms \[[@B12]\]. A case definition of multi-symptom illness was derived using linear factor analysis \[[@B12]\].
Symptoms
--------
In the UK study, we considered the analysis of 50 symptoms that occurred in the preceding month (\"[During the past month]{.underline}, have you suffered from any of the following symptoms?\") \[[@B11],[@B17],[@B18]\] (Table [1](#T1){ref-type="table"}). In the US study, we considered 35 symptoms that were reported as [current]{.underline} health problems \[[@B12]\] (Table [2](#T2){ref-type="table"}). The analyses only included subjects with complete symptom data (i.e., only a small proportion of veterans had missing symptoms: 2.2% in the UK Gulf cohort, 3.5% in the UK Bosnia cohort, and 1.4% in the UK Era cohort, 0% in the US study).
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Prevalence (%) of symptoms present in the past month across UK Study: Gulf, Bosnia and Era Cohorts
:::
During the past month have you suffered from: Gulf\* N = 3,454 Bosnia N = 1,979 Era N = 2,577
--------------------------------------------------------------------------------------------------------------------- ------------------ ------------------ ---------------
Feeling unrefreshed after sleep 56.1 32.5 31.5
Irritability/outburst of anger 54.7 32.2† 25.5
Headaches 54.2 36.5 36.8
Fatigue 51.1 26.9 28.2
Sleeping difficulties 47.8 30.5 28.3
Forgetfulness 44.7 19.4† 16.8
Loss of concentration 39.5 16.6 15.0
Joint stiffness 39.3 20.9 22.8
Flatulence or burping 34.0 15.7† 21.0
Pain without swelling or redness in several joints 31.7 13.7 14.2
Feeling distant or cut off from others 27.9 14.4† 10.3
Avoiding doing things/situations 26.5 12.4† 10.1
Feeling jumpy/easily startled 24.7 12.9† 9.4
Chest pain 24.5 12.5 11.6
Tingling in fingers and arms 24.3 8.4† 10.9
Night sweats that soak the bed sheets 23.7 12.0† 9.5
Itchy or painful eyes 22.9 10.5 11.9
Sore throat 22.3 15.1 13.6
Distressing dreams 21.6 13.1† 9.0
Numbness or tingling in fingers or toes 21.4 8.1† 10.9
Ringing in the ears 20.5 10.8 12.5
Wheezing 20.4 10.1 9.7
Diarrhea 20.2 11.1 11.9
Unable to breathe deeply enough 20.0 9.8† 7.8
Unintended weight gain greater than 10 lbs 18.7 10.8† 8.5
Dry mouth 17.4 9.1† 6.6
Loss of interest in sex 17.3 7.1 6.7
Dizziness 17.0 7.0 7.7
Tingling in legs and arms 16.8 5.4† 6.8
Rapid heartbeat 16.4 7.5 7.6
Feeling short of breath at rest 15.3 6.5 5.5
Increased sensitivity to noise 15.0 6.3 5.6
Increased sensitivity to light 14.7 6.0 5.8
Stomach cramp 14.6 7.8 7.5
Passing urine more often 14.3 4.9† 6.3
Persistent cough 13.9 7.8† 5.8
Loss or decrease in appetite 13.3 8.5† 5.2
Intolerance to alcohol 11.9 5.0 4.0
Shaking 11.6 5.3† 3.7
Constipation 10.9 5.9 5.2
Faster breathing than normal 10.4 4.4 3.3
Feeling disoriented 10.3 3.2 3.5
Feeling feverish 8.7 3.5 3.0
Nausea 8.7 3.7 3.7
Lump in throat 8.0 3.8 3.0
Unintended weight loss greater than 10 lbs. 5.5 3.9† 2.6
Double vision 5.4 2.5 2.1
Pain on passing urine 5.2 2.3 1.9
Burning sensation in sex organs 5.0 1.3 1.6
Vomiting 4.7 3.2 2.8
In general would you say your health is (mean, standard deviation) 1=Excellent, 2=Very Good, 3=Good, 4=Fair, 5=Poor 2.8 (1.1)‡ 2.3 (1.0) 2.3 (1.0)
\* Gulf War veterans significantly different (p \< 0.05) from Era and Bosnia veterans with respect to all symptoms
† Bosnia veterans were significantly different (p \< 0.05) from Era veterans.
‡ Gulf War veterans significantly different (p \< 0.05) from Bosnia and Era veterans
:::
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Prevalence (%) of symptoms reported as current health problems in the US Study of Gulf War veterans
:::
Current health problem Deployed to the Gulf (N = 1,163)
--------------------------------------------------------------------------------------------------------------------- ----------------------------------
Sinus congestion 51.8
Headache 50.0
Fatigue 42.9
Joint pain 35.5
Difficulty remembering or concentrating 34.4
Joint stiffness 30.4
Difficulty or problems to sleep 27.6
Gas, bloating, cramps or abdominal pain 26.7
Trouble finding words 26.1
Irritability or moodiness 25.5
Skin rashes or sores 23.0
Numbness or tingling in fingers or toes 21.0
Muscle pains 19.9
Hay fever or other allergies 19.0
Depression 18.0
Diarrhea (3 or more loose bowel movements in 24 hours) 17.6
Sore throat 17.4
Cough 17.1
Anxiety 17.0
Unintended weight gain greater than 10 lbs 16.9
Shortness of breath 16.4
Chest pain 15.0
Decreased sexual interest 14.3
Dizziness 13.9
Night sweats that soak your bed sheets 13.3
Fatigue lasting 24 hours after exertion 12.6
Sores inside your nose 10.8
Swollen lymph glands in your neck, armpit, groin 10.1
Inability to tolerate milk 7.1
Episodes of disorientation 6.6
Nausea or vomiting 6.3
Wheezing 5.9
Sensitivity to chemicals 5.2
Fever 4.9
Unintended weight loss greater than 10 lbs 2.7
In general would you say your health is (mean, standard deviation) 1=Excellent, 2=Very Good, 3=Good, 4=Fair, 5=Poor 2.3 (0.9)
:::
Statistical analyses
--------------------
We used chi-squared tests to compare symptom reporting among the UK Gulf, Bosnia and non-deployed cohorts, and between the UK and US Gulf War veterans. For factor analyses, data from each UK group and US study were randomly split into 2 halves (exploratory and confirmatory samples). Exploratory dichotomous factor analyses \[[@B20]\] were performed to determine the number of factors that explained the correlations among symptoms. Confirmatory dichotomous factor analyses \[[@B20]\] were conducted to test the reproducibility of the factor structure identified in the exploratory phase. We used a robust weighted least squares estimator to calculate factor loadings for the dichotomous model \[[@B20]\]. The promax oblique rotation was used to estimate factor correlations. For exploratory analyses, the scree plot was used to estimate the number of factors and utilized eigenvalues from the tetrachoric correlation matrix. The number of factors was considered sufficient to explain symptom correlations if the root mean square error of approximation (RMSEA) was ≤ 0.06 \[[@B20],[@B21]\]. Since in general, factor loadings are considered meaningful when they exceed 0.30 or 0.40 \[[@B14]\], we determined the stability of the factor structures by repeating the exploratory factor analyses in the exploratory sample after eliminating symptoms with factor loadings of \<0.40.
The confirmatory dichotomous model \[[@B20]\] specified the number of factors and the leading symptom in each factor (i.e., one with highest loading in its factor, and fixed zero loadings in the remaining factors) to test the exploratory structure in the confirmatory sample. We also set the factor variances to 1 so that the model would be identifiable. No other parameters were fixed. The confirmatory model was deemed to fit the data well if any of the following goodness-of-fit indices was satisfied: RMSEA of ≤ 0.06, Tucker-Lewis Index (TLI) of ≥ 0.95, Comparative Fit Index (CFI) of ≥ 0.95, or standardized root mean square residual (SRMR) of ≤ 0.08 \[[@B21],[@B22]\]. Finally, we fitted the confirmatory model to data from all subjects from the exploratory and confirmatory samples. We used M-plus version 2.14 \[[@B20]\] to fit the dichotomous factor models and SAS version 8.1 (SAS Inc., Cary, NC) to perform all other analyses.
Results
=======
Description of the samples
--------------------------
### The UK Study
Of the 3,454 veterans of the Gulf War, 93.3% were men, 75% were married or living with a partner, 92.5% had regular military status when they were deployed to the Gulf. Their average age was 34.4 years (standard deviation = 6.8). The Bosnia cohort had 1,979 veterans with average age of 29.3 years (standard deviation = 6.7) including 89.4% men, 57.5% married or living with a partner, and 91.1% with regular military status when deployed to Bosnia. The Era cohort included 2,577 veterans (92.7% men, 75.3% married or living with a partner, average age of 35.3 years (standard deviation = 7.2) and 48.8% regular military status).
### The US Air Force Study
The US Gulf sample included 1,163 veterans who were 94.0% men, 74.9% married or living with a partner, with an average age of 37.9 years (standard deviation = 8.4).
Symptom distribution
--------------------
The most common symptoms across all UK groups were feeling unrefreshed after sleep, irritability, headaches, fatigue, sleeping difficulties, forgetfulness, loss of concentration, joint stiffness and flatulence/burping (Table [1](#T1){ref-type="table"}). The prevalence of all symptoms reported by Gulf War veterans was significantly higher than that reported by Bosnia or Era veterans. On average, veterans of all groups reported their general health was at least good. However, scores for Gulf War veterans were significantly lower than those for Bosnia or Era veterans (t-test with Bonferroni adjustment, p-value \<0.05). Table [2](#T2){ref-type="table"} displays the symptom distribution among US veterans of the Gulf War and Table [3](#T3){ref-type="table"} shows the equivalence between symptoms assessed in the UK and US studies. Sixteen symptoms in the UK study were not assessed in the US study, and 11 symptoms in the US study were not assessed in the UK study. Among the 24 symptoms that were equivalent in both studies, 18 were significantly more prevalent among UK Gulf veterans than their US counterparts (chi-square p-value \<0.05).
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Equivalence between symptoms in UK and US Studies\*
:::
**UK Study** **US Study**
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Irritability/outburst of anger Irritability or moodiness
Headaches Headaches
Fatigue Fatigue
Sleeping difficulties Difficulty or problems to sleep
Forgetfulness OR Loss of concentration Difficulty remembering or concentrating
Joint stiffness Joint stiffness
Flatulence or burping OR Stomach cramp Gas, bloating, cramps or abdominal pain
Pain without swelling or redness in several joints Joint pain
Chest pain Chest pain
Night sweats that soak the bed sheets Night sweats that soak your bed sheets
Sore throat Sore throat
Numbness or tingling in fingers or toes Numbness or tingling in fingers or toes
Wheezing Wheezing
Diarrhea Diarrhea (3 or more loose bowel movements in 24 hours)
Unintended weight gain greater than 10 lbs Unintended weight gain greater than 10 lbs
Loss of interest in sex Decreased sexual interest
Dizziness Dizziness
Feeling short of breath at rest Shortness of breath
Persistent cough Cough
Feeling disoriented Episodes of disorientation
Feeling feverish Fever
Nausea OR Vomiting Nausea or Vomiting
Unintended weight loss greater than 10 lbs. Unintended weight loss greater than 10 lbs.
Diagnostic Criteria for Anxiety Disorder† Feeling distant or cut off from others OR Feeling jumpy/easily startled OR Unable to breathe deeply enough OR Tingling in legs and arms OR Rapid heartbeat OR Shaking OR Faster breathing than normal OR Lump in throat Anxiety
**16 could not find equivalent:**Avoiding doing things/situations, Tingling in fingers and arms, Feeling unrefreshed after sleep, Itchy or painful eyes, Distressing dreams, Ringing in the ears, Dry mouth, Increased sensitivity to noise, Increased sensitivity to light, Passing urine more often, Loss or decrease in appetite, Intolerance to alcohol, Constipation, Double vision, Pain on passing urine, Burning sensation in sex organs **11 could not find equivalent:**Trouble finding words, Depression, Muscle pains, Hay fever or other allergies, Fatigue lasting 24 hrs after exertion, Swollen lymph glands in your neck, armpit, groin, Inability to tolerate milk, Sensitivity to chemicals, Sinus congestion, Skin rashes or sores, Sores inside your nose
†All equivalent symptoms were significantly more prevalent among UK Gulf veterans than among UK Gulf veterans, except cough and joint pain that were less prevalent, and diarrhea, numbness or tingling in fingers or toes, shortness of breath, and weight gain that were not different in the 2 samples.
†*Diagnostic and statistical manual of mental disorders: DSM-IV--4th ed.*Washington, DC: American Psychiatric Association; 1994
:::
Dichotomous Factor Analyses
---------------------------
### UK Gulf Cohort
The exploratory sample consisted of 1,783 persons. The scree plot suggested 1 major factor, but it was not clear how many additional factors should be investigated (data available from authors). We removed the first eigenvalue from the plot, to better determine how much each additional factor contributed to the variance, and decided to examine 2 to 5-factor solutions. Although all solutions indicated a good fit between data and model (RMSEA ≤ 0.06), the 2-, and 3- factor models yielded non-interpretable factors, and the 5-factor solution could not be confirmed. Thus, we tested the 4-factor exploratory solution in the confirmatory sample that included 1,671 subjects. We specified the number of factors to be 4, the factor variances to be 1 and the leading symptoms of the first (pain on passing urine), second (loss of concentration), third (unable to breathe deeply enough), and fourth (tingling in fingers and arms) factors. Table [4](#T4){ref-type="table"} summarizes the final confirmatory 4-factor solution using data from all 3,454 subjects and 35 symptoms. This model fits the data well (CFI = 0.95, TLI = 0.98, RMSEA = 0.04, SRMR = 0.05). The order of the factors is not important, because in this model the variances were standardized to 1. The factors were labeled Gastrointestinal/Urogenital, Respiratory, Mood-Cognition, and Peripheral Nervous. The Respiratory, Mood-Cognition and Peripheral Nervous factors represent the same domains as the three factors in the study by Ismail et al \[[@B11]\]. This solution also yielded a very high correlation among the factors (range = 0.52--0.62). We could not estimate the variance explained by each factor, because the model standardized all variances to 1. Since factors correlate in an oblique solution, it is quite complex to calculate the proportion of variance explained by each factor. However, for descriptive purposes, we used the varimax orthogonal solution of the exploratory factor model to have an idea of the importance of each factor. Using all 3,454 subjects, 35 symptoms, and the 4-factor exploratory model we estimated that the proportion of variance explained by each factor was 16.3% (Gastrointestinal/Urogenital), 10.1% (Respiratory), 22.4% (Mood-Cognition), and 8% (Peripheral Nervous). Thus the Mood-Cognition Factor contributes most of the variance in the data, followed by the Gastrointestinal/Urogenital Factor.
::: {#T4 .table-wrap}
Table 4
::: {.caption}
######
Factor loadings for final 4-factor confirmatory model for symptoms reported in the UK Study-Gulf Cohort (N = 3,454), UK Study-Bosnia Cohort (N = 1,979), and UK Study-Era Cohort (N = 2,577)
:::
During the past month have you suffered from: **Gastrointestinal/Urogenital** **Gastrointestinal**
----------------------------------------------- --------------------------------- ---------------------- ---------
**Gulf** **Bosnia** **Era**
Nausea **.78** **.56** **-**
Vomiting **.77** \- \-
Diarrhea **.76** **.76** **.76**
Stomach cramp **.74** **.73** **.71**
Constipation **.59** **.78** **.57**
Flatulence or burping **.55** **.63** **.58**
Sore throat **.53** **.49** \-
Feeling feverish **.52** **.51** \-
Dry mouth **.48** **.49** \-
Pain on passing urine **.53** \- \-
Burning sensation in sex organs **.48** \- \-
Headaches **.48** \- \-
Loss or decrease in appetite **.47** \- \-
Unintended weight loss greater than 10 lbs. **.43** \- \-
**Respiratory**
**Gulf** **Bosnia** **Era**
Unable to breathe deeply enough **.89** **.87** **.89**
Wheezing **.77** **.75** **.91**
Feeling short of breath at rest **.73** **.89** **.81**
Faster breathing than normal **.66** **.63** **.66**
Persistent cough **.50** \- **.48**
Chest pain \- **.61** \-
Rapid heartbeat \- **.51** \-
**Mood-Cognition**
**Gulf** **Bosnia** **Era**
Loss of concentration **.93** **.70** **.79**
Forgetfulness **.87** **.66** **.71**
Feeling distant or cut off from others **.77** **.80** **.86**
Avoiding doing things/situations **.74** **.67** **.75**
Irritability/outburst of anger **.64** **.71** **.74**
Feeling unrefreshed after sleep **.62** **.68** \-
Feeling jumpy/easily startled **.60** **.73** **.79**
Sleeping difficulties **.57** **.66** **.56**
Feeling disoriented **.57** **.64** **.70**
Fatigue **.57** **.53** \-
Increased sensitivity to noise **.56** **.58** **.63**
Distressing dreams **.52** **.66** **.78**
Loss of interest in sex **.51** **.54** **.65**
Intolerance to alcohol \- **.50** **.46**
Shaking \- **.45** **.55**
Night sweats \- \- **.52**
**Peripheral Nervous**
**Gulf** **Bosnia** **Era**
Tingling in fingers and arms **.97** **.99** **.91**
Numbness or tingling in fingers or toes **.84** **.89** **.90**
Tingling in legs and arms **.77** **.80** **.89**
\- Blank entries in the table indicate that symptom had a factor loading \< .40 during the exploratory phase and was not considered in the confirmatory model
:::
### UK Bosnia Cohort
The Bosnia Cohort exploratory sample included 1,008 subjects and the confirmatory included 971. A 4-factor solution with 32 symptoms was confirmed (goodness-of-fit measures: CFI = 0.961; TLI = 0.986; RMSEA = 0.029; SRMR = 0.045; factor correlations range = 0.44--0.63). Results for all 1,979 subjects are displayed in Table [4](#T4){ref-type="table"}. The proportion of variance explained by each factor, based on the orthogonal varimax solution was 13.4% (Respiratory), 24.7% (Mood-Cognition), 9.4% (Peripheral Nervous), and 14.6% (Gastrointestinal).
Although the constructs identified from symptoms reported by Bosnia veterans were similar to those confirmed in the Gulf War veteran sample, we were unable to confirm the Gulf War confirmatory 4-factor solution in the Bosnia sample. Some symptoms from the Gulf cohort Gastrointestinal/Urogenital factor loaded in several Bosnia cohort factors, yielding a structure that was difficult to interpret.
### UK Era Cohort
There were 1,325 observations in the exploratory and 1,252 in the confirmatory samples. A confirmatory 4-factor model with 26 symptoms and all 2,577 subjects is displayed in Table [4](#T4){ref-type="table"} (goodness-of-fit measures: CFI = 0.99, TLI = 1.00, RMSEA = 0.02, SRMR = 0.04; factor correlations range = 0.41--0.58). Fatigue and unrefreshing sleep could not be confirmed in any factor. The proportion of variance explained by each factor based on the orthogonal varimax exploratory solution was 13.3% (Respiratory), 28.8% (Mood-Cognition), 10.3% (Peripheral Nervous), and 9.9% (Gastrointestinal).
Comparing the factor structures of the UK Gulf Cohort with Bosnia and Era Cohorts
---------------------------------------------------------------------------------
The overlap of symptom composition across samples was remarkable for the Respiratory, Peripheral Nervous and Mood-Cognition factors (Table [4](#T4){ref-type="table"}). The factor mostly defined by gastrointestinal symptoms comprised the major difference among the cohorts.
### US Air Force Gulf War Study
The exploratory sample consisted of 590 subjects and the confirmatory included 573. A 4-factor solution with 26 symptoms was confirmed and results for all 1,163 subjects are displayed in Table [5](#T5){ref-type="table"}. The proportion of variance explained by each factor based on the orthogonal varimax exploratory solution was 19.1% (Gastrointestinal/Respiratory), 7.7% (Allergies), 20.7% (Mood-Cognition), and 10.8% (Musculoskeletal).
::: {#T5 .table-wrap}
Table 5
::: {.caption}
######
Factor loadings for final confirmatory 4-factor model for symptoms reported in the US Study of Gulf War veterans (N = 1,163)
:::
Current health problem Factor 1 Factor 2 Factor 3 Factor 4
-------------------------------------------------------- ----------------------------------- --------------- -------------------- ---------------------
**Gastrointestinal/ Respiratory** **Allergies** **Mood-Cognition** **Musculoskeletal**
Nausea or vomiting **.80** .00 .00 .00
Diarrhea (3 or more loose bowel movements in 24 hours) **.73** .06 -.04 .02
Gas, bloating, cramps or abdominal pain **.71** -.01 .06 .02
Skin rashes or sores **.56** -.10 -.05 .20
Sore throat **.54** .36 -.17 .14
Fever **.53** .18 .06 .17
Swollen lymph nodes in your neck, armpit, groin **.52** .23 -.14 .08
Night sweats that soak your bed sheets **.52** -.07 .10 .16
Wheezing **.52** . 22 -.10 .18
Cough **.47** .36 -.16 .13
Chest pain **.44** .16 .13 .12
Sinus congestion .00 **.90** .00 .00
Hay fever or other allergies -.04 **.60** .05 -.09
Difficulty remembering or concentrating .00 .00 **.87** .00
Depression -.07 .17 **.77** -.08
Trouble finding words . 04 .05 **.75** -.11
Irritability or moodiness -.11 .28 **.74** .00
Anxiety -.05 .29 **.73** -.12
Episodes of disorientation .25 -.01 **.66** -.03
Fatigue lasting 24 hours after exertion .15 .05 **.48** .28
Fatigue .15 .13 **.48** .24
Decreased sexual interest .15 .00 **.45** .07
Dizziness .36 .04 **.40** .01
Joint pain .00 .00 .00 **.96**
Joint stiffness .06 .01 .08 **.80**
Muscle pain .07 .03 .15 **.65**
Goodness-of-fit measures: CFI = .970; TLI = .988; RMSEA = .029; SRMR = .043
Inter-factor correlations: Factor1, Factor2 = .474; Factor1, Factor3 = .670; Factor1, Factor4 = .525; Factor2, Factor3 = .388;
Factor2, Factor4 = .488; Factor3, Factor4 = .511
:::
Comparing the factor structures of the UK Gulf Cohort with US Gulf Cohort
-------------------------------------------------------------------------
We could not directly compare the factor structures because the symptom inventories were so different. For example, 3 peripheral nervous symptoms were asked from the UK veterans (Tingling in fingers and arms, Numbness or tingling in fingers or toes, Tingling in legs and arms) while the US study included only 1 (numbness or tingling in fingers or toes). Thus, a separate factor could not be derived from the US study. Nevertheless, both UK and US data yielded similar constructs, namely a mixed gastrointestinal factor, a mood-cognition factor, and a respiratory-related factor. The main difference was that the musculoskeletal construct could not be confirmed in the UK Gulf cohort, and it represented a separate factor in the US sample (Tables [4](#T4){ref-type="table"} and [5](#T5){ref-type="table"}).
Discussion
==========
The objective of this report was to identify and compare syndromes among 4 samples collected from UK \[[@B11],[@B17]-[@B19]\] and US \[[@B11]\] studies of Gulf War illness by using factor analysis. We used dichotomous factor analysis models because symptoms were measured on a nominal scale (Yes/No), either during the past month (UK study) or currently (US study). UK data included Gulf War servicemen, individuals deployed to Bosnia on a U.N. peacekeeping operation, and active duty military that had not been deployed. US data included only Gulf War veterans.
We identified and confirmed at most 4 correlated factors in each of the samples. Three of the four constructs (Respiratory, Mood-Cognition, Peripheral Nervous) overlapped considerably across the UK cohorts. These factors were identical to those derived in a linear factor analysis of these data \[[@B11]\]. However, the current study identified one factor including gastrointestinal and urogenital symptoms in the UK Gulf cohort that was noticeably different from the gastrointestinal factor identified from the Bosnia and Era cohorts. One possible explanation is that Gulf War veterans were more stressed than Bosnia or Era veterans, and this fact maybe associated with multi-system symptom reporting. More needs to be investigated in this area.
In addition, despite differences in study designs, methods of data collection, military populations and symptom inventories between the UK and US studies of Gulf War veterans, Gastrointestinal, Respiratory and Mood-cognition factors were identified in both UK and US studies. Of note, although joint pain and joint stiffness were measured in both UK and US samples of Gulf War veterans, a Musculoskeletal factor was only elicited as a separate factor from the US data.
In general, findings of this report were consistent with those from other studies that used factor analysis of symptoms to compare symptom patterns between Gulf and non-Gulf War veterans \[[@B3],[@B9]-[@B11]\]. However, in one comparative study, the factor structure derived from symptoms reported by Gulf War veterans included a neurological impairment factor that was absent among non-Gulf War subjects \[[@B6]\]. Based on our experience in analyzing symptom data, we suggest that, to achieve more precise comparability across studies, a standardized symptom questionnaire be developed and used on future studies of war-related illnesses. For example, symptoms can be measured on an interval, rather than binary or nominal scale, accounting for frequency and intensity as in the Psychosomatic Symptom Checklist \[[@B23]\].
In this report, we encountered difficulties confirming the dichotomous factor structures, or reproducing a factor structure in another sample, because many symptoms were rare, which created numerical problems. On the other hand, failure to reproduce factor structures across samples may also be due to different symptom distributions in the samples being considered, as was the case of the UK Gulf and Bosnia cohorts. We also acknowledge the difficulties in analyzing self-report symptom data. However, since the UK and US studies were independent of the military and confidential, we do not believe there was a reason form service personnel to exaggerate symptoms in order to gain compensation or eligibility for veterans.
Finally, it must be noted that, in each of the UK or US cohorts, factors were moderately or highly correlated. Correlated factors are complex to interpret because it is difficult to separate their independent effects \[[@B24]\]. This finding raises the question as to whether there is higher-order dimension, or general illness, representing the common pathway underlying all four factors. Hierarchical factor analysis models \[[@B24]-[@B26]\] may be useful in addressing this issue.
In conclusion, considerable progress has been made in defining medically unexplained illness associated with deployment to the 1991 Gulf War. Our results from independent studies conducted in the UK and US confirmed occurrence of an illness comprised of 4 correlated groups of symptoms (factors) in deployed military personnel from both countries. Similar illness occurred in troops who did not participate in the Gulf War (albeit at lower rates and with different specific characteristics), so we believe that this pattern of symptoms is not unique to Gulf War service nor does it represent a unique illness or \"Gulf War syndrome.\" In fact, similar illnesses to those affecting Gulf War veterans have been noted among veterans of US Civil War \[[@B27]\] and British Boer War \[[@B28]\]. Similar illnesses can also be expected to occur in association with current deployments in Afghanistan and Iraq. A better understanding of predisposing, precipitating, and perpetuating factors must be obtained to provide appropriate care for veterans and to devise prevention strategies. A central question remains: how to resolve whether such illnesses reflect a common pathophysiologic process.
Competing Interests
===================
None declared.
Authors\' Contributions
=======================
RN conceived of this analysis was responsible for its execution and had primary responsibility for the manuscript; KI was instrumental in the conception and design of the UK veterans\' study and had primary responsibility for its analysis; collaborated in analysis and interpretation of the present data and writing the manuscript; SW was Principal Investigator for the UK veterans\' study, Collaborated in the concept of the present study and collaborated in analysis, interpretation and the manuscript; CU collaborated in the UK veteran\'s study and collaborated in analysis and interpretation of data and drafting the manuscript for this study; LH collaborated in the UK veteran\'s study and collaborated in analysis and interpretation of data and drafting the manuscript for this study; WCR was Principal Investigator of the US Gulf War study, conceived the idea for the present study, served as Principal Investigator for the present study and collaborated in all aspects of data interpretation and writing the manuscript.
|
PubMed Central
|
2024-06-05T03:55:48.007335
|
2004-9-3
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519030/",
"journal": "Popul Health Metr. 2004 Sep 3; 2:8",
"authors": [
{
"first": "Rosane",
"last": "Nisenbaum"
},
{
"first": "Khalida",
"last": "Ismail"
},
{
"first": "Simon",
"last": "Wessely"
},
{
"first": "Catherine",
"last": "Unwin"
},
{
"first": "Lisa",
"last": "Hull"
},
{
"first": "William C",
"last": "Reeves"
}
]
}
|
PMC519031
|
Introduction
============
The CCN3 protein belongs to an emerging family of growth regulators referred under the CCN acronym (cysteine-rich protein, Cyr61, connective tissue growth factor, CTGF, and the nephroblastoma overexpressed gene, nov; CCN 1--3 respectively) \[[@B1]-[@B3]\]. The CCN family now comprises six identified members with properties of both positive and negative regulators of cell growth, sharing a common multimodular organization. New members of the CNN family have been described over the past few years, and recent reviews on the CCN proteins highlight their intimate involvement in a variety of key biological processes including development, angiogenesis, and cancer \[[@B1]-[@B4]\].
The CCN3 (NOV) gene had been initially characterized as an integration site for the myeloblastosis associated virus MAV \[[@B5]\] which induces kidney tumors resembling nephroblastoma and Wilms tumor \[[@B6]\]. In human and animal tumors, the expression of the CCN3 gene was found to be altered either positively or negatively \[[@B7]-[@B11]\]. Experiments performed in our laboratory have established that CCN3 is a marker of tumor differentiation in Wilms tumors \[[@B12]\] and several other tumor types \[unpublished observations\]. Furthermore, an increasing amount of results assigns growth inhibitory functions to CCN3 in several conditions (\[[@B7],[@B8],[@B13]-[@B15]\], Manara et al. submitted).
The CCN proteins share a strikingly conserved multimodular organization with distinctive functional features \[[@B1]\]. From the amino to the carboxy terminus of these proteins, four modules can be recognized : an insulin-like growth factor (IGF) binding protein (IGFBP)-type motif, followed by a Von Willebrand type C (VWC) domain likely responsible for oligomerisation, a thrombospondin type 1 (TSP1) repeat, responsible for interaction with extracellular matrix proteins, and a carboxy-terminal module (CT), postulated to represent a dimerization domain, as it contains a cysteine-knot motif that is present and involved in the dimerization of several growth factors such as nerve growth factor (NGF), transforming growth factor -2 (TGF-2) and platelet derived growth factor BB (PDGFB).
The multimodular structure of CCN3 and other CNN proteins raises interesting questions as to participation of each individual module in conferring the biological properties to the full length proteins. Either the biochemical functions of the individual IGFBP, VWC, TSP and CT modules are indeed conserved and in sum determine the ultimate function of the full length protein, or each module confers on the whole protein specific biological functions which may vary from the conserved function, and either substitute or add to those of individual modules.
Application of the yeast two-hybrid system and co-precipitation strategies to identify proteins interacting with CCN3 has revealed that full length CCN3 interacts with several receptors, signaling molecules, and proteins of the extracellular matrix (16--19), suggesting functional involvement of CCN3 in cell signaling and adhesion regulation.
Our results also established that truncated isoforms of CCN3 could bind specific targets and pointed the CT domain of CCN3 as a critical determinant for protein interaction. This led us to hypothesize that truncated isoforms of CCN3 could also modulate its biological activity (3). The question therefore arises whether different conformational states exist due to multiple protein interactions and thereby the presentation of known antigenic epitopes.
In the present study we have used an immunological approach to establish the cellular distribution of CCN3 in cell lines representing adrenocortical and glioblastoma tumors and to ask whether the CT module of CCN3 exists in different conformational states depending on its involvement in protein interactions and cellular location. We now provide evidence that the CT end of CCN3 exists in more than one conformational state.
Results
=======
Cell culture supernatants and cellular lysates from the H295R, G59/540, and parental G59 cell lines were electrophoresed under denaturing conditions and immunoblotted with anti-K19M IgG antibody. Immunoblot analysis revealed secreted forms of CCN3 for the H295R and G59/540 cell lines, consisting of two distinct bands at 51 kDa and 30 kDa \[Figure [1A](#F1){ref-type="fig"}\]. The latter likely corresponded to the previously described amino-truncated CCN3 isoform \[[@B3]\]. Intracellular CCN3 proteins were also detected in these cell lines. However, in addition to the two bands at 48 kDa and 30 kDa, two other high molecular species reacting positively with the antibodies were also detected in the lysates \[Figure [1B](#F1){ref-type="fig"}\]. The different sizes of these various isoforms likely results from post-translational modifications and oligomerisation of CCN3 protein.
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Western blot analysis. Representative gels illustrating the expression of CCN3 proteins in H295R, G59/540, and G59 cell lines. Conditioned medium and cellular lysates were electrophoresed under denaturing conditions and immunoblotted with anti-K19M IgG antibody. A. Starts: 1). supernatant collected form H295R cell line; 2). G59/540 transfected cells supernatant; 3). supernatant from G59 CCN3 negative cells; 4). lysate from H295R cells; 5). lysate from G59/540 cells; 6). lysate from G59 cells showing two bands at 48 kDa and 30 kDa.
:::
:::
When tested in ELISA, pre-incubation of the anti-K19M-AF antibodies with CCN3-containing H259R supernatant did not affect the binding of anti-K19M-AF antibodies to the K19M peptide coated on microtitre plates (Figure [2](#F2){ref-type="fig"}). Under identical conditions, the absorption of K19M-AF antibodies with serial dilutions of K19M peptide showed a dose-dependent absorption pattern with 7.78 μg/ml K19M peptide, yielding a 50% reduction in the binding of anti-K19M-AF to K19M peptide coated on plates (Figure [3](#F3){ref-type="fig"}). These results suggested that the K19M-AF antibodies did not recognize the CCN3 protein in its native configuration, whereas it can be detected in the same sample after denaturation and Western blotting.
::: {#F2 .fig}
Figure 2
::: {.caption}
######
Reactivity of affinity purified anti-K19M-AF antibodies in ELISA. Affinity chromatography fractions were tested in wells coated with: a) GST 1 μg/ml (hatched columns); b) GST-CCN3 1 μg/ml (blank columns); c) K19M peptide 1 μg/ml (black columns). Column fractions F1 to F3 contain the flow through unbound proteins while fractions F4 to F8 contain antibody bound to K19M peptide that eluted with glycine buffer pH 2.8.
:::
:::
::: {#F3 .fig}
Figure 3
::: {.caption}
######
Absorption ELISA to check the binding of anti-K19M-AF to CCN3 in liquid phase. A fixed dilution of anti-K19M-AF (1/250 in 1% BSA) was mixed with a) serial dilutions of K19M peptide \-- \-\-- \-\-- \-- b) serial dilutions of H295R supernatant, positive for CCN-3 \-\-- \-\-- \-\--; c). G59 supernatant, negative for CCN-3 \-\--**x**\-\-\--**x**\-\--; d). 1% BSA in PBS pH 7.4 \-\-- \-\-- \-\-- \-- and applied to wells coated with K19M peptide. Each point repsent the average of 4 determinations.
:::
:::
When fixed and non-permebialized cells were used in cell-ELISA with anti-K19M-AF antibodies it was shown that positive reaction of the antibodies could be recorded with H295R cells which are known to synthesize and secrete CCN3 protein, while the reaction with G59 cells was in the ranges of the negative background. After permebialization of the cells the intensity of the reaction was increased but a significantly positive reaction was recorded with H295R cells (Figure [4](#F4){ref-type="fig"}).
::: {#F4 .fig}
Figure 4
::: {.caption}
######
Detection of CCN3 expression on cultured cell lines by cell-ELISA. Cells from H295R line or glioblastoma G59 cells were treated with 1% bovine serum albumin in PBS, pH 7.4 (blank columns) or K19M-AF diluted 1/500 in 1%BSA (hatched columns). Treatment of cells: A -- G59 non-permeabilized cells; B -- C59 permeabilized cells; C -- H295R non-permeabilized cells; D -- H295R permeabilized cells. Each point repsent the average of 4 determinations.
:::
:::
Since CCN3 was secreted by H259R cells, it was important to check whether it could bind cell surface. Evidence for this would lend support to the previous suggestion of an autocrine mechanism of control by the CCN3 protein. To explore this possibility cells from H259R, G59/540 and G59 cell lines were incubated for 1 h on ice in the presence of supernatant containing CCN3 protein and then analyzed by cell ELISA as described above. The results obtained showed that such a treatment did not increase the intensity of the reaction with anti-K19M-AF bound to the cell surface. These experiments demonstrated that H295R, and G59/540 which expressed CCN3 on the cell surface and no further absorption occurred, and the control G59/540 cells did not absorb CCN3 from the culture supernatant (data not shown).
Cellular Localization of CCN3
-----------------------------
Paraformaldehyde fixed, non-permeabilized H259R cells treated with the anti-K19M antibody (Protein A purified) exhibited immunofluorescent membrane specific staining distributed over the cell surface (Figure. [5A](#F5){ref-type="fig"}) while similarly treated G59 CCN3 negative cells did not stain (not shown). The CCN3-transfected glioblastoma cell line G59/540 stained positively with a similar localization of the reaction product (Figure [5B](#F5){ref-type="fig"} -- G540). Interestingly, since cells grown on coverslips and fixed in paraformadehyde tend to slough, we did note the presence of positively staining cell footprints, suggesting deposition of CCN3 protein in a secretable extracellular matrix (Figures [5C,5D](#F5){ref-type="fig"}). After ethanol/formalin fixation and further permeabilization of the cells with 0.1% Triton X-100 the anti-K19M antibody (Protein A purified) gave an intensive granular fluorescence pattern which appeared perinuclear in a significant fraction of the cells with a similar pattern observed in H295R and G59/540 cells (Figure [5E,5F](#F5){ref-type="fig"}). On the other hand, the parent G59 cell line showed a weak, but still perinuclear cytoplasmic staining (Figure [5G](#F5){ref-type="fig"}). The latter may represent a smaller endogenous isoform of CCN3.
::: {#F5 .fig}
Figure 5
::: {.caption}
######
Indirect immunofluorescence staining with the anti-K19M IgG antibody. A, B The H295R and G540 cell lines, paraformaldehyde fixed and non-permeabilized, show a similar granular like surface membrane labeling pattern; C, D, Both in H295R and G540 cultures, paraformadehyde fixed and non-permeabilized, cell footprints are positively labeled; E, F, The H295R and G540 cell lines, formalin/ethanol fixed and permeabilized show a granular cytoplasmic labelling pattern that is perinuclear localized in ER and Golgi network; G, The G59/540 parent line, formalin/ethanol fixed and permeabilized, still shows a small amount of a perinuclear granular staining pattern.
:::
:::
In summary, the results produced using an immunological approach would suggest multiple conformations of the C-terminal end which harbors the immunogenic epitopes. Furthermore, these variations are associated with cell bound and secreted forms of CCN3. Cytoplasmic localization indicated abundant CCN3 protein localized with ER and Golgi networks.
Discussion
==========
In this study we exploited the range of binding affinities present in polyclonal antibodies raised against the C-terminal peptide of CCN3 and analyzed with different immunoaffinity methods to ask whether CCN3 exists in alternate conformational forms in cell cultures and supernatants. Whereas immunocytochemistry of fixed, permeabilized and non-permeabilized cells yielded evidence of both cell surface membrane and cytoplasmic expression and topographical distribution of native CCN3, ELISA method and western immunoblot revealed different possible conformational forms of CCN3. Taken together the results of the assays suggest that native CCN3 assumes different configurations that either expose or sequester the C-terminal peptide depending on whether CCN3 is cell associated or free within the culture supernatant. When considered in the light of recent evidence indicating that CCN3 can associate with specific integrins at the cell membrane \[[@B23],[@B24]\] the question also arises whether CCN3 associates with specific protein partners in the circulation and in the extracellular matrix produced by different cell types.
In these studies we focused on two cell lines, H295R and G59, representing adrenocortical and glial tissues, significantly different in their anatomical location and microenvironment. Since CCN3 has been demonstrated in plasma \[[@B25]\] it is conceptually feasible that CCN3 may be secreted by well organized ectodermal, mesodermal and endodermal cell types where it is expressed \[[@B26]-[@B28]\], and then is transported through complex extracellular matrix to enter the circulation. Moreover, as CCN3 has been shown to be expressed by endothelium \[[@B23],[@B29]\], the source of the circulating CCN3 may be restricted to endothelium. Keeping to this scenario, tissue expression of CCN3 would be restricted to regional cell types and its arena of activity relegated to the extracellular matrix and resident cells. Interestingly, we could show *in vitro*that CCN3 is sequestered in cell footprints representing a secreted extracellular matrix. Cell footprints can be deposited by various cell types in different arrangements and consists of extracellular matrix, including a variety of basement membrane proteins \[[@B30]-[@B32]\]. In our studies we noted a more uniform and punctuate deposition of CCN3 in the footprints suggesting possible association with regularly arranged clustered partners (e.g. integrins), yet to be determined. Localization of CCN3 to footprints is perhaps expected since it has been shown to mediate adhesion of endothelial cells \[[@B23]\], in turn triggering intracellular phosphorylation signaling events.
This then raises the notion that proximity of CCN3 to cell surfaces could allow CCN3 to function in possible autocrine and paracrine mechanisms. Depending on the associating proteins, CCN3 would likely undergo specific conformational changes with potentially different functional outcomes. A variety of functional states may exist since CCN3 is expressed in secretable and non-secretable isoforms and contains motifs that overlap with other proteins and therein, additional binding partners \[[@B1],[@B4]\]. Thus far the actual molecular function of native CCN3 has not been determined, although biologically it shows evidence of being able to regulate mitogenesis and motogenesis \[[@B3]\]. In turn, CCN3, compared to other CCN proteins, may be differentially regulated by mechanical stress \[[@B29]\]. As a heparan binding protein, CCN3 could associate with a large group of molecules at the cell membrane and in the extracellular matrix. Yeast two hybrid studies have indicated associations with fibulin 1C \[[@B16]\]. Other studies have shown CCN3 involved in calcium signaling \[[@B19],[@B33]\], associated with Notch signaling \[[@B17]\], and able to trigger membrane mediated phosphorylation events \[[@B34]\] Some of the cellular effects of CCN3 may also be mediated by different isoforms operating at the level of the nucleus \[[@B35]\].
The biological significance of different conformations of CCN3 is not known. However, examples from other studies have suggested that conformational changes can occur in serum proteins due to binding of bivalent cations \[[@B36]\]. Since we recently reported that CCN3 may interact with Ca2+ binding proteins like fibulin-1C, modulate calcium uptake, and considering that Ca2+ binding modulates function of other protein partners such as integrins \[reviewed in \[[@B33]\]\], it is conceivable that secreted CCN3 could assume an altered conformation by binding bivalent cations, directly or indirectly, like Ca2+ present in culture media. Whether calcium or some other bivalent cation could be involved and how this could occur is still speculative as the sequence of CCN3 does not suggest any obvious cation binding properties. It is also possible that secreted CCN3 complexes with an as yet unknown partner thus sequestering the antigenic epitopes.
Altered expression of CCN3 in a variety of cancers may reflect maintenance of a normal homeostatic function of the cell of origin, or may indicate requirement of specific CCN proteins for maintaining the undifferentiated tumor state. One such example where the two possibilities are not yet resolved is in Wilms tumor, where CCN3 is abundantly expressed during normal nephrogenesis and in tumors \[[@B12]\]. Interestingly, CCN3 was originally identified during MAV virus induction of nephroblastoma but is not a direct target of WT1, the Wilms tumor suppressor gene \[[@B34]\]. Thus far few mutations have been described for CCN family and none for CCN3. CCN proteins have however been associated with a variety of cancers where they can be markedly overexpressed \[[@B11],[@B37]-[@B39]\]. It may be that CCN proteins are not directly involved in tumorigenesis (e.g., Wilms tumor) but rather play supporting roles or may act as a negative regulator on malignant behavior reflecting their roles as integrators of cell-cell and cell-matrix communications. Thus having antibodies that can recognize the different isoforms of CCN proteins with great specificity and in respect to specific epitopes within the domains would be invaluable for quantitation \[[@B40]\] and for dissecting their functions in communication signaling.
Conclusions
===========
Our preliminary investigations here have revealed possible physical and functional states of native CCN3 localizing to cytoplasmic, cell membrane and extracellular matrix. Further complexity is added since shorter and larger isoforms of CCN3 can be detected using western blotting. The origin of these short forms is still not fully understood. As there do not appear to be alternate transcripts \[[@B1]\] this suggests post-translational processing including, in addition to variant glycosylation, phosphorylation, specific proteolytic events and sites. The C-terminal antibody recognizes these forms. The use of antibodies to other motifs in CCN3 will permit us to track the cleaved N-terminal peptide which potentially could be functionally active as it resembles IGFBP \[[@B1]\]. Therefore the cleavage products of CCN3 in concert with native CCN3 may also be involved in several aspects of the regulation of growth factor activity at the cell membrane or its management in extracellular repositories.
Finally, cells can coordinately express a variety of CCN proteins that are closely related, for example CCN1-3 with cross-over and opposite functional effects yet bearing similar functional domains. Evidence is starting to surface that they might compete for binding partners, such as integrins, thus forming protein complexes with different biological consequences to cell behavior \[[@B18],[@B19]\]. It will be important to understand how stoichiometric changes in CCN protein concentrations can change the behavior of cells, thus opening up opportunities for therapeutic manipulations in disease. It is obvious that there will be a necessity for antibody reagents and quantitative methodologies to enable these studies.
Materials and methods
=====================
Cell Lines
----------
NCI H259R (American Type Cell Collection) is a human adenocortical carcinoma cell line and was cultured in DMEM/F12 supplemented with 2.5 % Nu-serum plus ITS+ supplement (Sigma Co, St. Louis, USA). H295R cells have been characterized and were shown to secrete high levels of CCN3 protein \[[@B20],[@B21]\]. The glioblastoma cell line (G-59) has been described previously \[[@B22]\]. CCN3 expressing G59/540 sublines were obtained following transfection of G59 with pCMV CCN3 plasmid and G418 selection \[[@B13]\]. These cell lines and their derivatives were used in cell ELISA and indirect immunofluorescence labeling experiments as described below.
Antibodies
----------
Antibodies against C-terminal peptide K19M were used in these experiments after either purification by an antigen specific affinity chromatography (anti-K19M-AF) or by Protein A chromatography (anti-K19M IgGs).
Antibody Affinity Purification and Characterization
---------------------------------------------------
The K19M C-terminal peptide (KNNEAFLQELELKTTRGKM) of human CCN3 protein was coupled to CNBr activated Sepharose 4B (Pharmacia Biotech, Uppsala, Sweden) following the protocol recommended by the manufacturer. Briefly, 3 mg of peptide were dissolved in 5 ml of 0.1 M NaCO~3~pH 9.0 containing 0.5 M NaCl (coupling buffer) and added to 3.5 ml CNBr-Sepharose swelled gel and the mixture was rotated end-over-end for 2 hours at room temperature. Excess ligand was eluted with 20 ml of coupling buffer and the gel was incubated in 0.1 M Tris-HCl buffer pH 8.0 for 2 hours at room temperature. The gel was washed 5 times in cycles consisting of 20 ml of 0.1 M acetate buffer pH 4.0 followed by 20 ml of 0.1 M Tris-HCl buffer pH 8.0, each containing 0.5 M NaCl, and then packed into a PD-10 column.
The rabbit anti-K19M antiserum was absorbed with 1 mg/ml human serum albumin to remove cross-reactivity with human plasma and dialyzed overnight at 4°C against phosphate buffer pH 7.0. An aliquot of 3.5 ml serum was loaded on the affinity column and the flow through and the unbound proteins were collected in 3 ml fractions followed by thorough washing of the column with the loading buffer. The K19M peptide bound antibodies were eluted with 9 ml of 0.1 M Tris-glycine buffer pH 2.8 in 3 ml fractions that were collected into test tubes containing 100 μl 1 M Tris buffer pH 8.0. All column fractions were tested by ELISA for the presence of antibodies reacting against K19M peptide and the positively reacting fractions were further purified by affinity chromatography on pre-packed HiTrap Protein A columns (Pharmacia Biotech, Uppsala, Sweden) as recommended. Affinity purified antibody preparations were further tested to determine their reactivities and specificities. The affinity purified anti-K19M-AF antibodies reacted against the K19M peptide when tested in serial dilutions in ELISA (see below). The titers of K19M-AF antibodies were comparatively lower as compared to the unfractionated K19M antiserum. This finding was not unexpected as it likely reflects the polyclonal composition of the primary rabbit antiserum and differences in the content of the specific monoclonal specificities in the antiserum. Importantly, the affinity purified antibodies recognized the K19M peptide when coated on a solid phase.
K19M Peptide Enzyme-linked Immunoabsorbent Assay (ELISA)
--------------------------------------------------------
Affinity purified antibodies were titered by ELISA. Individual wells of polystyrene 96-well flat bottom plates (NUNC) were coated with 1 μg/ml of K19M peptide diluted in coating buffer (0.05 M carbonate buffer pH 9.6) by incubation overnight at 4°C. The unsaturated protein binding sites were blocked with 300 μl/well 2% BSA for 1 h at room temperature. The primary anti-K19M antiserum and affinity purified antibodies were added in serial dilutions in duplicates and the wells were incubated for 2 h at room temperature. After thorough washing the wells were incubated with goat anti-rabbit IgG serum conjugated with peroxidase (Sigma Co) diluted 1/5000 in blocking buffer for 1 h at room temperature. The bound enzyme activity was revealed by adding the enzyme substrate 0.5 mg/ml ortho-phenylenediamine in citrate buffer pH 5.0 containing 0.5 μl/ml H~2~0~2~. The enzyme reaction was stopped by addition of 50 μl/well of H~2~SO~4~and the color reaction was read at 492 nm in a MicroELISA reader.
Cell Enzyme-Linked Immunoabsorbent Assay (Cell ELISA)
-----------------------------------------------------
Tumor cell lines were cultured in complete medium in 96-well flat bottom plates (Corning) to form a subconfluent monolayer and further incubated overnight in serum free medium. The cells were washed 3 times for 5 min each with phosphate buffered saline (PBS, pH 7.2) and cells were fixed by treatment with ice-cold methanol for 30 min warming to room temperature. The endogenous peroxidase activity was blocked with 3% H~2~O~2~in distilled water for 7 min at room temperature followed by 3 × 5 min washes in PBS, pH 7.2. Non-specific binding was blocked with 1% bovine serum albumin (BSA) for 1 h at room temperature. Cells were washed once in PBS and incubated with K19M-AF diluted in 1%BSA for 2 h at room temperature. After 3 × 10 min washes in PBS goat-anti rabbit IgG conjugated with peroxidase diluted 1/10000 in 1% BSA-PBS was added for 1 hour at room temperature. The cells were washed again in PBS and the bound enzyme activity was developed by adding ortho-phenylendiamine (5 mg/10 ml citrate buffer, pH 5.0) containing 5 μl of 30% H~2~O~2~. The color reaction was stopped by adding 50 μl of 10% H~2~SO~4~and the intensity was read at 492 nm in a MicroELISA reader.
Gel Electrophoresis and Western blotting
----------------------------------------
To prepare proteins for immunoblotting, cells were lysed in NP40 buffer (50 mM Tris hydrochloride, pH 8.0, 150 mM NaCl, 5 mM EDTA and 2% NP40) with protease inhibitors (Cocktail Tablets, complete, Roche) and phosphatase inhibitors (50 mM NaF, 2 mM sodium orthovanadate) for 30 min at 4°C. After centrifugation at 15 000 g, extracts were stored at -80°C until use. CCN3 proteins in the conditioned medium were concentrated on Heparin Sepharose (Amersham, Uppsala, Sweden) as described by Chevalier et al (1998). Briefly, supernatants were incubated overnight with heparine and then washed 4 times in PBS containing protease inhibitors. Bound CCN3 was dissociated using 2-mercaptoethanol in Laemmli buffer, boiled for 10 min and then centrifuged to keep the free protein. Heparin Sepharose concentrated samples and cellular extracts were subjected to electrophoresis under reducing conditions in 12.5% polyacrylamide gels. Separated proteins were subsequently transferred to nitrocellulose by a semi-dry blotter (LKB Biotech, Sweden) as recommended by the supplier. The nitrocellulose sheet was blocked by incubation for 1 hour at room temperature with 5% nonfat milk in PBST (PBS with 0.2% Tween 20, pH 7.4). The membrane was then incubated in the same buffer with the anti-K19M IgG (1/2000) and then washed extensively. The blots were further incubated in goat anti-rabbit IgG conjugated with peroxidase (1/10 000 in blocking solution, Sigma Co, USA) for 1 hour at room temperature. Revelation was performed using the chemoluminescence protocol and reagents (Pierce, Rockford, IL, USA).
Indirect Immunofluorescence Labeling
------------------------------------
Cells were grown on alcohol flamed coverslips, rinsed in PBS and fixed in cold 70% ethanol containing 10% formalin (Sigma) for 10 min on ice, and stored in PBS. Immunofluorescence labeling was performed at room temperature. For this procedure, coverslips were placed into weighing boats \[Sigma; 4.5cm × 4.5cm\] maintaining cell side up. Cells were further permeabilized in 0.5% Triton X-100 in PBS for 15 min and then blocked in 5%FBS/PBS for 30 min.
Anti-K19M IgGs antibodies were applied at 1:1000 dilution in 5%FBS/PBS for 1 hour with intermittent rotation, followed by 5 washes in PBS containing 0.1% Tween 20. Subsequently, the cells were incubated in anti-rabbit IgG serum conjugated with either Alexa 488 (green fluorescence) or Alexa 594 (red fluorescence), in 5%PBS/BSA for 1 hour. After final washes in PBS/Tween 20 followed by one wash in PBS cells were mounted with antifade mounting medium (Bio-Rad, France), excess liquid adsorbed with filter paper, and coverslips sealed with clear nail polish. Immunofluorescence images were captured on 400 ASA film and processed further with Adobe Photoshop (version 7.0).
List of abbreviations
=====================
None.
Competing interests
===================
None declared.
Authors\' contributions
=======================
SK carried the affinity chromatography and immunoenzyme experiments;
HY carried out immunofluorescence labeling experiments;
AMB carried out IgG purification and Western blots;
BP conceived the study design and coordinated and edited the manuscript
Acknowledgements
================
This study was supported by funds to BP from Association pour la Recherche Contre le Cancer (ARC), Ligue Nationale Contre le Cancer (Comités du Cher et de l\'Indre), and Ministère de l\'Education Nationale, de la Recherche et de la Technologie. Part of this work has been achieved when the Laboratoire d\'Oncologie Virale et Moléculaire was affiliated to the INSERM. SK and HY were invited Professors of the Université Paris 7-D. Diderot. Permanent address for SK : Department of Molecular Immunology, Institute of Biology and Immunology of Reproduction, Bulgarian Academy of Sciences, Sofia, Bulgaria. Permanent address for HY : Department of Paediatric Laboratory Medicine, The Hospital for Sick Children and Laboratory Medicine & Pathobiology, University of Toronto, Toronto, Canada. AMB is recipient of a fellowship from the Fonds de la Recherche en Santé du Québec.
|
PubMed Central
|
2024-06-05T03:55:48.013171
|
2004-9-10
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519031/",
"journal": "Cell Commun Signal. 2004 Sep 10; 2:9",
"authors": [
{
"first": "Stanimir",
"last": "Kyurkchiev"
},
{
"first": "Herman",
"last": "Yeger"
},
{
"first": "Anne - Marie",
"last": "Bleau"
},
{
"first": "Bernard",
"last": "Perbal"
}
]
}
|
PMC519032
|
Entry
=====
Although no \"new\" retrovirus receptors were reported at the meeting, several talks centered on recently discovered receptors. N. Manel, from the groups that identified GLUT-1 as an entry receptor for HTLV-1 (N. Taylor, J.-L. Battini, and M. Sitbon) \[[@B1]\], proposed that part of the pathogenic effects of this virus may be due to its perturbation of glucose metabolism. HTLV-1-infected tissue culture cells display decreased glucose uptake as a result of envelope (Env) glycoprotein-GLUT-1 interaction. The authors speculated that if this disruption of glucose metabolism also occurs *in vivo*, it might provide insights into the neuronal damage that occurs in some HTLV-1-infected patients. They also suggested that Env-mediated impairment of GLUT-1 function might contribute to the emergence of preleukemic T cells with new selective advantages \[[@B2]\].
The co-receptor for feline immunodeficiency virus (FIV), perhaps the best non-primate model for HIV-1, has also recently been identified. Work presented by J. Elder showed that FIV preferentially infects certain subsets of T cells through interaction with CXCR4 and a 43 kDa protein. This 43 kDa protein turns out to be CD134, recently demonstrated to be a receptor for FIV \[[@B3]\]. CD134 was first described as a member of the tumor necrosis/nerve growth factor receptor family expressed on activated T cells. By analogy with the role of CD4 in HIV infection, CD134 may target FIV infection to a particular subset of T cells. Extending the CD4/HIV parallel, CD134 may be the molecule that initially engages FIV, followed by CXCR4 binding and virus/cell fusion. Elder suggested that CD134 should be referred to as the FIV attachment receptor and CXCR4 as the entry receptor.
The use of alternative chemokine co-receptors by primary HIV-1 isolates was discussed by S. Neil from R. Weiss\'s group. They proposed that some primary dual-tropic HIV-1 isolates, especially those isolated from early seroconverters, might infect primary astrocytes, endothelial cells and macrophages through the use of D6, a promiscuous chemokine receptor highly expressed on these cell types. They hypothesized that D6 usage to infect endothelial cells could influence colonization of endothelial compartments and promote placental transmission.
Two groups discussed the risk of pig endogenous retrovirus (PERV) infection of human cells as a potential problem for xenotransplantation. I. Harrison from the Stoye lab showed that recombination between different endogenous PERVs (A and C), which normally have very low titers on human cells, could lead to the production of virus with the capacity to efficiently infect human cells. This tropism change mapped in large part to the Env glycoprotein, but the Gag-Pol region was also implicated. D. Lavillette from the Kabat lab presented evidence that wild-type PERVs, or mutants lacking fully infectious envelopes due to alterations in a conserved PHQ motif (in SU) required for γ-retrovirus infection, could bind and enter human cells when added together with the envelope from gibbon-ape leukemia virus, which does infect human cells. The ability of functional Env glycoproteins from infectious viruses to trans-complement infection by viruses with mutant envelopes or with restricted tropism on particular target cells has been reported for several retroviruses \[[@B4],[@B5]\]. In the case of PERVs, such complementation has the potential of overcoming host-range and interference barriers and could pose a hazard for xenotransplantation.
For a number of years, investigators have attempted to engineer peptide ligands for cell surface receptors into retroviral Env glycoproteins with the goal of designing retroviral gene therapy vectors that would efficiently target specific cell types. These attempts have been hampered by low transduction efficiencies. L. Albritton presented work from her lab demonstrating that incorporation of a peptide sequence into the SU receptor binding site (RBS) may overcome this problem. Her lab constructed a chimera in which the RBS of the Moloney murine leukemia virus (MLV) Env was replaced with the peptide ligand somatostatin (Sst). Such chimeras efficiently infected human cells expressing the Sst receptor, but could no longer infect mouse cells expressing the natural receptor, ATCR1. The similarity in length of the peptide with the sequence it replaced, as well as the structural similarity between ATCR1 and the Sst receptor, may have contributed to the success of this approach, since substitution of the RBS with human stromal-derived factor-1 alpha (SDF-1α), which also uses a structurally similar receptor (CXCR4), has also been successful \[[@B6]\]. In contrast, attempts to make peptide ligand substitutions in this RBS that are either dissimilar in length or use structurally unrelated receptors have met with limited success (i.e. see \[[@B7]\].
Following binding between retroviral Env glycoproteins and their receptors, conformational changes must take place in both the SU and TM that expose the fusion peptide and enable membrane fusion to occur. H. Garoff presented work extending his recently published report \[[@B8]\] showing that for γ-retroviruses this conformational change involves SU-TM disulfide bond isomerization. The isomerization, which is inhibited by Ca^2+^, results in breakage of the SU-TM disulfide bond, the generation of an intra-SU bond, and subsequent exposure of the TM fusion peptide. Garoff speculated that the ability of γ-retroviruses such as MLV to fuse at the cell surface, in contrast to α-retroviruses like ALV that lack isomerization activity and which apparently undergo pH-dependent fusion in a subcellular compartment, is the result of this isomerization.
Several studies have implicated amino acid changes in the cytoplasmic domain of the MLV TM on SU conformation, with consequent effects on viral infectivity and antibody recognition \[[@B9],[@B10]\]. Work presented by R. Montelaro demonstrated that mutations in the cytoplasmic tail of the HIV-1 TM (gp41) can also result in escape from neutralization. Importantly, at least one of these antibody-escape mutants still retained wild-type infectivity, indicating that sequence changes in the TM intracytoplasmic domain should be considered in the characterization of antigenic variants of HIV-1 that escape neutralization.
Dendritic cells express a molecule known as DC-SIGN that binds HIV-1 particles and facilitates their transmission to susceptible target cells \[[@B11]\]. The mechanism by which this molecule promotes the transfer of infectious virions to target cells has been an active area of investigation for the past several years. Work from V. KewalRamani\'s lab (Wu et al.) showed that DC-SIGN is able to transfer HIV-1 infectivity *in trans*when expressed on some cell types but not when expressed on others. The ability of DC-SIGN to promote virus transfer appears to correlate with the localization of the particles on the DC-SIGN-expressing cell; in cells unable to mediate transfer, virions are internalized, whereas cells able to mediate efficient transfer retain virions at the cell surface. Wu and colleagues also observed that binding and transmission of HIV-1 by immature dendritic cells is Env- and DC-SIGN-dependent, whereas virus binding by mature dendritic cells does not require either Env on the particle or DC-SIGN on the dendritic cell. The molecule(s) expressed on dendritic cells that potentiate DC-SIGN-independent virus transmission await discovery.
Post-entry events
=================
The last two years have seen major advances in our understanding of the mechanisms by which cells from human and non-human primates restrict retroviral infection. In 2002, Sheehy et al. \[[@B12]\] reported that the HIV-1 accessory protein Vif interacts with the cellular cytidine deaminase APOBEC3G. In the absence of Vif expression, APOBEC3G is incorporated into HIV-1 virions and, during reverse transcription in the target cell, converts cytosines to uracils. This conversion results in the degradation of newly synthesized DNA through the action of host glycosidases and repair enzymes, and leads to G-to-A hypermutation in the newly synthesized viral DNA. Vif counters the antiviral activity of APOBEC3G by blocking its incorporation into virions in the producer cell. Interestingly, Vif displays species specificity in its ability to inactivate APOBEC3G; for example, HIV-1 Vif blocks the antiviral activity of human but not African green monkey APOBEC3G, and SIVagm Vif inactivates African green monkey but not human APOBEC3G. The labs of N. Landau and V. Pathak both reported that the determinant of this species specificity maps to amino acid 128 of APOBEC3G. Data in the Landau lab presentation (Schrofelbauer et al.) suggested that the inability of HIV-1 Vif to block the activity of African green monkey APOBEC3G was due to a lack of binding between these two proteins, whereas the Pathak lab (Xu et al.) reported that mutation of residue 128 of human APOBEC3G did not prevent binding of the mutant protein to Vif. Both labs recently published their findings \[[@B13],[@B14]\].
Since the incorporation of APOBEC3G into virus particles is required for its antiviral activity, several groups have focused on how this cellular protein is incorporated. The mechanism of APOBEC3G incorporation is of particular interest since it appears not to be specific for HIV-1 (e.g., human APOBEC3G is incorporated into MLV particles) and because inhibitors that disrupt Vif\'s ability to block APOBEC3G incorporation would presumably display antiviral properties. L. Kleiman\'s lab (Cen et al.) reported that APOBEC3G interacts directly with Gag in a manner dependent on the Gag nucleocapsid (NC) domain. The labs of W. Popik and X.F. Yu also observed that NC plays an important role in the APOBEC3G/Gag interaction. H. Xu from V. Pathak\'s group reported that mutation of NC reduced but did not abrogate APOBEC3G incorporation into virions. Since NC is a major determinant of RNA packaging into virions, these data, together with the above-mentioned finding that APOBEC3G is incorporated into MLV particles, can be rationalized by a model that proposes an important role for RNA (either viral or cellular) in APOBEC3G incorporation. Such a model would also be consistent with the apparent inability of HIV-1 to evade APOBEC3G incorporation simply by mutation of a specific protein-protein binding site. Interestingly, a study from D. Ho\'s lab (Simon et al.) found that isolates of HIV-1 that are unable to block APOBEC3G activity are relatively common in infected patients. The authors suggested that sporadic Vif inactivation might be a factor in promoting viral evolution *in vivo*since Vif-defective variants would exhibit a higher mutation rate.
In recent years, several groups have reported that HIV-1 is unable to efficiently infect cells from certain species of Old World monkey (for review see \[[@B15]\]). The block is imposed early post-entry, prior to reverse transcription, and is mediated by an inhibitory factor expressed in Old World monkey cells. The viral determinant of this restriction maps to the capsid (CA) domain of Gag, making this restriction somewhat reminiscent of the Fv1 block described by Lilly and others decades ago \[[@B16]\]. J. Sodroski\'s group recently published that the rhesus macaque version of the cytoplasmic body component TRIM5α \[[@B17]\] potently blocks HIV-1 infection. Presentations from the labs of J. Sodroski (Stremlau et al.) and P. Bieniasz (Hatziioannou et al.) reported that Ref1 and TRIM5α are species-specific variants of TRIM5α; this finding has now been published \[[@B18]\]. This factor is quite distinct from Fv1, which bears sequence homology to MLV CA \[[@B19]\]. A. Lassaux (from the Battini and Sitbon labs) reported that Fv1 and Ref1 recognize different amino acid combinations within the same 100 amino acid determinant of the MLV CA. Hatziioannou et al. also described their results on characterizing the ability of human- and monkey-derived TRIM5α\'s to block the entry of a panel of retroviruses. D. Sayah from J. Luban\'s lab provided a preview of the now-published paper \[[@B20]\] reporting the intriguing finding that in owl monkey cells, the post-entry block to HIV-1 infection is conferred by a TRIM5α-cyclophilin A fusion protein. In another presentation focused on post-entry blocks to retroviral infection, V. KewalRamani\'s lab (Martin et al.) reported that overexpression of a truncated form of an RNA binding protein that is a component of the poly A machinery blocks an early stage of the HIV-1 infection process without disrupting MLV infectivity.
J. Young (Narayan and Young) reported the development of a cell-free uncoating assay that will likely prove useful in defining the role of cellular factors in stimulating or blocking early post-entry steps in the replication cycle. Avian sarcoma/leukosis virus (ASLV) particles can be trapped in endosomes when cells expressing a GPI-linked version of the ASLV receptor are infected in the presence of NH~4~Cl. The virus-containing endosomes can then be isolated; upon removal of the NH~4~Cl *in vitro*, fusion and reverse transcription take place in a manner dependent upon ATP hydrolysis and the presence of cellular factors. This cell-free uncoating assay can be adapted to other viruses (e.g., HIV-1) by pseudotyping with the ASLV Env glycoprotein. The authors reported that monkey cell restriction factors, and cyclosporin A (which blocks cyclophilin A incorporation into HIV-1 particles), inhibit reverse transcription in this system, suggesting that it faithfully recapitulates certain key aspects of uncoating in infected cells. Some of the data in this presentation were recently published \[[@B21]\].
Assembly and Release
====================
Major developments have taken place in the past several years in our thinking about the location in the host cell at which retrovirus assembly takes place, and the mechanism by which Gag proteins target the subcellular site of assembly. Until recently, it was felt that viruses that follow the type C assembly pathway \[including the lentiviruses (e.g., HIV-1), δ-retroviruses (e.g., HTLV-1), γ-retroviruses (e.g. MLV), etc.\] assemble at the plasma membrane. However, it has long been recognized that in some cases (for example, HIV-1 in macrophages) assembly and budding take place at an intracellular compartment. Several groups have recently demonstrated that this compartment is the late endosome or multivesicular body (MVB), and it now appears that while the plasma membrane likely represents the predominant site of assembly for these viruses, Gag can also target and assemble in an endosomal compartment in a variety of cell types. M. Resh\'s lab (Perlman and Resh) used the tetracyteine/biarsenical live-cell labeling system reported by Gaietta et al. \[[@B22]\] to follow Gag trafficking relatively early (1--4 hrs.) post-synthesis. Their results suggest that Gag may first localize to secretory lysosomes and then subsequently \"ride\" these vesicles to the plasma membrane. M. Thali\'s lab recently reported that a significant fraction of HIV-1 Gag colocalizes with late endosomal markers both at intracellular membranes and at the plasma membrane \[[@B23]\]. Together with D. Ott\'s lab (Nydegger et al.), they have also started using the tetracysteine/biarsenical technology to analyze Gag localization. Like the Resh lab, they observe some association of Gag with late endosomal/MVB membrane, but a significant fraction of newly synthesized Gag appears to associate directly with discrete plasma membrane microdomains. P. Spearman\'s lab (Dong et al.) reported interesting findings implicating the AP-3 clathrin adaptor protein complex (which among other things regulates CD63 trafficking) in HIV-1 Gag targeting. They observed that the δ subunit of AP-3 interacts with the MA domain of Gag and that either overexpression of an N-terminal δ subunit fragment or siRNA knockdown of AP-3 δ subunit expression inhibits HIV-1 release.
H. Wang from L. Mansky\'s group observed that HTLV-1 assembly, like that of HIV-1, can take place in the MVB. Interestingly, while in HeLa cells HTLV-1 assembly appears to occur primarily at the plasma membrane, mutational disruption of the Pro-Thr-Ala-Pro (PTAP) late domain results in accumulation of virus particles in the MVB, consistent with published results (e.g., \[[@B24]\]). T. Hope\'s lab (Gomez and Hope) confirmed the finding \[[@B25]\] that HIV-1 mutants lacking the p6 late domain still assemble in MVBs in macrophages, indicating that interactions between p6 and cellular host factors (e.g., Tsg101) are not required for MVB localization. Reports from the labs of D. Muriaux (Grigorov et al.) and F.-L. Cosset (Sandrin et al.) suggested that interactions between MLV Gag and Env may occur in an intracellular compartment and that this interaction might influence both Gag trafficking and Env incorporation into virions. Some of this work has now been published \[[@B26]\].
A study from the Freed lab (Ono and Freed) examined the possibility that the phosphoinositide phosphatidylinositol-(4,5)-bisphosphate (PI(4,5)P~2~) plays a role in Gag targeting. This lipid is of interest since it is involved in the trafficking of a variety of cellular proteins that, like many retroviral Gag proteins, contain a basic membrane binding domain. Furthermore, work from A. Rein\'s lab \[[@B27]\] has shown that, *in vitro*, HIV-1 Gag binds molecules structurally related to phosphoinositides. A. Ono used enzymatic approaches to perturb cellular PI(4,5)P~2~levels in virus-expressing cells and observed that Gag targeting and virus assembly were shifted from the plasma membrane to intracellular compartments. These results indicate that cellular PI(4,5)P~2~plays a role in directing Gag to the plasma membrane.
Work from J. Lingappa\'s lab previously suggested the involvement of the cellular RNase L inhibitor HP68 in HIV-1 assembly \[[@B28]\]. This work was extended at the meeting by Dooher et al., who showed that HP68, Gag, and genomic RNA colocalize in virus-producing cells. The cellular protein nucleolin was also found to be a component of the Gag/HP68 complex.
Novel findings relating to the regulation of foamy virus (FV) release were reported by the Lindemann lab. FVs are unusual among retroviruses in that Env glycoprotein expression plays a critical role in particle release. The leader peptide of FV Env, which is generated by a cleavage event during Env trafficking to the plasma membrane and is incorporated into particles, seems to play an important role in the budding process. Lindemann et al. reported the identification of ubiquitylated forms of the leader peptide; suppression of these ubiquitylated forms markedly stimulated subviral particle release. These results suggest that ubiquitylation of the FV Env leader peptide modulates the ratio of particle vs. subviral particle budding.
Progress continues to be made in visualizing retrovirus assembly and release in real time in living cells. In addition to use of the tetracyteine/biarsenical live-cell labeling system described above, B. Muller from H.-G. Krausslich\'s lab discussed the development of an infectious HIV-1 derivative containing a GFP insert near the C-terminus of MA. This derivative produces particles with wild-type morphology; however, release kinetics are impaired. While the Gag-GFP virus is poorly infectious, infectivity can be restored upon coexpression with wild-type HIV-1. This Gag-GFP HIV-1 derivative should be useful for both assembly/release and post-entry studies. In a presentation from the labs of V. Vogt and W. Webb, D. Larson described the use of correlated fluorescence microscopy and scanning electron microscopy to visualize Rous sarcoma virus (RSV) budding in real time using a GagGFP derivative.
Major advances have been made in the past three years in elucidating the host cell machinery required for the release of retrovirus particles from infected cells \[[@B29],[@B30]\]. It is now well accepted that retroviruses use their late domains to commandeer machinery that normally plays a central role in promoting the budding of vesicles into the MVB. This machinery includes the so-called \"class E Vps\" factors originally identified in yeast as being crucial for MVB biogenesis \[[@B31]\]. Many of these class E Vps proteins are found in three multisubunit complexes known as ESCRT-I, -II, and -III. Retroviral late domains come in three flavors: Pro-Thr/Ser-Ala-Pro \[P(T/S)AP\], Pro-Pro-x-Tyr (PPxY), and Tyr-Pro-Asp-Leu (YPDL). HIV-1 release is controlled predominantly by a P(T/S)AP-type late domain; many retroviruses, including MLV and RSV, contain PPxY late domains; and equine infectious anemia virus (EIAV) harbors a YPDL late domain. Several retroviruses \[e.g., Mason-Pfizer monkey virus (M-PMV) and HTLV-1\] encode both P(T/S)AP and PPxY late domains. In addition to its P(T/S)AP motif, HIV-1 contains a secondary YPDL-related sequence whose role in HIV-1 release remains to be defined. It is now well established that the P(T/S)AP motif interacts with the ESCRT-I component Tsg101. Recent data from several labs (those of H. Gottlinger, W. Sundquist, and P. Bieniasz) have strongly suggested that AIP1 (also known as ALIX) is the host factor with which YPDL interacts. There is less certainty about the identity of the biologically relevant PPxY-interacting protein. PPxY motifs in cellular proteins often interact with WW domains, and several PPxY-containing retroviral Gag proteins have been reported to bind the ubiquitin ligase Nedd4 (or related proteins), which contains a series of centrally located WW domains. P. Bieniasz\'s lab (Martin-Serrano et al.) reported at the meeting that MLV Gag binds the Nedd4-related proteins WWP1 (which has also been shown to associate with HTLV-1 Gag \[[@B32]\]), WWP2 and ITCHY. The extent to which binding to these proteins was reduced by mutations in the PPPY motif correlated with the severity of the budding defect induced by the mutations. The authors also observed that WWP1 localizes to aberrant endosomes induced by expression of a dominant-negative Vps4 in a manner dependent on the ubiquitin ligase (or HECT) domain, suggesting that the HECT domain may link WWP1 (and consequently Gag) to the class E Vps machinery. J. Leis\'s lab previously reported that overexpression of the WW domain-containing region from a chicken Nedd4-like protein inhibited RSV particle production. At this year\'s meeting, this work was extended (Vana et al.) by showing that in cells overexpressing this WW domain-containing fragment RSV virions accumulated in intracellular inclusion bodies. Interestingly, V. Vogt\'s lab (Johnson et al.) found that overexpression of the C-terminal domain of Tsg101 formed aggresome-like structures that trapped HIV-1 Gag.
In yeast, ESCRT-I contains three protein components: Vps23 (the yeast homolog of Tsg101), Vps28 and Vps37. In mammalian cells, only the Vps23 and Vps28 homologs had been identified. At this year\'s meeting, M. Stuchell from W. Sundquist\'s lab reported the cloning of human Vps37. As in yeast, human Vps37 binds Tsg101 and is present along with Tsg101 and Vps28 in a high molecular weight ESCRT-I complex. Much of this work has recently been published \[[@B33]\], as have similar results from H. Stenmark\'s lab \[[@B34]\]. Further illustrating the importance of ESCRT-I in HIV-1 budding, fusion of Vps37 to the C-terminus of Gag reverses the release defect imposed by PTAP deletion \[[@B33]\]. Y. Yardin\'s lab (Amit et al.) described the identification of an E3 ubiquitin ligase (termed Tal, for Tsg101-associated ligase) that binds the N-terminal UEV domain of Tsg101 and apparently regulates its activity. This work has also recently been published \[[@B35]\].
M. Palmarini\'s lab (Mura et al.) described a novel type of retroviral interference that operates at the level of virus assembly and release. The sheep genome harbors a number of copies of endogenous retroviruses closely related to the pathogenic exogenous β-retrovirus Jaagsiekte sheep retrovirus (JSRV). One of these endogenous retroviruses (enJS56A1) displays a defect in assembly/release. EM analysis indicates that enJS56A1 particles form large perinuclear aggregates; these appear to trap JSRV particles intracellularly when enJS56A1 and JSRV are coexpressed. The authors speculate that enJS56A1 may have helped protect sheep from infection with related, exogenous retroviruses during evolution. Much of this study has recently been published \[[@B36]\].
It has been known for many years that several retroviruses express two forms of Gag: a conventional version and a larger, glycosylated form referred to as glycoGag. GlycoGag is synthesized using an alternative, upstream initiation codon, and unlike its smaller counterpart it is transported to the plasma membrane through the secretory pathway. H. Fan\'s lab (Low et al.) reported at this year\'s meeting that a packaging cell line that expresses Gag without glycoGag produces tube-shaped particles at the cell surface. This apparent assembly defect was corrected by coexpression of glycoGag. The expression of glycoGag increased both virus yield and infectivity. These results suggest that glycoGag may function, in a manner that remains to be elucidated, in regulating proper virus assembly and release.
Integration
===========
Retroviral preintegration complexes (PICs) and the integrase (IN) enzyme itself, interact with a variety of host factors during nuclear import of the PIC and integration of the newly synthesized viral DNA into the host cell chromosome. One such host factor, lens epithelium-derived growth factor (LEDGF/p75), was recently reported to bind HIV-1 IN \[[@B37],[@B38]\]. Several presentations at this year\'s meeting provided varied and conflicting results regarding the role of LEDGF/p75 in the integration process. S. Emiliani reported data from a collaboration between the labs of R. Benarous and Z. Debyser showing that knockdown of LEDGF/p75 expression using siRNA in HeLa P4 cells inhibited HIV-1 replication without affecting the import of IN to the nucleus. The Q168L mutation in HIV-1 IN abolished both virus replication and the interaction between IN and LEDGF/p75. Busschots from the Debyser lab showed that the interaction of LEDGF/p75 with IN increased the affinity of IN for DNA. Based on these data, it was postulated that LEDGF/p75 may play a role in tethering IN to chromosomal DNA. E. Poeschla\'s lab (Llano et al., also see \[[@B39]\]) observed that endogenous LEDGF/p75 co-immunoprecipitated with both HIV-1 and FIV IN. Stable knock-down of LEDGF/p75 expression in 293T cells induced a redistribution of both HIV-1 and FIV IN from the nucleus to the cytoplasm but apparently did not affect nuclear import of HIV-1 or FIV PICs since lentiviral vector infectivity was not reduced under these conditions. Furthermore, stable knock-down of LEDGF/p75 expression in the Jurkat T-cell line did not affect HIV-1 replication. However, LEDGF/p75 was found to be a component of lentiviral PICs. The authors concluded that LEDGF/p75 is not required for lentiviral integration but advanced the hypothesis that it might play a role in target site selection. Vandekerckhove and colleagues from the Debyser lab reported that stable knock-down of LEDGF/p75 expression in HeLa P4 or MOLT cells delayed HIV-1 replication but did not diminish infectivity mediated by a VSV-G pseudotyped lentiviral vector. The authors controlled for non-specific siRNA effects by using double mismatched siRNA. Results from A. Engleman and coworkers (Vandegraaff et al.) raised further questions concerning the role of LEDGF/p75 in HIV-1 integration. They observed that while two LEDGF/p75 siRNAs reduced LEDGF/p75 protein levels, only the one originally described by the Debyser lab impaired HIV-1 infectivity. This infectivity defect could not be reversed by partially restoring LEDGF/p75 expression. Based on these results, the authors cautioned that the effect of LEDGF/p75 siRNA on HIV-1 infectivity may be due to non-specific effects not directly related to LEDGF/p75. Clearly, additional studies need to be performed to clarify the role of LEDGF/p75 in lentiviral integration.
A number of presentations focused on the target site specificity of retroviral (or retrotransposon) integration. Different retroviruses and retroelements display strong preferences in selecting their target sites in the genomes of their host cells (for review see \[[@B40]\]). For example, the Ty1 and Ty3 retrotransposons integrate predominantly upstream of Pol III-transcribed genes; the Tf1 retrotransposon selects sequences upstream of Pol II-transcribed genes; HIV-1 tends to integrate in actively transcribed regions; and MLV prefers to integrate in the promoters of active genes. At this year\'s meeting, A. Narezkina from R. Katz\'s and A. Skalka\'s lab, and R. Mitchell from F. Bushman\'s group, both described the results of genome-wide analyses of ASLV integration sites. They observed that, unlike MLV, this avian retrovirus does not prefer to integrate at transcription start sites, and unlike HIV-1 does not display a strong preference for highly active genes. Both groups did observe a relatively modest tendency for integration within genes. H. Levin\'s group (Kelly et al.) extended their previous work on Tf1 integration. Using a target plasmid containing a single gene, they observed that nearly all integration events took place in the gene\'s promoter region. Interestingly, the integration sites displayed a periodic pattern in which integrated copies of Tf1 were separated by around 30 nucleotides. This targeting appeared to be dependent on promoter activity. Kelly and coworkers speculated that the chromodomain in the Tf1 IN binds histones and regulates integration into specific targets in a promoter-positioned nucleosome. Holman and Coffin reported on the analysis of base preferences immediately surrounding integrated HIV-1 proviruses. Using a large amount of data derived from previously reported integration sites, the authors observed strong base preferences within seven residues at either end of integrated proviruses. The presentation emphasized that HIV-1 integration shows target preferences on both a macro scale (as noted above) and on a microscale, involving the residues immediately adjacent to the integration site.
M. Katzman\'s lab (Konsavage et al.) reported an interesting RSV IN mutant that displayed enhanced 3\'-end processing activity but impaired DNA joining. The authors speculated that RSV IN has evolved suboptimal processing activity to allow it to catalyze DNA joining.
R. Craigie\'s lab previously reported that a protein termed \"barrier-to-autointegration factor\" (BAF) is a component of the MLV preintegration complex and that this factor enhances intermolecular integration reactions and blocks intramolecular integration (autointegration) \[[@B41]\]. At this year\'s meeting, Suzuki and Craigie extended this work by showing that BAF interacts with an inner nuclear membrane protein, lamina-associated polypeptide 2α (LAP2α). LAP2α is a component of the MLV preintegration complex and knockdown of its expression inhibits MLV replication.
Reverse Transcription
=====================
A number of studies over the years have demonstrated that retroviral NC proteins possess nucleic acid chaperone activity that plays an important role in various aspects of reverse transcription (for review, see \[[@B42]\]). Several presentations focused on this activity of NC. Work from J. Levin\'s lab (Guo et al.) demonstrated that in an *in vitro*assay that models minus-strand transfer, NC alone is able to catalyze the removal of small 5\' terminal genomic RNA fragments, which remain annealed to a minus-strand strong-stop DNA. Strand transfer product increased with increasing NC, and in the presence of NC, strand transfer product was generated even when reverse transcription was catalyzed by an RNase H-deficient RT. The NC zinc fingers appeared to be critical for this activity. These results suggest an important role for NC nucleic acid chaperone activity in removing terminal RNA fragments annealed to minus-strand strong-stop DNA following primary cleavage by RNase H. By examining reverse transcription in infected cells, R. Gorelick\'s lab (Thomas et al.) observed that mutations in the first zinc finger of NC strongly interfered with the progression of reverse transcription and impaired virus infectivity. The authors speculated that reduced binding of NC to the viral DNA allows cellular enzymes (nucleases and ligases) to modify the viral DNA ends thereby interfering with integration.
Reverse transcription is initiated by a host cell-derived tRNA bound to the primer binding site (PBS) near the 5\' end of the viral genome. Retroviruses are selective in their utilization of host tRNAs; HIV-1, for example, specifically primes reverse transcription with a tRNA^lys3^. The selectivity for particular tRNAs results from interactions between the tRNA and the PBS and it has been proposed by B. Berkhout and colleagues that a second motif in the viral RNA, termed the primer-activation signal (PAS), also forms specific contacts with the tRNA. Berkhout\'s lab (Abbink et al.) reported at this year\'s meeting that, by mutagenesis of the PBS and PAS, HIV-1 primer utilization could be shifted from tRNA^lys3^to tRNA^lys1,2^. Such mutants replicated poorly but could adapt during long-term passaging. In one case, adaptation evidently occurred through optimization of the putative PAS. Interestingly, a single amino acid change in the RNase H domain of RT also arose during adaptation, suggesting a possible role for RT in selective primer utilization.
While PCR techniques allow the progression of viral DNA synthesis to be monitored post-infection, it has not been possible to follow reverse transcription in a strand-specific fashion in infected cells. D. Thomas from V. Pathak\'s lab reported the development of a strand-specific amplification assay that uses so-called \"padlock\" probes -- long single-stranded oligonucleotides that hybridize with their target sequence simultaneously at their 5\' and 3\' ends. Following hybridization, the ends of the padlock probes are ligated to form circles that are amplified and detected by real-time PCR. This assay, which allows specific steps in reverse transcription to be measured quantitatively in a strand-specific manner, should be very useful for addressing a number of questions regarding the kinetics of reverse transcription and the efficiency of this process under a variety of conditions.
F. Maldarelli described the results of studies conducted with S. Palmer, J. Coffin and colleagues aimed at characterizing the evolution of HIV-1 populations *in vivo*. The authors monitored genetic variation in cohorts of drug-naïve and drug-resistant patients by analyzing individual *pro-pol*sequences. In both drug-naïve and drug-resistant patients, they observed little change in virus population structure over several years, implying that the replicating population is relatively large. Interestingly, recombination rates appeared to be very high regardless of levels of viremia, suggesting the presence of a substantial number of multiply infected cells even at low viral loads. The results emphasize the importance of recombination in generating viral diversity *in vivo*.
Pathogenesis
============
The keynote speaker at this year\'s meeting was Neal Copeland, who presented important findings from his and Nancy Jenkins\' lab regarding the use of high through-put analysis to map retroviral integration sites in tumors induced by MLVs. This rapidly developing approach is being used by a number of groups to elucidate cancer gene pathways \[[@B43]-[@B46]\], and to define retroviral integration site preferences. The Jenkins and Copeland labs have used infection of various hematopoietic stem cells followed by transplantation into lethally irradiated mice to identify not only novel proto-oncogenes, but also cooperating cancer genes, tumor suppressors, and genes involved in stem cell transformation and immortalization. While this technique is currently applicable only to hematopoietic lineage cells, current research in the Jenkins and Copeland labs is testing whether integration by transposable elements in other cell types can be used to identify similar genes and pathways in solid tumors.
In contrast to the majority of leukemia-inducing retroviruses in non-human species, most of which cause cancer by insertional mutagenesis, HTLV-I encodes accessory proteins, such as Tax, with known transforming activity. There were several talks at the meeting describing new accessory proteins that may also play a role in cell regulation. Two talks focused on the protein p12^I^, which is targeted to the endoplasmic reticulum/Golgi of infected cells and decreases MHC class I trafficking to the cell surface. R. Fukomoto from G. Franchini\'s lab presented data that p12^I^decreases activation of the transcription factor NFATI in T cells by binding to LAT and inhibiting T-cell receptor signaling. In contrast, M. Lairmore presented data that p12^I^expression in Jurkat cells results in \~20-fold activation of NFAT-dependent gene expression in a calcium-dependent manner (Kim and Lairmore). These authors also demonstrated that p12^I^acts in the endoplasmic reticulum to activate calcium-mediated T-cell activation during the early stages of infection, apparently through an interaction with calcineurin. These studies suggest a prominent role for p12^I^in common T cell activation pathways critical to the establishment of a persistent infection. Another protein, p13^II^, which was described by V. Ciminale (Silic-Benussi et al.), is localized to the inner mitochondrial membrane and induces changes in Ca^2+^and K^+^permeability. In culture, p13^II^reverses the morphological transformation of rat embryo fibroblasts expressing c-Myc and Ha-Ras and decreases their ability to form tumors in nude mice. There was speculation that HTLV-I encodes p13^II^to counteract the growth-inducing properties of the other viral accessory proteins (such as Tax) that are required for establishment of infection, thereby allowing the virus to persist in infected individuals.
In a theme that echoed in several of the simple retrovirus talks, V. Armbruester from the Mueller-Lantzsch laboratory reported on a novel protein generated by alternative splicing of the envelope gene of the HERV-K endogenous retrovirus. The transcript for this protein, np9, is highly expressed in mammary carcinomas and germ cells, and the gene product binds to the LNX protein, which is a ligand of Numb and targets it for proteasomal degradation. Since LNX/Numb/Notch is a known transformation pathway in tumors, Armbruester speculated that np9 may play a role in tumorigenesis by sequestering LNX, thereby stabilizing Numb.
RNA transcription, processing, export and packaging
===================================================
This session surveyed new findings on retroviral splicing, nuclear retention and export, translation and packaging. J. Madsen and M. Stoltzfus evaluated the role of an exonic splicing silencer (ESS) on HIV-1 replication in cultured T cells. An HIV-1 mutant with ESS substitutions displays a replication-defective phenotype that correlates with increased viral RNA splicing. This mutant was subjected to long-term passage and the viruses that emerged contained second-site reversions in splice sites flanking the exon containing the mutated ESS. Stoltzfus speculated that strains that do not contain the ESS maintain balanced expression of their viral genome by a novel, unknown mechanism.
A. Lever\'s lab (Poole et al.) described confocal microscopy and fluorescence resonance energy transfer (FRET) analysis of the interaction between HIV-1 Gag and its cognate genomic RNA. Using biotinylated probes to the full-length, unspliced RNA, he described an initial perinuclear co-localization between Gag and genomic RNA that subsequently shifted to the plasma membrane. Mutation of the Ψ packaging signal partially disrupted the perinuclear and plasma membrane colocalization.
J. Dudley\'s lab (J. Mertz et al.) described a new MMTV gene that encodes a viral RNA transport protein generated by alternative splicing of the *env*gene. The gene was designated *rem*, (for RNA export protein of MMTV RNA). Its product stimulated nucleocytoplasmic transport of the unspliced MMTV transcript, in a manner similar that of the Rec protein of HERV-K \[[@B47],[@B48]\]. This finding indicates that MMTV encodes at least three accessory genes (encoding dUTPase, superantigen, and Rem) in addition to the standard retroviral genes (*gag*, *pol*, and *env*). The Dudley group suggested that since MMTV exhibits a complex genetic structure it should be reclassified as a complex retrovirus.
K. Boris-Lawrie (Roberts et al.) presented genetic and biochemical data showing that the R-U5 region of SNV RNA adopts a stem-loop structure that stimulates cap-dependent translation. RNA affinity and proteomic analysis showed that RNA helicase A (RHA) bound to wild-type RNA but not to mutants containing substitutions in this structure. RHA interaction with SNV R-U5 stimulated translation of unspliced HIV-1 reporter mRNA. Boris-Lawrie speculated that this could occur by rearrangement of intramolecular RNA interactions that disrupt the packaging signal, thus facilitating mRNA translation.
*In vivo*, only a fraction of HTLV-infected cells actively expresses viral RNA, leading to speculation that the virus negatively regulates gene expression. P. Green (Younis et al.) described a new role for HTLV-1 and -II accessory proteins p30 and p28, respectively, in negatively regulating virus production during chronic infection. Tax/Rex expression was inhibited upon ectopic expression of p28 by a mechanism that involved nuclear retention of the mRNA. Analysis of RNAs bearing a luciferase reporter gene showed that the 3\' splice junction was sufficient to confer this nuclear retention. From this work and the studies from the Franchini and Lairmore labs described above, it is clear that HTLV-1 has evolved to regulate its expression in infected cells, thereby evading immune recognition and promoting viral persistence.
Antivirals
==========
As in previous years, there was a strong emphasis on the development of antiviral agents that interfere with reverse transcription. However, noteworthy progress was also reported in efforts to target a number of additional steps in the replication cycle.
S. Sarafianos reported data from E. Arnold\'s lab (Himmel et al.) on the structure of HIV-1 RT in a complex with an RNase H inhibitor. Interestingly, the binding site of the compound is quite distant (\>40 Angstroms) from the RNase H active site and partially overlaps the NNRTI binding pocket. These results raise the intriguing possibility that compounds could be designed that simultaneously act as RNase H inhibitors and as NNRTIs. M. Miller\'s lab (Shaw-Reid et al.) performed *in vitro*assays to examine the effect of RT polymerase inhibitors on RNase H activity. They observed that NNRTIs actually increased RNase H activity; structural studies suggested that this enhancement was due to greater accessibility of the DNA/RNA duplex by RNase H. Although a diketo acid RNase H inhibitor displayed decreased potency in the presence of an NNRTI, the diketo acid and NNRTI synergistically inhibited reverse transcription overall.
C. Wild, E. Freed, and colleagues, and independently C. Aiken\'s lab, previously reported that a dimethyl succinyl betulinic acid derivative (referred to as PA-457 or DSB) potently blocks HIV-1 infectivity by specifically disrupting the cleavage of the CA precursor (composed of CA and spacer peptide SP1) to mature CA \[[@B49],[@B50]\]. The block to CA-SP1 processing prevents proper core condensation in virions released from PA-457-treated cells. Interestingly, HIV-2 and SIV are insensitive to PA-457. This work was extended by the labs of C. Wild and E. Freed (F. Li et al.) to demonstrate that the determinant of PA-457 activity maps to the N-terminus of SP1. In addition, (Adamson et al.) the passaging of HIV-1 at sub-optimal concentrations of PA-457 led to the appearance of PA-457-resistant variants that contain mutations in the C-terminus of CA or the N-terminus of SP1.
A. Lever\'s lab (Brown et al.) described their efforts to inhibit HIV-1 replication using oligonucleotides that target the viral genome. The authors observed that oligos targeting the packaging signal (specifically stem-loops 2 and 3) disrupt Gag binding and reduced virus infectivity. T. Murakami and coworkers reported the development of an orally bioavailable compound that binds the HIV-1 chemokine coreceptor CXCR4. In culture, the compound potently inhibits infection by HIV-1 isolates that use CXCR4 as a coreceptor, but, as expected, do not block infection by strains that exclusively use CCR5 as a coreceptor. The compound suppressed HIV-1 infection in the hu-PBL-SCID mouse model. The results of this study suggest that this CXCR4 antagonist could potentially be an effective drug in infected humans.
It has been suggested that most virus originating in the central nervous system (CNS) derives from long-lived cells (e.g., macrophages) that would continue to produce virus for a significant period of time after the initiation of antiretroviral therapy. According to this model, CNS-derived virus should decay more slowly following the onset of therapy relative to virus derived from the blood. In the last presentation of the conference, data were presented from R. Swanstrom\'s lab (Harrington et al.) obtained from a study of HIV-1 population dynamics in cerebrospinal fluid (CSF) immediately following the initiation of antiretroviral therapy. Virus isolates in the CSF apparently derive from both the CNS and the blood plasma. Interestingly, using heteroduplex tracking assays, the authors observed that within the first several days following the initiation of therapy CNS-derived isolates in the CSF decline with similar kinetics to isolates shared with the blood, suggesting that virus from both compartments is produced by cells with a short life span.
Acknowledgements
================
We thank the meeting participants whose work is cited here for their willingness to share their unpublished results and acknowledge those who provided comments on this review. We apologize to the many participants whose studies are not discussed here.
|
PubMed Central
|
2024-06-05T03:55:48.015745
|
2004-9-9
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519032/",
"journal": "Retrovirology. 2004 Sep 9; 1:25",
"authors": [
{
"first": "Eric O",
"last": "Freed"
},
{
"first": "Susan R",
"last": "Ross"
}
]
}
|
PMC519033
|
Background
==========
The transport of capsules in the alimentary tract underlies complex influencing factors like the patients peristalsis, the hydration and the form and size of the capsules. A procedure which allows the instantaneous localization of the capsules supports a number of patient examinations as well as examinations of new drug forms \[[@B1]-[@B4]\]. Capsules can be marked radioactively (scintigraphy) or magnetically. The scintigraphy \[[@B5]\] has a lower time resolution compared to the magnetic localization, and due to radiation it is not appropriate for examinations with healthy probands.
The localization of magnetically marked capsules (magnetic markers) must be spatially accurate and with high temporal resolution. For the spatial localization the marker field must be separated from the external magnetic disturbing fields. This separation can be achieved by splitting the magnetic field in multipole moments \[[@B6]\]. The method proposed utilizes the multipole moments directly for the determination of the position and the magnetic moment of the marker. Thus, the separation of disturbing fields and the localization are integrated numerically effective into one procedure. This allows a fast online-localization of the marker capsules.
Multipole expansions are used also to model spatially distributed biological sources such as brain currents \[[@B7],[@B8]\].
The application of multipoles for the localization of magnetic dipoles is described in \[[@B9],[@B10]\], and is used in other technical areas without disturbing field suppression \[[@B11]\].
Marking of capsules and pills takes place by partially filling them with black iron oxide (Fe~3~O~4~) which is subsequently magnetized up to saturation. The magnetic field measurement is performed within magnetically shielded rooms by the use of highly sensitive SQUID arrays. For the investigation at hand we conduct simulation runs to determine the performance of the multipole localization.
Methods
=======
Algorithm
---------
The field of a magnetic marker located adjacent to the point of origin can be expressed by a multipole expansion in Cartesian coordinates (*x*~1~, *x*~2~, *x*~3~). If the distance  between marker and origin is small compared to the distance  between a magnetic sensor and the origin, the field of the marker at the sensor position is given by the first elements of the multipole expansion. With the notation
follows
with *c*^m^being the dipole, quadrupole and octopole moments of the field expansion.
The form functions  arise from a Taylor series expansion in the parameter  with  and . It holds
With the Kronecker delta  follows
and
Conversely, a Taylor series expansion of -- compared to the sensor coordinates -- far away located field sources in the parameter  with  yields a multipole expansion of external disturbing fields:
We denote the multipole moments *c*^ex^of the expansion of fields of external sources as \"outer moments\" to distinguish them from the \"inner moments\" *c*^m^.
To get the same normalization and symmetry properties for the outer and inner form functions, we define the outer form functions  by
It follows
and
The tensors of 3^rd^order  and of 4^th^order  own the following symmetry features which are identical for the inner and outer multipole expansion:
We combine the resulting 3, 5 and 7 linearly independent components of the tensors of 2^nd^, 3^rd^and 4^th^order to one vector for the marker field  and one vector for the external disturbing field :
The summation of equation (1) and equation (6) yields the field expansion for a magnetic marker with disturbing fields. We truncate this expansion after the octopole terms, and transcript it into a linear equation system for the determination of equivalent multipole moments **c**for a measurement **B**~meas~:
The structure of the vectors **B**~meas~and **c**and the matrix **F**is given below in the formulas (15\...24). The residuals 0(·) are sufficiently small, if the coordinates of the marker are small compared to the coordinates of the field sensors , and if the coordinates of the field sensors are small compared to the coordinates of the external disturbing field sources .
**B**~meas~is a vector with the measurement values of the magnetometer sensor field in the positions  with the directions :
The matrix **F**is built from the linearly independent form functions for inner and outer field sources given in equation (13). Their scalar product with the sensor normal directions  yields one row for every sensor:
The number of columns of **F**is the sum of the numbers of inner and outer field functions used. Each column describes the field of one specific magnetic moment with unit strength measured by the sensor system. The Matrix **F**is called the forward matrix of all moments considered. The Matrix **F**is structured into submatrices for different moments:
Matrix  and  are the forward matrices for inner and outer dipoles:
Matrix  and  are the forward matrices for inner and outer quadrupoles. The size of  is (*Nsen*/5) with the rows belonging to quadrupole moments with indices (1,1; 3,3; 1,2; 2,3; 3,1).
Matrix  and  are the forward matrices for inner and outer octopoles. The size of  is (*Nsen*/7) with the rows belonging to octopole moments with indices (1,2,2; 2,3,3; 3,1,1; 1,3,3; 2,1,1; 3,2,2; 1,2,3).
The vector of multipole moments **c**is composed of inner and outer dipole moments **c**~d~, quadrupole moments **c**~q~and octopole moments **c**~o~:
The inner dipole moments  describe a dipole at the point of origin, the outer dipole moments  describe a homogeneous disturbing field:
The  represent a quadrupole at the point of origin. The  describe an external gradient field, whose field strength vanishes at the origin and which has no spatial derivations of 2^nd^or higher order. This field can be measured by five ideal gradiometers at the origin and can be compared with the creation of software gradiometers.
The  represent an octopole at the origin. The  describe an external gradient field of 2^nd^order, which has no spatial derivations of 3^rd^or higher order and whose field strength and spatial derivatives of 1^st^order vanish at the origin. This field could be measured by 7 ideal second order gradiometers at the origin, it can be compared with the creation of software gradiometers of 2^nd^order:
Due to its small spatial extension, the magnetic marker can be described as a dipole of strength  at position  as a good approximation. The field of this dipole is
With the Taylor series expansion
follows in analogy to equation (1)
A comparison of coefficients of (1) and (27) yields
and
The dipole strength  can be determined by the dipole moment . An equation system for the adjacent calculation of the dipole position  from the dipole strength  and the quadrupole moment  follows from (29) and (23):
with
This equation system is named shift equation in analogy to \[[@B10]\]. It is overdetermined, and can be solved by means of the pseudo inverse of **m**.
We get the multipole moments **c**, which are required for the localization of the marker dipole, from solving the overdetermined equation system (14) by means of the pseudo inverse of **F**:
**c**= (**F**^T^·**F**)^-1^·**F**^T^·**B**~meas~. (33)
Here, the matrix of form functions **F**must contain columns at least for the moments  and .
Iterative dipole localization for a fixed dipole (e.g. one time point) is achieved by using the localization position as a new point of origin. The step length of the last localization step serves as a stop criterion for the iterative localization procedure. This is justified by considering the residuals of equation (14) within the convergence range of the procedure, and will practically be shown by the results of the following simulations.
The tracking of a moved dipole based on measurements at consecutive time steps works by updating both the point of origin and the measurement data set after each localization step (Fig. [1](#F1){ref-type="fig"}). The localization step must be monitored, since it contains information about the marker speed and the noise dependent and speed dependent localization errors.
::: {#F1 .fig}
Figure 1
::: {.caption}
######
**Flow chart of the algorithm for online localization.**This algorithm is meant for online localization, and therefore comprises only one iteration. A high signal to noise ratio and a high computing speed render 2--3 iterations per measurement cycle possible.
:::
:::
Measurement system
------------------
The simulations to determine the performance of the algorithm use the sensor geometry of the multi channel SQUID system Argos 200 from AtB (Advanced Technologies Biomagnetics, Pescara, Italy). The ARGOS 200 system contains fully integrated planar SQUID magnetometers produced using Nb technology with integrated pick-up loops. The sensing area is a square of 8 mm side length. The intrinsic noise level of the built in 195 SQUID sensors is below 5 fT Hz^-1/2^at 10 Hz. Three sensors form one orthogonal triplet in each case. The measurement plane with a diameter of 23 cm consists of 56 of those triplets. The reference array consists of seven SQUID sensor triplets located in the second level in a plane which is positioned parallel to the measurement plane at a distance of 98 mm. The third (196 mm above the first plane) and fourth (254 mm above the first plane) levels contain one triplet each (Fig. [2](#F2){ref-type="fig"}).
::: {#F2 .fig}
Figure 2
::: {.caption}
######
**SQUID Array Argos 200.**The ATB SQUID Array Argos 200 consists of 195 magnetometers which are arranged in orthogonal sensor triplets in four levels. The measurement area of each sensor is a square of 8 mm edge length.
:::
:::
The measurement system is positioned within a magnetically shielded room, consisting of 3 highly permeable shieldings and one eddy current shielding. The shielding performance is 38 db at 1 Hz, 55 db at Hz and 80 db at 20 Hz.
The sensor arrangement in orthogonal triplets facilitates the measurement of all 3 spatial components of the magnetic field. Thus, the required field coverage for the localization of a magnetic marker with unknown dipole strength is achieved.
The subdivision into 168 measurement and 27 reference sensors is meant for the creation of software gradiometers. We can use all sensors simultaneously for the multipole method which integrates the suppression of disturbing fields.
With the above described measurement system we performed simulations with different signal to noise ratios.
Results
=======
We examined the localization characteristics of the multipole method by means of simulation runs at the sensor geometry of the measurement system Argos 200 (Fig. [2](#F2){ref-type="fig"}). All simulations performed are based on a dipole at position (*x*, *y*, *z*) = (0, 0, -300 mm), i.e. 30 cm below the measurement plane, with a dipole strength of 20 Amm^2^. This is a realistic dipole position for an examination within the digestive tract. The dipole field was superimposed by uncorrelated, Gauss distributed noise. The noise level in fT is also given as signal-to-noise-ratio (SNR), based on the channel with the strongest amplitude of the dipole field.
The average localization accuracy over 100 simulations has been determined depending on the noise level and on the number of the multipole moments used in the vector **c**(21) (Fig. [3](#F3){ref-type="fig"}).
::: {#F3 .fig}
Figure 3
::: {.caption}
######
**Noise-dependent localization error.**The mean squared localization error e*rr*() over 100 simulations has been determined depending on the noise level and on the different number of multipole moments used. The curves are plotted up to the noise level, where all simulations still produced a stable localization result. We used the inner moments up to the 3^rd^order , , plotted in curves 3χ and the inner moments up to the 4^th^order , , , plotted in curves 4χ. The outer moments which were used to model the disturbing fields were none (curves χ0), 2^nd^order moments (curves χ2: homogeneous fields), 2^nd^and 3^rd^order moments (curves χ3: homogeneous and gradient fields), and 2^nd^to 4^th^order moments (curves χ4: external fields up to 2^nd^order). The simplest disturbing field to model is a homogeneous field having index χ2. The dipole field of a dipole with a strength of 20 Amm^2^at position (*x*, *y*, *z*) = (0, 0, -300 mm) is superimposed by white, Gaussian distributed noise, which is given in fT and as the signal to noise ratio (SNR).
:::
:::
The localization was run up to a stable point. We define the localization error as the mean quadratic error of the 100 stable points based on the true dipole position. The localization error increases if we use higher order multipole moments. This holds true for the inner moments **c**^m^and for the outer moments **c**^ex^as well. As a good approximation the interrelationship between noise level and localization error is linear, with raising proportionality factor for higher mode numbers. This corresponds to parallel translation of the curves in double logarithmic plotting.
We examined the localization speed depending on the distance of the starting point to the dipole position. For any tested distance the starting point has been moved from the dipole position into 100 random directions. The remaining mean distance to the dipole position after one localization step is depicted in Fig. [4](#F4){ref-type="fig"}. The localization speed turns to be significantly higher when using inner octopoles. It gets higher with a shorter starting distance in both an absolute and a relative manner based on the starting distance. Both effects are to be expected directly from the residuals of equation (14). The influence of the outer multipoles on the localization speed is low. The convergence radius at which the dipole was found from all 100 directions decreases slightly with the raising number of outer multipoles used, and increases slightly if inner octopoles are used (unequal right ends of the respective curves in Fig. [4](#F4){ref-type="fig"}). The convergence radius ranges between 6 and 10 cm. The maximum number of iterations for a target accuracy of 1 mm can be estimated from Fig. [4](#F4){ref-type="fig"} as 3.
::: {#F4 .fig}
Figure 4
::: {.caption}
######
**Localization error depending on the starting point distance for one iteration.**For each distance *d*~*s*~the start position has been moved from the dipole into 100 random directions. The mean remaining distance *d*~*r*~after one localization step is shown. The curves are plotted until the starting distance *d*~*r*~where the localization was still stable from all 100 directions. To get the result after multiple iterative localization steps, the *d*~r~-value has to be taken as the starting distance *d*~*s*~of the following step. We used the inner moments up to the 3^rd^order , , plotted in curves 3χ and the inner moments up to the 4^th^order , , , plotted in curves 4χ. The outer moments which were used to model the disturbing fields were none (curves χ0), 2^nd^order moments (curves χ2: homogeneous fields), 2^nd^and 3^rd^order moments (curves χ3: homogeneous and gradient fields), and 2^nd^to 4^th^order moments (curves χ4: external fields up to 2^nd^order).
:::
:::
In the following we examined the interrelationship between the convergence distance at y-direction and the noise level. The maximum y-distance of the starting position to the dipole, at which the dipole could be found with 100 random noise distributions, is depicted in Fig. [5](#F5){ref-type="fig"}. It shows that the convergence distance remains unchanged almost up to the point of critical noise level (see Fig. [3](#F3){ref-type="fig"}) at which localization becomes impossible. The convergence distance, also compare the maximum convergence radius from the curve ends of plot (Fig. [4](#F4){ref-type="fig"}), depends only marginally on the choice of the inner ansatz functions. It decreases slightly when using outer multipoles. Having a convergence radius of at least 6 cm for the dipole position tested, the choice of the starting position can be regarded as noncritical.
::: {#F5 .fig}
Figure 5
::: {.caption}
######
**Convergence distance depending on noise level.**The maximum y-distance *dy*between starting position and dipole position, at which for 100 random noise distributions the dipole could still get localized, is plotted. We used the inner moments up to the 3^rd^order , , plotted in curves 3χ and the inner moments up to the 4^th^order , , , plotted in curves 4χ. The outer moments which were used to model the disturbing fields were none (curves χ0), 2^nd^order moments (curves χ2: homogeneous fields), 2^nd^and 3^rd^order moments (curves χ3: homogeneous and gradient fields), and 2^nd^to 4^th^order moments (curves χ4: external fields up to 2^nd^order). The dipole field of a dipole with a strength of 20 Amm^2^at position (*x*, *y*, *z*) = (0, 0, -300 mm) is superimposed by white, Gaussian distributed noise given in fT and as the signal to noise ratio (SNR).
:::
:::
The computing time used for one localization step is 5 ms with an implementation in Matlab at a standard Windows PC with a 2 GHz clock frequency. With maximum 3 iterations per localization step and additional computing time needed for data transfer and a basic visualization, 10 localizations per second are possible. This rate is normally sufficient for marker localizations.
Discussion
==========
The localization speed rises when using inner octopoles , but this is associated with a higher localization error. At a signal to noise ratio lower than 10^3^inner octopoles cannot be used. An SNR of at least 10^2^is required for a source positioned 30 cm below the measurement plane.
The outer moments **c**^ex^used enlarge the localization error depending on the uncorrelated sensor noise, as shown in Fig. [3](#F3){ref-type="fig"}. Contrary, the localization error depending on the spatially correlated residual field within the measurement room lowers when using outer moments. Depending on the ratio between correlated and uncorrelated noise which has to be found with practical test series, noise suppression of homogeneous disturbing fields using  and possibly noise suppression of gradient fields using  are applicable. To ensure convergence, the starting point for the algorithm has to be within the convergence radius given in Fig. [4](#F4){ref-type="fig"}. With typical measurement conditions, thus, a starting point 10 cm below the center of the measurement system will suffice.
Conclusions
===========
The multipole localization is an effective algorithm because it unites a method for the suppression of disturbing fields with a localization method. It can be used iteratively and online for the tracking of magnetic marker timelines within the intestinal tract.
Acknowledgements
================
This work has been partially supported by the joint research project \"MagMon/NET0158\" within the \"InnoNet\" program of the German Federal Government Department of Research (BMWA).
|
PubMed Central
|
2024-06-05T03:55:48.019882
|
2004-9-1
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC519033/",
"journal": "Biomagn Res Technol. 2004 Sep 1; 2:6",
"authors": [
{
"first": "Bernd",
"last": "Hilgenfeld"
},
{
"first": "Jens",
"last": "Haueisen"
}
]
}
|
PMC520599
|
Introduction {#s1}
============
Hematopoietic stem cells (HSCs) are the best-described adult stem cell population at a phenotypic and functional level. Recent attempts have been made to characterize their molecular regulation by comparing their gene expression profiles with those of other stem cell populations ([@pbio-0020301-Ivanova1]; [@pbio-0020301-Ramalho-Santos1]; [@pbio-0020301-Fortunel1]). These analyses of normal steady-state stem cells revealed so-called stem cell signatures, but the overlap of genes that universally defined "stemness" was extremely limited ([@pbio-0020301-Fortunel1]). Here, we have focused on HSCs alone in order to systematically examine one process, that of HSC self renewal, comprising a cycle of quiescence, proliferation, and reinduction of a dormant state.
In a normal adult, HSCs reside in the bone marrow, where they are relatively inactive. Long-term HSCs divide infrequently to produce more proliferative short-term HSCs, which in turn generate the lineage-committed progenitors that manufacture the billions of differentiated hematopoietic cells that daily enter the peripheral blood. One hallmark of HSCs is their ability to rapidly proliferate in response to stressors such as myelosuppressive chemotherapy or bone marrow transplantation in order to quickly generate work-horse progenitors as well as additional stem cells, which then return to quiescence ([@pbio-0020301-Dixon1]). While this expansion of HSCs occurs naturally in vivo, there is as yet little understanding of the genes that control this process. A full appreciation of the molecular regulation of stem cell self renewal could illuminate the development of cancers ([@pbio-0020301-Sherr1]) as well as potentially inform strategies for in vitro stem cell expansion, which would have enormous clinical advantages. Thus, we sought to understand the molecular mechanisms by which HSCs respond to an activating trigger, initiate a program of cell division, and resume quiescence by suppression of cell division.
Our approach was to examine the transcriptional profiles of purified adult HSCs throughout a time course of induced proliferation, and compare the gene expression in these cells to that of naturally dividing fetal liver HSCs (FL-HSCs). Normal adult HSCs are largely nondividing, with around 1%--3% in cycle and approximately 90% in G0 ([@pbio-0020301-Morrison1]; [@pbio-0020301-Goodell1]; [@pbio-0020301-Bradford1]; [@pbio-0020301-Cheshier1]). A single injection of the pyrimidine analog 5-fluorouracil (5FU) kills cycling hematopoietic cells, bringing the spared quiescent HSCs into cycle to repopulate the depleted bone marrow ([@pbio-0020301-Van1]; [@pbio-0020301-Harrison1]; [@pbio-0020301-Randall1]). HSC proliferation proceeds in a time-dependent manner, peaking 5 to 6 d after treatment, with approximately 20% of HSCs in cycle, before returning to normal around day 10 ([Figures 1](#pbio-0020301-g001){ref-type="fig"}A and [S1](#sg001){ref-type="supplementary-material"}; [@pbio-0020301-Randall1]). Changes in the cell surface profile concomitant with cell cycle activation have been observed. The receptor tyrosine kinase c-Kit, normally expressed at high levels in quiescent HSCs, is down-regulated after 5FU treatment ([@pbio-0020301-Randall1]). Conversely, the markers Mac1 and AA4.1, absent on normal HSCs, are expressed at low levels after 5FU treatment ([@pbio-0020301-Szilvassy1]; [@pbio-0020301-Randall1]).
::: {#pbio-0020301-g001 .fig}
Figure 1
::: {.caption}
###### P-Sig and Q-Sig Defined by Gene Expression Levels in HSCs in Different Stages of Cell Cycle
\(A) Graphic depicting the changes in bone marrow cellularity and number of HSCs in cell cycle following 5FU treatment (adapted from [@pbio-0020301-Harrison1]; [@pbio-0020301-Randall1])*.*
\(B) Schematic of 5FU-HSC time course analysis. The genes that change over the time course can be split into two groups based on the day of maximum expression (TOM).
\(C) Schematic of pair-wise comparison between quiescent adult HSCs and FL-HSCs, showing groups of genes either up-regulated in the quiescent adult cells or up-regulated in the cycling FL-HSCs.
\(D) Genes that were both up-regulated in FL-HSCs and were in the proliferation group composed the P-sig. The P-sig shows 94% overlap with the group of genes that were up-regulated in FL-HSCs and changed over the time course.
\(E) Genes that were both in the quiescence group and up-regulated in adult HSCs were termed the Q-sig. The Q-sig overlaps 96% with the set of genes that were up-regulated in adult HSCs and changed over the time course.
\(F) Overlap of the ST-HSC signature with P-sig revealed 73% in common, defining the common P-sig.
\(G) Overlap of the LT-HSC signature with Q-sig revealed 58% in common and defined the common Q-sig.
This figure is interactive online, and provides contextual access to [Tables S1--S11](#st001){ref-type="supplementary-material"}. Use your mouse to highight animated areas of the graphic. Click on these areas to link to related files.
:::
:::
During the latter part of mammalian embryonic development, HSCs reside in the fetal liver, where they undergo a massive expansion prior to entering the bone marrow. Approximately 30% of murine FL-HSCs are in cycle ([@pbio-0020301-Morrison2]), and similar to 5FU-activated HSCs (5FU-HSCs), they express AA4.1 and Mac1 ([@pbio-0020301-Jordan1]; [@pbio-0020301-Morrison2]). Given the similarities between 5FU-activated HSCs and FL-HSCs, we hypothesized that they would share similar gene expression profiles vis-à-vis proliferation and that simultaneous comparison of FL-HSCs, adult quiescent HSCs, and 5FU-HSCs would define genes specifically involved with HSC proliferation. Indeed, we defined both proliferation and quiescence signatures for HSCs, validated these groupings using Gene Ontology (GO) classifications, and created a model of the HSC proliferation cycle.
Results {#s2}
=======
Experimental Design {#s2a}
-------------------
Our overall approach was to isolate highly purified HSCs in the states described above, obtain their gene expression profiles using Affymetrix microarrays, and apply statistical and bioinformatics methods to facilitate comparisons among the samples. To construct a profile of the time-dependent induction of HSC proliferation, 5FU-HSCs were isolated at days 0, 1, 2, 3, 6, 10, and 30 after treatment.
Adult quiescent HSCs and 5FU-HSCs were isolated according to Hoechst 33342 efflux, termed the side population (SP) and Sca1^+^ characteristics ([@pbio-0020301-Goodell1]) ([Table 1](#pbio-0020301-t001){ref-type="table"}; [Figure S2](#sg002){ref-type="supplementary-material"}A). Further analysis of these populations revealed them to be highly homogeneous with more than 97% having Sca1^+^/Lineage^−^ characteristics ([Figure S3](#sg003){ref-type="supplementary-material"}). Transplantation into lethally irradiated hosts, performed for both quiescent and 5FU-treated SP/Sca1^+^ cells, confirmed their stem cell activity (data not shown). FL-HSCs were isolated by FACS for AA4.1^+^, c-Kit^+^, Sca1^+^, and Lineage^−^ characteristics from embryos 13.5--14.5 d postcoitus ([@pbio-0020301-Jordan1]) ([Table 1](#pbio-0020301-t001){ref-type="table"}; [Figure S2](#sg002){ref-type="supplementary-material"}B.) RNA probes were prepared from HSCs using two rounds of in vitro transcription and applied to Affymetrix MGU74Av2 microarrays. Hybridization, scanning, and production of raw data files were performed according to standard protocols. To correct raw intensity values for systemic variables such as fragmentation efficiency, hybridization conditions, and scanner effects, microarrays were normalized before intensity values were converted to gene expression measures. Normalization and model-based expression measurements were performed with GeneChip Robust Multichip Analysis ([@pbio-0020301-Wu1]), which is more precise and accurate in estimating fold changes than Affymetrix MAS 5.0 and the recently published Robust Multichip Analysis method ([@pbio-0020301-Irizarry1]), and is available as part of the open-source Bioconductor project (<http://www.bioconductor.org>). Further statistical analysis was performed in R (<http://www.r-project.org>). Quality control was performed both pre- and postnormalization. Briefly, chips were inspected for spatial defects, intensity outliers, and amplification bias. After screening, the two chips representing biological replicates with the highest correlation (R^2^ = 0.97--0.99, average = 0.98) in each group or time point were selected for further analysis. Raw data and normalized expression data are available for download from Gene Expression Omnibus (<http://ncbi.nlm.nih.gov/geo>) or <http://franklin.imgen.bcm.tmc.edu/SCGAP/downloads/SPTimecourse>. Normalized expression data along with all filtering criteria used to obtain our gene lists are available in [Table S46](#st046){ref-type="supplementary-material"}. A gene-by-gene query tool is available at <http://franklin.imgen.bcm.tmc.edu/PLoS>.
::: {#pbio-0020301-t001 .table-wrap}
Table 1
::: {.caption}
###### Comparison of Phenotypic and Functional Characteristics of HSC Populations
:::
^a^ [@pbio-0020301-Goodell1]
^b^ [@pbio-0020301-Randall1]
^c^ [@pbio-0020301-Szilvassy1]
^d^ [@pbio-0020301-Jordan1]
^e^ [@pbio-0020301-Morrison1]
^f^ [@pbio-0020301-Morrison2]
^g^ [@pbio-0020301-Uchida1]
d.p.c., days postcoitus, N.D., not determined
:::
Time of Maximum Grouping Reveals Strong Time Ordering to Expression Data {#s2b}
------------------------------------------------------------------------
We began our analysis of the 5FU time course by identifying genes that varied over time. This was accomplished by fitting smooth curves to the expression profiles using regression analysis with time as a continuous variable. ANOVA on these profiles revealed 1,488 genes that showed a significant change over the time course (*p* \< 0.05). Principle component analysis revealed that the time course data consisted of two major groups: genes that up-regulated and genes that down-regulated over the time course (data not shown). We further explored the expression data with unsupervised (k-means) clustering and observed that when the number of predefined groups was low (2--3), only the overall pattern of up- or down-regulation was discernable; however, as we increased the number of groups (4--8), more complex patterns with peaks early or late in the time course were visible (data not shown). Since the 5FU treatment consisted of a single dose administered at time zero, we speculated that the downstream effects of 5FU treatment would be represented by groups of genes whose gene expression profiles showed time-ordered peaks propagating through the time course. The expression profile of groups created by k-means clustering supported this hypothesis. Therefore, to more directly delineate these peaking subsets, we sorted the genes into groups by their time of maximum expression (TOM). Strikingly, these groups had two predominant patterns over the time course: one group up-regulated with 5FU treatment with a TOM at day 2, 3, or 6, and one group down-regulated, exhibiting TOM at day 0, 1, 10, or 30 ([Figure 1](#pbio-0020301-g001){ref-type="fig"}). By correlating these patterns to HSC cell cycle status after 5FU treatment ([Figure 1](#pbio-0020301-g001){ref-type="fig"}A), we assigned the up-regulated genes to the "proliferation" group (680 genes) and the down-regulated genes to the "quiescence" group (808 genes) ([Figure 1](#pbio-0020301-g001){ref-type="fig"}B).
To validate these time-dependent expression-pattern-based gene groupings, we compared our quiescence and proliferation groups to the genes differentially expressed between quiescent adult HSCs and FL-HSCs. The latter were identified in a pair-wise comparison between adult HSCs and FL-HSCs that revealed 1,772 genes that were at least 2-fold differentially expressed ([Figure 1](#pbio-0020301-g001){ref-type="fig"}C). Since FL-HSCs are in cycle, as are 5FU-HSCs, a list of genes expressed in common between the time-course-defined proliferation group and those up-regulated in FL-HSCs should specifically contain genes involved in HSC proliferation, eliminating genes involved in interacting with their very different source environments. We designated this list of 338 genes our "proliferation signature" (P-sig; [Figure 1](#pbio-0020301-g001){ref-type="fig"}D). Likewise, the 298 genes in common between the time-course-defined quiescence group and those up-regulated in adult HSCs relative to FL-HSCs defined our "quiescence signature" (Q-sig; [Figure 1](#pbio-0020301-g001){ref-type="fig"}E). In [Figure 2](#pbio-0020301-g002){ref-type="fig"}B and [2](#pbio-0020301-g002){ref-type="fig"}D, each gene within the P-sig and Q-sig is represented by a single line, and its relative expression along the time course is represented by the intensity of the colors on the heat map. Genes discussed later in the text are highlighted. To examine whether similar signatures could be generated without the TOM groupings (which could potentially introduce a bias), we examined the list of genes overlapping between the set of those up-regulated in FL-HSCs and the entire set of genes that change during the time course (see [Figure 1](#pbio-0020301-g001){ref-type="fig"}D). A striking 94% of the P-sig overlaps with these genes. Similarly, 96% of genes in the Q-sig overlap with the set of genes that are up-regulated in adult HSCs and change over the entire time course (see [Figure 1](#pbio-0020301-g001){ref-type="fig"}E). In other words, overlapping the pair-wise comparison with our expression-pattern-based groups, i.e., TOM groupings, identified essentially the same genes as did overlapping the time course with quiescent adult HSC and FL-HSC data, thus correlating, at the gene level, the TOM groupings to populations with known biological differences.
::: {#pbio-0020301-g002 .fig}
Figure 2
::: {.caption}
###### P-Sig and Q-Sig Show Patterns of Activation and Down-Regulation with Respect to Cell Cycle Status
\(A) Averaged pattern of P-sig gene expression over the 5FU time course plotted in solid lines, with the contributing TOM subgroups plotted in dashed lines.
\(B) Heat map of each gene in P-sig over the 5FU time course showing TOM subgroups in brackets.
\(C) Averaged pattern of Q-sig gene expression over the 5FU time course plotted in solid lines, with the contributing TOM subgroups plotted in dashed lines.
\(D) Heat map of each gene in Q-sig over the 5FU time course showing TOM subgroups in brackets.
For both heat maps, relative expression levels are displayed according to color intensity, blue (lowest) to yellow (highest).
This figure is interactive online, and provides contextual access to [Tables S12--S18](#st012){ref-type="supplementary-material"}. Use your mouse to highight animated areas of the graphic. Click on these areas to link to related files.
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We then plotted the average pattern for the P-sig and Q-sig and examined their component TOM groups (see [Figure 2](#pbio-0020301-g002){ref-type="fig"}). The patterns of genes in the TOM subgroups of the P-sig were very similar, with an overall off-on-off pattern that corresponded to the number of HSCs in cycle after 5FU treatment (see [Figures 1](#pbio-0020301-g001){ref-type="fig"}A, [2](#pbio-0020301-g002){ref-type="fig"}A, and [2](#pbio-0020301-g002){ref-type="fig"}B). Although mutually exclusive gene lists, TOM 0 and 30 were almost identical in pattern and were highly similar at the functional level (see below). Genes in TOM 1 and 10 shared the overall pattern of down-regulation with the Q-sig, but showed early and late peaks, respectively, the significance of which is discussed below. Overall we found the individual TOM groups to be highly coherent with a high degree of correlation between the individual genes and the mean profile of each group ([Table S47](#st047){ref-type="supplementary-material"}).
Q-sig and P-sig Overlap with Published Data to Give "Common" Signature {#s2c}
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Encouraged by these results, we performed a parallel analysis on a raw dataset from [@pbio-0020301-Akashi1], who compared the transcriptional profiles of adult long-term HSCs (LT-HSCs) and short-term HSCs (ST-HSCs). Although isolated by different methods, the Rho^low^ KTSL cells isolated by Akashi et al. and our quiescent adult HSCs are functionally equivalent ([@pbio-0020301-Wolf1]; [@pbio-0020301-Goodell1]). ST-HSCs have the ability, as do LT-HSCs, to contribute to all lineages of the hematopoietic system, but are not able to maintain long-term engraftment in irradiated hosts. They are also more in cycle than LT-HSCs and express low levels of Mac1 ([Table 1](#pbio-0020301-t001){ref-type="table"}) ([@pbio-0020301-Morrison1]; [@pbio-0020301-Cheshier1]). We therefore suspected that the genes 2-fold differentially expressed between LT-HSCs and ST-HSCs, approximately 300 and 600 genes, respectively, would be enriched for quiescence and proliferation genes, respectively. When we compared these lists with the list of genes changing after 5FU treatment, we observed that almost all the genes in common between LT-HSC and time course lists were in the quiescence group list. Similarly, most of the genes in common between the ST-HSC and the time course lists were in the proliferation group list. This confirmed that many of the gene expression changes that occur between LT-HSCs and ST-HSCs are the same changes that occur after activation of HSC with 5FU, and we designated these list intersections as the LT-HSC signature and ST-HSC signature, respectively.
A natural question was whether the Q-sig and P-sig described above would have any overlap with the LT-HSC signature and ST-HSC signature groups. Remarkably, 58% of the genes were in common between LT-HSC signature and the Q-sig, and 73% of the genes were in common between ST-HSC signature and the P-sig. We named these highly selected lists (53 and 118 genes, respectively) the "common quiescence signature" (cQ-sig) and "common proliferation signature" (cP-sig) ([Figure 1](#pbio-0020301-g001){ref-type="fig"}F and [1](#pbio-0020301-g001){ref-type="fig"}G). As we show below, these "common" signatures derived from the three-way intersection of 5FU-HSC data, adult-HSC-versus-FL-HSC data, and LT-HSC-versus-ST-HSC data were highly enriched for genes related to HSC proliferation.
Novel Uses of Gene Ontologies Allowed Functional Validation of Gene Groupings {#s2d}
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To investigate the biological significance of the groupings described above, we developed novel methods for utilizing the GO annotations ([@pbio-0020301-Ashburner1]) (<http://www.geneontology.org>) to analyze the content of gene lists. The GO is a controlled vocabulary that describes gene functions in their cellular context and is arranged in a quasi-hierarchical structure from more general to more specific. Since the vocabulary of annotations is fixed, it allows for functional comparisons of mutually exclusive gene lists, such at the TOM groups. We began by mapping each gene in the lists being analyzed to the GO tree structure. This allowed us to count the number of times each gene hit at or below any particular node in the GO structure. Once the lists were mapped, we were able (a) to calculate a measure of similarity (distance) between the lists using the distributions of each list across the various levels of the GO tree and (b) to calculate the enrichment of the various GO categories in each list ([Figure 3](#pbio-0020301-g003){ref-type="fig"}A--[3](#pbio-0020301-g003){ref-type="fig"}C).
::: {#pbio-0020301-g003 .fig}
Figure 3
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###### GO Analysis and Chromosomal Clustering
\(A) Dendrogram of gene lists clustered solely according to their similarity in GO content.
\(B) Bar graph showing enrichments of selected GO groups in the Q-sig and P-sig. Fold changes are relative to whole microarray (*p* \< 0.05). Asterisk marks groups in which no genes were found (complete depletion).
\(C) Percentage of genes within each list that are in the GO groups "cell cycle" or "cell--cell adhesion."
\(D) Distribution of hits within Q-sig and P-sig on each chromosome normalized for number of expected hits for whole microarray. Pound sign denotes significant differences between Q-sig and P-sig (*p* \< 0.05).
This figure is interactive online, and provides contextual access to [Tables S19--S45](#st019){ref-type="supplementary-material"}. Use your mouse to highight animated areas of the graphic. Click on these areas to link to related files.
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We clustered the gene lists based on this distance metric ([Figure 3](#pbio-0020301-g003){ref-type="fig"}A). As can be seen, GO-based clustering recapitulated the previous expression-pattern-based groupings: TOM days 0, 1, 10, and 30 clustered with the list of genes up-regulated in adult HSCs; and TOM days 3 and 6 clustered with those genes up-regulated in FL-HSCs. We calculated a probability of 0.003 that we could arrive at the grouping pattern shown by chance. Importantly, this indicated that the content of these clusters, as defined by their biological process using GO, was highly similar despite the nonoverlapping nature of the TOM groups. Although recapitulating the expression-pattern-based groupings, our GO-based clustering also revealed that TOM 1 has a unique signature amongst the quiescence cluster, suggesting a distinctive role for the genes in this group in governing HSC quiescence ([Figure 3](#pbio-0020301-g003){ref-type="fig"}A).
Our strategy for mapping gene lists to the GO structure also allowed us to calculate statistically significant enrichments of particular GO categories within our gene lists. We achieved this by mapping the whole microarray (approximately 12,000 genes) onto the GO structure and then calculating fold enrichments for each GO category in our lists relative to the microarray. We expected to find differences between the Q-sig and P-sig in the frequencies of antiproliferative and proproliferative genes, and verification of this served as proof-of-principle for our experimental design. Indeed, we found the GO category "regulation of cell cycle" (containing genes like the antiproliferative genes *p21 \[cyclin-dependent kinase inhibitor 1A\]* and *GADD45β \[Growth arrest and DNA-damage-inducible 45, beta\]*) to be 2.1-fold increased in the Q-sig over the total array ([Figure 3](#pbio-0020301-g003){ref-type="fig"}B). Moreover, the category "DNA replication" was about 5-fold greater in the P-sig, while this category was absent in Q-sig ([Figure 3](#pbio-0020301-g003){ref-type="fig"}B).
Intriguingly, the GO group "defense response," containing many of the H2 genes of the MHC class I family, was slightly enriched in the Q-sig, but was depleted by over 5-fold in the P-sig ([Figure 3](#pbio-0020301-g003){ref-type="fig"}B). Signal transduction molecules such as those in the GO groups "protein kinase cascade" were enriched 4.3-fold in the Q-sig ([Figure 3](#pbio-0020301-g003){ref-type="fig"}B). The GO group "ATP synthesis coupled electron transport" was enriched almost 21-fold in the P-sig, which correlates with the high energy requirements of cell division ([Figure 3](#pbio-0020301-g003){ref-type="fig"}B).
As discussed above, our results and the data from [@pbio-0020301-Akashi1] have remarkable overlap at the gene level. Using the common signature lists, we observed further refinements in key GO categories. For example, "cell cycle" genes were less than 4% of all genes on the chip, yet they represented 21% of the genes in the common P-sig ([Figure 3](#pbio-0020301-g003){ref-type="fig"}C). Progressive enrichment in "cell--cell adhesion" was also observed ([Figure 3](#pbio-0020301-g003){ref-type="fig"}C). Although almost 19% of the genes in our "common" signatures have no previously defined biological process, given the remarkable enrichment of proliferation-related genes in our common signatures, we can infer that they also may be involved in HSC proliferation.
TOM Analysis Uncovered Orderly Progression of HSC Activation {#s2e}
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We further utilized the GO-based analysis of the TOM groups within the Q-sig and P-sig to gain insight into the biological activities of HSCs at these time points. Because of the high similarity of TOM 0 and 30 in both expression pattern and GO categorization, we treated them as a single group. "Regulation of transcription" was enriched 1.5-fold in TOM 0 and 30 and comprised 16 genes, including several key transcriptional regulators of cell cycle such as the oncogenes *c-fos* and *c-maf,* as well as the global transcriptional repressor *histone deacetylase 5*.
The GO categories "regulation of cell cycle," "cell--cell adhesion," and "defense response" were specifically enriched in TOM 1 (approximately 4-fold each). Many genes in these groups are negative regulators of cell cycle, such as *p21, Tob 1/APRO6 (Transducer of ErbB2.1-1), Btg3/APRO4 (B-cell translocation gene 3), cyclin G1, GADD45β, and melanoma antigen, family D, 1*. Prior experiments have shown a decrease in the number of HSCs in cycle during the first day after 5FU treatment as compared to untreated HSCs (see [Figure 1](#pbio-0020301-g001){ref-type="fig"}A; [@pbio-0020301-Randall1]). We therefore concluded that many of the genes in TOM 1 are responsible for this momentary pause in cell cycle, and this explained why these genes were initially up-regulated and then sharply down-regulated as rapid HSC proliferation began (see [Figure 1](#pbio-0020301-g001){ref-type="fig"}A and [2](#pbio-0020301-g002){ref-type="fig"}C).
In the P-sig, TOM 3 and TOM 6 showed astonishingly different GO contents despite their similar expression patterns (see [Figure 2](#pbio-0020301-g002){ref-type="fig"}A). Genes in the GO category "cell cycle" identified in the P-sig are concentrated in TOM 3. Specifically, genes in both "DNA replication" and "M phase" were enriched about 18-fold and 10-fold, respectively, indicating a preparation for cell division. TOM 6 was enriched almost 3-fold in genes involved with biosynthesis of many essential cellular components, such as ATP (8.8-fold), nucleotides (5.6-fold), and proteins (2.4-fold). These data suggest early and late phases of proliferation, represented by the genes in TOM 3 and TOM 6, respectively.
As discussed above, by day 10 after 5FU treatment the number of HSCs in cycle is reduced to near pretreatment levels (see [Figure 1](#pbio-0020301-g001){ref-type="fig"}A). Although the signals responsible for restoring quiescence remain elusive, we believe that this process may be mediated by JAK/STAT and other signaling pathways. Overall, the GO category "signal transduction" showed approximately 2-fold enrichment in the TOM day 10 list. *SOCS3 (Suppressor of cytokine signaling 3),* whose product suppresses responses to growth factors in part by inhibiting JAK/STAT signaling, was most highly expressed at day 10, along with *STAT3* and *STAT6*. JAK/STAT signaling has been implicated in regulation of proliferation and differentiation of various hematopoietic cell types.
Chromosomes 2, 7, 12, and 17 Contain HSC Proliferation Control Regions {#s2f}
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Our expression data can be combined with data from the mouse genome projects to correlate gene expression changes observed after 5FU treatment with higher order genome-wide regulation. For example, we analyzed the contents of Q-sig and P-sig for clustering on particular chromosomes. Four chromosomes exhibited significant enrichment between the two signatures: Chromosomes 12 and 17 were enriched in the Q-sig, and Chromosomes 2 and 7 were enriched in the P-sig (see [Figure 3](#pbio-0020301-g003){ref-type="fig"}D). Earlier work identified quantitative trait loci (QTL) on Chromosomes 17 and 7 associated with the control of HSC frequency and proliferation of hematopoietic progenitors, respectively ([@pbio-0020301-Phillips1]; [@pbio-0020301-Geiger1]). *p21,* a prototypic member of the Q-sig, was specifically found within a QTL on Chromosome 17 associated with regulating HSC frequency. This region is syntenic with human Chromosome 6p21, a known hot spot for translocations linked to leukemias and lymphomas ([@pbio-0020301-Huret1]; [@pbio-0020301-Johansson1]).
Microarray Gene Expression Changes Reflect Changes in Protein Expression and HSC Behavior {#s2g}
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In order to determine whether some of the observed gene expression changes were accompanied by measurable differences in protein expression, we identified two genes whose expression changed over time and whose product could be tracked using flow cytometry. Gene expression of *Sca1,* a known marker of HSCs, showed significant increase after 5FU treatment despite having a high starting level ([Figure 4](#pbio-0020301-g004){ref-type="fig"}A). Flow cytometric analysis showed that Sca1 antigen expression was also distinctly higher after 5FU ([Figure 4](#pbio-0020301-g004){ref-type="fig"}B). *Sca1*-null mice have a defect in HSC self renewal that has been interpreted as a loss of proliferative capacity ([@pbio-0020301-Ito1]). Our data support this finding since maximal expression of Sca1 both at the gene expression and protein level was at day 6/7 post 5FU treatment. We also analyzed CD48, a cell adhesion molecule previously associated with T-cell activation and proliferation ([@pbio-0020301-Kato1]; [@pbio-0020301-Chavin1]; [@pbio-0020301-Gonzalez-Cabrero1]), which peaked in gene expression 6 d after 5FU treatment ([Figure 4](#pbio-0020301-g004){ref-type="fig"}A). By flow cytometry, CD48 antigen was detected on quiescent HSCs, but exhibited a substantially higher level of expression at the height of HSC proliferation ([Figure 4](#pbio-0020301-g004){ref-type="fig"}B). To determine whether high levels of CD48 antigen on HSCs coordinated with proliferation in a similar fashion as on T-cells, we performed cell cycle analysis of CD48^+^ and CD48^−^ HSCs. Further characterization of CD48^+^ HSCs 6 d post 5FU revealed a greater than 3-fold enrichment in the number of cells in cycle over CD48^−^ HSCs ([Figure 4](#pbio-0020301-g004){ref-type="fig"}C). This finding is the first report of a marker that enriches for cycling HSCs.
::: {#pbio-0020301-g004 .fig}
Figure 4
::: {.caption}
###### Gene Expression Profiles Correlate with Protein Expression on HSCs
\(A) Gene expression over time. The actual observed values of each replicate at each time point are shown in red, and the line connects the predicted expression value at each time point based on our regression analysis.
\(B) Antigen expression on HSCs measured by flow cytometry. Gray lines represent negative control, red lines represent protein expression at day 0, and blue lines represent protein expression at day 7.
\(C) Cell cycle analysis of CD48^−^ and CD48^+^ HSCs isolated 6 d post 5FU treatment.
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Discussion {#s3}
==========
Here we have identified proliferation and quiescence signatures of HSCs. Our experimental design utilized a combination of pair-wise comparisons and time course microarray experiments. The pair-wise analysis allowed us to find the genes different between quiescent and cycling HSCs, while the time course data allowed us to order these genes in a time-dependent manner. The power of our overall methodology is reflected in the remarkable overlaps between the gene lists presented and those extracted from published data ([@pbio-0020301-Akashi1]), in particular the common P-sig and common Q-sig.
Applying a novel approach to utilizing the GO annotations, we calculated the statistical significance of the enrichment of particular GO categories in our lists. We also devised a new method for calculating the distance between gene lists based on the GO structure. This allows one to assess the functional similarity, in "GO space," of gene lists that may not have any actual genes in common (such as our TOM groups). Furthermore, since the GO vocabulary is not specific to any species, this method allows for cross-species and cross-platform comparisons of gene lists. Re-analysis of data from previous studies may reveal a functional stem cell signature in GO space that was not evident at the gene level ([@pbio-0020301-Ivanova1]; [@pbio-0020301-Ramalho-Santos1]; [@pbio-0020301-Fortunel1]).
Applying GO analysis to the TOM groupings revealed elemental subgroups within the signature lists that allowed us to construct a molecular model of the HSC activation cycle. The majority of unperturbed HSCs reside in a quiescence niche and express receptors, for example the metabolism- and ageing-associated receptor IGF1R and the receptor tyrosine kinase Tie1, that allow them to respond to multiple mitogenic signals ([Figure 5](#pbio-0020301-g005){ref-type="fig"}A). They also express high levels of transcription factors, such as c-fos and GATA-2, that enable swift activation of HSCs. This expression profile, found in the TOM 0 and 30 groups, suggests that although adult HSCs are quiescent, they are in a "state of readiness" to react to changes in their environment.
::: {#pbio-0020301-g005 .fig}
Figure 5
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###### Model of HSC Activation Cycle
\(A) Normal HSCs reside in a quiescent niche in a "state of readiness" exemplified by the indicated genes.
\(B) Upon stress (5FU treatment), HSCs "pause" by remaining quiescent and in their niche while they "prepare" to proliferate. HSCs receive signals from proinflammatory cytokines at this point. The signals induce a proliferative state that is divisible into early (C) and late (D) phases.
\(C) "Early proliferation" is marked by an increase in expression of genes involved in DNA replication, repair, and cell migration molecules that allow movement of HSCs from the quiescence niche to the proliferative zone.
\(D) "Late proliferation" is marked by expression of many cell cycle genes as well as many energy pathway molecules.
\(E) Re-induction of quiescence involves changes in migratory molecule expression, which leads to return of cells to their quiescence niche, as well the expression of antiproliferative genes.
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Immediately after activation is triggered (here by 5FU), HSCs enter a superquiescent "pause." This state, found at TOM 1 and also observed by cell cycle analysis ([@pbio-0020301-Randall1]), is mediated by antiproliferative genes such as *Tob1, p21,* and *Btg3* ([Figure 5](#pbio-0020301-g005){ref-type="fig"}B). Interestingly, *p21*-null mice have defects in HSC self renewal ([@pbio-0020301-Cheng1]). We observed up-regulation of TIMP3 and the serine proteinase inhibitor A-3 g, which inhibit cell migration ([@pbio-0020301-Qi1]). At least six interferon-γ-induced genes were also up-regulated at this point, suggesting that HSCs are responding to proinflammatory signals. We speculate that the pause in HSC proliferation and migration allows HSCs to survive 5FU cytotoxicity while the cells simultaneously "prepare" to proliferate and repopulate the bone marrow to ensure survival of the animal.
In the early phase of proliferation starting at day 3, when increased numbers of HSCs in cell cycle are first detected ([@pbio-0020301-Randall1]), HSCs have committed to cell division, as can be seen by the maximal expression of genes involved in DNA replication and repair ([Figure 5](#pbio-0020301-g005){ref-type="fig"}C). At day 6, the late phase of proliferation, when the greatest number of HSCs are in cycle, we see expression of genes involved with energy production, indicating an overall increase in metabolic activity in the HSCs ([Figure 5](#pbio-0020301-g005){ref-type="fig"}D). Prior work has linked HSC mobilization with proliferation ([@pbio-0020301-Wright1]; [@pbio-0020301-Heissig1]), and our data indicate that the opposite is also true: to proliferate, HSCs need to move out of their quiescence niche and into a proliferative zone ([Figure 5](#pbio-0020301-g005){ref-type="fig"}C and [5](#pbio-0020301-g005){ref-type="fig"}D). We see the up-regulation of *α4-integrin* at day 3 followed by a dramatic decrease at day 6 post 5FU treatment. Experiments that block α4-integrin function by blocking antibodies or via knockout technology have previously shown that down-regulation induces increased mobilization and delays recovery after 5FU treatment ([@pbio-0020301-Craddock1]; [@pbio-0020301-Scott1]). The gene expression pattern displayed by α4-integrin predicts that down-regulation of α4-integrin is necessary for 5FU-induced proliferation. As stated above, down-regulation of α4-integrin is sufficient to alter recovery of bone marrow progenitors after 5FU treatment, supporting the link between HSC proliferation and migration in our model. Down-regulation of c-Kit has also been linked to mobilization of HSCs ([@pbio-0020301-Heissig1]), and its expression is lowest at day 6 post treatment.
In order to "reset quiescence," HSCs need to return to their niche ([Figure 5](#pbio-0020301-g005){ref-type="fig"}E). This process begins at day 10, when the number of cycling HSCs falls and HSCs express the high levels of specific antiproliferative genes such as *Btg1* and several components of the JAK/STAT signal transduction pathway. Both SOCS3 ([@pbio-0020301-Soriano1]) and STAT3 ([@pbio-0020301-Levy1]) have been associated with both positive and negative regulation of proliferation and differentiation of various hematopoietic cell types. Simultaneous expression of *SOCS3, STAT3,* and *STAT6* suggests a complex regulation of HSC quiescence, but earlier work examining STAT signaling in other stem cell populations gave us insight into the role of JAK/STAT signaling in HSCs. Expression of STATs has been shown to establish and maintain stem cell pluripotency in embryonic stem cells ([@pbio-0020301-Raz1]). However in *Drosophila* testes, JAK/STAT activation is crucial for stem cell self renewal; perturbations by both loss and increase in expression lead to dramatic changes in the stem cell compartment ([@pbio-0020301-Kiger1]). Notably, activation of the JAK/STAT pathway by PKD1 induces cell cycle arrest through p21-dependent mechanisms ([@pbio-0020301-Bhunia1]). This supports our hypothesis that JAK/STAT signaling is important for inducing quiescence at day 10, since we have shown that p21 is likely involved in HSC cell cycle arrest. The involvement of JAK/STAT signaling in both stem cell pluripotency and HSC quiescence suggests that these processes may be linked in HSCs.
Endoglin, also found in the TOM 10 group, is known to be expressed on both murine ([@pbio-0020301-Chen1]) and human ([@pbio-0020301-Pierelli1]) HSCs, and has been shown to decrease cell migration by increasing cell--cell adhesion ([@pbio-0020301-Liu1]). Its expression pattern was negatively correlated with 5FU-HSC proliferation: it was lowest at day 6 after 5FU treatment, and highest at day 10. Our data suggest that HSC proliferation requires mobilization from the niche, and that restoration of quiescence is accompanied by a return to the niche. Endoglin\'s expression pattern makes it an ideal candidate for mediating HSC-to-niche homing and long-term association.
Our model derived from gene expression profiles correlates well with the literature on HSC cell cycle and mobilization. Although other models of HSC mobilization and 5FU treatment have previously been proposed ([@pbio-0020301-Heissig1]), our data allow association of specific genes with particular stages of HSC activation and recovery. Our model predicted that CD48 might preferentially mark cycling HSCs, and our cell cycle analysis of CD48^+^ and CD48^−^ HSCs confirmed this prediction. Our model also postulates the presence of "quiescence" and "proliferative" zones in the bone marrow; osteoblasts may be a component of this quiescence niche ([@pbio-0020301-Calvi1]; [@pbio-0020301-Zhang1]).
In summary, we present proliferation and quiescence signatures for HSCs that show remarkable overlap with published literature. In addition, this study revealed new, uncharacterized genes whose role in HSC self renewal needs to be explored: some of these genes may play as yet undiscovered roles in the development of cancer or may aid in the manipulation of stem cells for therapeutic uses. Finally, harnessing the GO using novel bioinformatics approaches to analyze our data at a global level allowed us to propose a model of the HSC activation cycle.
Materials and Methods {#s4}
=====================
{#s4a}
### Flow cytometry {#s4a1}
For quiescent adult HSCs and 5FU-HSCs, whole bone marrow (WBM) was collected from the femurs and tibias of ten to fifteen 8- to12-wk-old normal or 5FU-treated C57Bl/6 mice. For 5FU treatment, mice were injected intravenously with a single dose of 5FU (150 mg/kg body weight; Sigma, St. Louis, Missouri, United States) and killed at day 0, 1, 2, 3, 6, 10, or 30 after injection. Day 0 mice were untreated, and day 1 WBM was isolated 17--19 h after injection; all subsequent days were in 24-h increments. WBM was stained with Hoechst 33342 to identify the SP cells ([@pbio-0020301-Goodell1]) and then magnetically enriched for Sca1^+^ cells (autoMACS; Miltenyi Biotec, Sunnyvale, California, United States). Cells were stained with a biotinylated Sca1 antibody (clone E13--161.7; BD Pharmingen, San Diego, California, United States) and visualized with strepavidin-PE (Molecular Probes, Eugene, Oregon, United States). Sca1-enriched WBM was sorted for the SP profile and Sca1 positivity on a MoFlo (Cytomation, Fort Collins, Colorado, United States). Representative flow diagrams of cell sorting can be found in [Figure S2](#sg002){ref-type="supplementary-material"}A. Phenotypic purity was typically 95% or greater. Regarding functional purity of the sorted populations, evidence from multiple sources in our lab and others suggests that both normal bone marrow and 5FU-treated SP cells are very highly enriched for HSCs. The whole SP contains both LT-HSCs and ST-HSCs, but has very limited contamination from committed progenitors or differentiated hematopoietic cells.
For FL-HSCs, fetal livers were removed from embryos 13.5--14.5 d postcoitus and dissociated ([@pbio-0020301-Jordan1]). Fetal liver cells were magnetically enriched for c-Kit^+^ cells using c-Kit-biotin (clone 2B8, BD Pharmingen) and visualized with strepavidin-APC (Molecular Probes). The c-Kit-enriched cells were stained with a lineage cocktail consisting of cychrome-conjugated CD4 (L3T4), CD8 (53--6.7), B220 (RA3--6B2), GR1 (RB6--8C5), and Ter119 (Ter119) as well as Sca1-PE, and AA4.1-FITC (all antibodies from BD Pharmingen). FL-HSCs were identified as negative for the lineage markers and positive for Sca1, c-Kit, and AA4.1 (see [Figure S2](#sg002){ref-type="supplementary-material"}B). Percentage of enriched cells was between 0.02% and 0.04% of total cells, with a purity of approximately 90%.
For protein expression validation, SP cells from days 0 and 7 post 5FU treatment were analyzed for expression of Sca1-FITC, c-Kit-APC, and CD48-PE (HM48--1, BD Pharmingen) by flow cytometry.
### RNA isolation and amplification {#s4a2}
Total RNA was isolated from approximately 35,000--70,000 sorted HSCs using the RNaqeuous kit (Ambion, Austin, Texas, United States). All samples were then digested with DNaseI to eliminate residual genomic DNA, and extracted with phenol:chloroform. Total RNA was then subjected to two rounds of linear amplification using T7-based in vitro transcription (IVT) (MessageAmp, Ambion). Briefly, total RNA was reverse transcribed with an oligo-dT primer containing a T7 promoter sequence at the 5′ end (oligo-dT-T7 primer). To prime second-strand synthesis, RNA--cDNA hybrids were digested with RNaseH, producing patches of single-stranded cDNA. The second strand was filled in by DNA polymerase. The double-stranded cDNA served as a template for T7 RNA polymerase-driven IVT, which yielded up to 100× the starting mRNA pool. RNA probes were labeled in the second round of IVT with biotinylated nucleotides (Enzo Biotech, Farmington, Connecticut, United States). The second round of amplification was performed using random primers for first-strand synthesis and the oligo-dT-T7 primer to prime second-strand synthesis. Overall amplification was estimated to be 10,000-fold or greater ([@pbio-0020301-Gallardo1]).
### Microarray hybridization {#s4a3}
Affymetrix (Santa Clara, California, United States) MG-U74Av2 chips were hybridized with fragmented, biotinylated aRNA according to standard protocols. Chips were then washed and counterstained using PE-conjugated strepavidin. Signal was amplified using the Affymetrix protocol for antibody amplification. The raw image (.DAT) and intensity (.CEL) files were generated using MAS 5.0 software (<http://www.affymetrix.com>).
### Microarray analysis {#s4a4}
Chip quality was assessed using various parameters outputted by a combination of the following software packages: MAS 5.0 (<http://www.affymetrix.com>, BRB Array tools (<http://linus.nci.nih.gov/BRB-ArrayTools.html>, and Bioconductor version 1.2 (<http://www.bioconductor.org>). Twenty-one chips were hybridized and analyzed, but only 16 (approximately 75%) passed our quality control standards (scale factor ≤ 10, 3′-to-5′ ratio ≤ 25, R^2^ ≥ 0.97). Normalization and model-based expression values were calculated using the GeneChip Robust Multichip Analysis method ([@pbio-0020301-Wu1]), available as part of the Bioconductor package.
### Statistical analysis {#s4a5}
Time-dependent expression profiles for each gene were analyzed by regressing the normalized expression values using polynomial least squares regression. ANOVA was performed on the coefficients of regression to identify genes with significant time patterns (*p* \< 0.05). The smooth curve fitting assumed that the expression trajectory for each gene followed a continuous time pattern. The class of fifth-degree polynomials was chosen for the fits, because it was the highest degree polynomial that did not interpolate the time point means. Analysis was performed in R 1.7.1 (<http://www.r-project.org>) using the Bioconductor suite of R packages. Source code for the analysis, including the curve fitting procedure, is available in [Protocol S1](#sd001){ref-type="supplementary-material"}.
### GO analysis {#s4a6}
GO analysis was performed using the 1 October 2003 build of the gene ontologies (<http://www.geneontology.org>) and the GO annotations for each probe set on the MGU74Av2 chip, provided by Affymetrix (<http://www.affymetrix.com>, downloaded 8 October 2003). The GO vocabulary structure was then instantiated as a directed acyclic graph and traversed to obtain hit counts for the genes in our lists that mapped at or below each node in the GO structure. To assess the significance of gene counts at each term, the annotations for the entire array were mapped to the GO structure, and counts for the whole array were obtained at each GO term. The significance of counts in particular categories was obtained via a sampling-without-replacement statistical model for the gene counts in each GO category.
The probability of a count of *k* genes to a GO node at some level of the GO hierarchy was modeled according to the hypergeometric probability law:
In the formula, *B(x,y)* is the binomial coefficient for *x* choose *y*. The value *C* is the total number of genes annotated to the GO node under consideration for the entire gene set. The value of *L* is the number of genes annotated to all nodes at the same level of the GO hierarchy, again considering the entire arrayed gene set. The value *n* is the number of genes annotated to terms at the same GO level for the gene list under consideration. The *p* value (one sided) for the node under consideration is obtained by summing probabilities as determined by the formula for all values of *X* from *k* to *n*. A web-based tool to perform this analysis on any gene list is available at <http://franklin.imgen.bcm.tmc.edu/OntologyTraverser>.
The list distance metric was determined from the estimated joint distribution of probe counts across the GO structure for each gene list. This joint distribution was estimated by obtaining the counts at each GO node at each level. Only those nodes with non-zero counts in at least one list were included in the calculations. Relative frequencies at each GO node at each GO level were obtained by normalizing to the total counts at each level for each list. Once the frequency distribution at each level was determined, a Kullback--Leibler-like distance metric was constructed. Briefly, the distance metric is a weighted average of Kullback--Leibler distances at each level of the GO. The formula for computing distance between a pair of lists is
The weights α*~k~* were normalized to sum to one and were drawn from the Poisson mass function with a mean of four. Since the GO levels are ordered in terms of increasing specificity, the contribution of each level was weighted differently: positive weight was applied to the middle of the GO hierarchy (levels 3--8), and weights for levels lower than 3 and higher than 8 were set to 0. The indices *i* and *j* in the formula indicate the lists being compared. The index *k* indicates the level of the GO under consideration, and the index *γ* considers each GO node at the level *k.*
To compute the significance of our list dendrogram we determined the probability that we could arrive at the grouping pattern by chance. We determined the number of dendrograms with the "two group" pattern divided by the total number of labeled dendrograms. For our case, our "two group" dendrogram consisted of two subtrees with three and five arms, respectively. The total number of labeled dendrograms was the product of the number of labeled three-leaf dendrograms (three) and the number of labeled five-leaf dendrograms (105), which is 415. We divided this number by the total number of eight-leaf dendrograms (135,135) to attain the 0.003 probability. An R function for making this calculation is contained in the R script provided in [Protocol S1](#sd001){ref-type="supplementary-material"}.
### Chromosome analysis {#s4a7}
Gene hits per chromosome were counted for Q-sig and P-sig as well as the total MGU74Av2 chip. Number of hits in our signatures was centered to the expected frequency of the number of hits on the total chip using the following equation. The number of hits above/below expected equals *X* − *nP~i~,* where *X* equals the number of genes in list on chromosome *i, n* equals the total number of genes in list, and *P~i~* equals the frequency of chromosome *i* hits on total chip (which equals the number of genes on total chip on chromosome *i* divided by the number of genes on total chip with known chromosome position).
To determine the significance of enrichments and depletions of gene hits on each chromosome, we calculated a *Z*-score with the following equation.
Chromosome enrichment or depletion between signatures was considered significant if the additive *Z*-score of Q-sig and P-sig was significant to 0.02 \< α \< 0.05.
Supporting Information {#s5}
======================
Figure S1
::: {.caption}
###### Cell Cycle Analysis of HSCs
Cell cycle analysis of bone marrow SP cells before (left) and 6 d post (right) 5FU treatment. Before treatment, approximately 2% of adult quiescent HSCs are in cycle; 6 d after 5FU treatment, approximately 22% of HSCs are in cycle.
(2.0 MB EPS).
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######
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Figure S2
::: {.caption}
###### FACS Isolation of HSCs
\(A) Representative flow cytometry plots of bone marrow enriched for Sca1^+^ cells at each time point. The indicated regions contain the SP cells. The table shows prevalence and purity from several isolations.
\(B) Representative flow cytometry analysis of fetal liver enriched for c-Kit^+^ cells.
(2.9 MB EPS).
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######
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Figure S3
::: {.caption}
###### Homogeneity of SP Cells
SP profile of adult HSCs and 5FU-HSCs 6 d post 5FU treatment. Arrows point to analysis in SP cells of Sca1 and lineage marker expression showing greater than 97% homogeneity for Sca1^+^ and Lineage^−^ expression.
For analysis of adult HSCs on day 0, the lineage markers used were Mac1, CD4, CD8, B220, GR1, and Ter119. For analysis of 5FU-HSCs on day 6, all of the above markers were used except for Mac1, because of its low level expression on HSCs after 5FU treatment.
(2.2 MB EPS).
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######
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Protocol S1
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###### R Script for Constructing Gene Lists
(8 KB TXT).
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######
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Table S1
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###### Genes Up-Regulated in FL-HSCs
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######
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Table S2
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###### Genes in Proliferation Group
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######
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Table S3
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###### Genes That Change over 5FU Treatment Time Course
(1.4 MB HTML).
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Table S4
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###### Genes in Quiescence Group
(790 KB HTML).
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Table S5
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###### Genes Up-Regulated in Adult HSCs
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Table S6
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###### Genes in P-Sig
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Table S7
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###### Genes in Q-Sig
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######
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Table S8
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###### Genes in ST-HSC Signature
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Table S9
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###### Genes in LT-HSC Signature
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Table S10
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###### Genes in Common P-Sig
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Table S11
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###### Genes in Common Q-Sig
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######
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Table S12
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###### Genes in TOM0 Group of Q-Sig
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Table S13
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###### Genes in TOM1 Group of Q-Sig
(70 KB HTML).
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Table S14
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###### Genes in TOM10 Group of Q-Sig
(169 KB HTML).
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Table S15
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###### Genes in TOM30 Group of Q-Sig
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Table S16
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###### Genes in TOM3 Group of P-Sig
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Table S17
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###### Genes in TOM2 Group of P-Sig
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Table S18
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###### Genes in TOM6 Group of P-Sig
(280 KB HTML).
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Table S19
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###### Lists of GO Groups Enriched in Adult HSCs, FL-HSCs, and TOM Groups
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Table S20
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###### Genes in Q-Sig, P-Sig, Common Q-Sig, and Common P-Sig in the GO Category "Cell Cycle"
(7 KB HTML).
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Table S21
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###### Genes in Q-Sig, P-Sig, Common Q-Sig, and Common P-Sig in the GO Category "Cell--Cell Adhesion"
(3 KB HTML).
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Table S22
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###### Genes in P-Sig in the GO Category "ATP-Synthesis-Coupled Electron Transport"
(6 KB HTML).
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Table S23
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###### Genes in P-Sig in the GO Category "DNA Replication"
(8 KB HTML).
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Table S24
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###### Genes in P-Sig in the GO Category "Cell Cycle Checkpoint"
(6 KB HTML).
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Table S25
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###### Genes in P-Sig in the GO Category "Hydrogen Transport"
(7 KB HTML).
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Table S26
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###### Genes in Q-Sig in the GO Category "Regulation of Cell Cycle"
(7 KB HTML).
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Table S27
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###### Genes in Q-Sig in the GO Category "Defense Response"
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Table S28
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###### Genes in Q-Sig in the GO Category "Protein Kinase Cascade"
(7 KB HTML).
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Table S29
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###### Genes in Q-Sig in the GO Category "Cell--Cell Adhesion"
(6 KB HTML).
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Table S30
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###### TOM1 Genes within GO Categories and the Fold Enrichment of Each Category
(92 KB HTML).
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Table S31
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###### TOM1 Genes within GO Categories That Were Significantly Enriched
(31 KB HTML).
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Table S32
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###### TOM10 Genes within GO Categories and the Fold Enrichment of Each Category
(136 KB HTML).
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Table S33
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###### TOM10 Genes within GO Categories That Were Significantly Enriched
(45 KB HTML).
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Table S34
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###### Genes Up-Regulated in Adult HSCs within GO Categories and the Fold Enrichment of Each Category
(244 KB HTML).
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Table S35
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###### Genes Up-Regulated in Adult HSCs within GO Categories That Were Significantly Enriched
(14 KB HTML).
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Table S36
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###### TOM0 Genes within GO Categories and the Fold Enrichment of Each Category
(52 KB HTML).
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Table S37
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###### TOM0 Genes within GO Categories That Were Significantly Enriched
(8 KB HTML).
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Table S38
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###### TOM30 Genes within GO Categories and the Fold Enrichment of Each Category
(61 KB HTML).
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Table S39
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###### TOM30 Genes within GO Categories That Were Significantly Enriched
(14 KB HTML).
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Table S40
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###### TOM3 Genes within GO Categories and the Fold Enrichment of Each Category
(65 KB HTML).
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Table S41
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###### TOM3 Genes within GO Categories That Were Significantly Enriched
(32 KB HTML).
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Table S42
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###### TOM6 Genes within GO Categories and the Fold Enrichment of Each Category
(215 KB HTML).
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Table S43
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###### Lists of TOM6 Genes within GO Categories That Were Significantly Enriched
(199 KB HTML).
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Table S44
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###### Lists of Genes Up-Regulated in FL-HSCs within GO Categories and the Fold Enrichment of Each Category
(244 KB HTML).
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Table S45
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###### Genes Up-Regulated in FL-HSCs within GO Categories That Were Significantly Enriched
(14 KB HTML).
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Table S46
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###### GeneChip Robust Multichip Analysis Normalized Data and Filtering Information
(9.7 MB XLS).
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######
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:::
Table S47
::: {.caption}
###### Goodness of Fit within Each TOM Group
This table gives the 0.25, 0.5, and 0.75 quartile of the gene correlations (Pearson\'s) to their TOM group mean shown in [Figure 2](#pbio-0020301-g002){ref-type="fig"}A and [2](#pbio-0020301-g002){ref-type="fig"}C.
(27 KB DOC).
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######
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:::
Accession Numbers {#s5a1z}
-----------------
The LocusLink (<http://www.ncbi.nlm.nih.gov/LocusLink/>) accession numbers for the genes and gene products discussed in this paper are BTG1 (Locuslink 12226), Btg3/APRO4 (Locuslink 12228), CD48 (Locuslink 12506), c-fos (Locuslink 14281), c-maf (Locuslink 17134), cyclin G1 (Locuslink 12450), Endoglin (Locuslink 13805), GADD45β (Locuslink 17873), GATA-2 (Locuslink 14461), histone deacetylase 5 (Locuslink 15184), IGF1R (Locuslink 16001), melanoma antigen, family D, 1 (Locuslink 94275), p21 (Locuslink12575), receptor tyrosine kinase Tie1 (Locuslink 21846), serine proteinase inhibitor A-3 g (Locuslink 20715), SOCS3 (Locuslink 12702), STAT3 (Locuslink 20848), STAT6 (Locuslink 20852), Suppressor of cytokine signaling 3 (Locuslink 12702), TIMP3 (Locuslink 21859), Tob 1/APRO6 (Locuslink 22057), and α4-integrin (Locuslink 16401). The GEO ([www.ncbi.nlm.nih.gov/geo](www.ncbi.nlm.nih.gov/geo)) accession numbers for microarrays discussed in this paper are GSM26734-GSM26749.
This work was funded by grants from the National Institutes of Health (CA81179 and DK63588). MAG is a scholar of the Leukemia and Lymphoma Society. AAM is a Molecular Medicine Scholar. We thank Mike Cubbage and Chris Threeton for excellent flow cytometry assistance, Lisa White at the Baylor Core Microarray Facility, and S. Bradufute for critical reading of the manuscript. We also thank Linheng Li (Stowers Institute) for providing microarray data files from [@pbio-0020301-Akashi1].
**Conflicts of interest.** The authors have declared that no conflicts of interest exist.
**Author contributions.** TAV, AAM, CAR, and MAG conceived and designed the experiments. TAV and AAM performed the experiments. TAV, AAM, CAS, and MAG analyzed the data. NLW, ASY, and CAS contributed reagents/materials/analysis tools. TAV, AAM, CAS, and MAG wrote the paper.
Academic Editor: Bing Lim, Genome Institute of Singapore
Citation: Venezia TA, Merchant AA, Ramos CA, Whitehouse NL, Young AS, et al. (2004) Molecular signatures of proliferation and quiescence in hematopoietic stem cells. PLoS Biol 2(10): e301.
5FU
: 5-fluorouracil
5FU-HSC
: 5-fluorouracil-activated hematopoietic stem cell
FL-HSC
: fetal liver hematopoietic stem cell
GO
: Gene Ontology
HSC
: hematopoietic stem cell
IVT
: in vitro transcription
LT-HSC
: long-term hematopoietic stem cell
P-sig
: Proliferation Signature
Q-sig
: Quiescence Signature
QTL
: quantitative trait loci
SP
: side population
ST-HSC
: short-term hematopoietic stem cell
TOM
: time of maximum expression
WBM
: whole bone marrow
|
PubMed Central
|
2024-06-05T03:55:48.021922
|
2004-9-28
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC520599/",
"journal": "PLoS Biol. 2004 Oct 28; 2(10):e301",
"authors": [
{
"first": "Teresa A",
"last": "Venezia"
},
{
"first": "Akil A",
"last": "Merchant"
},
{
"first": "Carlos A",
"last": "Ramos"
},
{
"first": "Nathan L",
"last": "Whitehouse"
},
{
"first": "Andrew S",
"last": "Young"
},
{
"first": "Chad A",
"last": "Shaw"
},
{
"first": "Margaret A",
"last": "Goodell"
}
]
}
|
PMC520742
|
Background
==========
Topographic ordering is an important feature of the visual system, which is conserved among many visual areas \[[@B1]\]. Thus, the projection from retina to superior colliculus (SC) is established in a way, which retains neighbourhood relationships between neurons \[[@B2]-[@B4]\]. This implies that two axons of retinal ganglion cells (RGCs), which originate from neighbouring points in retina, terminate proximally in SC. It is assumed that this facilitates visual processing, which involves wiring local to the termination zone \[[@B5]\].
The mechanisms responsible for topographic ordering have been lately under thorough examination. Following the original suggestion by Sperry \[[@B6]\], it was shown that chemical labels play an essential role in formation of the map (reviewed in \[[@B3],[@B7]\]). For the projection from retina to SC the Eph family of receptor tyrosine kinases and their ligands ephrins were shown to be necessary for establishing correct topographic maps \[[@B7]-[@B10]\]. The coordinate system is encoded chemically in retina through graded expression of the Eph receptors by the RGCs. Thus, in mouse retina, two receptors of the family, EphA5 and A6, are expressed in the low nasal -- high temporal gradient \[[@B11]-[@B14]\]. The recipient coordinate system in the SC is established through high caudal -- low rostral gradient of ephrin-A2 and A5 ligands \[[@B15]\]. Since RGC axons expressing EphA receptors are repelled by high levels of ephrin-A ligands this system of reciprocal gradients allows sorting of the projecting axons in the order of increasing density of receptors, whereby contributing to the formation of topographic map \[[@B10],[@B15],[@B16]\] (Figure [1A](#F1){ref-type="fig"}). Thus, the system of reciprocal gradients is involved in formation of topographic representation along the nasal-temporal axis, albeit some additional fine-tuning is provided by activity-dependent mechanisms \[[@B17]-[@B19]\].
In this study we address the results of gain-of-function experiments, in which the retinocollicular maps were modified by genetic manipulations \[[@B20]\]. RGCs of the wild-type mouse express the LIM homeobox gene Islet2 (Isl2) \[[@B21]\]. Retina of a single animal is composed of two types of cells with regard to their expression of Isl2 gene, Isl2+ and Isl2-, which are intermixed in roughly equal proportion throughout the RGC layer (Figure [1B](#F1){ref-type="fig"}). To test the mechanisms of the retinocollicular map formation Brown et al. \[[@B20]\] generated \"knock-in\" mice, in which the Isl2 and EphA3 genes are coexpressed. This implies that each Isl2+ RGC and its axons, in addition to EphA5 and A6, also expresses EphA3, not found in the wild-type RGCs. The Isl2- cells remain EphA3-, as the wild-type cells. By doing so Brown et al. \[[@B20]\] increased the total level of EphA receptors in a given fraction of retinal cells. Since the overall level of EphAs is increased in Isl2+/EphA3+ cells, axons of two neighboring cells, knock-in and wild-type, should terminate in quite different places in SC (Figure [1B](#F1){ref-type="fig"}). The knock-in cells, interacting more strongly with the repellent should terminate at the position of decreased density of ephrins, i.e. more rostrally with respect to the wild-type cells. The neighborhood relationships between axons should be lost, the new map should lose its continuous nature, and it should split into two maps: one for wild-type RGCs, one for knock-in cells. This prediction was confirmed by experiments of Brown et al. \[[@B20]\] (Figure [2](#F2){ref-type="fig"}).
In addition to the observation of the overall map doubling in homozygous knock-ins (Figure [2C](#F2){ref-type="fig"}), Brown et al. discovered a curious behavior of the map in heterozygous animals. In these animals the exogenous levels of EphA3 were reduced roughly by a factor of two with respect to the homozygous knock-ins (Figure [2B](#F2){ref-type="fig"}). In terms of the expression density of EphA3 these animals stand between the wild-type and knock-in animals. Accordingly, the structure of the map resembles a hybrid of the wild-type and homozygous maps. The more rostral part of the map is single-valued, similarly to the wild-type, whereas about 60% of the caudal-most part is double-valued, like in the homozygous animals. This observation suggests that the map bifurcates somewhere between double-and single-valued regions. Although overall doubling of the map in homozygotes is easy to understand, any true model for the retinocollicular map formation should be able to account for the bifurcating behavior of map in heterozygotes. Therefore, experiments in heterozygotes represent a powerful tool to falsify various theoretical models.
Brown et al. \[[@B20]\] suggest that the bifurcating behavior of the map is consistent with the importance of relative rather than absolute values of the expression levels. Indeed, the relative difference of exogenous EphA3 to endogenous EphA5/6 is maximal in nasal retina (caudal SC), where the doubled map is observed (Figure [2B](#F2){ref-type="fig"}). In the temporal retina (rostral SC) the EphA3 to EphA5/6 ratio is not so large, which may account for the fact that the map is single-valued there. Thus a model for the topographic map from retina to SC should rely on the relative but not absolute levels of EphA signaling.
The point, which we make in this study, is that more experimental tests are needed to justify the suggestion about relative expression levels. To make our point clear we present a model for the retinocollicular map formation, which is based upon differences in the [absolute]{.underline} values of Eph/ephrin expression levels, rather than relative differences. Our model manages to reproduce all the essential features of experiments described in Brown et al. \[[@B20]\], including bifurcation of the map in heterozygotes. In the model presented here the map is single-valued in rostral part of heterozygous SC due to inhomogeneous gradients of ligand and receptor, rather than reduced relative difference of EphA receptors. Below we suggest experimental tests, which may distinguish these two classes of models. This model was presented previously at Society for neuroscience meeting 2001 and on the arXiv preprint server \[[@B22],[@B23]\].
To test various hypotheses we use a model for retinocollicular map formation employing stochastic Markov chain process. Our model is based upon three principles: chemoaffinity, axonal competition, and stochasticity. Some features of our model are similar to arrow model of Hope, Hammond, and Gaze \[[@B24]\]. The implementation of the model used here is available in \[[@B25]\].
Results
=======
Markov chain model
------------------
Let us first describe the 1D version of the model. We consider a linear chain of 100 RGC, each expressing individual level of EphA receptors given by *RA*(*i*), where *i*= 1\...100 is the RGC index, which also determines a discrete position of the cell in the retina. We have verified that results presented below do not depend on the number of cells, as long as this number is large enough. Each RGC is attached by an axon to one and only terminal cell in SC, which has an expression level of ligand given by *LA*(*k*), where *k*= 1\...100 is the index in SC, also describing the terminal\'s topographic position. The receptor density *RA*is an overall increasing function of its index *i*, while the ligand density *LA*is decreasing, when going from *k*= 1 (caudal) to *k*= 100 (rostral) positions (Figure [3](#F3){ref-type="fig"}). This determines the layout of chemical \"tags\" used to set up map\'s \"topography\". An additional feature is that no two cells can project to the same spot in SC, which is meant to mimic axonal repulsion/competition for positive factors in SC, described in detail by Ref. \[[@B10]\].
We start from a random map, in which the terminal positions of all RGC axons in SC are chosen randomly. We then modify the map probabilistically, using the following rule. We consider two axons projecting to the neighboring points in SC (1 and 2 in Figure [3](#F3){ref-type="fig"}). We attempt to exchange these axons in SC with probability
Here *α*\> 0 is the parameter of our model. The probability of the axons to stay unchanged *P*~*RETAIN*~is determined from *P*~*EXCHANGE*~+ *P*~*RETAIN*~= 1 and is therefore given by
Since the only difference between these probabilities is the sign in front of *α*, it is important to describe the nature of this sign.
Assume that the product of gradients in Eq. (1) is negative, i.e. the gradients run in the opposite directions, which corresponds to the correct order of axonal terminals in SC. Then *P*~*EXCHANGE*~\< 1/2 and *P*~*EXCHANGE*~\<*P*~*RETAIN*~, i.e. the probability or retaining the current ordering of the axonal pair is larger than changing it. This is consistent with the chemorepellent interactions of receptors and ligands. In the opposite case of the wrong order, i.e. when the product of gradients in Eq. (1) is positive and gradients run in the same directions, *P*~*EXCHANGE*~\>*P*~*RETAIN*~by the same reasoning. The described process will tend to exchange the order of gradients and, therefore establish the correct order of topographic projections. By using probabilities described by Eqs. (1) and (2) we incorporate the chemoaffinity principle into our stochastic model. This step is then repeated for another nearest neighbor couple, chosen randomly, and so on, until a stationary distribution of projections is reached. Such a process belongs to the class of Markov chain processes, since transformations to the map are determined only by the present state of the mapping and are not otherwise affected by development history \[[@B26]\].
Let us first consider cases in which final distribution can be understood without the use of computer. The model described by (1) can be solved exactly for at least two limiting cases: when *α*= 0 and when *α*is very large. In the former case (*α*= 0) the information about chemical labels cannot affect the solution, since it is multiplied by 0 in Eq. (1). Hence, the map is completely [random]{.underline} (Figure [4B](#F4){ref-type="fig"}). In the latter case (*α*is large) the molecular cues are very strong. They eventually produce solution in which the axons are perfectly [sorted]{.underline} in SC in the order of increasing density of receptor (Figure [4D](#F4){ref-type="fig"}). An intermediate situation with certain finite value of parameter *α*is described by a compromise between noise and chemical cues, with former randomizing the map on the finer scale, while the latter inducing the overall correct ordering (Figure [4C](#F4){ref-type="fig"}). We conclude that mean position of projections is controlled by the chemical signal, while the [spread]{.underline} of projections or the size of TZ is determined by noise (Figure [4C](#F4){ref-type="fig"}).
It should be noted that in the case of large *α*(perfect sorting, Figure [4D](#F4){ref-type="fig"}) our model is equivalent to the arrow model, introduced by Hope, Hammond, and Gaze in \[[@B24]\]. The arrow model uses exchanges between nearest axons if they terminate the wrong way in tectum/SC. It can also include stochastic steps, as described in \[[@B24],[@B27]\]. The stochastic behaviors of the model described here \[Eqs. (1) and (2)\] and the arrow model are not the same (see Discussion).
Topographic maps in knock-in mice
---------------------------------
Figure [5](#F5){ref-type="fig"} summarizes results obtained in our model. The top row shows distributions of chemical \'tags\' corresponding to the wild-type, heterozygous, and homozygous knock-in conditions in Brown et al. \[[@B20]\]. The second row shows the corresponding probability distributions for axonal projections. The third row in Figure [5](#F5){ref-type="fig"} displays maxima of the probability distributions, shown to make map structure more visible. These results qualitatively agree with Brown et al. \[[@B20]\] (see Figure [2](#F2){ref-type="fig"} above), for all three cases.
Maps in both wild-type mice and homozygote conditions (Figure [5](#F5){ref-type="fig"}, columns A and C) can be understood on the basis of axonal sorting in SC in the order of monotonously increasing levels of EphAs. Results of such sorting are displayed in the bottom row in Figure [5](#F5){ref-type="fig"}. It is clear that maps resulting from simple sorting reproduce all essential features of mapping observed in wild-type and homozygotes. At the same time, bifurcation, observed in heterozygotes (column B), is not captured by simple sorting procedure. This observation led us to develop the version of noisy sorting, based on chemical cues, described here.
Why does the blending of two maps occur in rostral SC? This question is addressed below in discussion section. Here we display manipulations with \'chemical tags\', which can shift the bifurcation point in our model. These manipulations point to two factors, which contribute to the location of the bifurcation point. The first factor is inhomogeneous endogenous EphA5/6 density. It results in a smaller separation between two branches of the map observed in rostral SC (Figure [5B](#F5){ref-type="fig"} and [5C](#F5){ref-type="fig"}, bottom). The second factor is a smaller gradient of ligand in rostral SC (single-valued map region) than in caudal SC. Both these factors are addressed below.
Let us now demonstrate the impact of inhomogeneous EphA gradient on bifurcation. Figure [6](#F6){ref-type="fig"} (column A) shows that if the endogenous gradient of receptor is made more inhomogeneous, the point of bifurcation is shifted caudally. This means that the single-valued part of the map becomes larger. To see this, notice that the density of receptor in Figure [5](#F5){ref-type="fig"} (column B) has a minimum value of about 0.3. The minimum value of the receptor density in Figure [6](#F6){ref-type="fig"} (column A) is about twice as small. Hence the endogenous receptor density in Figure [6A](#F6){ref-type="fig"} changes faster than in Figure [5](#F5){ref-type="fig"}. The results of simple sorting of axons according to increasing level of receptor are also shown in Figure [6A](#F6){ref-type="fig"} (bottom). Two branches of the map approach each other closer than in Figure [5B](#F5){ref-type="fig"}. This is consistent with the expanded single-valued part of the map observed in Figure [6A](#F6){ref-type="fig"}.
But is receptor distribution the sole determinant of the position of the bifurcation point? To demonstrate that the latter is also controlled by the gradient of ligand in SC we reduce the density of ligand uniformly by 25% (Figure [6B](#F6){ref-type="fig"}). This may mimic experiments in which increment in RGC receptor is combined with reduction in ephrin-A ligand density. As a result, the point of transition between single-valued and double valued parts of the map is located more caudally in Figure [6B](#F6){ref-type="fig"} than in Figure [5A](#F5){ref-type="fig"}. Hence, we can affect the point of transition by changing the densities of both receptor and ligand to a similar degree. These results are explained below in the discussion section.
Finally, we verify that increasing of the gradient of ligand leads to a small expansion of double-valued part of the map. This result is demonstrated in Figure [6C](#F6){ref-type="fig"}. This example shows once again that ligand concentration can affect the position of bifurcation point and that increasing the ligand profile inhomogeneity (Figure [6C](#F6){ref-type="fig"}, top) leads to a more pronounced bifurcation effect (compare to Figure [5B](#F5){ref-type="fig"}).
Results for 2D model
====================
We simulated 2D development using the hypothesis that another pair of chemical tags, EphB family of receptors and their ligands, ephrins-B, are responsible for establishing topographic projection from dorsal-ventral (DV) axis on retina to lateral-medial axis in SC \[[@B9]\]. EphB2/3/4 are expressed in high-ventral-to-low-dorsal gradient by RGCs \[[@B28]-[@B30]\], while ephrins-B are expressed in high-medial-to-low-lateral gradient in tectum/SC \[[@B30]\]. Since dorsal/ventral axons project to lateral/medial SC this implies attractive interactions between EphB+ axons and ephrin-B rich environment \[[@B31]\] (see, however \[[@B32]\]). In our model the attractive interactions are modeled by the following exchange probability of two axonal terminals in the DV direction:
Here *RB*(1), *RB*(2), *LB*(1), and *LB*(2) are EphB receptor and ephrin-B ligand densities at neighboring points 1 and 2 in SC. This probability is similar to Eq. (1). Notice a sign change compared to Eq. (1), which insures that *P*~*EXCHANGE*~\>*P*~*RETAIN*~if the order of gradients is wrong, i.e. if the gradients of receptor and ligand are antiparallel. By choosing this sign we therefore ensure attraction between axons and ligands.
The details of our simulations are described in Methods. Our model allows not only exploration of two-dimensional maps (Figure [7](#F7){ref-type="fig"}) but also observing and modeling temporal development (Figure [8](#F8){ref-type="fig"}). Videos with detailed evolution of the map are available in \[[@B25]\].
Discussion
==========
Why does the map in heterozygotes bifurcate?
--------------------------------------------
In our model the map is formed through interaction of three factors: Eph/ephrin-based chemorepulsion/attraction, competition between axons for space, and noise. It is the latter that fuses two maps together in rostral SC (Figures [5B](#F5){ref-type="fig"}) in this model. Therefore, to understand position of the bifurcation point one has to consider the interplay between signal and noise at different positions in the map.
As we have shown above both ligand and receptor distributions influence the range of single-valued portion of the map independently (Figure [6](#F6){ref-type="fig"}, columns A and B). Let us first address the impact of ligand distribution. Figures [9](#F9){ref-type="fig"} and [12A](#F12){ref-type="fig"} show that the gradient of ligand is the smallest in rostral SC. This leads to a larger impact of noise there. Since noise drives blending of two branches of the map, this blending first occurs in rostral SC, in agreement with Brown et al. \[[@B20]\]. Interestingly, Brown et al. also shows larger diameters of axonal TZ in the single-valued part of the map, which is consistent with the larger impact of noise there.
The second factor contributing to bifurcation in heterozygotes is inhomogeneity of EphA gradient in retina. Consider the case of no noise. Mapping in this case is obtained by sorting axonal terminals in the order of increasing density of EphA (Figures [10](#F10){ref-type="fig"}, [5](#F5){ref-type="fig"}, [6](#F6){ref-type="fig"}). Separation between two maps is the smallest in rostral part (Figure [10B](#F10){ref-type="fig"}). This is because of inhomogeneous gradient of receptor in \'retinal\' cells (Figure [10A](#F10){ref-type="fig"}). Therefore, even if noise were the same in all parts of the map, rostral part has the smallest signal in terms of separation between two maps, and the largest potential to be blended by noise.
We conclude that two factors, increased noise and reduced signal, cooperate in rostral SC in fusing the wild-type and knock-in maps. This leads to the formation of single-valued map there. In caudal part both noise is reduced and distance between maps is larger. Hence, the map is double-valued in caudal SC.
Mapping in Isl2/EphB knock-ins has two bifurcations
---------------------------------------------------
It is possible to spatially separate these two blending factors, increased noise and decreased signal, if one applies the same logic to the DV axis of the map. In our model this mapping is implemented by attractive interactions between EphB+ axons and ephrin-B rich environment. Hence, DV mapping is \"flipped\" with respect to the TN one in the sense that high EphB gradient region of retina maps to a high ephrin-B gradient region in SC. Two blending effects described above (reduced signal and increased noise) are therefore spatially separated for the DV axis. To observe mapping in these conditions we performed a numerical \"experiment\" on the Isl2/[EphB]{.underline} knock-in conditions. This may have relevance to mapping in DV direction. The results are shown in Figure [11](#F11){ref-type="fig"}.
Two bifurcations observed in Figure [11](#F11){ref-type="fig"} confirm the hypothesis about two factors operating in the numerical model. The ventral bifurcation is associated with receptor, since separation between two maps in perfectly ordered conditions is the smallest in medial SC. The second bifurcation, dorsal, occurs due to noise, since noise is maximal where the gradient of ligand is the smallest, i.e. in lateral SC. Thus, we suggest that experiments on Isl2/EphB knock-ins should make clear if inhomogeneity in receptor density or noise is more important.
It is also possible that activity-dependent mechanisms drive blending of two maps. Activity leads to focusing of projections whereby axons with close locations in retina are effectively attracted to each other in SC. Activity-dependent attraction will blend axons positioned proximally in SC, therefore ventral bifurcation, described above, may be robust with respect to these factors. The dorsal bifurcation, on the other hand, may or may not be observable if activity-dependent focusing of projections takes place. These questions will be addressed in future studies.
Absolute versus relative
------------------------
Brown et al. \[[@B20]\] demonstrates that retinocollicular mapping is based on relative levels of EphA/ephrin-A expression in the broad meaning of this term. Indeed, the absolute value of EphA density does not determine where an axon terminates in colliculus. This is because axonal TZ may shift in the presence of axons with altered expression of chemical tags. For example, wild-type axons terminate more caudally in the presence of Isl2+/EphA3+ axons. Hence, an important factor is the presence of other axons, relative to which given axon establishes its termination point. This idea is also evident from retinal and collicular/tectal ablation experiments in rodents \[[@B33],[@B34]\] and other species \[[@B2]\].
Can we take this idea to the next level and hypothesize that relative differences between neighboring retinal cells represent the chemical signal? This suggestion was used \[[@B20]\] to explain blending of the two maps in heterozygous rostral SC, since relative differences in receptor levels are the smallest in the corresponding part of retina (temporal). In this study we present a model, which uses differences in [absolute]{.underline} values of chemical label, as seen from Eq. (1). Indeed, in our model adding a constant value to all densities does not change the resulting mapping, since (1) depends only on differences in expression levels. But this manipulation decreases the relative differences in the expression of EphAs between neighboring knock-in and wild-type cells. Hence, our model is not based on relative differences between receptor densities. Yet, we demonstrate that it can account for experimental results in detail. Thus, we suggest that existing experimental evidence is not sufficient to distinguish relative and absolute labeling in the narrower sense.
Of course, our model also accounts for the caudal displacement of wild-type TZs, thus resulting in a relative labeling system in the broad sense. In the first approximation, this model performs a sorting procedure, understood mathematically, of the fibers based on the expression levels of EphA. Our procedure uses differences in absolute values of EphA densities rather than relative differences. We suggest that more quantitative evidence is needed to distinguish these two \"relativity principles\".
Relative labeling in the narrow sense can be incorporated in our model too, if coefficient *α*is a function of label densities. Thus, the condition *α*∝ 1/(*RA*·*LA*) ensures the Weber\'s law for axonal \"perceptual thresholds\", since chemical signal is proportional to the relative differences.
Comparison to other theoretical models
--------------------------------------
Theories based on chemoaffinity principle are reviewed in \[[@B4]\]. Some features of our approach are similar to the arrow models described in Ref. \[[@B24],[@B27]\], which employs exchanges between neighbouring axons to establish ordered retinotectal/collicular maps. At the same time some features of our model are different from the arrow model. First, we employ information about chemical labels, Ephs and ephrins. At the heart of our model are equations (1--3), which rely on the known distributions of chemical labels. These equations are unique to our approach. As it was noted above, in the absence of stochasticity (*α*→ ∞), when perfectly ordered map is formed, our 1D model with nearest neighbor exchanges is equivalent to the 1D version of the arrow model. However, in the stochastic regime, description of developmental noise is different here. In particular, we relate features of the map, to the distribution of chemical labels. We argue that this feature is important in understanding experiments \[[@B20]\], since distribution of labels determines where TZs fuse to form bifurcations. Second, we consider both nearest neighbour and distant neighbour exchanges (see Methods for more detail). Indeed, Eq. (1--3) can be applied to determine exchange probability for a pair of distant axons too. This feature may be crucial, since development of map in the RC direction is determined by original primary axonal overshoot with subsequent retraction of inappropriate projections \[[@B3],[@B9]\]. In this process the interstitial branches of the same primary axon are eliminated and subsequently added non-locally. We show below in Method section that in many cases local and global exchanges produce the same results in terms of final distribution of projections. But, the process of development is different in the local and global exchange cases.
Prestige and Willshaw \[[@B35]\] suggested to divide developmental mechanisms into two groups. In group I mechanisms each RGC axon has maximum affinity to certain unique point in the target, even without other axons. In group II mechanisms, the position of TZ results from competitive interactions with other axons. Our model definitely belongs to the second group, since we assume that all axons experience maximum affinity to rostral medial SC and are spread over entire SC by competition. Our approach is similar to described in Prestige and Willshaw in the way how graded distributions of molecular tags are represented. The details of map modifications are somewhat different in this study and are precisely defined by Eqs. (1--3).
In a recent study Honda \[[@B36]\] considered results of experiments \[[@B20]\]. He used servomechanism model to explain the overall structure of the maps in mutants. Servomechanism model is a hybrid between group I and II models in terminology of Prestige and Willshaw, since it assumes that axons have equilibrium points in SC and they are subject to competition with each other. Although Ref. \[[@B36]\] reproduces doubling of the map in homozygotes it does not succeed in obtaining the bifurcation observed in heterozygotes, which is one of the purposes of the present study.
On the biological realism
-------------------------
When dealing with numerical simulations one always faces the question of the degree of realism with which to model the data. Does one have to model behaviors of individual atoms, or description on the level of axons is sufficient? In this work we choose the level of description on the basis of what is known about this system. We realize that our model does not capture many behaviors, but we argue that the mechanisms involved are unclear at the moment to be incorporated into a more detailed model. Our approach also fulfils its original goal, which is to reproduce the results of experiments \[[@B20]\] and to generate experimentally testable predictions, thus satisfying the requirement of parsimony.
Model presented here does not describe the difference between development along TN and DV axes. The former mapping is controlled by original axonal overshoot along the RC direction in SC, with subsequent elimination of topographically inappropriate projections \[[@B3],[@B9]\]. In contrast, primary axons from the same DV retinal position enter SC in a broad distribution along ML axis. Topographically precise termination is provided by producing additional interstitial branches in the ML direction \[[@B31],[@B32],[@B37],[@B38]\]. These findings cannot be reproduced by our model, since no distinction is made between the primary RGC axon and its branches. Instead, our model deals with terminal points of interstitial branches produced by RGC axons.
Conclusions
===========
We present a model for retinocollicular map development, which can account intriguing behaviors observed in gain-of-function experiments by Brown et al. \[[@B20]\], including bifurcation in heterozygous Isl2/EphA3 knock-ins. The model is based on chemoaffinity, axonal repulsion/competition, and stochasticity. We discuss possible mappings in ephrinA-/Isl2+/EphA3+ knock-out/ins and Isl2/EphB knock-ins.
Methods
=======
1D model
--------
To find a stationary distribution of the RGC\'s axons in the SC, we use the following computational procedure. We consider a linear chain of 100 RCG that are connected to one and only terminal cell in SC each. The receptor and ligand expression level profiles used in the computations for wild-type, heterozygote and homozygote are shown at Figure [5A,5B,5C](#F5){ref-type="fig"}. We start with the random map where the position of every axon in SC does not depend on the level of its receptor expression. Then we perform stochastic reconstructions through an exchange of the positions of the neighboring axons in SC. Namely, at each step we randomly choose one pair of axons out of 99 neighboring pairs and switch their positions with the probability given by Eq. (1). In both cases, whether the positions of the axons are exchanged or they retain at their old locations we proceed to the next step when we choose a new pair of neighboring axons. We repeat the process until a stationary distribution of the probabilities for the positions of the RGC\'s axons in SC is reached.
The typical stationary solution for one realization is shown at Figure [4](#F4){ref-type="fig"}. Here the number of iterations is 10^6^(nearest neighbor exchanges). The main parameter of our model is taken to be *α*= 30 throughout the paper. It is chosen to fit the experimental data from Brown et al. \[[@B20]\]. We have observed that the value of *α*is roughly equal to inverse of the relative diameter of the TZ squared. Thus, in our results, TZ occupies, roughly, 20% of the entire SC, which corresponds to the value of *α*given above. The probability distribution and the position of the maximums shown at Figure [5](#F5){ref-type="fig"} and [6](#F6){ref-type="fig"} are obtained by temporal averaging over 5 × 10^4^realizations of stationary solution separated in time by 10^3^iterations (nearest neighbor exchanges).
The choice of receptor/ligand expression profiles
-------------------------------------------------
We base our choice of parameters for the distribution of molecular markers on experimental observations in mouse retina and SC. Thus, the distribution of ephrinA2 and A5 is obtained in \[[@B10]\]. The total distribution of ligand in SC is shown in Figure [12A](#F12){ref-type="fig"}. It resembles closely the distribution used in this study *LA*(*x*) = exp(-*x*) (Figure [4A](#F4){ref-type="fig"}, etc). Note that the constant factor in front of the exponential is taken to be 1 in our model, since any non-unit factor is absorbed into parameter *α*\[cf. Eq. (1)\].
The distribution of receptors in retina requires more thorough consideration. The distribution of strength of EphA S-RNA hybridization signals is measured in \[[@B20]\] and is shown in Figure [12B](#F12){ref-type="fig"}. From this distribution one has to obtain the density of receptor expression in single axon, emanating from given point in retina. To this end the overall strength of the hybridization signal is divided by the RGC density in cells/mm^2^, obtained in \[[@B39]\] (Figure [12C](#F12){ref-type="fig"}). The resulting distribution of EphA receptors per cell is shown in Figure [12D](#F12){ref-type="fig"}. It is matched closely by the function used in this study *RA*(*x*) = exp(-*x*) (see Figure [4A](#F4){ref-type="fig"}, etc) in \> 95% of retina. Additional distortions introduced by non-uniform linear magnification factor are estimated by us to be small (\< 10%), based on data from \[[@B39],[@B40]\]. Such distortions cannot be calculated directly, since a complete topographic map from retina to SC is not available. The errors introduced by non-uniform map do not exceed the precision with which the density of receptors is originally measured, estimated from the noise in \[[@B20]\].
In the EphA3+ retina the density of receptor is increased in every second cell by 50% and 25% of the maximum value in homo and heterozygotes respectively. These parameters are chosen to match the overall map structure (Figure [5](#F5){ref-type="fig"}) to that observed experimentally in \[[@B20]\] (Figure [2](#F2){ref-type="fig"}). The particular parameter which was chosen for such comparison was the overall distance between the wild-type and knock-in cells, equal approximately to 40 and 20 percent in homo and heterozygotes. Since such distance is approximately constant in the homozygotes, the effects of receptor dimerization, discussed in \[[@B7]\], are assumed to be negligible. This may occur due to saturated conditions (almost all receptors are in the dimerized state). The effects of ligand dimerization are impossible to estimate at the moment. To assess this effect in our model we verify that our results are not changes significantly if ligand density is below dissociation density for dimerization, i.e. the effective ligand density interacting with the receptor is equal to the square of actual density, *LA*(*x*) = exp(-2*x*) (Figure [6C](#F6){ref-type="fig"}).
The profiles of expression of EphB/ephrinB pair are measured in \[[@B31]\] similar to EphA/ephrinA. They are taken to be *LB*(*y*) = exp(-*y*) and *RB*(*y*) = exp(-*y*). As with the EphA/ephrinA the non-unit overall factors in these distributions are absorbed in parameter *β*(see below).
2D model
--------
Here we describe our 2D model in more detail. We consider an array of 100 by 100 RGC, which are connected to 100 by 100 different points in colliculus. Each RGC is characterized by two levels of expression for two receptors, EphAs and EphBs, described in the text. The concentration profiles are taken to be the same for EphA and EphB receptors in the wild-type species. In the homozygote and heterozygote cases the concentration of EphA is taken as shown at Figure [5](#F5){ref-type="fig"}, while the concentration of EphB is unchanged. RGCs do not express ligand in our model. The collicular receptacles are described by two ligand concentrations with the same profiles as shown at Figure [5](#F5){ref-type="fig"} but with different gradient directions discussed in the text.
The process of development is modeled as follows. We randomly choose a pair of axons in SC separated either in RC or in ML direction. We exchange their positions with the probability given by Eq. (1) or Eq. (3) respectively. We then repeat the process until a stationary distribution of probabilities is reached in the same manner as for 1D case. Note, that this time a chosen pair of axons, say in RC direction, may not be a neighboring pair, but consist of two axons separated by any distance in SC. This procedure dramatically decreases the convergence time to the stationary distribution, which is the same as in the case when we choose the neighboring axons only. The noise level is taken to be the same for both RC and ML directions, that is *α*= *β*= 30.
The spatial 2D distribution of the axons corresponding to labeled RGCs is shown at Figure [7](#F7){ref-type="fig"}. The \"labeling spot\" in retina is a circle with radius R = 7.3, the coordinates of the center are (15,50), (50,50) and (85,50) on the 100 × 100 grid. The distribution is obtained by averaging the positions of the labeled axons in SC over 1000 realizations after it reached the stationary solution at 1 × 10^6^iterations. The temporal evolution of the map for the label in the central retina is shown at the Figure [8](#F8){ref-type="fig"}. It corresponds to averaging over 1000 different realizations at each time interval.
In both 1D and 2D cases the calculations were performed on Dell PowerEdge 1600SC server. The programs, written on Matlab (MathWorks, Inc.), are available for download in \[[@B25]\].
Limiting probabilities between 0 and 1
--------------------------------------
Equations for the probability of switching of two axons (1) and (2) can yield probabilities, which are below 0 or larger than 1. Thus, in the numerical implementation of our model instead of (1) and (2) we use expressions with soft cutoff at 0 and 1, i.e.
These probabilities are restricted to be between 0 and 1. In addition, when differences in ligand and receptor densities between neighboring points are not large, (4) and (5) are equivalent to (1) and (2).
Local versus global transitions
-------------------------------
One could use exchanges between nearest neighbors to implement map development, as described in text above and in \[[@B24]\]. Alternatively, one could consider swaps between two distant axons chosen randomly. An exact statement, a proof of which we provide here, is that the [final]{.underline} probability distribution for connectivities does not depend on whether the swaps are local or global. This statement is true, for any distribution of chemical labels, in 1 or 2D. It is true however if Eq. (4) is used to calculate probabilities of transitions. In particular, we show that Eq. (4) leads to a Boltzmann distribution of the probabilities of connections, which does not depend on the locality/globality of transitions. Thus, we can present final maps for both local and global transitions interchangingly, since results pertaining to the final state of the map, such as in Figures [4](#F4){ref-type="fig"},[5](#F5){ref-type="fig"},[6](#F6){ref-type="fig"},[7](#F7){ref-type="fig"} and [10](#F10){ref-type="fig"},[11](#F11){ref-type="fig"}, do not depend on the choice of transitions. However, the temporal dynamics of map evolution does depend on this choice. Normally, the convergence of the map to the final distribution is faster with global transitions. Thus, Figure [8](#F8){ref-type="fig"} shows evolution of the map for the case of global swaps. The sequence in Figure [8](#F8){ref-type="fig"} would be different, if the swaps between nearest neighbors were used.
Let us now derive the probability distribution of projections in the final map. We perform our derivation for the 1D case; in 2D it is similar. We proceed using the detailed equilibrium principle, frequently employed in statistical mechanics \[[@B41]\]. Consider two states of the map, symbolically denoted by A and B. These states are described by corresponding probabilities *P*~*A*~and *P*~*B*~. These probabilities satisfy the detailed equilibrium condition \[[@B41]\]
where the transition probabilities are given by equation (4). After some algebra, it is possible to show that the transition probabilities are given by a simpler than (4) form
where *E*~*A*~and *E*~*B*~are \'state\' variables, depending on the current arrangement of axons in the target
Here summation is assumed over all termination sites in SC, denoted by index *i*, with *L*(*i*) being the ligand concentration and *R*(*i*) the receptor concentration. The latter, of course, depends on the arrangement of axons, corresponding to the state A. The transition probability *P*~*B*→\ *A*~is given by the same expression, with exchanged indexes A and B. The detailed equilibrium condition (6) leads then to Botzmann probability distribution of the states of the map
Eq. (9) is instrumental in showing that the final distribution of projections in our approach does [not]{.underline} depend on the methods of reconstruction. Thus, both global and local transitions will lead to identical final arrangement of the map. This property is well-known in considering Metropolis Monte-Carlo procedures. What does depend on the methods of reconstruction is the time, which it takes to reach the final configuration. Thus, as it was mentioned above, global transitions lead to the final state much faster. With local transitions, on the other hand the map can freeze in the original state, and it may take an exponential time to reach the final configuration.
We thus conclude that our results presented in this study are universal in that they do not depend on the exact developmental mechanism, but only on the distribution of \'chemical\' tags.
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
**Chemical labelling system in retinocollicular map in miceA.**Formation of the map in the wild-type mouse. Retinal ganglion cells (RGC) express EphA5/6 receptors in temporal \> nasal gradient (bottom), whereas the cells in SC express the ephrin-A ligands in caudal \> rostral gradient (top). Since axons of Eph+ RGC (red arrows) are repelled by ephrins this distribution of chemical markers leads to establishing of ordered topographic map in which nasal/temporal retina projects to caudal/rostral SC. This is because RGC axons expressing highest levels of Eph receptors (temporal) experience the largest repulsion and are expelled to the rostral part of SC, where such repulsion is minimal. Axons of nasal RGC are more indifferent to the action of ligands and occupy more caudal positions. Such system allows positioning of RGC axons in the order of increasing expression level of EphA receptors. **B.**Map in the mutant mouse from Ref. \[20\]. The expression level of EphA receptors was artificially increased in every second cell by genetic manipulations (dark gray). This is done by co expressing EphA3, which is absent in the wild-type RGCs (see **A**), with another gene, Isl2, which is expressed roughly in 50% of RGCs. Since ephrin ligands bind and activate all receptors from EphA family, albeit with different affinity, this results in anomalous projection to SC, based roughly on the total levels of EphA in each axon. Similarly to **A**this leads to sorting of axons in the order of increasing density of EphAs (red arrows). Note that two RGC neighboring in retina become separated in SC (bold arrows). This aberration in the topographic map leads to two termination zones (TZs) in SC for two neighboring cells in retina, rather than a single zone in wild-type \[20\].
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
**Maps in Isl2+/Eph3+ mice.**The top row is reproduced from Ref. \[20\] (Figure 5). The bottom row illustrates the corresponding distribution of EphAs.
:::
:::
::: {#F3 .fig}
Figure 3
::: {.caption}
######
Description of the 1D model
:::
:::
::: {#F4 .fig}
Figure 4
::: {.caption}
######
**Typical solutions of 1D modelA**. Distribution of ligand (top) and receptor (bottom). **B**. Solution of the model for *α*= 0. Red dots represent terminal positions of individual axons, originating at various points in retina. If the case *α*= 0 the map is completely random, since all the chemical cues are multiplied by zero in Eq. (1), and, therefore, cannot contribute to the solution. **D**. *α*is very large. Solution represents perfect ordering of axons in SC in the order of increasing density of receptor. This is because the chemical cues are extremely strong in this case, much stronger than noise. **C**. *α*= 30. At the intermediate value of *α*solution is a compromise between chemical signal and noise.
:::
:::
::: {#F5 .fig}
Figure 5
::: {.caption}
######
**1D maps in wild-type and knock-in animals.A**. column of results for wild-type conditions. **B**. Column corresponding to heterozygous Isl2/[Eph3]{.underline} knock-in conditions. The bifurcation of the probability distribution is similar to results of Ref. \[20\] (see Figure 2 above). **C**. Results for homozygous knock-in conditions. For all three conditions, the top row represents distributions of chemical labels. The second row shows the probability distributions. The brightness of color at each point in the middle image represents probability that an axon originating from the horizontal position projects to the point\'s vertical position. The bottom row shows positions of maxima of probability density distributions displayed above. The red squares correspond to wild-type cells; black markers determine maxima of distributions for Isl2+/EphA3+ RGCs. A slight even-odd oscillation observed in these panels is an artifact of ordering of wild-type and EphA3+ axons in retina. The bottom row shows maps obtained by sorting retinal receptor density.
:::
:::
::: {#F6 .fig}
Figure 6
::: {.caption}
######
**Manipulations with chemical labels, which lead to shifts in the bifurcation pointA.**The endogenous receptor gradient is made steeper compared to Figure 5B. The single-valued part of the map expands caudally. **B**. Density of ligand is reduced by 25%. Similar expansion of the single-valued part of the map is evident. **C**. The ligand gradient is made steeper. This is to reproduce the possible effect of ligand dimerization. The bifurcation point is moved slightly rostrally, expanding the double-valued part of the map. In all three columns the vertical arrangement of panels is similar to Figure 5.
:::
:::
::: {#F7 .fig}
Figure 7
::: {.caption}
######
**Numerical simulation of labelling in the 2D model.**The top row shows anterograde \"labeling spots\" in retina. The following three rows display corresponding distribution of label in SC. The size of both retinal and collicular arrays is 100 by 100 cells. The three rows show results for wild-type, heterozygous knock-ins, and homozygous knock-ins, as marked on the left. Notice the doubling transition, when going from temporal to nasal injection in heterozygotes. This Figure is to be compared to Figure 4 from Ref. \[20\]. *α*= *β*= 30. The color map is shifted in each image for visibility. Abbreviations: D, dorsal; V, ventral; N, nasal; T, temporal; C, caudal; R, rostral; L, lateral; M, medial.
:::
:::
::: {#F8 .fig}
Figure 8
::: {.caption}
######
**Map refinement.**Wild-type (left) and ki/ki (right) map development for axons in the central retina. The retinal injection site is the same as in Figure 7, top row and central column. The temporal evolution of the map is shown for t = (0, 8, 16, 24, 32, and 100) × 10000 iterations. The orientation of images is the same as in Figure 7. The color map is rescaled in each image for visibility.
:::
:::
::: {#F9 .fig}
Figure 9
::: {.caption}
######
Reduced gradient of ligand in rostral SC may explain single-valued map there.
:::
:::
::: {#F10 .fig}
Figure 10
::: {.caption}
######
**Mapping for heterozygotes in case of no noise.**The separation between wild-type and EphA3 knock-in axonal terminals is larger in caudal than in rostral SC, due to inhomogeneity in EphA profile.
:::
:::
::: {#F11 .fig}
Figure 11
::: {.caption}
######
**Mapping in heterozygous Isl2/EphB knock-ins.**Two bifurcations are observed, one in medial, another in lateral SC.
:::
:::
::: {#F12 .fig}
Figure 12
::: {.caption}
######
**The choice of receptor/ligand expression profiles.A**, Density of ephrinA ligands in SC obtained from RNA hybridization \[10\]. B, Density of EphB receptors in retina from RNA hybridization \[20\]. C, density of RGC in retina \[39\]. D, Density of EphA receptor per cell, obtained by dividing B by C. Vertical axes in A, B, and D are in arbitrary units. Dashed lines show the exponential approximations used in this study.
:::
:::
|
PubMed Central
|
2024-06-05T03:55:48.026557
|
2004-8-31
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC520742/",
"journal": "BMC Neurosci. 2004 Aug 31; 5:30",
"authors": [
{
"first": "Alexei A",
"last": "Koulakov"
},
{
"first": "Dmitry N",
"last": "Tsigankov"
}
]
}
|
PMC520743
|
Background
==========
Knee pain in older adults is a common disabling problem. Approximately 25% of the population aged over 55 years are affected at any one time and half of these will have some restriction of normal daily activities \[[@B1],[@B2]\]. After excluding \`red flags\' and specific pathologies such as inflammatory arthritis, most knee pain in older adults is due to osteoarthritis. Controlling the pain and minimising loss of function are the principal aims of treatment. Most sufferers are managed exclusively in primary care \[[@B3]-[@B5]\], where the usual approaches include analgesics and exercise \[[@B6]-[@B11]\]. A report from Arthritis Care \[[@B12]\] of patients\' perspectives highlighted that people with knee osteoarthritis want treatment offering more pain relief and help with mobility. Easy to understand information was also felt to be important, as was exercise, to help manage the problem. A recent review of international guidelines suggests that, for patients with knee pain, the best non-pharmacological care consists of education, muscle strengthening and exercise \[[@B13]\].
Patients with musculoskeletal pain often choose methods of treatment that are not widely available within the NHS, such as complementary medicine \[[@B14]\]. Reports from the United States and the United Kingdom have indicated the popularity of complementary medicine with the general public and health care professionals \[[@B15]-[@B19]\]. Complementary medicine is available in approximately 40% of general practice surgeries and general practitioners and physiotherapists are the largest providers of complementary medicine within the NHS \[[@B17]\]. Acupuncture is one of the most popular complementary medicine modalities in the UK: reports suggest that it is available in 84% of chronic pain clinics and approximately 4000 general practitioners and physiotherapists are trained in acupuncture \[[@B21],[@B22]\]. Although recent authors have promoted the concept of integrated practice incorporating conventional and complementary therapies \[[@B20]\], current guidelines highlight the need for further research evidence for the use of acupuncture for knee pain in older adults \[[@B13]\]. The clinical effectiveness of acupuncture, and the question of whether it is superior to sham interventions has not been established. In addition to providing exercise and advice, physiotherapists are also one of the largest groups of acupuncture providers within both primary and secondary care in the NHS \[[@B23]\]. Physiotherapy is therefore an appropriate and important arena in which to investigate the effectiveness of integrated mainstream and complementary therapy.
Evidence for advice and exercise
================================
International guidelines suggest that the best package of care for this patient group is one that includes patient education, advice and exercise \[[@B13]\]. There is strong evidence for the usefulness of education, muscle strengthening and aerobic exercise. The beneficial effects of exercise on knee pain are well documented and it is a key component of successful rehabilitation programmes for patients \[[@B24],[@B25]\]. Active rehabilitation programmes for patients with musculoskeletal and arthritic pain not only improve joint function and reduce pain, but also improve strength, walking speed and self-efficacy \[[@B26]\] as well as quality of life, and they reduce risk of other chronic conditions \[[@B27]\]. Randomised clinical trials consistently show the benefit of exercise for knee pain in older adults \[[@B28]-[@B31]\]. Recent studies also highlight the need to provide adequate instruction, feedback and practice in order to ensure that the key muscle groups around the knee, such as the quadriceps, are activated \[[@B32]\]. The European League Against Rheumatism (EULAR) recommendations have recently been updated and in particular, advocate exercise for knee pain related to osteoarthritis \[[@B33]\]. In line with this evidence base, the current trial was designed so that all participants receive a package of care which includes education, advice, and exercise.
Evidence for acupuncture
========================
The physiological properties of acupuncture have been well described in the laboratory. Acupuncture activates central mechanisms of pain control and elicits release of specific neurotransmitters (mainly opioids) in the central nervous system \[[@B34],[@B35]\]. Effects on the autonomic nervous system have also been demonstrated during and after acupuncture stimulation \[[@B36],[@B37]\]. Despite this, its clinical effectiveness remains a matter of controversy \[[@B38],[@B39]\]. This is partly because of methodological limitations in many trials of acupuncture, including small sample sizes, lack of credible sham-controls, and inadequate blinding \[[@B40]\]. Acupuncture has been shown to have a short-term analgesic effect in musculoskeletal pain \[[@B41],[@B42]\]. A recent evaluation of acupuncture by the National Institutes of Health concluded that it has an analgesic effect on dental and orofacial pain and is a useful adjunct in a range of painful conditions, including musculoskeletal and myofascial pain \[[@B43]\]. In fibromyalgia, there is increasing evidence demonstrating the usefulness of acupuncture \[[@B44],[@B45]\]. One meta-analysis concluded that acupuncture might offer benefit to patients with knee osteoarthritis when used as an adjunct to mainstream management strategies \[[@B46]\].
Appropriate sham interventions for acupuncture have been widely debated and several placebo needles have been introduced and tested \[[@B47],[@B48]\]. A trial conducted in Germany recently concluded that true acupuncture has a better effect than sham acupuncture in the treatment of knee and back pain, but not for migraine headache \[[@B49]\]. In addition, another study reported positive effects of acupuncture for knee pain \[[@B50]\]. However, a key limitation to these studies is the lack of long-term follow-up, something which the current study has been designed to address \[[@B51]\].
We have designed, and are currently implementing, a prospective sham controlled randomised trial within the primary care setting addressing the important clinical question: is acupuncture a useful adjunct to physiotherapy care (advice and exercise) for treating knee pain in older adults? Research and development in primary care is important to public health and necessary to support the decisions and treatments in this setting \[[@B52]\].
The primary objective is to compare, at 6 months, the clinical outcomes of true acupuncture plus advice and exercise, with advice and exercise alone for treating people aged 50 years and over referred directly from primary care with knee pain. Our secondary objectives are
i\) to compare, at 6 weeks and 12 months, the clinical outcomes of adding true acupuncture to advice and exercise alone, in the same patient group.
ii\) to compare, at 6 weeks, 6 and 12 months, the clinical outcomes of sham acupuncture plus advice and exercise, with advice and exercise alone, in the same patient group.
iii\) to measure patients and physiotherapists beliefs, preferences and expectations about the treatments being tested and to explore their effect on clinical outcome.
Methods
=======
Trial design
------------
This multicentre, three-arm sham-controlled randomised trial will be conducted in 43 individual Physiotherapy Centres that provide services for Primary Care Physicians located in 21 NHS Trusts situated in the Midlands and Cheshire regions of the UK. Multi-centre ethical approval has been obtained from the West Midlands Multicentre Research Ethics Committee and local approval was given by 12 ethics committees (Southern Derbyshire, Shropshire, Worcestershire, Warwickshire, Mid Staffordshire, South Staffordshire, Sollihull, North Birmingham, South Birmingham, West Birmingham, East Birmingham, East Cheshire). The trial was designed by a steering group with expert input from physiotherapists, an acupuncture specialist and trial methodologists. Information will be collected from the individual participating physiotherapists (demographics, current training and use of acupuncture, attitudes and beliefs about knee pain, and beliefs and expectations of the three treatment packages being compared in the trial) prior to the commencement of the trial and after the trial has been completed (Table [1](#T1){ref-type="table"}).
Study population
----------------
Participants include patients with knee pain aged 50 years and over referred to physiotherapy centres by their general practitioner. Participants will be randomised to one of three groups: (i) advice and exercise alone, (ii) advice and exercise plus true acupuncture, (iii) advice and exercise plus sham acupuncture. Follow up will be at 2 weeks (by telephone), 6 weeks, 6 months and 12 months after randomisation, by postal questionnaire. Non-responders will be followed up.
Inclusion criteria
------------------
Eligible patients are male and female subjects aged 50 years and above with pain (with or without stiffness) in one or both knees presenting to primary care. They must be naïve to acupuncture treatment (i.e. have never experienced acupuncture before for their present or any past complaints), and considered suitable for referral to a physiotherapy outpatients department by their general practitioner. Participants must be able to read and write English, be willing to consent to participation, and able give full informed consent. They must also be available for telephone contact.
Exclusion criteria
------------------
Patients with potentially serious pathology (e.g. inflammatory arthritis, malignancy etc) on the basis of general practice or physiotherapy diagnosis or from past medical history, those who have had a knee or hip replacement on the affected side(s), are already on a surgical waiting list for total knee replacement, or for whom the trial interventions are contraindicated are excluded from the trial. Those who have received an exercise programme, from a physiotherapist, for their knee problem within the last 3 months (normal recreational involvement in sport or exercise will not be an exclusion) or an intra-articular injection to the knee in the last 6 months are also excluded.
Participant recruitment
-----------------------
Eligible patients referred by their GP to the physiotherapy departments will be invited to take part. Recruitment will take place over 18 months and will operate in one of two ways (See Figure [1](#F1){ref-type="fig"}):
### 1) Trial nurse
To identify potentially eligible patients, a trial nurse will review GP referral letters received by participating physiotherapy departments that fall within a feasibly commuteable geographical area of the Research Centre.
### 2) Local physiotherapy assessor
A minimum of two members of the physiotherapy team will be involved at centres that fall outside the trial nurse\'s geographical area, one will be the nominated local assessor and a second will treat participants.
The nominated local physiotherapy assessor or trial nurse will perform an initial screen of the referrals to the physiotherapy department for potential participants. Potentially eligible patients will be posted information about the study, and their GP will be notified that the patient has been approached to take part. The GP will be asked to notify the Physiotherapy Department if they feel the patient is ineligible or unsuitable.
Consent
-------
A minimum of 48 hours after receiving the information leaflet, patients will be telephoned by the nominated local assessor/trial nurse (within 10 working days) to further screen eligibility. Information will be recorded on a standard proforma. For those patients either not eligible or not willing to be recruited, the proforma will be used to detail the reason for ineligibility, or reason for decline. Where patients are willing, two additional questions are asked to those that decline to participate in the trial to capture their treatment preference and expectations with respect to acupuncture and an advice & exercise treatment package. This information will be anonymised.
For patients willing to be recruited to the trial, an appointment is arranged for a research assessment at the patient\'s local physiotherapy department. After gaining verbal consent, the patient will be posted the baseline questionnaire to complete prior to their research appointment. At the research assessment visit the local physiotherapy assessor/trial nurse will perform a more detailed eligibility screen, explain the study, gain informed written consent to randomisation and conduct a baseline research interview and examination. Following consent to the study, the participant will be registered with the Research Centre by fax and allocated a unique trial number. The baseline assessment will be carried out blind to subsequent treatment allocation. An appointment will be made for the treating physiotherapist to begin treatment within 10 working days of the research assessment. Consent to treatment will be gained from each treating physiotherapist prior to commencing treatment, as is current physiotherapy practice. All participants will have an initial clinical physiotherapy assessment and treatment session of up to 40 minutes duration. During this session the physiotherapist will identify and record potential acupuncture points to be used should the participant be randomised to receive acupuncture (true or sham). A minimum of 6 and maximum of 10 points will be selected, based upon the participant\'s presentation and the clinical opinion of the physiotherapist. This will be carried out as part of the overall physical examination of the knee -- the therapist will not draw the participant\'s attention to the localisation of acupuncture points to avoid raising their expectations about the possibility of receiving acupuncture. The advice and exercise package will then be started during this initial treatment visit.
Randomisation
-------------
Randomisation will take place after this initial physiotherapy session. The treating physiotherapist will telephone the Research Centre at Keele University, during normal working hours. This methodology ensures that the initial physiotherapy assessment and advice and exercise package provided is performed blind to subsequent treatment allocation. The specific trial interventions will commence during the participant\'s second treatment visit. During the randomisation telephone call the physiotherapist will be asked to identify the selected acupuncture sites to check that the participant has received their first pre-randomisation treatment session. The physiotherapists will also be asked questions about their own expectations of the individual participant\'s likely clinical outcome and their beliefs about which treatment they would like the participant to receive. Participants recruited to the trial will then be randomised to one of the three trial interventions in a 1:1:1 ratio based on their unique trial number. Computerised third-party randomisation will be performed using random permuted blocks of 12 (blocked by treatment centre).
Interventions
-------------
The interventions will be delivered within 10 working days of randomisation by experienced physiotherapists, trained in acupuncture to at least the minimum standard for basic membership of the Acupuncture Association of Chartered Physiotherapists (AACP) (35 hrs of training). The participant\'s GP will be contacted at the time of randomisation and asked to avoid co-interventions for the period of the trial wherever possible, but especially until the 6-week follow up has been completed. However, if the GP feels that symptoms are sufficiently troublesome to need further treatment this will be at the GPs discretion. Information about co-interventions will be collected in the follow-up questionnaires and by review of a sample of participants\' clinical records.
### a) Advice and exercise
Advice will be supplemented by a leaflet based on the **arc**Knee OA publication. This leaflet contains standard advice on the use of analgesia. If already using non-steroidal anti-inflammatory drugs, participants will be permitted to continue their stable dose. Participants will have the opportunity to discuss elements of the advice leaflet and exercise programme with their physiotherapist. In line with current practice, a maximum of 6 × 30-minute treatment sessions will be given over a period of 6 weeks. The advice and exercise programme has been developed through the use of reviews of current best evidence \[[@B23],[@B27],[@B55]\], clinical guidelines \[[@B9]\], a survey of current physiotherapy practice for knee pain \[[@B56]\], consensus workshop, and local physiotherapy practice.
The exercise programme will include concentric, eccentric, isometric and balance exercises. Specificity of training, particularly in the first 6 weeks, is important and therapists will aim for a mix of functional exercises, open & closed kinetic chain exercises and accelerated walking elements. They will also clearly identify a home exercise programme with set targets. The intensity of the exercises will be progressively increased at each session. Previously sedentary individuals who are relatively untrained will initially be prescribed exercise of a low intensity (eg. 1--3 sets of 8--12 repetitions of an exercise, 2--3 times per week). Progression to medium and high intensity exercise will occur only once adaptation to the current level of training has occurred.
Exercises will be prescribed and individualised for each participant by the treating physiotherapist from \"Physio Tools\" <http://www.physiotools.net>, a frequently used software package in physiotherapy. Hydrotherapy, group-based work, electrotherapy, additional acupuncture outside of the protocol and intra-articular injections will not be permitted. Participants may receive advice on the use of walking aids, and hot and cold applications. The key messages within the advice to participants include the common nature of knee problems and that rest for more than a day or two usually does more harm than good.
### b) Advice and exercise plus true acupuncture
In addition to advice and exercise as detailed above, participants randomised to this group will receive 6 × 30-minute treatments of acupuncture, delivered over a period of 3 weeks. The acupuncture protocol is based on the concept of \"treatment adequacy\" which has been introduced by Ezzo et al \[[@B46]\] and Melchart et al \[[@B57]\] and has been shown recently to affect long term clinical outcome \[[@B58]\]. Physiotherapists delivering the treatment are provided with a choice of a total of 16 most commonly cited local and distal points from which they are required to chose between 6 -- 10 points for each session. Local points available include: Sp 9, Sp 10, St 34, St 35, St 36, Xiyan, Gb 34 and trigger points. Distal points available include: LI 4, TH 5, Sp 6, Liv 3, St 44, Ki 3, BI 60 and Gb 41.
Treatment will be performed with sterilised disposable steel needles, 30 × 0.3 mm. The depth of the needle insertion should be between 0.5 -- 2.5 cm depending on the points selected for treatment and the needles will be manipulated until de-qi sensation is achieved. Therapists allow 25 (min) to 35 (max) minutes between insertion of the last needle and cessation of treatment and during that time they are to revisit the needles as appropriate. If the sensation is maintained, they should manipulate each needle lightly, if the de-qi sensation is no longer there, they use stronger manipulation in order to elicit it.
Participants will be informed that they may or may not experience an aching, warm or \`tingling\' sensation from this type of stimulation. Therapists question participants at each session to ask them to describe the sensation they feel on needling, which is then recorded on a standard proforma. This also collects information on attendance, failed appointments, physiotherapist\'s diagnosis and whether any additional treatment modalities or specialist referrals are made.
### c) Advice and exercise plus placebo acupuncture
In addition to advice and exercise as detailed above, participants randomised to this group will receive sham acupuncture which involves the placement of mock needles \[[@B47]\] upon a pre-defined set of points. The mock needle is a new device, which participants find indistinguishable from true acupuncture and has been used with success in a randomised trial comparing the effects of true versus placebo acupuncture in the treatment of shoulder pain \[[@B59]\]. The mock needle operates by allowing the shaft of the needle to collapse in the handle, creating an illusion of insertion (Figure [1](#F1){ref-type="fig"} -- adapted from \[[@B47]\])
The points chosen for the sham intervention receive no stimulation and participants will be told, as for the true acupuncture group, that they may or may not experience any particular sensation from this type of stimulation. The same parameters as for true acupuncture apply: placement of a minimum of 6 needles, and 6 × 30 minutes sessions within 3 weeks, with monitoring of elicited sensations.
Audit of interventions
----------------------
Using a standard proforma, the physiotherapists record the number and duration of treatment sessions each participant receives, plus details about the advice and exercises prescribed, the location and number of acupuncture points (where applicable) and any adverse reactions. The sensation that needling (true or placebo) evokes has been shown to be a significant correlate of acupuncture-induced analgesia (this has been a finding from both clinical and experimental studies). Hence, the sensation evoked from each treatment in the acupuncture groups will also be recorded. Acceptability and credibility of the interventions will be evaluated using a telephone follow-up at 2 weeks from the beginning of treatment and a questionnaire administered at 6 weeks \[[@B60]\].
Baseline measures
-----------------
Participants who give verbal consent to participate in the trial are posted a baseline questionnaire which they are asked to complete and bring with them to the research interview and examination. Information collected on this questionnaire is detailed in Table [2](#T2){ref-type="table"}. These variables will be used to describe the study sample and as baseline measures of outcomes. Immediately following written informed consent, participants undergo a research interview and examination which follows a previously published schedule \[[@B66]\].
Follow-up
---------
Outcome measures will be performed at 2 weeks (Table [3](#T3){ref-type="table"}), 6 weeks, 6 months and 12 months (Table [4](#T4){ref-type="table"}). Follow-up assessments will be performed using a telephone call at 2 weeks after the first treatment and self-completed postal questionnaires at all other time points. Non-responders will be telephoned 2 weeks after mailing the follow-up questionnaire on up to 2 occasions and posted a replacement questionnaire with a reminder letter if there is still no response at 4 weeks.
Sample size calculation
-----------------------
The primary outcome measure for this trial is the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain sub-scale \[[@B61]\]. We have defined overall success as a 20% difference in the WOMAC pain sub-scale between true acupuncture and advice and exercise alone at 6 months. For this comparison, a minimum of 90 participants is needed in each group to reject the null hypothesis with 80% power and at a 5% significance level (two-tailed) \[[@B68]\]. As our trial will compare sham acupuncture with advice and exercise alone we have three groups and so need 270 participants. Allowing for a 30% drop out rate in those recruited to the trial, the total number of participants required to be randomised is 350.
Analysis
--------
Collection of data and statistical analysis will be performed blinded to treatment allocation. Analysis will be performed on an intention to treat basis and the primary outcome will also be analysed on a \"per protocol basis\".
Univariate analysis will be performed using t-tests to analyse numerical data and chi-square tests for categorical data. The clinical and demographic data collected at baseline will be inspected and if there are any important differences between the trial groups, these factors will be used as covariates. These analyses will be performed using ANOVA and logistic regression as appropriate.
The analysis of the secondary outcomes will be exploratory. A univariate analysis with respect to the different treatment will be performed for the WOMAC pain sub-scale at 6-weeks and 12-months and for the WOMAC functioning sub-scale at 6-weeks, 6- and 12-months. The global outcome assessment with be analysed both as an ordinal and a dichotomous variable (categories 1--3 defined as \"success\"). Moreover, area under the curve slopes will be calculated for each treatment group over the whole treatment period and compared.
Statistical significance will be set at the 5% level (two-tailed). Statistical analysis will be performed using Stata 7.0. The trial will be monitored by an independent Data Monitoring and Ethics Committee. No interim analysis of the primary or secondary outcomes will be undertaken during the trial period.
Conclusions
===========
The APEX trial is a major trial of physiotherapy treatment for knee pain. Obtaining participation by physiotherapists, across the regions of the West Midlands and Cheshire in 21 NHS Trusts, to work to agreed treatment protocols has been an important achievement. We have presented the rationale, design, and strategy for implementation of a multi-centre RCT examining whether acupuncture is a useful adjunct to usual physiotherapy care of advice and exercise for treating knee pain in older adults. The primary objective of the trial is to compare the clinical outcomes of true acupuncture plus advice and exercise, with advice and exercise alone for treating people aged 50 years and over referred directly from primary care with knee pain. The secondary objectives are to compare, at 6 weeks and 12 months, the clinical outcomes of adding true acupuncture to advice and exercise alone; to compare, at 6 weeks, 6 and 12 months, the clinical outcomes of placebo acupuncture plus advice and exercise, with advice and exercise alone; and to measure patients and therapists beliefs, preferences and expectations about the treatments being tested and to evaluate the association between these variables with clinical outcomes. The results of this trial will be presented as soon as they are available.
Competing interests (medicine)
==============================
The authors declare that they have no competing interests.
Authors\' contributions
=======================
All authors participated in the design of the trial and drafting the manuscript. All authors have read and approved the final manuscript.
Pre-publication history
=======================
The pre-publication history for this paper can be accessed here:
<http://www.biomedcentral.com/1471-2474/5/31/prepub>
Acknowledgements
================
This study is supported financially by a Project Grant awarded by the Arthritis Research Campaign, UK (grant code: H0640) and Support for Science funding secured by the North Staffordshire Primary Care Research Consortium for NHS service support costs.
The authors would like to thank Jo Bailey, Claire Calverley, Wendy Clow, Rhian Hughes, Chan Vohora, Sue Weir, Gail White, Hannah Yates, Dr Krysia Dziedzic, and Professor Peter Croft (Primary Care Sciences Research Centre), and the participating physiotherapists based within the following NHS trusts: Amber Valley PCT, East Cheshire PCT, East Staffordshire PCT, Eastern Birmingham PCT, Heart of Birmingham Teaching PCT, Mid Cheshire NHS Trust, Mid Staffordshire General NHS Trust, North Birmingham PCT, Robert Jones and Agnes Hunt Orthopaedic and District Hospital NHS Trust, Queens Hospital NHS Trust, Royal Shrewsbury Hospital NHS Trust, Shropshire Community PCT, South Birmingham PCT, South Staffordshire PCT, South Warwickshire General Hospital NHS Trust, South Warwickshire PCT, Southern Derbyshire Acute NHS Trust, The Princess Royal Hospital NHS Trust, Worcestershire Acute NHS Trust.
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
Placebo needle insertion
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
APEX Knee Study Schema
:::
:::
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Content of physiotherapist questionnaires
:::
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
**Concept** **Measurement method** **Details**
---------------------------------------------------------------------------------------------- ------------------------------------------------------------------------------------------------ -------------------------------------------------------------------------------------------------------------
*Information recorded on individual physiotherapists (collected before and after the trial)*
Physiotherapist\'s information \- year qualified\ \
- gender\ \
- current clinical practice setting\ community trust, acute trust\
- clinical grade of current post\ staff/junior, senior II, senior I, extended scope practitioner/clinical specialist, superintendent/manager\
\ full time, part time\
- current work status\ very satisfied, satisfied, neither, unsatisfied, very unsatisfied
- satisfaction with employment situation
Use of acupuncture \- currently use it\ \<1 year, 1--3 years, 3--5 years, 5+ years\
- length of time practising\ no, associate, basic, full, advanced
- use it for knee pain\
- member of AACP\
- previous training in acupuncture
Beliefs about knee pain (section B) adapted from \[53\] 13 items on 7 point Likert scale: completely disagree to completely agree
Causes of knee problems Illness Perceptions Questionnaire Revised (IPQ(R)) \[54\] 1 dimension: causes
Beliefs and expectations about treatment \- most helpful treatments for managing chronic knee pain\ OTC medication, prescribed medication, advice, exercise, acupuncture, rest\
- most effective\ advice and exercise, acupuncture, sham acupuncture\
- expected general improvement with each of the trial treatment\ 11 point numerical rating scale (NRS)\
- expect improvement in pain, movement and function with each specific trial treatment \
4 point scale: of great help, of some help, of little help, of no help
*Information recorded on individual patients (collected prior to randomisation)*
Therapists perception of patients\' knee severity 5 point Likert scale
Therapists prediction of likely outcome of patient\'s knee problem 5 point Likert scale
Therapists treatment preference for the patient advice and exercise, acupuncture, no preference
Therapists expectation of treatment benefit for patient \- expectation of degree of improvement for the patient with each of the available treatments\ 11 point NRS/ 4 point Likert scale\
- expectations for improvement in specific outcomes of pain, function, and movement 11 point NRS/ 4 point Likert scale
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
:::
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Content of baseline measures from self-completed questionnaire
:::
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
**Concept** **Measurement method** **Details**
---------------------------------------------------- ------------------------------------------------------------------------- -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Bodily pain \- self-completed manikin \"In the past 4 weeks have you had pain that has lasted for one day or longer in any part of your body?\"
Complaint specific functioning Western Ontario and McMaster Universities OA index (WOMAC LK3.0) \[61\] pain (0--20), stiffness (0--8), physical function (0--68) subscales
Participant-nominated principal functional problem \"Because of your knee, what one thing gives you the most problems?\"\
11 point NRS
Knee pain intensity and unpleasantness 11 point NRS
Illness perceptions Illness Perceptions Questionnaire Revised (IPQ(R)) \[54\] 9 dimensions: illness coherence, treatment control, personal control, timeline (acute/chronic), timeline (cyclical), consequences, emotional representation, identify, causes
Patient\'s self-efficacy Arthritis Self-Efficacy Scale \[62\] 11 items on 10 point NRS
Experiences and preferences for treatment \- previous experience with exercise\ yes, no\
- preference for trial treatments\ \
- perceived helpfulness of trial treatments\ 5 point Likert scale\
- outcome expectancy with trial treatments \
4 point Likert scale\
\
11 point NRS
Quality of life EuroQol EQ-5D \[63\] Summary score and 100 mm VAS score
Occupational characteristics \- current employment status\ working full time, working part time, working in the home, unemployed/seeking employment, not working due to ill health/disability, student, retired\
\ very satisfied, satisfied, neither, unsatisfied, very unsatisfied\
\ \
- satisfaction with employment situation\ \
- current/recent job title\ SOC 2000 \[64,65\]
- socio-economic classification\
- work loss in last 6 months due to knee problem
Demographic characteristics \- date of birth, gender\ \
- marital status single, married, widowed, divorced, cohabiting, single
Anthropometric characteristics -self-reported height\
-self-reported weight
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
:::
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Content of 2-week phone call measures
:::
---------------------------------------------------------------------------------------------------------------------------------
**Concept** **Measurement method** **Details**
------------------------------ ---------------------------------------------------------- ---------------------------------------
Treatment compliance \- number of times visited trial physiotherapist so far\ \
- extent of compliance with prescribed exercises 5 point Likert scale
Change in knee symptoms \- any change\ yes, no\
- specific change 5 point Likert scale
Knee pain intensity 11 point numerical rating scale (NRS)
Credibility of interventions \- confidence in received treatment\ 5 point Likert scale
- logic of received treatment Adapted from \[60\]
Experiences and expectations \- treatment met expectations\ 5 point Likert scale\
- expected improvement with treatment 11 point NRS
Treatment preference \- want to change treatment receiving yes, no, not sure
---------------------------------------------------------------------------------------------------------------------------------
:::
::: {#T4 .table-wrap}
Table 4
::: {.caption}
######
Content of follow-up measures from self-completed questionnaire collected at 6-weeks, 6- and 12-months
:::
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
**Concept** **Measurement method** **Details**
---------------------------------------------------- ------------------------------------------------------------------------- -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Bodily pain \- self-completed manikin \"In the past 4 weeks have you had pain that has lasted for one day or longer in any part of your body?\"
Complaint specific functioning Western Ontario and McMaster Universities OA index (WOMAC LK3.0) \[61\] pain (0--20), stiffness (0--8), physical function (0--68) subscales
Participant-nominated principal functional problem \"Because of your knee, what one thing gives you the most problems?\" 11 point NRS
Knee pain intensity and unpleasantness 11 point NRS
Bothersomeness of knee problem 5 point scale: not at all, slightly, moderately, very much, extremely
Illness perceptions Illness Perceptions Questionnaire Revised (IPQ(R)) \[54\] 9 dimensions: illness coherence, treatment control, personal control, timeline (acute/chronic), timeline (cyclical), consequences, emotional representation, identify, causes
Patient\'s self-efficacy Arthritis Self-Efficacy Scale \[62\] 11 items measuring patient\'s \"certainty\"
Global outcome \[67\] 6 point scale: completely recovered, much improved, improved, same, worse, much worse
Credibility of interventions \- confidence in received treatment\ 5 point Likert scale
- logic of received treatment Adapted from \[58\]
Side effects \- self-reported side effects nausea/vomiting, drowsiness/sleepiness, bruising, fainting, headaches, soreness to joints
Health care utilisation for knee problem \- consultations GP, district nurse, physiotherapist, hospital consultant, osteopath, chiropractor, homeopath, acupuncturist
Medication for knee problem \- prescribed/OTC medication medicine name, dose, number taken
Experiences and preferences for treatment \- previous experience with exercise\ yes, no\
- preference for trial treatments\ 5 point Likert scale\
- perceived helpfulness of trial treatments\ 4 point Likert scale\
- outcome expectancy with trial treatments \
11 point NRS
Quality of life EuroQol EQ-5D \[63\] Summary score and VAS score
Occupational characteristics \- current employment status\ working full time, working part time, working in the home, unemployed/seeking employment, not working due to ill health/disability, student, retired\
\ very satisfied, satisfied, neither, unsatisfied, very unsatisfied\
- satisfaction with employment situation\ \
- current/recent job title\ \
- socio-economic classification\ SOC 2000 \[63,64\]
- work loss since last\
questionnaire due to knee problem
Demographic characteristics \- date of birth, gender\ \
- marital status single, married, widowed, divorced, cohabiting, single
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
:::
|
PubMed Central
|
2024-06-05T03:55:48.031223
|
2004-9-2
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC520743/",
"journal": "BMC Musculoskelet Disord. 2004 Sep 2; 5:31",
"authors": [
{
"first": "Elaine",
"last": "Hay"
},
{
"first": "Panos",
"last": "Barlas"
},
{
"first": "Nadine",
"last": "Foster"
},
{
"first": "Jonathan",
"last": "Hill"
},
{
"first": "Elaine",
"last": "Thomas"
},
{
"first": "Julie",
"last": "Young"
}
]
}
|
PMC520744
|
Background
==========
Clustering is one of the most common methods for discovering hidden structure in micro-array gene expression data. Clustering of samples has been used to discover new disease taxonomies \[[@B1]-[@B3]\]. Cluster analysis is often performed with hierarchical \[[@B4]\], K-means \[[@B5]\] or Self-Organizing Map \[[@B6]\] algorithms, using the entire set of genes as the basis for calculating pair-wise distances between samples. This gives equal weights to the expression of all genes and may be effective in cases where there is a large difference between subsets of samples (*e.g.*comparing samples of normal and cancerous tissues). Many diseases, though, are characterized by small numbers of genes that differentiate between different disease states. Giving equal weight to relevant and irrelevant genes will obscure this difference. Figure [1](#F1){ref-type="fig"} shows an example, where clustering in all genes masks the biological differences between samples with BRCA1 and BRCA2 mutation (data from Hedenfalk *et al*\[[@B7]\])
In this article we propose an iterative algorithm, where we initially do a clustering using all the genes. This clustering (which gives a binary partition of the samples) is used to select genes that differentiate between the two clusters. The clustering is done again, but this time, only in the set of genes that was selected in the previous iteration. This alternation between clustering and feature selection continues until there is no change in the set of genes (and partition) between two iterations. The final gene set is removed, and the process repeated on the remaining genes to find other partitions. The algorithm generates a set of binary partitions, along with corresponding sets of genes which differentiate the clusters present in these partitions.
Similar approaches have been used in other algorithms. Ben-Dor *et al*\[[@B8]\] use simulated annealing to efficiently search the space of all binary sample partitions. Xing and Karp \[[@B9]\] use a Normalized Cut algorithm to restrict the search to only the promising partitions and use a similar method of iteration between clustering and feature selection. Von Heydebreck *et al*\[[@B10]\] and Tang *et al*\[[@B11]\] present algorithms that select sample partitions and corresponding gene sets by defining a measure of partition quality and then using greedy search (in the former) and simulated annealing (in the latter) to maximize this measure. Iteration between cluster analysis and gene selection is also used in the \"gene shaving\" algorithm of Hastie *et al*\[[@B12]\]; though their goal was clustering of genes rather than samples.
Algorithm
=========
We use a Minimal Spanning Tree (MST) based algorithm \[[@B13],[@B14]\] for clustering along with the Fukuyama-Sugeno clustering measure. Gene selection is done on the basis of the two-sample t-statistic with pooled variance. In the next three subsections we will look in detail at the clustering and feature selection aspects before presenting the formal algorithm.
Minimal spanning trees
----------------------
Let *V*= {*x*~1~, *x*~2~\..., *x*~*N*~} be a set of points with distances *d*~*ij*~= *d*(*x*~*i*~,*x*~*j*~) defined between all *x*~*i*~and *x*~*j*~. A tree on *V*is a graph with no loops whose vertices are elements of *V*and edge lengths are *d*~*ij*~. A *minimal spanning tree*(MST) is a tree that connects all points such that the sum of the length of the edges is a minimum. An MST can be efficiently computed in O(N^2^) time (including distance calculations) using either Prim\'s \[[@B13]\] or Kruskal\'s \[[@B14]\] algorithm.
Deletion of any edge from an MST results in two disconnected trees. Assuming the length of the deleted edge to be *δ*and denoting the sets of nodes in the two trees as *V*~1~and *V*~2~, we have the property that there are no pairs of points (*x*~1~,*x*~2~), *x*~1~∈ *V*~1~, *x*~2~∈ *V*~2~such that *d*(*x*~*i*~,*x*~*j*~) \<*δ*. Define the smallest distance between any two points, one in *V*~1~and the other in *V*~2~, as the *separation*between *V*~1~and *V*~2~. Then we have the result that the separation is at-least *δ*.
The significance of this result is that by deleting an edge of length *δ*we are assured of a partition where the two clusters have a separation of at-least *δ*. This means that if we are interested in looking at all binary partitions with large separations between the clusters, it is sufficient to look at partitions obtained by deleting edges of the MST. Instead of looking at all possible binary partitions (which number 2^*N*-1^-1) our algorithm looks only at partitions obtained by deleting single edges from the MST (which number *N*-1).
Minimal Spanning Trees were initially proposed for clustering by Zahn \[[@B15]\]. More recently, Xu *et al*have used MST for clustering gene expression data \[[@B16]\].
Clustering measure
------------------
To compare the partitions obtained by deleting different edges of the MST, we use the Fukuyama-Sugeno clustering measure \[[@B17]\]. Given a partition *S*~1~, *S*~2~of the sample index set *S*, with each *S*~*k*~containing *N*~*k*~samples, denote by *μ*~*k*~the mean of the samples in *S*~*k*~and *μ*the global mean of all samples. Also denote by  the *j*-th sample in cluster *S*~*k*~. Then the Fukuyama-Sugeno (F-S) clustering measure is defined as
Small values of *FS(S)*are indicative of tight clusters with a large separation between clusters.
We have considered various other clustering measures. The ideal clustering measure should show local minima at each viable partition and have good performance even with a large number of noisy features. We have found the Fukuyama-Sugeno (F-S) measure to give the best performance in these two respects (Supplementary data -- [Additional file 1](#S1){ref-type="supplementary-material"}).
Feature selection
-----------------
For a given partition with two clusters, we can ask if a particular gene shows sufficient differential expression between samples belonging to the different clusters. A gene which is very differently expressed in samples belonging to different clusters can be said to be relevant to the partition or to support the partition. There can be many ways of measuring a gene\'s support for a partition. Here we use the two sample t-statistic with pooled variance. The t-statistic is computed for each gene to compare the mean expression level in the two clusters. Genes with absolute t-statistic greater than a threshold *T*~*thresh*~are selected. The percentile threshold parameter *P*~*thresh*~*∈*(0,100) is used to compute *T*~*thresh*~. *T*~*thresh*~is the *P*~*thresh*~/2-th percentile of a random variable distributed according to Student\'s t-distribution with mean zero and *N*-2 degrees of freedom (*N*is the number of samples). Here we use the t-statistic as a heuristic measure of the contribution of each gene to the selected partition; no statistical significance is implied.
The condition for selection of a gene becomes stricter with each iteration. In the first iteration we choose genes with absolute t-statistic greater than *T*~*thresh*~/2. This cutoff increases linearly with the number of iterations until it reaches *T*~*thresh*~. This is done so that we do not lose any useful genes by putting a too-stringent selection criterion before the partition has evolved close to its final form.
The algorithm
-------------
Initially, an MST is created using all the genes; then each binary partition obtained by deleting an edge from the tree is considered as a putative partition. The partition with the minimum value of the F-S clustering measure is selected. The t-statistic is used to select a subset of genes that discriminate between the clusters in this partition. In the next iteration, clustering is done in this set of selected genes. This process continues until the selected gene subset converges (remains the same between two iterations), resulting in a set of genes and the final partition. Having identified a partition and the associated set of genes, these selected genes are removed from the pool of genes. This prevents the algorithm from detecting the same partition the next time. The whole process repeats in the pool of remaining genes to find other partitions.
The inputs to the algorithm are the gene expression matrix {*x*~*s*,*g*~}, the maximum number of partitions to be found *MaxN*~*p*~and percentile threshold *P*~*thresh*~. *P*~*thresh*~is used to compute *T*~*thresh*~. The outer loop of the algorithm runs as long as the number of discovered partitions is less than *MaxN*~*p*~. The set of selected genes *F*is initialized to be the set of all genes *Fset*and the cutoff *t*is initialized as *T*~*thresh*~/2. In the inner loop, an MST is created using the genes in *F*, and for all partitions obtained by deleting single edges from this MST, the F-S measure is calculated. For the partition *P*\* with the lowest F-S measure, genes are selected from *F*based on the t-statistic. These selected genes form the new gene set *F*~*new*~. If *F*~*new*~≠ *F*, the cutoff *t*is increased and another iteration of the inner loop is performed. If *F*~*new*~= *F*, this means that the gene set has remained unchanged between two iterations and the current partition *P*\* along with the current gene set *F*is output. The number of discovered partitions is increased and another iteration of the outer loop is performed.
Since this is an unsupervised method, the partitions picked might be indicative of biological differences that are relevant, irrelevant (like age or sex of patients) or unknown. We control the detection of chance partitions (*i.e.*generated due to noise and not due to any biological difference) by requiring a minimum of 2*M*(1 - *P*~*thresh*~/100) genes in support of a partition (*M*is the total number of genes); the algorithm is terminated if there are fewer.
*P*~*thresh*~plays an important part in the kind of partitions that are extracted. A value of *P*~*thresh*~close to 100 will preferentially extract partitions that are supported by genes with large differential expression between the two clusters. A smaller value of *P*~*thresh*~will pick up partitions that are supported by larger number of genes with lower differential expression between the clusters.
*P*~*thresh*~cannot be interpreted as a measure of the statistical significance of the partitioning since we are doing both the partitioning and the feature selection on the same set of samples. Here we only use *P*~*thresh*~as a parameter for selecting genes.
**Algorithm 1:**Algorithm for iterative clustering
**Input***MaxN*~*p*~, *P*~*thresh*~, *x*~*s*,*g*~;
*Fset*← {1, 2\..., n};
*N*~*p*~← 0; /\*Number of currently discovered partitions\*/
**Compute***T*~*thresh*~;
**While***N*~*p*~\<*MaxN*~*p*~**do**
*F*← *Fset*;
*T*← *T*~*thresh*~/2;
While 1 do
**If**length of *F*\< 2 *M*(1 - *P*~*thresh*~/100) **then**
/\*Not enough genes support partitions\*/
exit;
end
Create MST in feature set *F*with metric *d*;
Delete edges one at a time and calculate F-S measure for each ensuring binary partition;
Find partition *P*\* with the lowest F-S measure;
Compute t-statistic *t*~*g*~for all genes g ∈ F for this partition;
Set *F*~*new*~to the set of genes {g**:**\|*t*~*g*~\| \>*t*};
**If***F*~*new*~= *F***AND***t*= *T*~*thresh*~**then**
/\*Feature set has converged \*/
output *P*\* and *F*;
/\*Remove genes in *F*from *Fset\**/
*Fset*← *Fset*\\ *F*;
*N*~*p*~= *N*~*p*~+ 1;
break;
else
*F*← *F*~*new*~;
Increase *t*;
end
end
Results
=======
Synthetic data
--------------
We first tested the algorithm on synthetic data to compare its performance against a hierarchical clustering method at detecting planted partitions. We also estimated the probability of detection of spurious partitions created by noise (*i.e.*the false detection rate).
For both iterative clustering and hierarchical clustering, we found that the probability of detecting the true partition depended only on the Euclidean distance between the clusters in the partition, and for a fixed distance, is relatively insensitive to the number of signal genes (Supplementary data -- [Additional file 2](#S2){ref-type="supplementary-material"}).
Figure [2](#F2){ref-type="fig"} shows the results of a logistic regression analysis of the dependence of probability of detection of the true partition on the distance between the clusters for both clustering methods. Independent of the total number of genes *N*, iterative clustering detects the planted partition when the two clusters are separated by about half the distance compared to hierarchical clustering. For genes with similar levels of differential expression, this means that the iterative clustering method will detect clusters supported by a quarter of the number of genes required for detection by hierarchical clustering.
The false detection rate was found to be very low: 0.012 for the correlation and 0.011 for the Euclidean distance.
Microarray data
---------------
To test whether classes with strong biological significance can be discovered without knowledge of the class labels, we tested the algorithm on three publicly available sets of micro-array data.
1\. BRCA mutation data reported by Hedenfalk *et al*\[[@B7]\] with 6512 cDNA clones of 5361 genes for 7 samples with BRCA1 mutation, 8 samples with BRCA2 mutation and 7 with sporadic breast cancer.
2\. Leukemia data-set reported by Golub et al. \[[@B6]\]. Expressions for 7070 genes are provided for 47 acute lymphoblastic leukemia (ALL) samples and 25 acute myeloid leukemia (AML) samples.
3\. Lymphoma data-set reported by Alizadeh et al. \[[@B1]\] containing 46 samples of tissues with diffuse large B-cell lymphoma (DLBCL). Expressions for 4026 genes were measured for each of these samples.
It must be noted that if class labels are already available and the goal is to discover genes that differentiate between samples of different classes, then class comparison and class prediction methods exist that are more suitable \[[@B21]\]. Such methods make use of the prior information (in the form of class labels) to detect genes that are significantly differentially expressed between the various classes. The expression of these genes can be used to develop classifiers that predict the class of new samples.
Our iterative method is for cases where no a-priori class labels are assigned. Nevertheless, we have used data for which class labels are known so that there is a ground truth to which the results of the iterative method can be compared. This is similar to what has been done by other authors for validating the results of unsupervised clustering algorithms \[[@B8]-[@B11]\].
A-priori gene filtering and normalization performed were similar to that done for the dataset by the original authors. The iterative algorithm was then run with maximum number of partitions *N*~*p*~= 10 and *P*~*thresh*~= 0.999.
Table [1](#T1){ref-type="table"} shows the distribution of BRCA1 and BRCA2 samples present in the two clusters for the first four partitions discovered in the BRCA dataset. The fourth partition obtained from the BRCA data separates samples with BRCA1 and BRCA2 mutations with one misclassification. Figure [1](#F1){ref-type="fig"} shows the result of hierarchical clustering on the BRCA data-set. The tree structured clustering using all the genes fails to differentiate between samples with BRCA1 and BRCA2 mutations. Figure [3](#F3){ref-type="fig"} shows hierarchical clustering using only the genes selected by the iterative clustering method (61 genes). BRCA1 and BRCA2 samples are separated into different branches of the tree with only one misclassification.
With the Leukemia data-set, the first partition obtained matches well with ALL-AML classification, with one cluster containing 46 ALL samples (out of 47 total) and 1 AML sample while the second cluster contains 24 AML samples (out of 25 total) and 1 ALL sample (Table [2](#T2){ref-type="table"}).
To see whether the gene set obtained in support of the partition correlating with the AML/ALL classification truly separates ALL and AML samples, we used a split-sample method. The iterative algorithm was used on part of the dataset (38 samples, corresponding to the \"training set\" used in \[[@B6]\]) and several partitions were obtained. We did not obtain exactly the same partitions as when the whole dataset was used, but the second partition corresponded well to the ALL/AML classification. It contained one cluster with 25 ALL and no AML samples and another cluster with 11 AML and 2 ALL samples. There were 252 genes that were selected in support for this partition.
If the 252 selected genes were truly discriminatory between the ALL and AML samples, then we should be able to separate the two classes in unknown data by unsupervised clustering using these genes. This was verified by clustering the rest of the samples in the dataset (containing 34 samples corresponding to the \"testing set\" used in \[[@B6]\]) using these genes. Since the iterative algorithm uses a combination of MST and F-S measure to do clustering, we performed the validation using a similar clustering method. An MST was created using the 252 genes and then the edge to be deleted selected according to minimum F-S measure. This identical to the clustering method used in the inner loop of the iterative clustering algorithm (Algorithm 1).
We obtained two clusters with the first cluster containing 20 ALL and 1 AML samples while the second cluster contained 13 AML and no ALL samples. This almost-complete separation of ALL and AML in the testing data shows that the genes selected by the iterative clustering are truly supportive of the partition discovered in the training data.
The biological differences present in the Lymphoma data-set were originally detected using hierarchical clustering \[[@B1]\] after manual selection of genes. We have included our results using the iterative method to show how successful the iterative clustering algorithm is in picking out these disease subclasses (Table [3](#T3){ref-type="table"}). The third partition best corresponds to the subclasses discovered by Alizadeh et al. One cluster has 24 GC B-like DLBCL samples and 7 Activated B-like DLBCL samples while the other cluster has 16 Activated B-like DLBCL samples.
The results from the iterative clustering algorithm is compared to that obtained by Overabundance Analysis (OA) \[[@B8]\] (Table [4](#T4){ref-type="table"}) and CLIFF \[[@B9]\] (Table [5](#T5){ref-type="table"}). Ben-Dor *et al*use the *Jaccard index*\[[@B20]\] to measure the similarity of the partitions discovered by OA to the true biological classes. For comparison, we calculated the same index for partitions discovered by iterative clustering. The Jaccard index ranges from 0 for complete mismatch to 1 for complete match.
Both OA and iterative clustering pick out partitions corresponding to the ALL/AML classification, though OA detects it as the fourth partition while iterative clustering detects it as the first partition. There is a small but definite improvement in the Jaccard index for the results obtained for the Lymphoma data by iterative clustering as compared to OA.
Compared to CLIFF, iterative clustering picks a partition in the Leukemia data that is marginally better (2 misclassified as compared to 3 for CLIFF).
Discussion
==========
We have presented a clustering method that uses a minimal spanning tree to lead the search for partitions of samples that form good clusters. Iteration between minimal spanning tree cluster analysis and feature selection is used to converge onto partitions that form well separated clusters and gene subsets that support these partitions.
At the convergence of each set of iterations, the result is a partition of the samples and a set of genes that support them. These genes are removed from the pool of genes before searching for other partitions. This removes genes that obscure other partitions supported by smaller numbers of less differentially expressed genes. Genes that support more than one partition will be selected in favor of the partition for which their support is stronger.
Testing on synthetic data shows that the algorithm picks out planted clusters with high accuracy and low false positive rate. Application of the algorithm to breast cancer, leukemia and lymphoma data returns partitions with very well separated clusters, some of which have a strong biological significance. The results are comparable to those obtained by other similar algorithms, and superior to those obtained by standard hierarchical clustering.
The kind of partitions discovered depends very much on the value of *P*~*thresh*~. Values of *P*~*thresh*~close to 100 will give preference to partitions that are supported by a small number of very highly differentially expressed genes. On the other hand, smaller values of *P*~*thresh*~will preferentially detect partitions that are supported by a large number of genes differentially expressed to a lesser degree. If the first application of the algorithm returns several partitions that are correlated with each other, then we could suspect that there is one partition that is supported by a large number of genes and run the algorithm again with a smaller value of *P*~*thresh*~to detect all these genes. We have not been able to specify a single value of *P*~*thresh*~that works in all cases, although the range of values we used (*P*~*thresh*~= 99.9-99.95) works well in most situations.
The partitions and supporting gene sets detected by the use of this algorithm must be further analyzed using gene annotation and clinical data to determine whether they are biologically relevant and worth further investigation. The significance of the detected partitions must be further investigated by evaluating the clinical correlates of patients in different clusters. Clinical observations made on patients, like survival duration, response to therapy and grade of tumor can be compared among the clusters obtained to see if there are any detected partitions whose clusters are correlated with clinical features.
Another, complementary, approach is to analyze the genes that are differentially expressed between two clusters for regulatory relationships with each other or prior known influence on the disease in question. Software tools for searching gene annotations \[[@B18]\], and exploring PubMed and GeneCards for prior published relationships among given genes \[[@B19]\] are available.
The results of these two approaches can help the biologist to formulate hypotheses about the significance of the partitions as well as the role of the selected genes in influencing the course of the disease. Examples of this process can be seen in \[[@B1]\] and \[[@B2]\].
Methods
=======
Synthetic data were created by generating normally distributed expression profiles for each gene. Each planted partition is supported by a fraction of the genes (called signal genes) which were differentially expressed between the two clusters. Each signal gene is differentially expressed to the same extent. The expressions were normally distributed; *x*~*s*,*g*\~~*N*(0,0.5^2^) for samples s belonging to cluster 1 and *x*~*s*,*g*\~~*N*(*c*,0.5^2^) for samples belonging to cluster 2. The rest of the genes are not differentially expressed and are called noise genes and are distributed according to a normal distribution *N*(0,0.5^2^). If we have *k*signal genes, each differentially expressed by *c*between the two clusters, the Euclidean distance between the cluster-means will be .
Sets of synthetic data were generated for number of genes *M*= 1000 and *M*= 10000 with varying fraction of signal genes *ε*and distance between cluster means *D*~*c*~. Each set of data was analyzed both by the iterative and the hierarchical clustering method (using average linkage). The iterative clustering method was used to obtain the first partition discovered using the Euclidean distance (*P*~*thresh*~= 99.95). Hierarchical clustering was used to obtain a tree, and the branch at the highest level was split to produce a partition.
The match of these two partitions with the true partition was calculated and the detection accuracy was assigned 1 if the match was greater than 75% and 0 otherwise. A logistic regression analysis was used to model the dependence of the probability of detection on the distance between the clusters *D*~*c*~.
To estimate the false detection rate, the algorithm was run on synthetic data containing 10 -- 100 samples with *P*~*thresh*~= 99.9. Each sample is a 1000-dimensional vector drawn from a multivariate normal distribution. Thus any clusters detected can be expected to be spurious clusters formed by chance.
For the micro-array data, the iterative method was used to detect the first 10 partitions, (*P*~*thresh*~= 99.9) using (1-correlation coefficient) as the distance measure for the MST. For the BRCA data, we also clustered the data using standard hierarchical clustering using centered correlation as the distance metric \[[@B4]\] to compare the results of our algorithm with that obtained by clustering with respect to all genes.
Supplementary Material
======================
::: {.caption}
###### Additional File 1
**Comparison of clustering measures**Synthetic data was created with 100 samples and 1000 genes containing clusters embedded in the first 50 genes. The other 950 genes were normally distributed noise. There are three clusters in the first 50 genes: Samples 1 through 20, samples 21 through 70 and samples 71 through 100. For each binary partition of the points *S*~1~= {1, 2\..., i}, *S*~2~= {i+1, i+2\..., 100}, we calculated the clustering measure. The figure shows the value of the measure for each split point. It can be seen that the Average Linkage and Xie-Beni \[22\] measures have weak minima and they suffer from extreme values for unbalanced splits. The Log-Likelihood measure has performance similar to the F-S measure but has extreme values for unbalanced splits.
:::
::: {.caption}
######
Click here for file
:::
::: {.caption}
###### Additional File 2
**Detection of true partition for different data parameters**Sets of synthetic data were generated for 1000 and 10000 total number of genes with varying fraction of signal genes *ε*and distance between cluster means *D*~*c*~. The figure shows detection of planted partition for various values of *ε*and *D*~*c*~. Blue points are data for which the percentage match between the first discovered partition and the planted partition is less than 75%. The red points are data for which the match is greater than 75%. Detection (match \> 75%) depends only on the distance between the clusters for both hierarchical and iterative clustering.
:::
::: {.caption}
######
Click here for file
:::
Acknowledgements
================
We are grateful to the anonymous reviewers for suggesting several improvements in the statistical analysis, discussion and presentation of figures, which we have incorporated in the article.
Figures and Tables
==================
::: {#F1 .fig}
Figure 1
::: {.caption}
######
**Hierarchical clustering of BRCA data using all genes.**Hierarchical clustering of BRCA data using centered correlation with average linkage. Inclusion of all genes in the clustering swamps out the differences between samples with BRCA1 and BRCA2 mutation.
:::
:::
::: {#F2 .fig}
Figure 2
::: {.caption}
######
**Detection probability vs. cluster separation.**Probability of detection of the planted partition as a function of the distance between the clusters in the partition.
:::
:::
::: {#F3 .fig}
Figure 3
::: {.caption}
######
**Hierarchical clustering of BRCA data using selected genes.**Hierarchical clustering of BRCA data using only the genes supporting Partition 4. BRCA1 and BRCA2 are separated with one misclassification.
:::
:::
::: {#T1 .table-wrap}
Table 1
::: {.caption}
######
Results on BRCA data-set
:::
**Partition number** **Cluster number** **BRCA1** **BRCA2** **Number of genes selected**
---------------------- -------------------- ----------- ----------- ------------------------------
**1** 1 0 4 80
2 7 4
**2** 1 7 4 110
2 0 4
**3** 1 5 3 73
2 2 5
**4** 1 6 0 61
2 1 8
:::
::: {#T2 .table-wrap}
Table 2
::: {.caption}
######
Results on Leukemia data-set
:::
**Partition number** **Cluster number** **AML** **ALL** **Number of genes selected**
---------------------- -------------------- --------- --------- ------------------------------
**1** 1 1 46 578
2 24 1
**2** 1 4 29 650
2 21 18
**3** 1 25 38 108
2 0 9
**4** 1 20 27 81
2 5 20
:::
::: {#T3 .table-wrap}
Table 3
::: {.caption}
######
Results on Lymphoma data-set
:::
**Partition number** **Cluster number** **GC B-like DLBCL** **Activated B-like DLBCL** **Number of genes selected**
---------------------- -------------------- --------------------- ---------------------------- ------------------------------
**1** 1 20 22 121
2 4 1
**2** 1 3 4 226
2 21 19
**3** 1 24 7 156
2 0 16
**4** 1 15 12 309
2 9 11
:::
::: {#T4 .table-wrap}
Table 4
::: {.caption}
######
Comparison of results with that obtained using Overabundance Analysis (Ben-Dor et al \[8\])
:::
**Data-set** Jaccard index of first 4 partitions discovered by iterative clustering Jaccard index of first 4 partitions discovered by Overabundance Analysis
-------------------- ------------------------------------------------------------------------ --------------------------------------------------------------------------
**Leukemia** 0.906 0.469
0.424 0.344
0.454 0.469
0.378 0.949
**Lymphoma DLBCL** 0.452 0.362
0.429 0.324
0.611 0.354
0.343 0.350
:::
::: {#T5 .table-wrap}
Table 5
::: {.caption}
######
Comparison of results with that obtained using CLIFF (Xing and Karp \[9\])
:::
**Cluster number** **AML** **ALL**
-------------------------- -------------------- --------- ---------
**Iterative clustering** 1 1 46
2 24 1
**CLIFF** 1 0 44
2 25 3
:::
|
PubMed Central
|
2024-06-05T03:55:48.035334
|
2004-9-8
|
{
"license": "Creative Commons - Attribution - https://creativecommons.org/licenses/by/4.0/",
"url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC520744/",
"journal": "BMC Bioinformatics. 2004 Sep 8; 5:126",
"authors": [
{
"first": "Sudhir",
"last": "Varma"
},
{
"first": "Richard",
"last": "Simon"
}
]
}
|
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