Cell-wide responses to low-oxygen exposure in Desulfovibrio vulgaris Hildenborough - PubMed (original) (raw)
. 2007 Aug;189(16):5996-6010.
doi: 10.1128/JB.00368-07. Epub 2007 Jun 1.
Alyssa M Redding, Marcin P Joachimiak, Adam P Arkin, Sharon E Borglin, Paramvir S Dehal, Romy Chakraborty, Jil T Geller, Terry C Hazen, Qiang He, Dominique C Joyner, Vincent J J Martin, Judy D Wall, Zamin Koo Yang, Jizhong Zhou, Jay D Keasling
Affiliations
- PMID: 17545284
- PMCID: PMC1952033
- DOI: 10.1128/JB.00368-07
Cell-wide responses to low-oxygen exposure in Desulfovibrio vulgaris Hildenborough
Aindrila Mukhopadhyay et al. J Bacteriol. 2007 Aug.
Abstract
The responses of the anaerobic, sulfate-reducing organism Desulfovibrio vulgaris Hildenborough to low-oxygen exposure (0.1% O(2)) were monitored via transcriptomics and proteomics. Exposure to 0.1% O(2) caused a decrease in the growth rate without affecting viability. Concerted upregulation of the predicted peroxide stress response regulon (PerR) genes was observed in response to the 0.1% O(2) exposure. Several of the candidates also showed increases in protein abundance. Among the remaining small number of transcript changes was the upregulation of the predicted transmembrane tetraheme cytochrome c(3) complex. Other known oxidative stress response candidates remained unchanged during the low-O(2) exposure. To fully understand the results of the 0.1% O(2) exposure, transcriptomics and proteomics data were collected for exposure to air using a similar experimental protocol. In contrast to the 0.1% O(2) exposure, air exposure was detrimental to both the growth rate and viability and caused dramatic changes at both the transcriptome and proteome levels. Interestingly, the transcripts of the predicted PerR regulon genes were downregulated during air exposure. Our results highlight the differences in the cell-wide responses to low and high O(2) levels in D. vulgaris and suggest that while exposure to air is highly detrimental to D. vulgaris, this bacterium can successfully cope with periodic exposure to low O(2) levels in its environment.
Figures
FIG. 1.
Overview of selected O2-responsive proteins in D. vulgaris. (A) Localization and mechanistic roles of individual proteins in O2 reduction in the gram-negative D. vulgaris cell. While all candidates are represented in the transcriptome data, those for which proteomics data were available are shaded. Also shown is the Fenton's reaction between Fe2+ and H2O2, which generates harmful hydroxyl radicals. (B) Predicted PerR regulon (candidates with potential PerR binding motifs) and other selected candidates. The underlined genes are reported to encode NADH peroxidases. DVU numbers are shown in parentheses.
FIG. 2.
Protein distribution in COGs. Proteins identified in the proteomics data cover all major COG categories (except categories B and V, which have 1 and 32 proteins, respectively). In each COG category, the fractions of protein that showed increases and decreases in the air stress experiment are indicated. The COG categories are sorted in order of decreasing fraction identified (gray bars). Notably, the largest fraction of changes was observed in COG category S (function unknown). COG categories R, L, U, and T appear to be underrepresented. Category U contains many membrane proteins, which are often not present in high abundance. The low abundance of signaling proteins may also be the reason for disproportionately low fraction of proteins in COG category T. Category X represents all proteins with no assigned COG and is the largest fraction of the total proteome, containing 1,066 proteins.
FIG. 3.
Effect of O2 exposure on growth of D. vulgaris. Growth of D. vulgaris was measured by counting the number of cells per milliliter (acridine orange direct counting). Each value is an average for three technical replicates. (A) D. vulgaris cell counts after sparging (200 ml/min) with 0.05% O2 in N2 (▵), 0.1% O2 in N2 (▪), or N2 (□) measured over 60 h. Over the 72-h period, D. vulgaris showed similar growth profiles in 0.5% O2 and N2 (control), while in 0.1% O2 much lower maximal growth was observed. (B) D. vulgaris cell counts after sparging (200 ml/min) with N2 (open bars) or 0.1% O2 (filled bars) at 0 and 240 min. In order to assess the cell-wide changes initiated in response to the 0.1% O2 exposure, biomass for transcript and protein analysis was collected at 240 min after initiation of exposure, prior to entry into stationary phase. Note that the effect of 0.1% O2 sparging is evident only at later time points.
FIG. 4.
Genes whose expression changed most significantly in response to 0.1% O2 exposure (cutoff threshold, log2 R ≥ 2; corresponding z-score, ≥2). The heat map shows changes in mRNA levels over time (in minutes) in response to either 0.1% O2 or air stress. The range of changes observed for the two experiments is shown in the key below the heat map, in which the values are log2 R values. Asterisks indicate predicted PerR regulon genes.
FIG. 5.
Transcriptomic responses of selected genes in 0.1% O2- and air-exposed cultures. The heat map shows changes in mRNA levels over time (in minutes) in response to either 0.1% O2 or air stress. Candidates are grouped by function or gene identification numbers, and groups are not from automated clustering. The range of changes observed for the two experiments is shown in the key to the right of the heat map. The candidates included are genes considered important in redox changes and genes for central pathways, such as electron transport, ATP synthesis, carbon uptake, and metabolism.
FIG. 6.
Transcriptomic responses of signature SRB genes during 0.1% O2 and air exposure. The heat map shows changes in mRNA levels over time (in minutes) in response to either 0.1% O2 or air stress. Signature genes described by Chhabra et al. (5) were used. Genes are categorized by function. The range of changes observed for the two experiments is shown in the key to the right of the heat map.
FIG. 7.
Comparison between proteomics and microarray data for selected candidates: graphical representation of data presented in Table 1. The open symbols represent 0.1% O2 exposure, whereas the filled symbols represent air exposure. Circle 1 highlights all of the candidates belonging to the low-oxygen-exposure group. The most significant changes occurred in oxidative stress genes and in ZraP. Air exposure caused a much larger level of change. Circle 2 highlights the large increases observed in proteases and chaperones during air exposure. Circle 3 highlights the group of periplasmic binding ABC transport proteins that show opposite trends, namely, increased protein levels but decreased transcript levels. More candidates show this trend, compared to the few candidates that show increased transcript levels but decreased protein levels (top left quadrant).
FIG. 8.
iTRAQ proteomics for exposure to 0.1% O2 and air. (A) The 0.1% O2-exposed sample was labeled with both tag116 (replicate 1) and tag117 (replicate 2), allowing assessment of the internal error. (B) Log2 (0.1% O2/_T_0) compared to log2 (N2/_T_0). Proteins whose z-score was ≥ 2 were considered significant, and these candidates are highlighted, as indicated in the key. (C) Log2 (air/N2) at 120 min compared to the log2 (air/N2) at 240 min. Proteins that have the samelevel of change at both time points would fall on the 45° line. The clustering of data around the 45° line demonstrated that there was a trend in changes observed between 120 min and 240 min. Selected proteins are color coded as indicated in the key.
FIG. 9.
Analysis of microarray data to extract genes that show changes correlated with changes in the predicted PerR regulon. (A) Heat map showing changes in mRNA levels for the predicted members of the PerR regulon with 0.1% O2 and air exposure. The average trend for each time point for all the members is shown in the bottom panel. The average values from panel A were used to search the entire data set. A Pearson correlation similarity measure showed 58 genes with a trend better than or equal to that of the worst-fitting member of the PerR regulon (see Fig. S4 in the supplemental material). (B) Heat map for mRNA changes for the 58 genes. The color key indicates the predicted functional categories of these genes. For complete details of this list and the Pearson correlation function used, see Table S1 in the supplemental material.
FIG. 10.
Microarray data for air stress. (A) Comparison of mRNA data for exposure to 0.1% O2 and for exposure to air shows no linear relationship (Pearson correlation coefficient, 0.03; P = 0.01805). (B) Comparison mRNA data of two biological replicates exposed to air at 240 min. Although exposure to air created a heterogeneous population, the responses of two different biological replicates correlate strongly (Pearson correlation coefficient, 0.69; P < 0.000005). The data for the second biological replicate are data from an independent experiment. (C) Heat shock (50°C, 120 min) data from the study of Chhabra et al. (5) compared with the 120-min air exposure data. Direct comparisons of these data were possible because both experiments used the same microarray design, the biomass samples came from the same pipeline, and the microarray experiments used genomic DNA as a control. A stronger linear relationship exists between the overall trends observed for heat shock versus air exposure (Pearson correlation coefficient, 0.45; P < 0.000005). All P values are based on the one-tailed t-statistic.
References
- Baughn, A. D., and M. H. Malamy. 2004. The strict anaerobe Bacteroides fragilis grows in and benefits from nanomolar concentrations of oxygen. Nature 427**:**441-444. -PubMed
- Brenot, A., K. Y. King, and M. G. Caparon. 2005. The PerR regulon in peroxide resistance and virulence of Streptococcus pyogenes. Mol. Microbiol. 55**:**221-234. -PubMed
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