![]() | ![]() |
Formats:
|
||||||||||||||||||||||||||
Copyright © 2007, American Society for Microbiology Cell-Wide Responses to Low-Oxygen Exposure in Desulfovibrio vulgaris Hildenborough †Virtual Institute of Microbial Stress and Survival,1 Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, California,2 Department of Chemical Engineering, University of California, Berkeley, California,3 Department of Bioengineering, University of California, Berkeley, California,4 Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California,5 Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee,6 Biochemistry and Molecular Microbiology & Immunology Departments, University of Missouri, Columbia, Missouri,7 Institute for Environmental Genomics and Department of Botany and Microbiology, Oklahoma University, Norman, Oklahoma8 *Corresponding author. Mailing address: Berkeley Center for Synthetic Biology, 717 Potter Street, Berkeley, CA 94720. Phone: (510) 495-2620. Fax: (510) 495-2630. E-mail: keasling/at/berkeley.edu ‡A.M.R. and M.P.J. contributed equally to this study. §Present address: Department of Civil and Environmental Engineering, Temple University, Philadelphia, PA 19122. ¶Present address: Biology Department, Centre for Structural and Functional Genomics, Concordia University, 7141 Sherbrooke West, Montreal, Quebec, Canada H4B 1R6. Received March 12, 2007; Accepted May 20, 2007. This article has been cited by other articles in PMC.Abstract The responses of the anaerobic, sulfate-reducing organism Desulfovibrio vulgaris Hildenborough to low-oxygen exposure (0.1% O2) were monitored via transcriptomics and proteomics. Exposure to 0.1% O2 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% O2 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 c3 complex. Other known oxidative stress response candidates remained unchanged during the low-O2 exposure. To fully understand the results of the 0.1% O2 exposure, transcriptomics and proteomics data were collected for exposure to air using a similar experimental protocol. In contrast to the 0.1% O2 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 O2 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 O2 levels in its environment. Sulfate-reducing bacteria (SRB) like Desulfovibrio spp. are truly cosmopolitan organisms that flourish in deep subsurface sediments, rice paddies, lake and ocean sediments, insect and animal guts, sewers, and oil pipelines (8, 27, 40, 41, 51). Although considered obligate anaerobes for many years after their discovery, Desulfovibrio spp. are found in many environments that are regularly or periodically exposed to oxygen (8, 20, 35). A number of Desulfovibrio spp. have been documented to reduce millimolar levels of O2 (12), and in an O2 gradient Desulfovibrio vulgaris Hildenborough localizes to very low O2 concentrations rather than the anoxic region (30). However, D. vulgaris does not couple growth to O2 respiration (8, 12), and even small amounts of O2 affect growth adversely (57). Although D. vulgaris has been shown to survive long periods of air exposure (8, 9), it grows optimally in an anaerobic environment (46). Several studies have focused on discovering the D. vulgaris genes involved in its oxidative stress response (7, 36), and a basic model for O2 stress response in D. vulgaris has been proposed and reviewed (7, 37). D. vulgaris has two major mechanisms for superoxide removal, namely, the superoxide reductase (Sor) and the superoxide dismutase (Sod). The gene encoding Sor, also called desulfoferrodoxin or rubredoxin oxidoreductase (rbo), occurs as part of an operon that also encodes a rubredoxin (rub) and the rubredoxin oxygen oxidoreductase (roo). The Sor reportedly works in conjunction with peroxidases (e.g., AhpC and rubrerythrins [18, 37]) and electron transfer proteins such as rubredoxins (7) to convert superoxides to water. For reactive oxygen species (ROS) removal, the Sor mechanism is considered to be the preferred pathway as it does not regenerate any intracellular O2 (14, 26, 28, 42). The D. vulgaris genome includes multiple genes, such as genes encoding rubrerythrins, rubredoxins, and a nigerytherin, that are anticipated to be involved in peroxide reduction (Fig. (Fig.1).1
Despite these protective mechanisms, ROS, such as superoxides and peroxides, are still produced during O2 reduction and trigger a variety of cellular damage in both aerobic and anaerobic organisms (37, 45, 53). While it is the ROS that cause the majority of O2-related damage, O2 itself also irreversibly deactivates critical periplasmic proteins, such as reduced Fe hydrogenases (54). Oxidative stress due to O2 exposure is known to have multiple effects on cellular physiology, and exposure to O2 at both high and low levels can be expected to elicit cellular responses, especially for anaerobic organisms. Our current knowledge of the oxidative stress response mechanisms in D. vulgaris is derived mainly from studies conducted using exposure to air or 100% O2 (13, 16-18, 59). A survey of these studies also revealed that differences in experimental protocols led to important differences in cellular responses. For example, a study of oxygen-responsive genes in D. vulgaris (18) reported a loss of viability in response to air exposure, yet a similar microarray study of air exposure (59) observed no such loss. Further, the modulation of the multiple protective mechanisms in response to low-O2 exposure was not explored. The specificity of many of these mechanisms in O2 exposure also remains undefined, as many of the candidate proteins are intimately linked with the redox status of the cell and may have redundant functions. We hypothesized that a cell-wide study of D. vulgaris in a low-oxygen environment might uncover new information about these mechanisms. Consistent with this, a recent study showed a roo mutant to be sensitive to 0.2% O2 exposure (57). Cell-wide data from an air stress response study may provide the perspective required to determine the specificity of responses to low-O2 exposure. In order to minimize the variability resulting from experimental setup and to place our data in the context of previous studies, we conducted controlled experiments to measure D. vulgaris responses to both low oxygen levels and air. MATERIALS AND METHODS Bacterial growth and maintenance. Bacterial strains were grown and maintained as described previously (39). In brief, D. vulgaris Hildenborough (ATCC 29579) was grown in a defined lactate (60 mM)-sulfate (50 mM) medium, LS4D medium (39). To minimize subculturing during experimentation, D. vulgaris stocks stored at −80°C were used as 10% (vol/vol) inocula in 100 to 200 ml of fresh LS4D medium and the cells were grown to mid-log phase (optical density at 600 nm [OD600], 0.3 to 0.4). For every transcriptome and proteome experiment, fresh starter cultures at mid-log phase were used as 10% (vol/vol) inocula in 1- to 3-liter biomass production cultures and grown at 30°C, as noted previously (39). Cell counts and growth assays during air and 0.1% O2 exposure. One liter of a D. vulgaris culture in LS4D medium at mid-log phase (OD600, 0.35) was sparged with either humidified sterile N2, 0.1% O2 in N2, or air (21% O2). The sparge bottles were constructed from 2-liter medium bottles with three-valve standard high-performance liquid chromatography delivery caps (ULTRA-WARE; Kimble/Kontes). One valve was used to allow gas to enter, another was used for sampling, and the third was used for gas venting. Gas was sparged through porous Teflon tubing (International Polymer Engineering, Tempe AZ) filled with glass microbeads to keep the tubing submerged in the culture. Samples were taken at 0, 60, 120, and 240 min following exposure. For measuring growth, cells were counted using the acridine orange direct count method (31). For measuring viability, CFU were determined. For these tests aliquots were taken at the time points mentioned above and diluted serially in anaerobic LS4D medium to obtain 102 and 104 dilutions. A 200-μl sample of each dilution was suspended in molten LS4D medium containing 0.8% (wt/vol) agar before it was spread on LS4D medium plates containing 1.5% (wt/vol) agar and grown anaerobically; colonies were counted after 7 days. Biomass production for integrated “omics” experiments. Biomass for microarray analysis and proteomics experiments was generated as described previously (39). All production cultures were grown in triplicate. At an OD600 of 0.3 (initial time point [T0]), triplicate samples were collected (300 ml each for microarrays and 50 ml each for proteomics). Once T0 sampling was completed, the stress was applied by sparging humidified sterile air, 0.1% O2 in N2, air, or N2 (control) at a rate of approximately 200 ml/min through the 2-liter cultures. Prior to T0, the doubling time for D. vulgaris was measured to be approximately 5 h. Samples were collected at 30, 60, 120, and 240 min after sparging was initiated. Processing and chilling times were minimized by pumping samples through a metal coil immersed in an ice bath as described previously (39). The chilled samples were harvested via centrifugation, flash frozen in liquid nitrogen, and stored at −80°C until analysis. Consistent with previous studies (18), pH measurements during sparging indicated that all treatments (N2, 0.1% O2, or air) resulted in a small pH (<0.8-U) increase that may have been caused by H2S and CO2 loss during sparging. After 4 h, the pH of each culture was between 7.8 and 8.0. Using the previously reported specific oxygen-reducing potential of wild-type D. vulgaris (57), it could be estimated that the maximum oxygen-reducing potential of the culture was approximately 5.4 μmol O2/min. At a sparging rate of 200 ml/min, 7.8 μmol O2/min was estimated to be added to the culture (see Calculation S1 in the supplemental material) (http://vimss.lbl.gov/Oxygen/). Measurements with a Foxy Fospor-R oxygen sensor (Ocean Optics, Florida) indicated that continuous sparging with 0.1% O2 increased the levels of dissolved O2 in the blank media. The higher levels of O2 (relative to the levels with pure N2 sparging) were detectable in a live D. vulgaris culture while it was being sparged and ensured that there was constant exposure to O2 during the 0.1% O2 treatment (see Fig. S2 in the supplemental material; the supplemental material is also available at http://vimss.lbl.gov/Oxygen/). Microarray transcriptomic experiments and data analysis. DNA microarrays using 70-mer oligonucleotide probes covering 3,482 of the 3,531 annotated protein-encoding sequences of the D. vulgaris genome were constructed as previously described (33). Briefly, all oligonucleotides were commercially synthesized without modification by MWG Biotech Inc. (High Point, NC), prepared in 50% (vol/vol) dimethyl sulfoxide (Sigma-Aldrich, St Louis, MO), and spotted onto UltraGAPS glass slides (Corning Life Sciences, Corning, NY) using a BioRobotics Microgrid II microarrayer (Genomic Solutions, Ann Arbor, MI). Each oligonucleotide probe had two replicates on a single slide. Probes were fixed onto the slides by UV cross-linking (600 mJ) according to manufacturer's protocol. Total RNA extraction, purification, and labeling were performed independently for each cell sample using previously described protocols (5). Each replicate sample consisted of cells from 300-ml cultures. Labeling of cDNA targets from purified total RNA was carried out using the reverse transcriptase reaction with random hexamer priming and the fluorophore Cy5-dUTP (Amersham Biosciences, Piscataway, NJ). Genomic DNA was extracted from D. vulgaris cultures at stationary phase and labeled with the fluorophore Cy3-dUTP (Amersham Biosciences, Piscataway, NJ). To hybridize a single glass slide, the Cy5-dUTP-labeled cDNA probes obtained from stressed or unstressed cultures were mixed in equal amounts with the Cy3-dUTP-labeled genomic DNA. After washing and drying, the microarray slides were scanned using the ScanArray Express microarray analysis system (Perkin Elmer). The fluorescence intensity of both the Cy5 and Cy3 fluorophores was analyzed with the ImaGene software, version 6.0 (Biodiscovery, Marina Del Rey, CA). Microarray data analyses were performed using gene models from NCBI. All mRNA changes were assessed with total genomic DNA as a control. Log2 ratios and z-scores were computed as previously described (39). A mean log2 ratio cutoff of ≥ 2 across time points and an accompanying z-score of ≥ 2 were used to identify genes whose expression changed most significantly. Searches of the microarray data with the mean gene expression profile of genes in the predicted PerR regulon were performed using the Pearson correlation coefficient as the scoring function and the Euclidean distance to sort the final search results The 0.71 correlation of the rubredoxin-like protein encoded by DVU3093, the lowest-scoring gene from the predicted PerR regulon, was used as an empirical significance cutoff for the profile search results (for additional notes and analysis information see Fig. S5 in the supplemental material). All heat maps of gene expression data were rendered as vector graphics and output in Encapsulated PostScript format using JColorGrid (29). The rendering configuration specified a constant maximum and minimum data range (log2 ratio range, −6.25 to 6.25), a log2 ratio increment of 0.5, and the log2 ratio color scale centered at a log2 ratio of 0. The specificity of transcription changes in the predicted PerR regulon genes was assessed using the mean expression of genes in the regulon computed across different experimental conditions corresponding to six previously published VIMSS studies (e.g., heat shock [5], salt stress [39], nitrite [22], and stationary phase [6]). The mean expression of genes in the PerR regulon was computed for each time point in each experiment, along with the global mean and standard deviation across all time points and experiments. To assess the confidence of the observed gene expression changes, z-scores were computed for the mean PerR gene expression at each time point in the 0.1% O2 and air stress experiments. Assuming a normal distribution, the 95% confidence interval corresponds to a z-score of 2, and at most 5% of the data are expected to have more significant changes. In the microaerobic experiment the z-scores were 0.4, 1.2, and 1.7 for 60, 120, and 240 min, respectively. In the air stress experiment, the z-scores were −0.4, −0.8, −1.3, −1.6, and −2.5, for 0, 10, 30, 120, and 240 min, respectively. Note that this is the only calculation of z-score across multiple experiments; all other z-scores reported in this study were computed across the 0.1% O2 and air exposure experiments only. Microarray data for this study are available at http://www.microbesonline.org/cgi-bin/microarray/viewExp.cgi?locusId=&expId=28+74. Raw microarray data can also be accessed at the following websites for 0.1% O2 exposure and air stress: http://www.microbesonline.org/microarray/rawdata/exp28_E35 and http://www.microbesonline.org/microarray/rawdata/exp74_E12, respectively. Proteomics and proteomics data analyses. Sample preparation, chromatography, and mass spectrometry for iTRAQ proteomics were performed as described previously (47), with modifications to the lysis buffers used. Frozen cell pellets from triplicate 50-ml cultures were thawed and pooled prior to cell lysis. For the 0.1% O2-exposed biomass, cells were lysed via sonication in 500 mM triethylammonium bicarbonate (pH 8.5) (Sigma-Aldrich), and the clarified lysate was used as total cellular protein. Sample denaturation, reduction, blocking, digestion, and labeling with isobaric reagents were performed according to the manufacturer's directions (Applied Biosystems, Framingham, MA). The fourplex iTRAQ labels were used as follows: tag114, T0 control; tag115, 240-min control; tag116, 240-min 0.1% O2-sparged sample; and tag117, 240-min 0.1% O2-sparged sample (replicate). tag116 and tag117 provided technical replicates to allow assessment of internal error. For the air-exposed biomass, cell pellets were lysed via sonication in lysis buffer (4 M urea, 500 mM triethylammonium bicarbonate; pH 8.5), and the clarified lysate was diluted with water to 1 M urea before being used. The same labeling procedure was used, and the labels were used as follows: tag114, 120-min N2-sparged control; tag115, 240-min N2-sparged control; tag116, 120-min air-sparged sample; and tag117, 240-min air-sparged sample. Strong cation-exchange was used to separate both 0.1% O2- and air-exposed, iTRAQ-labeled samples into 21 to 23 salt fractions. Fractions were desalted, dried, and separated on a C18 reverse-phase nano-LC-MS column using a Dionex LC system coupled with an ESI-QTOF mass analyzer (QSTAR hybrid quadrupole time of flight; Applied Biosystems, Framingham, MA) as previously described (47). Collected mass spectra were analyzed using Analyst 1.1 with ProQuant 1.1, ProGroup 1.0.6 (Applied Biosystems, Framingham, MA), and MASCOT version 2.1 (Matrix Science, Inc, Boston, MA). A FASTA file containing all the putative open reading frame sequences of D. vulgaris, obtained from microbesonline.org (1), was used for the theoretical search database along with the common impurities trypsin, keratin, cytochrome c, and bovine serum albumin. The same search parameters were used in both programs, as described previously (47). Only proteins identified by at least two unique peptides at greater than 95% confidence by both ProQuant and MASCOT were considered for further analysis. All protein ratios were obtained from the ProQuant database using ProGroup. Tag ratios for each protein were computed as the weighted average from all peptides that were uniquely assigned to that protein. Technical replicates (tag116 and tag117 used to label 0.1% O2-exposed biomass) were used to assess variability in quantification of log2 ratios. To define a cutoff for internal error, the deviation between the absolute values of log2(tag116/ tag115) and log2(tag117/ tag115) for a given protein was used. The internal error cutoff was set at the value of deviation at which 95% of all proteins showed deviation that was less than or equal to that value. The internal error cutoff was found to be 0.13. To compute the level of significant change, a z-score was computed for all log2 values. Protein log2 values with z-scores of ≥ 2 were considered to be significantly changed. Cluster of orthologous groups (COG) categories as defined by Tatusov et al. (52) were used to plot the fraction of each COG category identified (Fig. (Fig.2).2
RESULTS Effect of different growth conditions on biomass and viability. For genome-wide assessment of the cellular response, growth assays were conducted to determine the level of O2 that affected the growth rate but was not lethal. Extended exposure to 0.05% O2 had no overall effect on D. vulgaris growth (Fig. (Fig.3A).3A
When biomass was exposed to air (21% O2) for a similar length of time, the effect on both the growth rate and viability was drastic. Direct cell counts showed that the air-sparged samples contained only 40% of the number of cells present in the control (N2 sparged) after 240 min of sparging. Further, measurement of the CFU indicated that only a fraction of cells formed colonies when they were plated (~10%) compared the control culture at T0 (see Fig. S3 in the supplemental material). This result is consistent with most previous studies in which a similar reduction in viability has been documented (18); there was only one exception where CFU remained unaffected (59). Genome-wide transcriptional response. The transcript profiles of cultures exposed to 0.1% O2 were analyzed. Applying a log2 ratio cutoff of ≥ 2 at at least one time point (and a z-score of ≥ 2) for genes whose expression changed significantly revealed only 12 significantly upregulated genes. These results suggest that 0.1% O2 exposure produced a mild perturbation in D. vulgaris. The upregulated genes included five of the six predicted members of the predicted PerR regulon (Fig. (Fig.4).4
It is noteworthy that following exposure to 0.1% O2, expression of the perR transcript increased with time, as did the expression of the transcripts of all other predicted PerR regulon genes (Fig. (Fig.4).4
In contrast, air exposure generated a large number of differentially expressed genes; 393 candidates showed significant upregulation, whereas 454 genes were found to be downregulated (for complete data see the microarray data website provided in Materials and Methods). Among these, genes in the predicted PerR regulon were downregulated, as were signature SRB genes and other genes considered to provide protection from oxidative stress (Fig. (Fig.4,4
Proteomic response. An iTRAQ proteomics strategy was used to identify differences in protein content for the same samples used for the microarray analysis. A total of 251 proteins were identified by two independent mass spectrometry analysis software packages (see Materials and Methods) (47). As in the microarray data, proteins were considered to be significantly changed if their absolute z-scores were >2. Responses at the protein level may lag those at the transcript level, and this may account for the milder proteomic changes compared to the microarray results. The greatest change noted was more than twofold (log2 ratio, 1.37). For z-scores of ≥ 2 there were only four proteins with increased levels and two proteins with decreased levels. Three of the six predicted PerR regulon members were identified in the proteomics data, and all were present at higher levels in the 0.1% O2-exposed biomass (Fig. (Fig.88
Proteomics analysis of air-stressed biomass was conducted at both 120 min and 240 min. As shown in Fig. Fig.8C,8C PerR regulon expression profile. The genes of the predicted PerR regulon showed a distinct expression pattern with both 0.1% O2 exposure and aerobic stress across several time points (Fig. (Fig.9).9
DISCUSSION While continuous bubbling of the D. vulgaris culture with 0.1% O2 ensured cell exposure to a proportional amount of O2, this level of O2 exposure produced only a mild perturbation. This finding is reflected in the small number of genes that changed expression and the fact that no changes were observed in central metabolic genes. This may be an indication that under normal growth conditions, D. vulgaris already contains adequate levels of most of the enzymes required to respond to low levels of O2 exposure. Concerted upregulation of the entire predicted PerR regulon was observed during 0.1% O2 exposure, and ahpC was one of the most upregulated candidates at both the transcript and protein levels. Along with the tmc transmembrane cytochrome c3 operon response, these were the only cellular responses to 0.1% O2 exposure. PerR regulons have been described in many bacteria (3, 21, 24, 25, 48, 58), and genes regulated by PerR are often involved in defense against ROS accumulation. In D. vulgaris, predicted members of the PerR regulon, such as a rubrerythrin (DVU0265), have been identified as important enzymes during exposure to both O2 and other oxidative stresses (18). The air stress had a much more drastic effect on a cell-wide level. The responses at the mRNA level were reproducible across biological replicates (Fig. 10B
Using the mean expression profile for the predicted PerR regulon genes across the two exposures, the microarray data were searched for other transcripts with similar expression profiles. The resulting list contained several members of the eight-gene operon encoding the transmembrane tetraheme cytochrome c3 complex (DVU0258 to DVU0266) and also the cydAB operon (DVU3270 and DVU3271) encoding the cytochrome d ubiquinol oxidase proteins. The cytochrome bd oxidase system is typically involved in oxidative phosphorylation, and increases in the transcription of the corresponding genes during oxidative stress have been reported for other anaerobic bacteria, such as Desulfovibrio gigas (38), Moorella thermoacetica (11), and Bacteroides fragilis (2). These enzymes also appear to have a protective role in aerobic bacteria such as Escherichia coli and Salmonella during oxidative stress (15, 34). The existence of cytochrome bd oxidases in D. vulgaris has been a matter of historical discussion since pure cultures of D. vulgaris are unable to grow in oxygen (8). Here, the significant increase observed in transcripts for the electron transfer systems such as the tmc cytochrome c3 complex and for the oxidative phosphorylation enzymes like cytochrome bd oxidase may indicate that additional copies of these enzymes play a protective role during 0.1% O2 exposure. Several redox-active proteins, such as a thiol peroxidase, bacterioferritin, flavodoxin, and ferredoxins, also correlated with the mean PerR regulon gene expression profile. Since the levels of these candidates also increased during 0.1% O2 exposure, they may also be required for defense against O2 in D. vulgaris. Other oxidative response genes, including the rubredoxin gene (DVU3184), present in the Sor operon and the Sor gene itself were also identified by the gene expression profile search, but no significant upregulation of these candidates was observed. Of the 58 candidates, more than one-third (21) have no predicted functions. Among the genes for which a functional annotation exists, several chemotaxis and signal transduction genes were identified. These genes are ideal candidates for further study to confirm any specific role in the oxidative stress response. It has recently been demonstrated that a roo deletion strain of D. vulgaris was more sensitive to microaerobic stress than the wild type (57); however, we observed no change in expression of this gene at either the transcript or protein level in the 0.1% O2 exposure experiments. Deletion of the genes encoding Sor and Sod has been shown to create strains with greater O2 sensitivity (18). While neither of these genes showed a significant transcriptional change during 0.1% O2 exposure, candidates that confer fitness and ensure survival may already be present and not necessarily show changes in transcript or protein levels. Compared to 0.1% O2 exposure, exposure to air appears to have a severely detrimental effect on cellular growth. It should be noted, however, that increases in the Sod protein levels and the few additional upregulated transcripts in oxidative stress response genes (such as the genes encoding putative peptide methionine sulfoxide reductases, msrA and msrB [DVU0576 and DVU1984]) in the air-stressed biomass may be physiologically relevant for the small population of cells that remain viable during air exposure. Genes in the predicted PerR regulon have exhibited perturbations in other D. vulgaris functional genomics studies (e.g., studies of heat shock [5], salt stress [39], nitrite stress [22], and stationary phase [6]). An increase in all members of this predicted regulon was also seen with heat shock (5), but the time-dependent increase shown by these genes appears to be unique to 0.1% O2 exposure. Additionally, while a large number of upregulated genes were documented in the heat shock study, the upregulation during 0.1% O2 exposure of the predicted PerR regulon genes constitutes a much more specific and limited transcriptional response. Based on all the data, it appears that PerR derepression is the primary D. vulgaris response to low-O2 exposure. Interestingly, the air stress transcriptomic data correlated better with heat shock data than with the data from 0.1% O2 exposure (Fig. (Fig.10),10 Another candidate that was universally upregulated across multiple stress conditions monitored in D. vulgaris was a protein annotated as zinc resistance-associated protein ZraP (DVU3384). Although it was highly upregulated in both conditions studied here, DVU3384 may be a general stress response candidate. Additionally, although zinc uptake regulons have been shown to increase with O2 exposure in lactobacilli (50) and with oxidative stress in Bacillus (19), the DVU3384 protein may not be a zinc binding protein. In proteins with confirmed zinc binding motifs, such as E. coli YjaI, known to preferentially bind Zn and Ni (43), Zn binding is conferred by a two-part motif: an N-terminally located sequence, HRWHGRC, and a C-terminally located sequence, HGGHGMW. Due to the evolutionary distances between this gammaproteobacterium and the deltaproteobacterium sulfate reducer and the low sequence similarity to experimentally validated proteins, more experimental proof is required to confirm the metal ion binding specificity of the D. vulgaris ZraP (DVU3384). However, the D. vulgaris ZraP sequence contains a cysteine residue in the C-terminal region, as well as multiple histidine residues in the N-terminal region, both contained in glycine-rich and presumably flexible regions of the protein. Together, these data suggest that D. vulgaris ZraP contains a likely metal binding site and is an interesting candidate for follow-up experiments. Many bacteria traditionally categorized as anaerobic organisms, including Helicobacter pylori (56) and Bacteroides fragilis (2), contain numerous mechanisms to counter O2 stress. Other anaerobes, such as Clostridium spp., M. thermoacetica, and Spirillum winogradskii (4, 10, 11, 32, 44), have also been found to tolerate transient exposure to oxic environments. While some of these organisms are microaerophilic, D. vulgaris, like H. pylori and Clostridium spp., cannot utilize O2 for growth and is anaerobic by definition. However, our data indicate that this bacterium can survive 0.1% O2 exposure both in terms of growth and in terms of cellular response and appears to be entirely suited for ecological niches that experience transient exposure to O2. Results from previous studies have shown that the members of the Sor operon and other oxidative stress response genes are important for the survival of D. vulgaris during O2 exposure (18, 55). Our study suggests that additional protection may be provided by the peroxidases in the predicted PerR regulon and membrane-bound cytochromes. The very concerted increase and temporal response of the predicted PerR regulon in D. vulgaris upon exposure to low concentrations of oxygen is consistent with a physiological response to a condition that may be frequently encountered in the natural environment. Seasonal episodic infiltration of snow melts and rainfall events bring oxygenated waters to previously established anoxic and reducing environments. Given the ability of D. vulgaris to cope with low O2 levels for short periods, these weather-related effects are unlikely to be catastrophic. Further, despite the graver consequences of exposure to higher levels of O2, even the limited viability ensures propagation of the bacterium through this exceedingly harsh stress. This further suggests why D. vulgaris and other SRB are so resilient in a variety of habitats, including those where exposure to oxygen may occur periodically. [Supplemental material]
Acknowledgments We are grateful to Morgan Price, Eric Alm, and Katherine Huang for helpful discussions. We thank Rick Huang, Richard Phan, and Mary Singer for technical help with biomass production, Barbara Giles for sharing experimental observations, and Keith Keller and Janet Jacobsen for help with the supplemental materials link. This work was part of the Environmental Stress Pathway Project (ESPP) of the Virtual Institute for Microbial Stress and Survival (http://vimss.lbl.gov) supported by the U.S. Department of Energy Office of Science Office of Biological and Environmental Research Genomics: GTL Program through contract DE-AC02-05CH11231 with Lawrence Berkeley National Laboratory. Oak Ridge National Laboratory is managed by University of Tennessee-Battelle LLC for the Department of Energy under contract DE-AC05-00OR22725. Footnotes Published ahead of print on 1 June 2007.†Supplemental material for this article may be found at http://jb.asm.org/. REFERENCES 1. Alm, E. J., K. H. Huang, M. N. Price, R. P. Koche, K. Keller, I. L. Dubchak, and A. P. Arkin. 2005. The MicrobesOnline Web site for comparative genomics. Genome Res. 15:1015-1022. [PubMed] 2. 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] 3. 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] 4. Briolat, V., and G. Reysset. 2002. Identification of the Clostridium perfringens genes involved in the adaptive response to oxidative stress. J. Bacteriol. 184:2333-2343. [PubMed] 5. Chhabra, S. R., Q. He, K. H. Huang, S. P. Gaucher, E. J. Alm, Z. He, M. Z. Hadi, T. C. Hazen, J. D. Wall, J. Zhou, A. P. Arkin, and A. K. Singh. 2006. Global analysis of heat shock response in Desulfovibrio vulgaris Hildenborough. J. Bacteriol. 188:1817-1828. [PubMed] 6. Clark, M. E., Q. He, Z. He, K. H. Huang, E. J. Alm, X. F. Wan, T. C. Hazen, A. P. Arkin, J. D. Wall, J. Z. Zhou, and M. W. Fields. 2006. Temporal transcriptomic analysis as Desulfovibrio vulgaris Hildenborough transitions into stationary phase during electron donor depletion. Appl. Environ Microbiol. 72:5578-5588. [PubMed] 7. Coulter, E. D., and D. M. Kurtz, Jr. 2001. A role for rubredoxin in oxidative stress protection in Desulfovibrio vulgaris: catalytic electron transfer to rubrerythrin and two-iron superoxide reductase. Arch. Biochem. Biophys. 394:76-86. [PubMed] 8. Cypionka, H. 2000. Oxygen respiration by Desulfovibrio species. Annu. Rev. Microbiol. 54:827-848. [PubMed] 9. Cypionka, H., F. Widdel, and N. Pfennig. 1985. Survival of sulfate-reducing bacteria after oxygen stress, and growth in sulfate-free oxygen-sulfide gradients. FEMS Microbiol. Lett. 31:39-45. 10. Das, A., E. D. Coulter, D. M. Kurtz, Jr., and L. G. Ljungdahl. 2001. Five-gene cluster in Clostridium thermoaceticum consisting of two divergent operons encoding rubredoxin oxidoreductase-rubredoxin and rubrerythrin-type A flavoprotein-high-molecular-weight rubredoxin. J. Bacteriol. 183:1560-1567. [PubMed] 11. Das, A., R. Silaghi-Dumitrescu, L. G. Ljungdahl, and D. M. Kurtz, Jr. 2005. Cytochrome bd oxidase, oxidative stress, and dioxygen tolerance of the strictly anaerobic bacterium Moorella thermoacetica. J. Bacteriol. 187:2020-2029. [PubMed] 12. Dilling, W., and H. Cypionka. 1990. Aerobic respiration in sulfate-reducing bacteria. FEMS Microbiol. Lett. 71:123-127. 13. Dolla, A., M. Fournier, and Z. Dermoun. 2006. Oxygen defense in sulfate-reducing bacteria. J. Biotechnol. 126:87-100. [PubMed] 14. Emerson, J. P., E. D. Coulter, R. S. Phillips, and D. M. Kurtz, Jr. 2003. Kinetics of the superoxide reductase catalytic cycle. J. Biol. Chem. 278:39662-39668. [PubMed] 15. Farr, S. B., and T. Kogoma. 1991. Oxidative stress responses in Escherichia coli and Salmonella typhimurium. Microbiol. Mol. Biol. Rev. 55:561-585. 16. Fournier, M., C. Aubert, Z. Dermoun, M. C. Durand, D. Moinier, and A. Dolla. 2006. Response of the anaerobe Desulfovibrio vulgaris Hildenborough to oxidative conditions: proteome and transcript analysis. Biochimie 88:85-94. [PubMed] 17. Fournier, M., Z. Dermoun, M. C. Durand, and A. Dolla. 2004. A new function of the Desulfovibrio vulgaris Hildenborough [Fe] hydrogenase in the protection against oxidative stress. J. Biol. Chem. 279:1787-1793. [PubMed] 18. Fournier, M., Y. Zhang, J. D. Wildschut, A. Dolla, J. K. Voordouw, D. C. Schriemer, and G. Voordouw. 2003. Function of oxygen resistance proteins in the anaerobic, sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough. J. Bacteriol. 185:71-79. [PubMed] 19. Gaballa, A., and J. D. Helmann. 2002. A peroxide-induced zinc uptake system plays an important role in protection against oxidative stress in Bacillus subtilis. Mol. Microbiol. 45:997-1005. [PubMed] 20. Hardy, J., and W. A. Hamilton. 1981. The oxygen tolerance of sulfate-reducing bacteria isolated from North Sea waters. Curr. Microbiol. 6:259-262. 21. Hayashi, K., T. Ohsawa, K. Kobayashi, N. Ogasawara, and M. Ogura. 2005. The H2O2 stress-responsive regulator PerR positively regulates srfA expression in Bacillus subtilis. J. Bacteriol. 187:6659-6667. [PubMed] 22. He, Q., K. H. Huang, Z. He, E. J. Alm, M. W. Fields, T. C. Hazen, A. P. Arkin, J. D. Wall, and J. Zhou. 2006. Energetic consequences of nitrite stress in Desulfovibrio vulgaris Hildenborough, inferred from global transcriptional analysis. Appl. Environ Microbiol. 72:4370-4381. [PubMed] 23. Heidelberg, J. F., R. Seshadri, S. A. Haveman, C. L. Hemme, I. T. Paulsen, J. F. Kolonay, J. A. Eisen, N. Ward, B. Methe, L. M. Brinkac, S. C. Daugherty, R. T. Deboy, R. J. Dodson, A. S. Durkin, R. Madupu, W. C. Nelson, S. A. Sullivan, D. Fouts, D. H. Haft, J. Selengut, J. D. Peterson, T. M. Davidsen, N. Zafar, L. Zhou, D. Radune, G. Dimitrov, M. Hance, K. Tran, H. Khouri, J. Gill, T. R. Utterback, T. V. Feldblyum, J. D. Wall, G. Voordouw, and C. M. Fraser. 2004. The genome sequence of the anaerobic, sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough. Nat. Biotechnol. 22:554-559. [PubMed] 24. Helmann, J. D., M. F. Wu, A. Gaballa, P. A. Kobel, M. M. Morshedi, P. Fawcett, and C. Paddon. 2003. The global transcriptional response of Bacillus subtilis to peroxide stress is coordinated by three transcription factors. J. Bacteriol. 185:243-253. [PubMed] 25. Horsburgh, M. J., M. O. Clements, H. Crossley, E. Ingham, and S. J. Foster. 2001. PerR controls oxidative stress resistance and iron storage proteins and is required for virulence in Staphylococcus aureus. Infect. Immun. 69:3744-3754. [PubMed] 26. Imlay, J. A. 2002. What biological purpose is served by superoxide reductase? J. Biol. Inorg. Chem. 2002. 7:659-663. 27. Jayaraman, A., P. J. Hallock, R. M. Carson, C. C. Lee, F. B. Mansfeld, and T. K. Wood. 1999. Inhibiting sulfate-reducing bacteria in biofilms on steel with antimicrobial peptides generated in situ. Appl. Microbiol. Biotechnol. 52:267-275. [PubMed] 28. Jenney, F. E., M. F. Verhagen, X. Cui, and M. W. Adams. 1999. Anaerobic microbes: oxygen detoxification without superoxide dismutase. Science 286:306-309. [PubMed] 29. Joachimiak, M. P., J. L. Weisman, and B. May. 2006. JColorGrid: software for the visualization of biological measurements. BMC Bioinformatics 7:225. [PubMed] 30. Johnson, M. S., I. B. Zhulin, M. E. Gapuzan, and B. L. Taylor. 1997. Oxygen-dependent growth of the obligate anaerobe Desulfovibrio vulgaris Hildenborough. J. Bacteriol. 179:5598-5601. [PubMed] 31. Kepner, R. L., Jr., and J. R. Pratt. 1994. Use of fluorochromes for direct enumeration of total bacteria in environmental samples: past and present. Microbiol. Rev. 58:603-615. [PubMed] 32. Lehmann, Y., L. Meile, and M. Teuber. 1996. Rubrerythrin from Clostridium perfringens: cloning of the gene, purification of the protein, and characterization of its superoxide dismutase function. J. Bacteriol. 178:7152-7158. [PubMed] 33. Li, X., Z. He, and J. Zhou. 2005. Selection of optimal oligonucleotide probes for microarrays using multiple criteria, global alignment and parameter estimation. Nucleic Acids Res. 33:6114-6123. [PubMed] 34. Lindqvist, A., J. Membrillo-Hernandez, R. K. Poole, and G. M. Cook. 2000. Roles of respiratory oxidases in protecting Escherichia coli K12 from oxidative stress. Antonie Leeuwenhoek 78:23-31. [PubMed] 35. Lobo, S. A., A. M. Melo, J. N. Carita, M. Teixeira, and L. M. Saraiva. 2007. The anaerobe Desulfovibrio desulfuricans ATCC 27774 grows at nearly atmospheric oxygen levels. FEBS Lett. 581:433-436. [PubMed] 36. Lumppio, H. L., N. V. Shenvi, R. P. Garg, A. O. Summers, and D. M. Kurtz, Jr. 1997. A rubrerythrin operon and nigerythrin gene in Desulfovibrio vulgaris (Hildenborough). J. Bacteriol. 179:4607-4615. [PubMed] 37. Lumppio, H. L., N. V. Shenvi, A. O. Summers, G. Voordouw, and D. M. Kurtz, Jr. 2001. Rubrerythrin and rubredoxin oxidoreductase in Desulfovibrio vulgaris: a novel oxidative stress protection system. J. Bacteriol. 183:101-108. [PubMed] 38. Machado, P., R. Felix, R. Rodrigues, S. Oliveira, and C. Rodrigues-Pousada. 2006. Characterization and expression analysis of the cytochrome bd oxidase operon from Desulfovibrio gigas. Curr. Microbiol. V 52:274-281. 39. Mukhopadhyay, A., Z. He, E. J. Alm, A. P. Arkin, E. E. Baidoo, S. C. Borglin, W. Chen, T. C. Hazen, Q. He, H.-Y. Holman, K. Huang, R. Huang, D. C. Joyner, N. Katz, M. Keller, P. Oeller, A. Redding, J. Sun, J. Wall, J. Wei, Z. Yang, H.-C. Yen, J. Zhou, and J. D. Keasling. 2006. Salt stress in Desulfovibrio vulgaris Hildenborough: an integrated genomics approach. J. Bacteriol. 188:4068-4078. [PubMed] 40. Nemati, M., G. E. Jenneman, and G. Voordouw. 2001. Mechanistic study of microbial control of hydrogen sulfide production in oil reservoirs. Biotechnol. Bioeng. 74:424-434. [PubMed] 41. Neria-Gonzalez, I., E. T. Wang, F. Ramirez, J. M. Romero, and C. Hernandez-Rodriguez. 2006. Characterization of bacterial community associated to biofilms of corroded oil pipelines from the southeast of Mexico. Anaerobe 12:122-133. [PubMed] 42. Niviere, V., and M. Fontecave. 2004. Discovery of superoxide reductase: an historical perspective. J. Biol Inorg Chem. 9:119-123. [PubMed] 43. Noll, M., K. Petrukhin, and S. Lutsenko. 1998. Identification of a novel transcription regulator from Proteus mirabilis, PMTR, revealed a possible role of YJAI protein in balancing zinc in Escherichia coli. J. Biol. Chem. 273:21393-21401. [PubMed] 44. Podkopaeva, D. A., M. Grabovich, and G. A. Dubinina. 2003. Oxidative stress and antioxidant cell protection systems in the microaerophilic bacterium Spirillum winogradskii. Mikrobiologiya 72:600-608. (In Russian.) [PubMed] 45. Poole, R. K. 1994. Oxygen reactions with bacterial oxidases and globins: binding, reduction and regulation. Antonie Leeuwenhoek 65:289-310. [PubMed] 46. Postgate, J. R. 1984. The sulfate-reducing bacteria. Cambridge University Press, Cambridge, United Kingdom. 47. Redding, A. M., A. Mukhopadhyay, D. C. Joyner, T. C. Hazen, and J. D. Keasling. 2006. Study of nitrate stress in Desulfovibrio vulgaris Hildenborough using iTRAQ proteomics. Briefs Funct. Genomics Proteomics 5:133-143. 48. Ricci, S., R. Janulczyk, and L. Bjorck. 2002. The regulator PerR is involved in oxidative stress response and iron homeostasis and is necessary for full virulence of Streptococcus pyogenes. Infect. Immun. 70:4968-4976. [PubMed] 49. Rodionov, D. A., I. Dubchak, A. Arkin, E. Alm, and M. S. Gelfand. 2004. Reconstruction of regulatory and metabolic pathways in metal-reducing delta-proteobacteria. Genome Biol. 5:R90. [PubMed] 50. Scott, C., H. Rawsthorne, M. Upadhyay, C. A. Shearman, M. J. Gasson, J. R. Guest, and J. Green. 2000. Zinc uptake, oxidative stress and the FNR-like proteins of Lactococcus lactis. FEMS Microbiol. Lett. 192:85-89. [PubMed] 51. Tanaka, Y., M. Sogabe, K. Okumura, and R. Kurane. 2002. A highly selective direct method of detecting sulphate-reducing bacteria in crude oil. Lett. Appl. Microbiol. 35:242-246. [PubMed] 52. Tatusov, R. L., E. V. Koonin, and D. J. Lipman. 1997. A genomic perspective on protein families. Science 278:631-637. [PubMed] 53. Valentine, J. S., D. L. Wertz, T. J. Lyons, L. L. Liou, J. J. Goto, and E. B. Gralla. 1998. The dark side of dioxygen biochemistry. Curr. Opin. Chem. Biol. 2:253-262. [PubMed] 54. Vincent, K. A., A. Parkin, O. Lenz, S. P. J. Albracht, J. C. Fontecilla-Camps, R. Cammack, B. Friedrich, and F. A. Armstrong. 2005. Electrochemical definitions of O2 sensitivity and oxidative inactivation in hydrogenases. J. Am. Chem. Soc. 127:18179-18189. [PubMed] 55. Voordouw, J. K., and G. Voordouw. 1998. Deletion of the rbo gene increases the oxygen sensitivity of the sulfate-reducing bacterium Desulfovibrio vulgaris Hildenborough. Appl. Environ Microbiol. 64:2882-2887. [PubMed] 56. Wang, G., P. Alamuri, and R. J. Maier. 2006. The diverse antioxidant systems of Helicobacter pylori. Mol. Microbiol. 61:847-860. [PubMed] 57. Wildschut, J. D., R. M. Lang, J. K. Voordouw, and G. Voordouw. 2006. Rubredoxin:oxygen oxidoreductase enhances survival of Desulfovibrio vulgaris Hildenborough under microaerophilic conditions. J. Bacteriol. 188:6253-6260. [PubMed] 58. Wu, H. J., K. L. Seib, Y. N. Srikhanta, S. P. Kidd, J. L. Edwards, T. L. Maguire, S. M. Grimmond, M. A. Apicella, A. G. McEwan, and M. P. Jennings. 2006. PerR controls Mn-dependent resistance to oxidative stress in Neisseria gonorrhoeae. Mol. Microbiol. 60:401-416. [PubMed] 59. Zhang, W., D. E. Culley, M. Hogan, L. Vitiritti, and F. J. Brockman. 2006. Oxidative stress and heat-shock responses in Desulfovibrio vulgaris by genome-wide transcriptomic analysis. Antonie Leeuwenhoek 90:41-55. [PubMed] |
PubMed related articles
Your browsing activity is empty. Activity recording is turned off. |
|||||||||||||||||||||||||
Annu Rev Microbiol. 2000; 54():827-48.
[Annu Rev Microbiol. 2000]Appl Microbiol Biotechnol. 1999 Aug; 52(2):267-75.
[Appl Microbiol Biotechnol. 1999]Biotechnol Bioeng. 2001 Sep 5; 74(5):424-34.
[Biotechnol Bioeng. 2001]Anaerobe. 2006 Jun; 12(3):122-33.
[Anaerobe. 2006]Lett Appl Microbiol. 2002; 35(3):242-6.
[Lett Appl Microbiol. 2002]Arch Biochem Biophys. 2001 Oct 1; 394(1):76-86.
[Arch Biochem Biophys. 2001]J Bacteriol. 1997 Jul; 179(14):4607-15.
[J Bacteriol. 1997]J Bacteriol. 2001 Jan; 183(1):101-8.
[J Bacteriol. 2001]J Bacteriol. 2003 Jan; 185(1):71-9.
[J Bacteriol. 2003]J Biol Chem. 2003 Oct 10; 278(41):39662-8.
[J Biol Chem. 2003]J Bacteriol. 2001 Jan; 183(1):101-8.
[J Bacteriol. 2001]Antonie Van Leeuwenhoek. 1994; 65(4):289-310.
[Antonie Van Leeuwenhoek. 1994]Curr Opin Chem Biol. 1998 Apr; 2(2):253-62.
[Curr Opin Chem Biol. 1998]J Am Chem Soc. 2005 Dec 28; 127(51):18179-89.
[J Am Chem Soc. 2005]J Biotechnol. 2006 Oct 20; 126(1):87-100.
[J Biotechnol. 2006]J Bacteriol. 2006 Sep; 188(17):6253-60.
[J Bacteriol. 2006]J Bacteriol. 2006 Jun; 188(11):4068-78.
[J Bacteriol. 2006]Microbiol Rev. 1994 Dec; 58(4):603-15.
[Microbiol Rev. 1994]J Bacteriol. 2006 Jun; 188(11):4068-78.
[J Bacteriol. 2006]J Bacteriol. 2003 Jan; 185(1):71-9.
[J Bacteriol. 2003]J Bacteriol. 2006 Sep; 188(17):6253-60.
[J Bacteriol. 2006]Nucleic Acids Res. 2005; 33(19):6114-23.
[Nucleic Acids Res. 2005]J Bacteriol. 2006 Mar; 188(5):1817-28.
[J Bacteriol. 2006]J Bacteriol. 2006 Jun; 188(11):4068-78.
[J Bacteriol. 2006]BMC Bioinformatics. 2006 Apr 27; 7():225.
[BMC Bioinformatics. 2006]J Bacteriol. 2006 Mar; 188(5):1817-28.
[J Bacteriol. 2006]J Bacteriol. 2006 Jun; 188(11):4068-78.
[J Bacteriol. 2006]Appl Environ Microbiol. 2006 Jun; 72(6):4370-81.
[Appl Environ Microbiol. 2006]Appl Environ Microbiol. 2006 Aug; 72(8):5578-88.
[Appl Environ Microbiol. 2006]Genome Res. 2005 Jul; 15(7):1015-22.
[Genome Res. 2005]Science. 1997 Oct 24; 278(5338):631-7.
[Science. 1997]J Bacteriol. 2003 Jan; 185(1):71-9.
[J Bacteriol. 2003]Antonie Van Leeuwenhoek. 2006 Jul; 90(1):41-55.
[Antonie Van Leeuwenhoek. 2006]J Bacteriol. 2006 Mar; 188(5):1817-28.
[J Bacteriol. 2006]Mol Microbiol. 2005 Jan; 55(1):221-34.
[Mol Microbiol. 2005]J Bacteriol. 2005 Oct; 187(19):6659-67.
[J Bacteriol. 2005]J Bacteriol. 2003 Jan; 185(1):243-53.
[J Bacteriol. 2003]Infect Immun. 2001 Jun; 69(6):3744-54.
[Infect Immun. 2001]Infect Immun. 2002 Sep; 70(9):4968-76.
[Infect Immun. 2002]J Bacteriol. 2005 Mar; 187(6):2020-9.
[J Bacteriol. 2005]Nature. 2004 Jan 29; 427(6973):441-4.
[Nature. 2004]Antonie Van Leeuwenhoek. 2000 Jul; 78(1):23-31.
[Antonie Van Leeuwenhoek. 2000]Annu Rev Microbiol. 2000; 54():827-48.
[Annu Rev Microbiol. 2000]J Bacteriol. 2006 Sep; 188(17):6253-60.
[J Bacteriol. 2006]J Bacteriol. 2003 Jan; 185(1):71-9.
[J Bacteriol. 2003]J Bacteriol. 2006 Mar; 188(5):1817-28.
[J Bacteriol. 2006]J Bacteriol. 2006 Jun; 188(11):4068-78.
[J Bacteriol. 2006]Appl Environ Microbiol. 2006 Jun; 72(6):4370-81.
[Appl Environ Microbiol. 2006]Appl Environ Microbiol. 2006 Aug; 72(8):5578-88.
[Appl Environ Microbiol. 2006]Antonie Van Leeuwenhoek. 2006 Jul; 90(1):41-55.
[Antonie Van Leeuwenhoek. 2006]FEMS Microbiol Lett. 2000 Nov 1; 192(1):85-9.
[FEMS Microbiol Lett. 2000]Mol Microbiol. 2002 Aug; 45(4):997-1005.
[Mol Microbiol. 2002]J Biol Chem. 1998 Aug 14; 273(33):21393-401.
[J Biol Chem. 1998]Mol Microbiol. 2006 Aug; 61(4):847-60.
[Mol Microbiol. 2006]Nature. 2004 Jan 29; 427(6973):441-4.
[Nature. 2004]J Bacteriol. 2002 May; 184(9):2333-43.
[J Bacteriol. 2002]J Bacteriol. 2001 Mar; 183(5):1560-7.
[J Bacteriol. 2001]J Bacteriol. 2005 Mar; 187(6):2020-9.
[J Bacteriol. 2005]J Bacteriol. 2006 Mar; 188(5):1817-28.
[J Bacteriol. 2006]J Bacteriol. 2006 Mar; 188(5):1817-28.
[J Bacteriol. 2006]