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Department of Microbial and Molecular Pathogenesis, Texas A&M University Health Science Center, College Station, TX 77843-1114, USA
Correspondence
Jonathan T. Skare
jskare{at}medicine.tamhsc.edu
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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The array data discussed in this publication have been deposited in the NCBI Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/) and are accessible through GEO series accession number GSE4856.
Present address: South Texas Center for Emerging Infectious Diseases and the Department of Biology, University of Texas at San Antonio, San Antonio, TX 78249, USA.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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). In 2002, the Center for Disease Control and Prevention reported 23 763 cases of Lyme disease in the USA, a 40 % increase from the previous year, indicating that it is a re-emerging infectious disease. The distinctive host environments that B. burgdorferi occupies (i.e. the arthropod vector and mammalian host) suggest that it must be able to quickly adapt to disparate conditions. The response to temperature and pH accounts for some of the environmental cues that modulate gene expression in B. burgdorferi (Brooks et al., 2003; Carroll et al., 1999, 2000; Ojaimi et al., 2003; Revel et al., 2002; Schwan et al., 1995; Yang et al., 2000). Additional studies, using host-adapted spirochaetes, indicate that other unknown host factors also modulate gene expression in B. burgdorferi (Akins et al., 1998; Brooks et al., 2003). As an extension of these observations, previous studies have demonstrated that dissolved oxygen levels modulate the expression of B. burgdorferi genes and, as such, may be a possible cue for pathogenic and/or regulatory networks (Seshu et al., 2004a). It is likely that the redox environment of an unfed versus a fed tick would be vastly different and this, coupled with the known differences in dissolved oxygen levels within mammalian host tissues, suggests that B. burgdorferi must cope with various oxidative stressors throughout its complex lifecycle.
A member of the Fur family of regulators has been identified in B. burgdorferi, which was subsequently designated BosR, for Borrelia oxidative stress regulator (Boylan et al., 2003). Our recent observations, along with others, have demonstrated that BosR is involved in the regulation of the oxidative stress response in B. burgdorferi (Boylan et al., 2003; Seshu et al., 2004b). In other bacteria, BosR homologues, referred to as PerR, are metalloregulatory proteins that sense oxidative stress, and regulate the expression of genes involved in the detoxification of reactive oxygen species (ROS) (Bsat et al., 1998; Fuangthong et al., 2002; Helmann et al., 2003; Herbig & Helmann, 2001; Horsburgh et al., 2001a, b; Mongkolsuk & Helmann, 2002). Several independent studies have demonstrated that BosR (also designated Fur) binds to regulatory elements in napA (Boylan et al., 2003), the borrelial dps/dpr homologue sodA (Seshu et al., 2004b), bosR/fur, as well as a gene adjacent to bosR/fur, bb0646 (Katona et al., 2004), and presumably regulates the expression of these genes in B. burgdorferi. A previous study identified a unique allele, bosRR39K, in the non-infectious strain B31 derivative CHP100, which manifests a unique regulatory activity relative to the wild-type bosR allele (Seshu et al., 2004b). Specifically, characterization of the bosRR39K-containing non-infectious strain (CHP100), relative to infectious MSK5 (containing the bosR allele), has indicated that CHP100 is more sensitive to ROS than MSK5 (Seshu et al., 2004b). Genetic inactivation of the bosRR39K allele (bosRR39K : : kanR) results in strain JS167, which is as resistant to ROS as the low-passage infectious B. burgdorferi clonal isolate MSK5 (Seshu et al., 2004b). The model that has emerged suggests that the redox-resistant phenotype observed for JS167 is due to the de-repression of genes involved in the oxidative stress response that are repressed in the redox-sensitive parent strain CHP100 by the binding of BosRR39K to transcriptional regulatory elements. Hence, the objective of this study was to identify the borrelial genes that are transcribed in the ROS-resistant isolate versus an ROS-sensitive isolate, as a first step in delineating the oxidative stress response in this pathogen, with the long-term goal of relating this to infectious isolates to define an ROS-responsive regulon. Based on the hypothesis indicated above, the transcriptional profile analysis of strain JS167 relative to its parent CHP100 might identify genes that account for the differential sensitivities to ROS observed between these two derivatives. Results presented herein demonstrate that 88 genes are significantly affected in the JS167 strain relative to its isogenic parent CHP100. Inasmuch as strain JS167 and infectious B. burgdorferi are resistant to ROS, some of the genes identified in this study may be involved in host adaptation, in addition to those required for the oxidative stress response. If so, some of the genes identified herein may be involved in pathogenic processes operative in B. burgdorferi infection.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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). For RNA isolation, B. burgdorferi was grown statically at 32 °C under conventional microaerophilic conditions (in a 1 % CO2 atmosphere) in complete Barbour–Stoenner–Kelly (BSK)-II medium to a density of 5x107 cells ml–1.
PCR.
PCR was performed to evaluate the plasmid content of strains, using oligonucleotides specific for all linear plasmids, cp9 and cp26, as previously described by Labandeira-Rey & Skare (2001), and for the cp32 plasmids as previously indicated by Purser & Norris (2000).
Macroarray used in this study.
The B. burgdorferi nylon macroarrays were generated as described previously by Ojaimi et al. (2003). Briefly, 1628 of the 1697 known ORFs of B. burgdorferi strain B31 were spotted in duplicate onto nylon membranes (Sigma–Genosys).
RNA isolation and probe synthesis.
Three independent cultures of either B. burgdorferi strain CHP100 or JS167 were grown to the exponential growth phase, and total RNA was isolated from 1x109 cells using a Versagene kit (Gentra) for each extraction. RNA samples were treated with DNase I (Roche) and Superase-In (Ambion) to eliminate contaminating DNA and inhibit RNase activity. The three independent RNA samples for both strains tested were separately pooled and examined for DNA contamination and crude RNA yield by PCR and RT-PCR, respectively. The purified RNA was converted to [
-33P]-labelled cDNA using an Ambion Strip-EZ RT kit together with 5 µg pooled total RNA and [-33P]dATP (Perkin–Elmer). The probe was then purified on a gel filtration spin column, and the specific activity was determined by scintillation counting. Probes with specific activities >1x106 c.p.m. µg–1 were used for hybridization.
Hybridization.
The nylon macroarray membranes were prehybridized with 10 ml ExpressHyb (Clonetech) at 50 °C for 1 h. The 33P-labelled probes were hybridized to the macroarray membranes for 18 h at 50 °C, washed with a low-stringency solution [2x saline sodium citrate (SSC), 0.05 % SDS] at 37 °C for 10 min, and then incubated in a high-stringency wash (0.1x SSC, 0.1 % SDS) at 50 °C for 10 min. The membranes were exposed to a phosphor screen (Amersham Pharmacia Biotech) for 48 h at room temperature. Signals were detected using the Storm 860 phosphorimager (Amersham Biosciences). Macroarray membranes were stripped of probe as per the Strip-EZ RT kit (Ambion), exposed to a phosphor screen, and analysed using the Storm 860 phosphoimager to confirm that the signal was removed, and then reprobed as described above.
Array data analysis.
Following scanning with the Storm 860 phosphorimager, the detected signals were analysed with Array Vision software version 6.0 (Imaging Research) to quantify background-adjusted spot densities. Values were imported into a Microsoft Excel spreadsheet for analysis, as previously described (Brooks et al., 2003; Conway et al., 2002). Raw density values for an individual spot were converted into percentage density values relative to the total density, and then duplicate spots were combined and averaged. Data from three independent arrays were analysed by two-tailed Student's t test to ascertain genes expressed at a significant level (P<0.01) between the different B. burgdorferi isolates. Density values 
2 SD above background densities, and induction values <1.5-fold were excluded from the final datasets. ORFs whose transcripts represented 0.002 % of the total transcripts, or that were located on plasmids absent from the non-infectious B31 strains, were removed from the final datasets. The complete macroarray dataset is posted at the NCBI Gene Expression Omnibus (GEO) at http://www.ncbi.nlm.nih.gov/geo/, and is accessible through GEO Series accession number GSE4856.
Quantitative RT-PCR.
A defined set of genes was subjected to quantitative RT-PCR to corroborate the macroarray data. Oligonucleotide primers were designed using Primer Express software (PE Biosystems) (Table 1). Selected primer pairs were tested to confirm that they specifically amplified a single product of known size, using genomic B. burgdorferi DNA as template. Reverse transcription reactions were performed by combining TaqMan reverse transcription reagents (Applied Biosystems) with purified B. burgdorferi total RNA. The total RNA used for quantitative RT-PCR was independently isolated and distinct from that used in the macroarray analysis. A control lacking reverse transcriptase was performed for each primer set using total RNA from each B. burgdorferi strain, to confirm the absence of contaminating DNA. Real-time PCR reactions were performed using an Applied Biosystems 7500 Real-time PCR system. SYBR Green PCRs were performed in triplicate, and each experiment was repeated in triplicate, resulting in nine data points for each gene of interest for each B. burgdorferi strain tested. A constitutively expressed gene, flaB, was used to normalize all transcripts tested for each B. burgdorferi strain. Fold levels of ORFs were determined by the 
Ct method, as previously described by Brooks et al. (2003), Conway et al. (2002) and Seshu et al. (2004a).
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RESULTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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). Subsequently, all assays conducted with other ROS indicated that the infectious MSK5, was significantly more resistant relative to the non-infectious strain, CHP100 (Seshu et al., 2004b). The insertional inactivation of bosRR39K allele in CHP100 (bosRR39K : : kanR) resulted in a strain, designated JS167, that was as resistant to ROS as the infectious MSK5 strain (Seshu et al., 2004b), suggesting that these resistant strains derepressed/induced genes required for resistance to oxidative stressors relative to the ROS-sensitive CHP100 strain. Unfortunately, it is difficult to compare strain MSK5 with either CHP100 or JS167, since the plasmid content of the infectious and non-infectious isolates are so disparate. In addition, attempts to inactivate bosR in MSK5 (and other low passage isolates) have been unsuccessful. Thus, a focused comparison of transcriptional profiles between the redox-sensitive CHP100 relative to the redox resistant JS167 isolate was conducted to identify genes that are responsible for the phenotype observed between these genotypic strains. It is important to note that the growth rate (i.e. doubling times) are indistinguishable between strains CHP100 and JS167 when these strains are grown at 32 °C (data not shown).
To test the hypothesis that differential gene expression accounts for the aforementioned sensitivity/resistant phenotypes observed, macroarrays containing 1628 B. burgdorferi ORFs were probed with cDNA derived from total RNA extracted from ROS-sensitive parent strain CHP100 and the ROS-resistant JS167 isolates. Macroarrays were probed with cDNA derived from pooled total RNA obtained from three independent cultures for each strain tested. In addition, for each strain analysed, hybridizations were performed in triplicate on alternating membranes to reduce the bias of the individual macroarray and possible spotting inconsistencies. A strong correlation was observed between the different macroarrays probed, indicating equivalent transcript populations, cDNA labelling and membrane hybridizations, resulting in high r values for JS167 (mean r value of 0.95) and CHP100 (mean r value of 0.87). It is important to note that the clonal non-infectious B31 isolate, CHP100, is missing the following plasmids relative to infectious strain B31 B. burgdorferi: cp9, cp32-6, cp32-8, lp25, lp28-4, lp36 and lp38 (Fig. 1). PCR analysis, using primers that flank bosR, amplified 0.5 and 2.5 kb fragments in the parent CHP100 and JS167, respectively, confirming that the transposon insertion in the bosRR39K allele was stably maintained within JS167 (Fig. 1). The bosRR39K : : kanR isolate is apparently missing lp5 and lp28-2, but was otherwise identical to its non-infectious parent (Fig. 1). Previous studies indicated that the sensitivity to oxidative stressors in the redox-resistant JS167 strain (missing lp5 and lp28-2) could be converted back to a redox-sensitive strain via complementation with intact bosRR39K (Seshu et al., 2004b), indicating that the phenotypic difference observed is due to the status of the bosR allele and is independent of lp5 and lp28-2.
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). Of these 88 ORFs, 66 (75 %) were located on the chromosome and 22 on plasmids (25 %) (Fig. 2). Among the 88 significantly expressed ORFs, 51 had no known function, including 18 ORFs categorized as hypothetically conserved, 31 as hypothetical and two as ‘other’ by The Institute for Genomic Research (TIGR; Fig. 3) (Fraser et al., 1997). Several genes of known function were also affected by inactivation of the bosRR39K allele, including superoxide dismutase (sodA), as well as all of the genes that define a putative glp operon involved in glycerol uptake and utilization (bb0240–bb0243). The observed induction of sodA is consistent with the increased resistance to oxidative stressors seen for JS167 (Seshu et al., 2004b), whereas the increased expression of the glp operon implies that BosRR39K represses genes important for physiological responses, specifically, the utilization of glycerol as a carbon source. Additional genes of interest include: (i) bb0116, a malX homologue involved in the transport of maltose and glucose (induced 5.25-fold); (ii) bb0042, a phoU homologue involved in the regulation of phosphate transport (induced 3.11-fold); and (iii) p66 (induced 1.83-fold), a putative porin (Skare et al., 1997) and integrin adhesin (Coburn & Cugini, 2003). In the case of the malX and phoU borrelial homologues, the variable expression of these distinct transporters suggests that the compounds they import may affect cellular homeostasis and directly or indirectly alter the observed response to oxidative stressors. The induction of p66 suggests that metabolite transport may also be involved in the resistance to ROS. Two independent array-based studies have indicated that p66 is induced under host-adapted conditions independent of temperature (Brooks et al., 2003; Revel et al., 2002), and suggest that BosRR39K may directly or indirectly affect p66 transcription. Finally, the gene encoding a two-component regulatory protein (bb0763) exhibited decreased transcription in JS167 (Table 2). The bb0763 locus encodes a response regulator designated Rrp-2 that modulates the expression of rpoS in a RpoN-dependent manner (Yang et al., 2003). rrp-2 exhibited a 1.8-fold decrease in transcription in JS167. The reduction in rrp-2 transcripts in a borrelial cell that demonstrates significant resistance to ROS suggests that the two-component system does not require additional Rrp-2 to mediate this response. It is interesting to note that the transcriptional profiles for sodA, p66 and rrp-2 observed in the JS167 isolate are identical in infectious B. burgdorferi isolate MSK5 (J. A. Hyde and J. T. Skare, unpublished observations), suggesting that these genes play a key role in the ROS-resistant phenotype observed in these strains.
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; Brooks et al., 2003; Ojaimi et al., 2003; Tokarz et al., 2004), the comparison presented herein indicated that the quantitative RT-PCR and macroarray analyses yielded a correlation coefficient (r) of 0.70, indicative of a linear relationship between these two methodologies. It is important to note that the RNA used for quantitative RT-PCR analysis was isolated independently from that used for the macroarray. In most cases the same trend in the expression of a given gene between these different experimental modalities was observed (Fig. 4).
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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). Each stage in the transmission of the pathogen and the subsequent dissemination within the host(s) represents a unique and complex environment for the spirochaete. Within the midguts of unfed Ixodes ticks, the dissolved oxygen level would presumably be quite low; however, once a tick takes a blood meal, temperature and respiration would increase, resulting in a concomitant increase in the levels of dissolved oxygen. Thus, as B. burgdorferi transits from the infected arthropod vector to the mammalian host(s), it must adapt and respond accordingly to oxygen and its potentially toxic byproducts.
ROS, such as superoxide anion, hydrogen peroxide and hydroxyl radicals, can damage DNA, proteins and lipids, and are an important parameter in a non-specific host defence toward pathogens. In addition, as a consequence of respiration, ROS can be generated endogenously within bacterial cells, causing potentially lethal damage (Mongkolsuk & Helmann, 2002; Storz & Imlay, 1999). In response to these threats, micro-organisms have evolved several adaptable responses that sense oxidation and modulate the expression of appropriate genes. One such regulatory system is defined by PerR, a metalloregulatory protein of the Fur family of regulators (Bsat et al., 1998; Fraser et al., 1997). In Bacillus spp. and Staphylococcus aureus, PerR alters global gene expression in response to oxidative stress (Helmann et al., 2003; Horsburgh et al., 2001a). Under conditions of low redox in Bacillus spp., PerR binds to DNA and represses transcription of catalase (katA), peroxidases (ahpC, ahpF), a non-specific DNA binding protein (dps), and the regulatory locus fur (Fuangthong et al., 2002; Herbig & Helmann, 2001). Furthermore, in S. aureus, PerR is autoregulatory (Horsburgh et al., 2001a, b). The repressor activity of PerR in Bacillus is dependent on metal binding involving coordination of Mn2+, Fe2+ or Zn2+ (Helmann et al., 2003). Another redox-responsive transcriptional regulator is OxyR, which is activated by the oxidation of cysteine disulfide bonds that induce genes involved in the oxidative stress response (Aslund et al., 1999; Zheng et al., 1998, 2001). OxyR is able to bind DNA in the reduced or oxidized state; however, it is only able to activate transcription when oxidized (Aslund et al., 1999). By analogy with other bacterial systems, some of the candidate genes that might constitute an oxidative stress regulon in B. burgdorferi include homologues to sodA (Nichols et al., 2000; Whitehouse et al., 1997), dps (napA), thioredoxin reductase (trxB), thioredoxin (trxA) and a CoA disulphide reductase (cdr; previously annotated as nox) (Boylan et al., 2006). To date no gene encoding a catalase or peroxidase has been identified in the B. burgdorferi genome.
In support of the hypothesis that BosR regulates the oxidative stress response in B. burgdorferi, sodA was significantly induced in JS167 relative to its genetic parent, CHP100 (Table 2
). The transcriptional profile analysis also identified many genes of unknown function, suggesting that some of these loci may contribute to the resistance to ROS observed. Most genes identified generally had no predicted function, and no bias toward any particular paralogous family was observed (Fig. 3). Whether any of these genes are associated with the oxidative stress response will require additional characterization.
In addition to genes that could be overtly linked to redox resistance, analysis also indicated that the glp operon, composed of glpF, glpK, bb0242 and glpA, was induced in borrelial strains that were resistant to ROS. It is worth noting that the glp operon is also induced at 23 °C relative to 35 °C (Ojaimi et al., 2003), and, in that study, Ojaimi and others speculate that the glp operon may be required for borrelial cells to generate ATP as an adaptive response to low temperature. Data that indicate that JS167 induces the glp operon imply again that energy acquisition, via the metabolism of glycerol and its incorporation into the glycolytic pathway (Schwan et al., 2003), is an important parameter in the oxidative stress response. Alternatively, it is tempting to speculate that the glp operon is used secondarily to eliminate or metabolize oxidized lipids. In this hypothetical scenario, oxidized lipids would be deacylated by an as yet unknown lipase, with the resulting glycerol phosphate backbone shuttled into the glycolytic pathway in the form of either glyceraldehyde 3-phosphate or dihydroxyacetone phosphate (following an oxidation reaction mediated by a dehydrogenase in both cases).
Increased expression of the putative porin and integrin adhesin p66 was also observed (Table 2). Previous transcriptional profile analysis of B. burgdorferi incubated within the peritoneal cavity of rats has indicated that p66 is induced under these conditions (Brooks et al., 2003). Earlier studies have estimated that interstitial fluid has significantly reduced dissolved oxygen levels (Siegemund et al., 1999; Venkatesh et al., 2000) and it is probable that the conditions within the peritoneal cavity have a comparable oxygen tension. If so, it is likely that p66, amongst other genes, is redox-regulated in a manner that may be directly or indirectly affected by BosR. DbpA, a decorin-binding protein, has been shown previously to have a higher level of synthesis in JS167 relative to the non-infectious CHP100 parent (Seshu et al., 2004b). This corresponds with the observed transcriptional data for dbpA, with a 7.14-fold increase in expression and a P value 0.043, which fell slightly outside of the predetermined statistical parameter (data not shown). Thus, by analogy to dbpA, it is possible that BosR may regulate other genes that are also important in mammalian host adaptation and/or pathogenic mechanisms.
One of the two two-component regulatory systems found in B. burgdorferi was not transcribed to the same extent in the ROS-resistant JS167 strain relative to CHP100 (Table 2). This two-component system, defined by bb0763 and bb0764, encodes the response regulator rrp-2 and its cognate sensor kinase, respectively. Rrp-2 works together with borrelial RpoN to activate expression of RpoS, which in turn results in the transcription of several unlinked genes, including ospC, dbpA and mlp8 (Hubner et al., 2001; Yang et al., 2003). Although unproven for this particular two-component system, several sensor kinases respond to the redox environment of the cells (Chou et al., 1993). It is thus possible that BB0764 senses the redox status of B. burgdorferi and responds accordingly. If this hypothesis is true, then it is possible that an overlap or cooperative effort between the BosR and the RpoN-RpoS regulatory pathways may exist.
In order to determine if commonly expressed genes have a BosR binding consensus sequence that might define a regulon, the upstream sequences of several of the genes listed in Table 2 were compared and analysed. Phenogram analysis of the putative promoter regions of ORFs significantly expressed in JS167 did not identify any significant consensus sequence for a possible BosR regulatory binding site (data not shown), suggesting that BosRR39K alters the regulation of some of these genes indirectly.
A clonal isolate of non-infectious B. burgdorferi, CHP100, was used to isolate the strain (JS167) containing the bosRR39K : : kanR allele (Seshu et al., 2004b). CHP100 lacks cp9, lp25, lp28-4, lp36 and lp38, contributing to the non-infectious status of the isolate (Fig. 1). After isolating the bosRR39K : : kanR mutant, the levels of lp5 and lp28-2 were found to be reduced in this clonal isolate (Fig. 1). A role for lp5 and lp28-2 in the redox-resistant phenotype observed seems unlikely, based on the previous observation that the redox-resistant bosRR39K : : kanR isolate can be converted back to a redox-sensitive strain by adding intact bosRR39K alone in trans (Seshu et al., 2004b). As such, if lp5 or lp28-2 were important in the redox-resistant phenotype, then one would expect that the aforementioned genetic complementation would not reverse the redox-resistant phenotype. This effect, coupled with the previous observation that the bosRR39K : : kanR strain JS167 is as resistant to ROS as the infectious clonal isolate MSK5 (Seshu et al., 2004b), suggests that genes common to these isolates, either chromosomally or plasmid encoded, are responsible for the phenotype observed. Also, the effect of lp5 and lp28-2 in the resistance to ROS is further marginalized, in as much as all seven genes on lp5 and 20 of the 32 ORFs on lp28-2 have paralogues on one or several other plasmids, or within the chromosome, indicating that most of the activity lost from both of these plasmids could be provided by distal genes throughout the genome. Finally, none of the lp5 or lp28-2 paralogues was significantly expressed in the JS167 strain, suggesting that these genes do not contribute to the ROS resistance observed.
This study globally analysed the transcriptional profile of a B. burgdorferi mutant and its parental derivatives to begin defining genes involved in the oxidative stress response. The ideal study would directly investigate redox regulation via BosR, but the isolation of a bosR mutant within an infectious B. burgdorferi background has been unsuccessful. This is due presumably to the conditional lethality associated with the absence of bosR and the effect that this BosR deficiency has on borrelial viability. It is conceivable that under the proper experimental growth conditions, a bosR mutant can be isolated and characterized. In the interim, it is possible to address the potential role of a subset of genes identified in this analysis by genetically inactivating these loci and/or by conducting BosR-specific gel shift or footprint assays, to establish a link with their role in the borrelial oxidative stress response, and to ascertain whether BosR binds to regulatory domains within these genes, respectively. Experiments to characterize these genes, and thus refine the putative borrelial BosR regulon, are currently under way.
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ACKNOWLEDGEMENTS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONREFERENCES |
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Received 14 March 2006;
revised ;
accepted 18 May 2006.
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