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Infection and Immunity, October 2006, p. 5848-5859, Vol. 74, No. 10
0019-9567/06/$08.00+0 doi:10.1128/IAI.00755-06
Copyright © 2006, American Society for Microbiology. All Rights Reserved.
Australian Bacterial Pathogenesis Program,1 Department of Microbiology, Victorian Bioinformatics Consortium, Monash University, Victoria 3800, Australia,2 David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California 90095,3 Division of Infectious Diseases, Veteran Affairs Greater Los Angeles Healthcare System, Los Angeles, California 90073,4 Bacterial Diseases of Livestock Research Unit, National Animal Disease Center, USDA Agricultural Research Service, Ames, Iowa 50010,5 Australian Research Council Centre of Excellence in Structural and Functional Microbial Genomics, Monash University, Victoria 3800, Australia6
Received 12 May 2006/ Returned for modification 20 June 2006/ Accepted 8 July 2006
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There is some limited information about how Leptospira responds at the transcriptional or translational level to different temperatures, but no studies at a global level have been conducted. Leptospires respond to temperature upshift by the increased synthesis of standard heat shock proteins, such as GroEL, DnaK, and Hsp15 (4, 5, 25, 38). The peripheral membrane protein P31LipL45, also known as Qlp42, was shown in one study to be up-regulated by a temperature shift from 30°C to 37°C (25) and, in another study, to be up-regulated by transition from the log phase of growth to the stationary phase (23). The expression of LipL36, an outer membrane lipoprotein which is known to be down-regulated in vivo and in stationary phase (11), was also shown to be reduced at 37°C (9, 27) and under low iron concentrations (9). Other undefined outer membrane proteins have also been shown to be temperature regulated (9). On the other hand, the expression of the outer membrane lipoproteins LipL21, LipL41, LipL48, and others was unaffected by temperature (9, 27). Interestingly, the most abundant leptospiral surface protein, LipL32 (10), undergoes processing into a range of mass and pI isoforms, with the processing varying at different temperatures (9, 47). In contrast, the amount of leptospiral lipopolysaccharide produced was shown to be diminished on bacteria recovered from acutely infected guinea pig liver but not on leptospires chronically colonizing rat renal tubules (26). The Lk73.5 sphingomyelinase was also detected in leptospires grown in vivo but not in vitro (2). The environmental cue(s) for these changes are unknown.
Global analysis of gene expression on pathogenic bacteria has yielded important information on genes required for host adaptation and potential virulence-associated genes. For example, microarray analysis of the tick-borne Lyme disease spirochete Borrelia burgdorferi at 23°C and 37°C to simulate the environment encountered in unfed and fed ticks confirmed the previously known down- and up-regulation paradigm of OspA and OspC, respectively (33, 45), and was therefore able to identify a range of genes responsive to the fed tick environment and subsequently to conditions found in the mammalian host environment, although differences identified in the two studies do raise possible limitations of array studies. The majority of differentially expressed genes were those involved in cell envelope biosynthesis, energy metabolism, motility and chemotaxis, and protein synthesis and those encoding transport and binding proteins. Many genes of unknown function were both up- and down-regulated. Interestingly, the change in expression of many of these genes was transitory and returned to base levels after adaptation to the mammalian host (33). The identification of a subset of differentially expressed genes generated a priority subset for characterization with respect to their roles in pathogenesis (7). In the swine pathogen Haemophilus parasuis, microarray analysis under a range of conditions, including temperature stress, identified a total of 75 differentially regulated genes, which encoded iron and sugar transporters, metabolic enzymes, and proteins of unknown function (24). Likewise, temperature shift of Mycoplasma hyopneumoniae from 37°C to 42°C to mimic conditions encountered during febrile infection identified a range of known heat shock proteins as well as 54 genes encoding proteins with unknown function (20).
The availability of the two highly related genome sequences for serovars Lai and Copenhageni of L. interrogans (29, 32) allows, for the first time, the possibility of examining global changes in gene expression of Leptospira growing at different temperatures and also the comparison of profiles following temperature upshift with those after long-term growth.
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Microarray construction. A revised annotation of the L. interrogans serovar Lai strain 56601 genome (which includes 3,626 coding sequences, 36 tRNA genes, and 4 rRNA genes) (http://vbc.med.monash.edu.au/genomes/) was used to design oligonucleotides of 70 bases in length using the program ArrayOligoSelector (http://arrayoligosel.sourceforge.net/). The program first calculates scores of uniqueness, sequence complexity, lack of self-binding, and GC content for every candidate oligonucleotide. The second part of the program then uses scores generated by the first program to select the optimal oligonucleotide for each gene. Since the program has a bias for the 3' end of genes, genes were trimmed to a maximum of 750 bases, while 50 of the longest open reading frames (ORFs) and pseudogenes were represented by a 5' and 3' oligonucleotide. L. interrogans serovar Lai possesses 6 insertion sequences with multiple copies; each unique transposase was represented by one oligonucleotide on the microarray.
The microarrays were printed by the Australian Genomics Research Facility onto Nexterion Slide A+ substrates (Schott, Louisville, KY). Each oligonucleotide was printed in pairs in 16 subarrays, each with a 22-column by 24-row configuration. The 16 subarrays were printed in duplicate so that each oligonucleotide was present in quadruplicate.
Experimental design. Three independent RNA samples (biological replicates) from L. interrogans serovar Lai grown at 20°C, 30°C, 37°C, and 39°C were cross-compared in a loop design (15) (Fig. 1). Three independent RNA samples were also obtained from the 37°C upshift cultures which were paired with the three 30°C and 37°C RNA samples (Fig. 1).
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FIG. 1. Experimental design for comparison of transcriptional differences at each of the four temperatures: 20°C, 30°C, 37°C, and 39°C. Each line represents a direct hybridization between the two samples, with the arrow going from the Cy3 to the Cy5 channel for biological replicate sets 1 and 3. The opposite orientation of Cy3 to Cy5 was used for biological replicate set 2. For the comparison of 30°C and 37°C samples with the overnight 37°C upshift samples, two hybridizations (dye swaps) were performed for each of the three biological replicates.
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Preparation of probes for microarray hybridizations. Labeled cDNA probes were synthesized from 2.5 µg of total RNA using random primers contained in the 3DNA Array 900MPX expression array detection kit (Genisphere, Hatfield, PA) according to the instructions of the manufacturer. The cDNA hybridization mix was made using the 2x formamide-based hybridization buffer (vial 7) from the 3DNA Array 900MPX expression array detection kit (Genisphere) to a final volume of 50 µl.
Microarray hybridizations. The microarray was prehybridized using a solution containing 25% formamide, 5x SSC (1x SSC consists of 0.15 M NaCl with 0.015 M sodium citrate), 0.1% sodium dodecyl sulfate, 10 mg/ml bovine serum albumin, and 1 mg/ml sheared herring sperm DNA. The solution was placed on the microarray under a coverslip, and incubation was carried out for 45 min in a slide hybridization chamber (Corning, Inc., Big Flats, NY) placed in a 50°C water bath, after which the slides were washed in ultrapure H2O and dried by centrifugation at 1,000 x g for 3 min. Hybridization with the cDNA hybridization mix, 3DNA hybridization mix, and washes were carried out as per the 3DNA Array 900MPX expression array detection kit (Genisphere) protocol. The cDNA hybridization mix and 3DNA hybridization mix were both made up using 2x formamide-based hybridization buffer (vial 7) to a final volume of 50 µl and applied onto the microarray under a 22- by 40-mm LifterSlip (Erie Scientific Company, Portsmouth, NH). The cDNA hybridization was carried out at 50°C overnight, while the 3DNA hybridization was done at 50°C for 4 h. After the final set of washes, slides were dried by centrifugation at 1,000 x g for 3 min and scanned immediately.
Analysis of microarray images. Microarray hybridizations were scanned using a GMS 418 array scanner (Genetic MicroSystems, Inc., Woburn, MA). The Cy3 and Cy5 images were aligned then overlaid with a grid using ImaGene version 5.1 (Biodiscovery, El Segundo, CA) to allow accurate gene identification and quantification of fluorescence intensity. Spots were examined manually, and poor spots were flagged for elimination from the analysis.
The four temperature conditions were examined using all six pairwise comparisons. Each comparison had three biological replicates, one being a dye-swap, resulting in 18 arrays (Fig. 1). Each array was background corrected using the "normexp" method from Limma (36), which provides smooth transformations of the intensities and results in only positive values. Each array was normalized independently using print-tip loess normalization (46). The log ratios from the arrays were then scaled such that all arrays had the same median absolute deviation. The Limma package was then used to fit a linear model to each gene, taking into account the correlation between replicate spots (37). For each gene, the coefficients from the linear model were then used to calculate the relative change for all six pairwise comparisons. The moderated t statistics and associated P values were calculated using empirical Bayes (36). The P values were then adjusted for multiple testing to control the false-discovery rate. Genes with an absolute relative ratio of greater than 1.5, and significant at a P value of <0.05, were selected as differentially expressed.
Further analysis was performed to compare the two lower-temperature conditions to the two higher-temperature conditions to represent environmental and physiological conditions, respectively. This was an analysis of a pool of the 20°C and 30°C data against the 37°C and 39°C data. The normalization and fitting of linear models were as described above. A contrast was then computed to pool the appropriate conditions. Again, the moderated t statistics were computed, and genes were selected as differentially expressed if they had a greater than 1.5-fold change and an adjusted P value of <0.05.
Raw data from the direct comparisons between 37°C upshift versus 30°C or 37°C long-term passaging were analyzed using the web-based program BioArray Software Environment (34). Raw data from replicate arrays (6 for each comparison) were combined and used for further analyses. Spot-specific median signals were corrected for local background by subtracting spot-specific median background intensities. Spots with very low intensities (<250) were omitted, and the data were normalized using the global median ratio, which scales the intensities such that the median of the ratio between the Cy3 and Cy5 channels is 1 while omitting spots within 5% of the highest or lowest intensities. Each array was then normalized independently using loess per print tip group, followed by normalization between replicate arrays such that they all had the same median absolute deviation. As before, genes were considered to be differentially expressed if they were at least 1.5-fold up- or down-regulated with a P value of <0.05 as determined by the Student t test.
Validation of microarray data by real-time RT-PCR. Primer Express software (ABI, Foster City, CA) was used to design primers for real-time reverse transcription (RT)-PCR. RT reaction mixtures contained 2 to 10 µg of total RNA, 30 µg of random hexamers, 10 U of Superscript II (Invitrogen) reverse transcriptase, and 500 µM concentrations (each) of dATP, dCTP, dGTP, and dTTP. Samples were incubated at 42°C for 2.5 h, followed by 15 min at 70°C. The synthesized cDNA was then diluted 1/80 prior to use in real-time PCR. Reactions were done in triplicate. Each 25-µl reaction mixture contained 2.5 µl of cDNA, 50 nM concentrations of each gene-specific primer (Table 1), and 12.5 µl of SYBR green PCR master mix (ABI). Real-time PCR was carried out using an ABI PRISM model 7700 sequence detection system. Known concentrations of L. interrogans serovar Lai genomic DNA were used to construct a gene-specific standard curve so that the concentration of template in each reaction mixture could be determined. The gene encoding flagella subunit B, flaB, was used as the normalizer for all reactions. Melting curve analysis confirmed that all PCRs amplified a single product.
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TABLE 1. Oligonucleotides used for real-time quantitative RT-PCR
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Gene expression of L. interrogans grown at each of the temperatures was compared in a loop design (Fig. 1) so that differences between two different temperatures could be compared directly as well as indirectly via another sample in the loop. For example, gene expression at 20°C can be compared directly to expression at 30°C, but the two conditions can also be indirectly compared via the 37°C and 39°C samples. This method of analysis is more powerful than simply using the three biological replicates for any two given conditions, since it allows the use of the other arrays as if they were against a common reference. The loop design has been shown to be more efficient than the reference design where multiple samples are compared using a common reference sample (43).
Genes that were at least 1.5-fold up- or down-regulated at a confidence level of 95% were considered to be differentially expressed. Other studies have found that a 1.5-fold change in gene expression can be biologically relevant (13, 35). The number of genes that were differentially expressed in each pairwise comparison is shown in Table 2. The greater the differences between temperatures, the more genes were found to be differentially expressed.
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TABLE 2. Number of genes differentially expressed in L. interrogans grown at the first temperature compared to the second temperature
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FIG. 2. Proportion of up-regulated (A) and down-regulated (B) genes in each general COG grouping expressed as a percentage of the total number of differentially expressed genes in each comparison. The percentage of genes up- or down-regulated in the first temperature compared to the second in three biological replicates is shown for each general COG grouping.
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TABLE 3. Number of genes differentially expressed in L. interrogans in the first temperature pool compared to the second temperature pool
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TABLE 4. L. interrogans genes of known or predicted function which were up-regulated at physiological temperatures compared with environmental temperatures in three sets of biological replicates
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TABLE 5. L. interrogans genes of known or predicted function which were down-regulated at physiological temperatures compared with environmental temperatures in three sets of biological replicates
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Two ORFs (LA0872 and LA3652) encoding the alternative sigma subunit
E were found to be 1.5- and 2-fold up-regulated, respectively. Sigma factors are directly involved in transcription of sets of genes, and their expression is induced in response to stress. In E. coli, the rpoE gene was found to be essential for bacterial growth at high temperatures (12), while in Salmonella enterica serovar Typhimurium,
E facilitates survival under nutritional deprivation and oxidative stress and is strongly induced upon reaching stationary phase (41). In other bacteria,
E has been found to play a role in virulence. For example,
E mutants of Vibrio cholerae were highly attenuated, with a marked decrease in their ability to colonize the intestine (16), while nontypeable Haemophilus influenzae requires
E expression to persist in mammalian cells and survive in macrophages (8). Since L. interrogans rpoE was up-regulated at physiological temperatures relative to environmental temperatures, it is possible that leptospiral
E may regulate genes required for pathogenesis and/or virulence.
Cellular processes and signaling. Export of membrane proteins is mediated by the Sec pathway in conjunction with signal peptidase I (LepB), the lipoprotein synthesis pathway (Lgt, LspA, and Lnt), and proteins involved in transport and incorporation of lipoproteins into the outer membrane (LolA, LolC, and LolD). At physiological versus environmental temperatures, lnt (LA1124), lolD (LA1285), lolE (LA1284), and lepB were up-regulated, while another homolog of lnt (LA4078) was down-regulated. Genes encoding LolA (LA0410 and LA1136) and other copies of LolD (LA0274 and LA2982) and LolE (LA0273 and LA2983) were not significantly differentially expressed. It is likely that bacteria would need to express a different repertoire of outer membrane proteins to adapt to different conditions. Differences in expression of lnt, lolD, and lolE homologs suggest variation in the spectrum of lipoproteins expressed under the different temperature conditions. The lipoproteins LipL36 and Qlp42 were previously shown to be differentially expressed at the protein level at different temperatures (9, 11, 25, 27). However, these lipoproteins were not found to be differentially expressed in our experiments, suggesting regulation at the translational level.
In B. burgdorferi, changes in morphology, motility, and growth rate were observed in cultures grown at 35°C versus 23°C (42). The changes coincided with up-regulation of chemotaxis and sensing regulons as well as proteins involved in protein processing. Pathogens need to be able to sense and respond rapidly to different environmental signals. Therefore, it was unsurprising that many differentially expressed genes with known or predicted function encoded proteins involved in two-component signal transduction systems, chemotaxis, and motility. L. interrogans is a highly invasive pathogen and, therefore, motility is likely to play a major role in the disease process. Motility and chemotaxis are essential for the organism to target and migrate to specific organs and initiate infection. Three genes involved in endoflagellar synthesis or encoding components of endoflagella were differentially expressed in L. interrogans grown at physiological versus environmental temperatures. However, while flgC was up-regulated, flgA and flgK were down-regulated. Since these genes are found on different parts of the genome and do not constitute an operon, it is conceivable that different endoflagellar-related genes would undergo different mechanisms of regulation to modulate flagellar structure and/or rotary speed in response to environmental cues.
Several genes encoding chaperones or proteins involved in the stress response were differentially expressed, such as clpA, htpG, and htpX. The uspA gene, which is commonly found across several bacterial species to be up-regulated under stress conditions (17), was also 1.9-fold up-regulated at physiological temperatures. However, genes encoding proteins commonly expressed in response to heat shock, such as GroEL and DnaK, were not found to be differentially expressed in our experiments despite being shown to be up-regulated at the protein level (5, 38). In B. burgdorferi, genes encoding typical heat shock proteins, such as GroEL and DnaK, were also not up-regulated by temperature shift (30). Expression of ClpA, which performs the ATP-dependent chaperone function of DnaK and DnaJ (44), was up-regulated 3.5-fold at physiological temperatures, while a DnaJ-related molecular chaperone was down-regulated 1.5-fold. Therefore, it appears that in spirochetes which are able to survive in a range of temperatures either in the environment or in a host, transition and subsequent adaptation to higher temperatures does not induce a substantial heat shock or stress response.
Metabolism. A broad range of metabolic genes was differentially expressed. It is unclear why genes involved in cobalamin synthesis would be expressed at lower levels at physiological versus environmental temperatures, or conversely, expressed more highly at the lower temperatures. Although vitamin B12 is a component of EMJH in vitro growth medium, it appears that metabolic requirements differ at physiological versus environment temperatures, and for reasons unknown, de novo synthesis at lower temperatures is necessary. Genes encoding proteins involved in defense against oxidative stress were also up-regulated at physiological temperatures, namely katE (which encodes a catalase) and btuE (encoding a glutathione peroxidase). Several genes involved in transport of nutrients and ions across the outer membrane were differentially expressed. Those that were up-regulated at physiological temperatures include genes involved in potassium and copper transport, trkA and copZ, respectively, as well as LA3242, which encodes a homolog of a TonB-dependent receptor. Genes involved in amino acid transport and metabolism, lysC and aroK, were down-regulated at physiological versus environmental temperatures. Lipid metabolism and, therefore, lipid composition of the membrane and lipopolysaccharide may also be altered at physiological temperatures due to up-regulation of caiA (acyl coenzyme A [acyl-CoA] dehydrogenase involved in ß-oxidation of fatty acids), desA (fatty acid desaturase), and an epimerase homolog. A glycosyltransferase homolog and another acyl-CoA dehydrogenase homolog were down-regulated at physiological temperatures compared to environmental temperatures.
Effects of temperature upshift on gene expression patterns. To identify genes which are potentially involved in establishment of disease upon entry into the host from the environment, early- to mid-log-phase cultures of L. interrogans were subjected to overnight (16 to 20 h) upshift from 30°C to 37°C. Gene expression levels from these upshifted cultures were compared to those from cultures grown at 30°C long term and also with cultures grown at 37°C long term to identify genes which may be involved in long-term adaptation to the host environment. Table 6 shows the number of genes which were found to be differentially expressed in each upshift comparison. The number of genes that were up- or down-regulated in each COG category for 37°C upshift versus 30°C long term and 37°C upshift versus 37°C long term are shown in Fig. 3 and 4, respectively. For full lists of differentially expressed genes in each upshift comparison, refer to Tables S3 and S4 in the supplemental material. The 37°C upshift versus 30°C long term comparison showed the greatest number of differentially expressed genes of all comparisons in this study, a finding consistent with the notion that many changes in gene expression are indeed required for the immediate and/or short-term transition from environmental temperatures to physiologically relevant temperatures. Again, many of the genes found to be differentially expressed in both of the upshift comparisons are those encoding hypothetical or poorly characterized proteins (53% of those at 37°C upshift versus 30°C long term and 61% at 37°C upshift versus 37°C long term).
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TABLE 6. Number of genes differentially expressed in L. interrogans during 37°C overnight upshift compared to L. interrogans grown at 30°C and 37°C long term
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FIG. 3. Number of differentially expressed genes by COG category during overnight upshift to 37°C compared with long-term growth of L. interrogans at 30°C across three sets of biological replicates. The COG functional categories are as follows: information storage and processing (11.2% of coding sequences in L. interrogans serovar Lai genome) (includes J, translation; K, transcription; L, replication, recombination, and repair); cellular processes and signaling (19% of coding sequences in the serovar Lai genome) (includes D, cell cycle control, cell division, chromosome partitioning; V, defense mechanisms; T, signal transduction mechanisms; M, cell wall, membrane, or envelope biogenesis; N, cell motility; U, intracellular trafficking, secretion, and vesicular transport; O, posttranslational modification, protein turnover, chaperones); metabolism (18.9% of coding sequences in the serovar Lai genome) (includes C, energy production and conversion; G, carbohydrate transport and metabolism; E, amino acid transport and metabolism; F, nucleotide transport and metabolism; H, coenzyme transport and metabolism; I, lipid transport and metabolism; P, inorganic ion transport and metabolism; Q, secondary metabolite biosynthesis, transport, and catabolism); poorly characterized (50.9% of coding sequences in the serovar Lai genome) (includes R, general function prediction only; S, function unknown; and , not in COGs).
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FIG. 4. Number of differentially expressed genes by COG category during overnight upshift to 37°C compared with long-term growth of L. interrogans at 37°C across three sets of biological replicates. The COG functional categories are as described in the legend to Fig. 3.
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As observed in the physiological versus environmental comparison, many genes that were differentially expressed upon upshift from 30°C to 37°C are involved in signal transduction mechanisms, chemotaxis, or processing of membrane proteins (COG functional categories T and M), a not unexpected finding, given that pathogens need the ability to respond rapidly to changes upon invasion of a host.
Validation of microarray data by real-time RT-PCR. Real-time quantitative RT-PCR was used to validate the microarray data. Six genes which appear in at least 2 of the 3 gene lists (physiological versus environmental and the two temperature upshift lists) were selected at random. The flaB gene did not show any variation in expression under the different temperature conditions and, therefore, was used for normalization. There was a high correlation between the expression values obtained by microarray analysis and those measured by quantitative real-time RT-PCR for all three comparisons (r > 0.95) (Fig. 5).
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FIG. 5. Comparison of real-time RT-PCR and microarray data. Six genes which appear in at least 2 of the 3 gene lists (physiological versus environmental [A], 37°C upshift versus 30°C [B], and 37°C upshift versus 37°C [C]) were selected at random for real-time RT-PCR analysis. The correlation coefficient (r) in each case was >0.95.
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TABLE 7. Comparison of differentially expressed genes with known or predicted function that are common between the physiological versus environmental and 37°C upshift gene lists
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A subset of genes appears to be transiently expressed or switched off. These genes are differentially expressed in the upshift comparisons but not at physiological versus environmental temperatures. The exception to this was ligB, which was 1.6-fold down-regulated at physiological versus environmental temperatures but 1.7-fold and 2.2-fold up-regulated during 37°C upshift versus 30°C long term and 37°C long term, respectively. This supports data from previous studies which found that ligA and ligB are expressed by low-passage virulent strains of L. interrogans serovar Copenhageni, but expression is lost upon repeated subculturing, which is concurrent with loss in virulence (21, 31). L. interrogans serovar Lai lacks a copy of ligA but has ligC as well as ligB (28, 32). At 37°C upshift versus 30°C long term, ligC was also up-regulated by 1.6-fold (see Table S3 in the supplemental material), while there was no significant difference in expression at 37°C versus 37°C long term. Taken together, our microarray data indicate that ligB and ligC are expressed immediately upon exposure to stress or sudden changes in environmental cues and may assist in initial colonization and establishment of disease in the host. Expression of ligB and other genes in the transiently expressed subset may continue during infection of the host, but in our experiments, in the absence of other environmental cues apart from upshift in temperature, ligB expression decreased with prolonged culturing at 37°C. Osmolarity has also been found to induce expression of LigB (22), and due to its similarity to other bacterial host cell adherence and invasion proteins, such as invasin in Yersinia spp. and intimin in enteropathogenic E. coli, it is thought that LigB is also likely to play a similar role in pathogenesis (21).
Another interesting, transiently up-regulated gene was cheW, which encodes a chemotaxis-related protein. In E. coli, CheW is a coupling protein which stabilizes the complex between CheA, a histidine kinase, and its receptor. CheW expression was also found to be up-regulated in B. burgdorferi in response to temperature upshift and the presence of blood (42). A motility-associated gene, flgL, was also transiently up-regulated, but flgC and flgA were found to exhibit no change in expression upon temperature adaptation. It can be surmised that flagellar activity and structure may need to be modulated upon host entry and during the course of infection.
Of the three genes consistently expressed across all three gene lists, up-regulation of uspA, which encodes a universal stress protein, implies that growth at and transition to higher temperatures is stressful to the organism.
Concluding remarks. We have identified genes which are differentially expressed under different temperature conditions. Furthermore, we have conducted a novel investigation into differences in long- and short-term changes in gene expression in response to temperature. However, proteins which were shown in previous studies to be differentially expressed at different temperatures, namely LipL36 (9, 27) and Qlp42 (25), were not found to be differentially expressed in our experiments. It is thus possible that regulation of these proteins occurs at the translational level rather than during transcription.
Genes that were found to be up-regulated may potentially be involved in colonization of the host and/or the early stages of pathogenesis. Differentially expressed genes of unknown function may hold clues to processes involved in establishment of disease and persistence in host species.
This work was supported by a grant from the National Health and Medical Research Council Program in Medical Genomics, Canberra, Australia (B.A.), by NIH grant AI-34431 (D.A.H.), and by VA Medical Research funds (D.A.H.).
Supplemental material for this article may be found at http://iai.asm.org/. ![]()
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