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Department of Veterinary Microbiology and Preventive Medicine, Iowa State University, Ames, IA 50011, USA
Correspondence
F. Chris Minion
fcminion{at}iastate.edu
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTS AND DISCUSSIONREFERENCES |
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The Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo) accession number for microarray data for this paper is GSE8494.
A supplementary table with details of genes differentially expressed during exposure to 100 µM norepinephrine and a supplementary figure showing the locations of significantly regulated genes on the M. hyopneumoniae chromosome are available with the online version of this paper.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTS AND DISCUSSIONREFERENCES |
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, 2001). The mechanisms involved in colonization and disease are not well understood. In experimental systems, pathogen-free pigs infected with M. hyopneumoniae present a progressive lung disease until about 28 days, at which time the disease slowly resolves, reaching a chronic state of infection. Depending upon the strain, lesions can involve up to 30 % of the lung at the height of disease, and in many animals, the organism is never completely eliminated. In more conventional piggeries, an important effect of M. hyopneumoniae in the respiratory tract is to increase the severity of disease caused by other pathogens such as Pasteurella multocida, PRRSV (Thacker et al., 1999a) and PCV2 (Opriessnig et al., 2004). To achieve this, M. hyopneumoniae must circumvent the host immune response, both the innate and adapted phases.
Adherence mechanisms have been studied (Djordjevic et al., 2004; Hsu et al., 1997; Jenkins et al., 2006) and the genome sequence is now available (Minion et al., 2004), but the fundamental processes used by M. hyopneumoniae to effect changes to the host immune response have not been elucidated. In previous studies, transcriptional responses of M. hyopneumoniae to heat shock, iron deprivation and oxidative stress, all environments encountered in vivo, have been analysed using microarrays (Madsen et al., 2006a, b; Schafer et al., 2007).
Recently, the responses of bacterial pathogens to the host stress factors epinephrine and norepinephrine have been studied with surprising results (Waldor & Sperandio, 2007). Originally it was thought that bacteria would not respond to mammalian signalling molecules such as catecholamine neuroendocrine hormones, but this has not been the case. Several different bacterial species have been shown to respond, notably by increasing growth rates and inducing virulence factors. Freestone et al. (2007) showed that Escherichia coli O157 : H7 and Yersinia enterocolitica increased their growth rate when exposed to epinephrine and norepinephrine. E. coli O157 : H7 demonstrated a twofold increase not only in growth rate but also in shiga toxin production when stimulated with norepinephrine (Voigt et al., 2006). In addition, enhancement in attaching and effacing lesions occurs as a consequence of AI-3 and norepinephrine binding (Reading et al., 2007) resulting in increased binding to murine caecal mucosa (Chen et al., 2003). It is also interesting to note that the AI-3 receptor QseC serves as the epinephrine/norepinephrine receptor in E. coli O157 : H7 (Clarke et al., 2006). Bansal et al. (2007) also showed that norepinephrine affected E. coli O157 : H7 chemotaxis and adherence to HeLa S3 cells. Another recent study of E. coli transcription levels showed that several virulence factor transcripts were upregulated in response to norepinephrine as well as iron-acquisition systems and SOS-response genes (Dowd, 2007).
Other studies have noted changes by pathogens in response to norepinephrine. Klebsiella pneumoniae, Pseudomonas aeruginosa, Enterobacter cloacae, Shigella somnei and Staphylococcus aureus showed increased growth rates when exposed to norepinephrine, which seemed to be due to iron availability (O'Donnell et al., 2006). In Vibrio parahaemolyticus, the modulation of virulence factors was observed (Nakano et al., 2007). Norepinephrine was shown to bind and upregulate the adherence protein OspA in Borrelia burgdorferi (Scheckelhoff et al., 2007). There was an increase in the pathogenic potential of Campylobacter jejuni (Cogan et al., 2006), and norepinephrine upregulated the gene for the ferric enterobactin outer-membrane receptor BfeA in Bordetella bronchiseptica and Bordetella pertussis, thereby enhancing growth (Anderson & Armstrong, 2006). Thus, many pathogens respond to host catecholamines by enhancing their growth and upregulating genes needed for colonization and survival in the host environment.
Norepinephrine release is one of the stress responses in lung infections, and thus it was of interest to better understand how M. hyopneumoniae might respond to a clinical level in broth culture. For these studies, microarrays were used to assess the transcriptional responses of M. hyopneumoniae following supplementation of growth media with norepinephrine. Interestingly, our results showed that M. hyopneumoniae demonstrated reduced growth and significant changes in transcript levels in response to norepinephrine exposure.
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTS AND DISCUSSIONREFERENCES |
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). Mycoplasma growth in the presence or absence of 50 or 100 µM norepinephrine (Sigma) was measured by colour-changing units (DeBey & Ross, 1994). To confirm the colour-changing unit results, DNA real-time PCR was performed on a time-course experiment measuring increases in mycoplasma DNA in the presence of 100 µM norepinephrine. Samples were collected at 0, 4, 24 and 48 h following addition of norepinephrine. Two hundred microlitres of culture was removed and DNA was extracted using the QIAamp DNA mini kit (Qiagen). The DNA was carefully eluted in 100 µl elution buffer. Real-time assays contained 2.5 µl template DNA, 50 nM forward primer (5'-CCAGAACCAAATTCCTTCGCTG-3'), 900 nM reverse primer (5'-ACTGGCTGAACTTCATCTGGGCTA-3') and 50 nM probe (5'-6_FAM-AGCAGATCTTAGTCAAAGTGCCCGTG-BHQ_1) with the Universal PCR master mix (Applied Biosystems) in a total volume of 25 µl. Primers were obtained from Integrated DNA Technologies. The following cycling parameters were used: 95 °C, 10 min; 40 cycles of 95 °C, 15 s; then 60 °C, 1 min. All real-time assays were performed on a Rotor-Gene RG-3000 (Corbett Research). Data were analysed according to Gallup & Ackermann (2006).
For microarray studies, twelve 250 ml flasks containing 150 ml culture were grown to early exponential phase as determined by colour change of phenol red. Norepinephrine from a 5 mM stock solution in water was added to six flasks to a final concentration of 100 µM, and all twelve flasks were incubated at 37 °C for 4 h. Cells were pelleted and stored at –70 °C in RNAlater (Ambion) as previously described (Madsen et al., 2006a).
Microarray.
The M. hyopneumoniae microarray consists of 618 PCR-amplified M. hyopneumoniae ORF gene products 125–350 bp in length. These products encompass 89 % (618/698) of the ORFs in the genome. The construction and validation of these arrays have been previously described (Madsen et al., 2006a).
Experimental design.
Six independent RNA samples from norepinephrine-exposed cultures were paired with six independent RNA samples from control cultures for hybridization to six two-colour microarrays. For three arrays, the control RNA sample was labelled with Cy3 dye and the experimental RNA sample was labelled with Cy5 dye; the dyes were reversed for the other three arrays to account for any dye bias.
RNA isolation.
RNA was isolated from frozen cell pellets using the Versagene RNA purification System (Gentra Systems). The manufacturer's protocol was followed with the exception of the DNase treatment, which was extended to 40 min. The filter cutoff of 150 bp prevented small RNA fragments from interfering in subsequent manipulations.
Target generation and hybridization.
Fluorescently labelled cDNA targets were generated with a 129 oligo-specific hexamer primer set used in previous studies (Madsen et al., 2006a). Fluorescently labelled cDNA was prepared by the incorporation of aminoallyl dUTP (Fermentas) during reverse transcription. Reverse transcription reactions contained 10 µg total RNA; 11.6 µg hexamer primers (Integrated DNA Technologies); 380 U Superscript III reverse transcriptase (Invitrogen); 1 mM each of dATP, dCTP, and dGTP; 200 µM dTTP; 400 µM aminoallyl dUTP; 10 mM dithiothreitol; and 1x RT buffer (Invitrogen). The reaction was allowed to proceed overnight at 42 °C. RNA was hydrolysed with 10 mM EDTA and 10 mM sodium hydroxide (final concentrations) for 10 min at 65 °C. The solution was neutralized with 500 mM HEPES pH 7.0, and the aminoallyl-labelled cDNA was then purified using the UltraClean PCR Clean-Up kit (Mo Bio Laboratories).
The subsequent coupling of Cy3 and Cy5 dyes (GE Healthcare) to the purified aminoallyl-labelled cDNA was performed in 17.5 µl reaction including 10 µl nuclease-free water, 1.5 µl 100 mM sodium bicarbonate (pH 9.0) solution (90 mM final concentration) and 6 µl dye. To prepare the dye, one vial of Cy3 (product PA23001, GE Healthcare) or Cy5 (product PA25001) was first dissolved in 72 µl DMSO, from which 6 µl aliquots were made and stored in the dark at –70 °C. The reaction was incubated at room temperature in the dark for a minimum of 2 h. The dye-labelled cDNA was then purified using the UltraClean PCR Clean-Up kit and dye incorporation evaluated by spectrophotometry (model ND-1000 NanoDrop, NanoDrop Techologies). After the purification of the labelled cDNA targets, they were hybridized to the array using the previously described protocol (Madsen et al., 2006a). Slides were washed using the Corning UltraGAPS slide wash protocol and dried by centrifugation at 1500 g for 2 min.
Data acquisition, normalization and data analysis.
After hybridization and washing, the arrays were scanned and analysed as described previously (Madsen et al., 2006a, b). Spot signals were corrected for background, transformed, and adjusted to a common median for each scan of the same array–dye combination. Locally weighted scatterplot smoother (LOWESS) normalization was applied and triplicate spots were averaged together to produce one normalized measurement for each probe on the array. A separate mixed linear model analysis was conducted for each probe sequence using the normalized data (Wolfinger et al., 2001). t-tests for differential expression between treatments were conducted for each probe in the mixed linear model analyses. P-values from these tests were converted to q-values using the method of Storey & Tibshirani (2003). These q-values were used to approximate the false discovery rate (FDR) for any given P-value as described by Benjamini & Hochberg (2000). Fold changes of expression between treatments were also estimated for each probe by taking the inverse natural log of the estimated mean treatment difference from our mixed linear model analyses.
Validation of microarray data.
Significant transcriptional differences between the treatment and control cultures were verified by qRT-PCR. Four upregulated (mhp008, mhp092, mhp549 and mhp684) and two downregulated genes (mhp034 and mhp078) were chosen for confirmation based on the magnitude of transcriptional change or their presumed importance in proliferation and virulence. The gene mhp345 was used as a control for RT reactions because it has not shown significant change in previous work (Madsen et al., 2006a, b) or this study. The qRT-PCR was performed using the Brilliant SYBR Green qRT-PCR kit (Stratagene), following the manufacturer's protocol. The primers used are listed in Table 1. Cycling was performed on the MyIQ Single-Colour Real-time-PCR Detection System (Bio-Rad). Data were analysed according to Gallup & Ackermann (2006).
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RESULTS AND DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTS AND DISCUSSIONREFERENCES |
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; Dowd, 2007; Freestone et al., 2007; Nakano et al., 2007). Surprisingly, norepinephrine slowed growth of M. hyopneumoniae cultures by approximately twofold (data not shown). Cultures with 100 µM norepinephrine took twice as long as control cultures to reach exponential phase as measured by colour changes. Cultures with 50 µM norepinephrine exhibited similar slowed growth but not as dramatic. To confirm this, a DNA real-time PCR assay was used to measure changes in mycoplasma DNA concentration in cultures treated with 100 µM norepinephrine compared to controls. The results of this analysis are shown in Fig. 1, which clearly shows a decrease in growth based on DNA concentration in cultures exposed to 100 µM norepinephrine. At 24 h, difference between control and norepinephrine-treated samples was significant at P<0.05. Based on these results, 100 µM norepinephrine was added to the treated group in the microarray studies.
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Microarray results
Microarrays were used to compare mRNA steady-state levels between control and norepinephrine-treated strain 232. Six microarrays representing six biological replicates of each treatment were analysed using a mixed linear model design. Estimated mean differences were significant for 84 genes at P<0.01 with a q-value <0.035 (Table 2, Fig. 2). Fifty-three of the 84 genes were upregulated (63 %) and 31 (37 %) were downregulated. Two of the upregulated genes, mhp170 and mhp377, are putative lipoprotein genes. Forty-three of the 84 genes (51 %) differentially transcribed are classified as hypothetical.
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. All six genes tested, four upregulated and two downregulated, demonstrated concordant transcript changes (Table 2).
Upregulated genes
A cursory examination comparing the genes upregulated with those downregulated demonstrates a larger proportion involved with transcription and translation in the former group. One region of the genome, mhp188–mhp206, contains numerous ribosomal protein genes. Almost all of the genes within this region indicate an upregulation upon exposure to norepinephrine when using a cutoff of P<0.05 (Table 2; see also Supplementary Table S1, available with the online version of this paper). The positions of the regulated genes on the chromosome where P<0.05 are shown in Supplementary Fig. S1. Genes mhp478–mhp482 are conserved hypothetical genes, forming an apparent operon with unknown function. Another notable upregulated gene is dnaN (mhp002), the DNA polymerase β sliding clamp (Sutton, 2004). It is involved in SOS DNA repair, is a negative regulator of dnaA, and possibly functions to bind with other proteins such as MutS, Lig and GyrA for the broader repair of DNA (Wang & Crowley, 2005). FtsY (mhp008), the functional homologue of the mammalian signal recognition particle (SRP), is needed for the assembly of other proteins, and it binds to membranes and blocks trigger factor binding in the ribosome. Trigger factor is a ribosome-associated molecular chaperone involved in proline-limited protein folding (Scholz et al., 1997). The alteration of trigger factor association with the ribosome could have dramatic effects on protein function in the cell independent of transcription. Upregulation of the RNA polymerase 
chain protein, RpoA (mhp213), may affect transcription efficiency, as would upregulating the elongation factor ts (tsf, mhp059), which is in an operon with rpsB (P=0.0118), both of which are also upregulated and involved in translation. The upregulation of the SsrA-binding protein gene smpB (mhp110) may effect the trans-translation process to recycle ribosomes stalled on problematic mRNAs by interacting with tmRNA (Ivanova et al., 2005). Trans-translation releases stalled ribosomes from truncated mRNAs and tags defective proteins for proteolytic degradation using tmRNA. The overall effect of an increased SmpB protein concentration in the cell would be to enhance the efficiency of translation without having to alter the concentration of ribosomes in the cell.
Various other genes were upregulated at a significance level of P<0.01 in response to norepinephrine, including 26 hypothetical genes. This represents approximately 49 % of the genes, a proportion equivalent to the entire genome (Minion et al., 2004; Vasconcelos et al., 2005). The gene for topoisomerase I, topA (mhp097), is activated during oxidative stress (Weinstein-Fischer & Altuvia, 2007) in addition to being responsive to norepinephrine. It has also been shown to be differentially regulated in E. coli in a Fis-dependent manner (Weinstein-Fischer & Altuvia, 2007). polC, the gene for DNA polymerase III chain, is also upregulated, and both it and topA are involved in DNA replication. The oligopeptide transport system permease complex mhp498–mhp501 (oppBCDF) is upregulated (P<0.05); this has also been observed during heat shock in M. hyopneumoniae (Madsen et al., 2006a). Perhaps this operon is part of a general stress response of the mycoplasma. Adenylate kinase (adk; mhp208), which is involved with maintaining adenine homeostasis, and methionine aminopeptidase (map; mhp209), which removes N-terminal methionines from proteins, are upregulated in response to norepinephrine. One of the P97 adhesin-binding homologue protein genes, p146 (mhp684), is also upregulated (Adams et al., 2005; Minion et al., 2004). The function of P146 is unknown, but it could have an important role in tissue adherence and colonization. Finally, the upregulation of transketolase (tktD, mhp431), ribonucleoside-diphosphate reductase β chain (nrdF, mhp156) and pepP (mhp680), Xaa-Pro aminopeptidase, could serve to enhance metabolism in subtle, but undefined ways.
Downregulated genes
Fewer genes were downregulated in response to norepinephrine at a significance level of P<0.01. Among the 32 downregulated genes were 17 (53 %) hypothetical genes. parC, the catalytic centre for DNA cleavage and rejoining in topoisomerase IV is included among the genes with known functions. Interestingly, we demonstrated that parC (mhp034) is upregulated during heat shock in M. hyopneumoniae (Madsen et al., 2006a), but it is downregulated in this study. How this gene may be differentially regulated in response to heat and catecholamines is unknown since little is known about the mechanisms of regulation of mycoplasma genes. Several genes directly involved in intermediate metabolism were downregulated in this study. These include serS (mhp128), seryl-tRNA synthetase, rbsC (mhp246), ribose ABC transporter, an ATP-binding transporter, mglA (mhp318), two GTP-binding proteins, lepA (mhp078) and era (mhp226), and glycerol kinase (glpK, mhp370). Several genes involved in energy metabolism are downregulated, including mmsA (mhp153), a dehydrogenase, pdhD (mhp504), a dihydrolipoamide dehydrogenase, and nagE (mhp590), a member of the phosphotransferase (PTS) system. One protein involved in cell division, ftsZ (mhp407), was downregulated; this correlates with our observation that exposure of M. hyopneumoniae to norepinephrine slows growth, in contrast to what has been observed with other bacteria (Waldor & Sperandio, 2007).
An apparent operon containing mhp144–mhp153 is downregulated in response to norepinephrine. Among the genes in this operon are a putative dehydrogenase (mhp144), a putative ribose-binding protein (mhp145), a ribose transporter (mhp146), a ribose transport ATP-binding protein (mhp147), proteins involved in myo-inositol catabolism (iolD; mhp149 and iolC; mhp152), and methylmalonate-semialdehyde dehydrogenase (mms; mhp153). Three other genes in this operon are conserved hypothetical genes with unknown function. Many of these genes are upregulated under heat shock and low-iron conditions (Madsen et al., 2006a, b).
Interpretation of the differential responses
When comparing the direction of regulation of differentially expressed genes in norepinephrine-exposed M. hyopneumoniae to those genes shown to be differentially expressed under heat shock (Madsen et al., 2006a), iron deprivation (Madsen et al., 2006b), oxidation conditions (Schafer et al., 2007) and in vivo growth (Madsen et al., 2008), an interesting correlation was observed. Genes upregulated during norepinephrine exposure were generally downregulated under the other conditions, if at all (Supplementary Table S1). Downregulated genes during norepinephrine exposure were generally upregulated under other conditions. These observations tend to support several hypotheses. First, M. hyopneumoniae has active gene regulatory mechanisms that have yet to be defined. It is well known that mycoplasmas have only a single sigma factor in their genomes and few known transcriptional regulators (Chang et al., 2008), so how this regulation occurs and the components involved are still unknown. These regulatory mechanisms may not be as robust as in other organisms, resulting in smaller fold change values, but given the small size, slow growth, truncated energy-producing pathways and other limiting factors associated with a minimal genome, they obviously are sufficient for survival under the difficult environmental conditions encountered in the host. Second, at least two of the conditions studied, norepinephrine and iron, require an active sensor system for which no genes have been annotated. The genes are most likely in the large hypothetical group and may code for some of the 53 lipoproteins (Minion et al., 2004). There is also a large group of transport-related proteins that might be involved and serve as receptors. Finally, given the diversity of genes regulated under different environmental conditions such as heat shock (Madsen et al., 2006a), iron deprivation (Madsen et al., 2006b), oxidative stress (Schafer et al., 2007) and the pig lung (Madsen et al., 2008), transcription in M. hyopneumoniae must involve multiple factors and mechanisms. We are only beginning to decipher those components and their mechanisms of action (Chang et al., 2008).
In summary, our studies indicate that M. hyopneumoniae responds to the host catecholamine norepinephrine by differential expression of specific genes. An overall increase in transcription- and translation-related genes occurs, as does a decrease in several metabolically related genes. This is just one of the environmental changes expected to impact the overall physiology of M. hyopneumoniae as it colonizes and parasitizes the swine respiratory tract. Whether this growth effect due to norepinephrine occurs in vivo in the presence of other stressors is not clear since the levels of norepinephrine may fluctuate in response to many factors in the lung and the effects of multiple factors may be confounding on gene expression in M. hyopneumoniae. Interestingly, the set of genes identified by this study is different from those identified in other stress-related studies (Madsen et al., 2006a, b; Schafer et al., 2007). Perhaps a combination of stressors is necessary to induce the full complement of genes needed by M. hyopneumoniae to survive the host environment. Since so little is known about how mycoplasmas regulate their genes, more mechanistic studies will be needed to decipher the importance of single stressor signals in the overall pathogenesis of M. hyopneumoniae.
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ACKNOWLEDGEMENTS |
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Edited by: C. Citti
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REFERENCES |
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Received 2 May 2008;
revised 10 June 2008;
accepted 11 June 2008.
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