- Research article
- Open Access
The role of sigma factor RpoH1 in the pH stress response of Sinorhizobium meliloti
© de Lucena et al; licensee BioMed Central Ltd. 2010
Received: 29 April 2010
Accepted: 18 October 2010
Published: 18 October 2010
Environmental pH stress constitutes a limiting factor for S. meliloti survival and development. The response to acidic pH stress in S. meliloti is versatile and characterized by the differential expression of genes associated with various cellular functions. The purpose of this study was to gain detailed insight into the participation of sigma factors in the complex stress response system of S. meliloti 1021 using pH stress as an effector.
In vitro assessment of S meliloti wild type and sigma factor mutants provided first evidence that the sigma factor RpoH1 plays a major role in the pH stress response. Differential expression of genes related to rhizobactin biosynthesis was observed in microarray analyses performed with the rpoH1 mutant at pH 7.0. The involvement of the sigma factor RpoH1 in the regulation of S. meliloti genes upon pH stress was analyzed by comparing time-course experiments of the wild type and the rpoH1 mutant. Three classes of S. meliloti genes could be identified, which were transcriptionally regulated in an RpoH1-independent, an RpoH1-dependent or in a complex manner. The first class of S. meliloti genes, regulated in an RpoH1-independent manner, comprises the group of the exopolysaccharide I biosynthesis genes and also the group of genes involved in motility and flagellar biosynthesis. The second class of S. meliloti genes, regulated in an RpoH1-dependent manner, is composed of genes known from heat shock studies, like ibpA, grpE and groEL5, as well as genes involved in translation like tufA and rplC. Finally, the third class of S. meliloti genes was regulated in a complex manner, which indicates that besides sigma factor RpoH1, further regulation takes place. This was found to be the case for the genes dctA, ndvA and smc01505.
Clustering of time-course microarray data of S. meliloti wild type and sigma factor rpoH1 mutant allowed for the identification of gene clusters, each with a unique time-dependent expression pattern, as well as for the classification of genes according to their dependence on RpoH1 expression and regulation. This study provided clear evidence that the sigma factor RpoH1 plays a major role in pH stress response.
Stress response in bacteria is essential for effective adaptation to changes in the environment, as well as to changes in the bacterial physiological state. This response is mediated by global regulatory mechanisms that operate in an effective method of transcriptional control, with the participation of specialized RNA polymerase subunits, the alternative sigma factors . Bacteria usually display two distinct responses to stress conditions: a response that controls the conditions in the cytoplasm, which is orchestrated by the alternative sigma factor σ32, and a response to the conditions in the periplasm, which is orchestrated by the alternative sigma factor σE. Each response deals with the cellular ability to sense protein folding and other signals, and leads to the activation of proteins such as molecular chaperones, proteases, and regulatory factors, which play an important role in promoting homeostasis under stress conditions [3–5].
The heat shock response is a widespread phenomenon found in all living cells. In bacteria, it is controlled at the transcriptional level by the alternative sigma factor RpoH (σ32) [6–8]. In addition to the response to high temperatures, RpoH is known to be involved in the response to pH and oxidative stress [9–11]. The σ32 regulon protects many cytoplasmic molecules and processes, including transcription factors, as well as cytoplasmic membranes and inner membrane proteins [6, 8]. In E. coli, RpoH controls the expression of about 91 genes , including many coding for heat shock proteins, which are important for survival during stress conditions. Among these are the genes encoding chaperones, such as GroEL, GroES, DnaK, DnaJ and GrpE and proteases, like FtsH and Lon . Induction of heat shock proteins represents an important protective mechanism to cope with environmental stress, for these proteins mediate the correct folding and assembly of polypeptides. Major functions of heat shock proteins are to prevent inactivation of cellular proteins, to reactivate once inactivated proteins, and to help degrade non-reparable denatured proteins that accumulate under stress conditions .
Sinorhizobium meliloti is a Gram-negative α-proteobacterium that establishes root-nodulating, nitrogen fixing, symbiosis with leguminous host plants, such as alfalfa [14–16]. Several important steps in the symbiosis process, like nodule formation and nitrogen fixation, are affected by stress conditions, which might be considered limiting factors. In the soil, variations of temperature, osmolarity, or pH, as well as nutrient starvation, are the stress conditions most frequently faced by rhizobia . Commonly, bacterial genomes contain a single rpoH gene, but several α-proteobacteria have more than one rpoH homologue. Two rpoH genes have been identified in Brucella melitensis and Rhodobacter sphaeroides, and in the nitrogen-fixing symbionts Mesorhizobium loti and Rhizobium etli[9, 11, 18, 19]; Bradyrhizobium japonicum possesses three rpoH-like genes . The S. meliloti 1021 genome contains 14 genes for sigma factors , two of which code for RpoH sigma factors. However, rpoH1 and rpoH2 are not functionally equivalent [22, 23]. The two genes are expressed differentially during growth in culture and during symbiosis, and only rpoH1 is required for growth in heat shock stress and for successful symbiosis with alfalfa [23, 24]. The presence of several copies of RpoH sigma factors suggests that rhizobia may respond more specifically to environmental changes and that the heat shock response could overlap the response to other stimuli . Previous studies with S. meliloti revealed that an rpoH1 mutant exhibits increased sensitivity to various stress agents, including acid pH, suggesting that RpoH1 is required to protect the bacterial cell against environmental stress encountered in solo or within the host .
Soil acidity constrains symbiotic nitrogen fixation and affects the exchange of molecular signals between rhizobia and their host, reducing nodulation [26–28]. Environmental pH stress constitutes therefore a limiting factor for S. meliloti survival and development, both in the soil and in planta . In a previous study, it was observed that the response to acidic pH stress in S. meliloti is versatile and characterized by the differential expression of whole sets of genes associated with various cellular functions, such as exopolysaccharide I biosynthesis and chemotaxis . The purpose of the present study was to gain detailed insight into the complex stress response regulatory system of S. meliloti using pH stress as an effector and to verify if specific sigma factors in S. meliloti are involved in pH stress response. Our aim was likewise to provide a basis for understanding the molecular mechanisms of sigma factor regulation and identify genes involved in pH stress response whose expression is sigma factor-dependent. Because the regulation of gene expression is a dynamic process, special attention was granted to the characterization of changes in gene expression over time.
Identification of sigma factors involved in the pH stress response of S. meliloti
Transcription profiling of the rpoH1 mutant versus wild type at neutral pH reveals RpoH1 involvement only in the regulation of the rhizobactin operon
Growth characteristics of S. meliloti wild type and rpoH1 mutant in response to an acidic pH shift
Effects of an acidic pH shift on S. meliloti wild type and rpoH1 mutant assessed by time-course transcriptome analysis
In order to characterize the regulation of S. meliloti response to pH stress, the progressive transcriptomic response of both S. meliloti wild type and the rpoH1 mutant to sudden environmental acid shift was investigated by global gene expression time-course analyses. The experimental setup for the procedure with the wild type was identical to that of the rpoH1 mutant, allowing therefore for significant data comparison. With the aim to identify S. meliloti genes involved in pH stress, cells were grown in medium at pH 7.0 until reaching an optical density of 0.8 at 580 nm, and then transferred to medium at pH 5.75 or pH 7.0 (control). Cells were harvested at time points 0, 5, 10, 15, 30 and 60 minutes after the transfer. For each point of time, the microarray hybridization analyses were performed comparing the cells shocked at pH 5.75 with control cells again transferred to medium at pH 7.0. Log2 ratio or fold change of gene expression was obtained for each gene at each time point against the time-matched control and the normalized model-based expression values of genes were compared. In order to identify genes that play a role in the cellular response to acidic pH, significant change in expression was determined in combination with a cut-off value of approximately threefold change. That is, only genes that showed a significant increase or decrease in the expression ratio of circa threefold (M-value ≥ 1.4 or ≤ -1.4) between the two pH classes, for at least one of the six time points, were considered. Out of 14,000 array elements interrogated, a total of 210 nonredundant genes were selected, whose expression was altered significantly at one or more time points in the wild type arrays (Additional file 3).
Overall, the observed response of the S. meliloti wild type following acid shift is in agreement with that described by Hellweg et al.. Most transcriptional changes occurred within 20 minutes after pH shift and upregulation was slightly dominant over downregulation at all time points. The response to acidic pH stress was characterized by an intricate variation in the expression of gene sets associated with various cellular functions over time. Among the most strongly upregulated genes (M-value ≥ 1.8) were lpiA, which codes for a low pH induced protein; degP1, which codes for the DegP1 serine protease; and cah, which codes for a carbonic anhydrase. Among the groups of genes responding to the shift to acidic pH were those of the exopolysaccharide I biosynthesis as well as flagellar and chemotaxis genes [34, 35]. While the genes of the exopolysaccharide I biosynthesis were upregulated, the expression level of flagellar genes decreased in response to acidic pH. Other responding functional groups of genes were those coding for chaperone proteins, which were upregulated, and genes involved in nitrogen uptake and metabolism.
In the S. meliloti rpoH1 mutant arrays following acid shift, 132 of the 6,208 genes on the S. meliloti 1021 microarray showed significant time-dependent variation in expression in at least one of the six time points. Those genes exhibited approximately threefold change in at least one time point throughout the 60 minute time-course. Approximately 30 annotated genes among the 132 genes that are differentially expressed in the rpoH1 mutant arrays are not found within the set of 210 genes that are differentially expressed in the wild type after pH shock. Among the genes most strongly induced in the rpoH1 mutant arrays were nex18, a gene that codes for a nutrient deprivation activated protein  and again lpiA. Both of these acid-induced genes display an extracellular stress response function . Similarly to the wild type arrays, several genes of the flagellar regulon were repressed at low pH, whereas the genes of the exopolysaccharide I biosynthesis were upregulated. In contrast to the S. meliloti wild type, some genes coding for nitrogen uptake and metabolism and several genes coding for chaperone proteins were not observed among the differentially expressed genes in the rpoH1 mutant arrays (Additional file 4).
Time-course microarray data of S. meliloti wild type following an acidic pH shift were grouped in 6 K-means clusters
Cluster A grouped genes with the strongest transcriptional induction after shift to low pH. It consists of 28 genes, including nex18, involved in the response to nutrient deprivation stress  and lpiA, involved in the formation of lysyl-phosphatidylglycerol, which is a low pH induced protein in S. medicae. The exopolysaccharide biosynthesis genes exoV, exoH, exoN, and the gene for the Lon protease, a regulator of exopolysaccharide synthesis that is required for nodulation with alfalfa , also grouped in this cluster. Cluster B comprises genes that were gradually upregulated during the time-course and reached a plateau at approximately 20 minutes after pH shift. The genes in cluster B had, in comparison to the genes in cluster A, average lower M-values throughout the time course. This group includes several genes involved in exopolysaccharide I biosynthesis. The upregulation of exopolysaccharide biosynthesis genes upon sudden pH shift probably accounts for the mucoid phenotype in S. meliloti cells grown on plates at low pH and is in accordance to what has already been reported by Hellweg et al. (2008). Moreover, this cluster also includes a broad range of genes coding for heat shock proteins and chaperones involved in stress response, such as ibpA, grpE, hslVU and groEL5 and the genes coding for the proteases HflCK, HtpX, FtsH, ClpAB, ClpP1 and ClpS. Cluster C is composed of genes which were transiently induced after pH shift. It contains the dicarboxylate transport system DctA, which is essential for symbiosis in S. meliloti. Also, the gene smc01505, which plays the function of the anti-sigma factor for the extracytoplasmic function sigma factor RpoE2 , was transiently upregulated (Figure 4).
Most genes in cluster D were gradually downregulated up to 30 minutes after pH shift, and maintained the peak of downregulation at 60 minutes. This cluster comprises a number of genes related to flagella biosynthesis and pillus assembly. Cluster E is composed of genes whose expression decreased continuously for the whole duration of the time-series experiment. The expression was gradually downregulated as of 5 minutes after pH shift, followed by greater downregulation up to 60 minutes. Among the genes in this cluster were the flagellar genes flgG flgL, flgB and fliE. Cluster F consists of genes which were transiently downregulated in their expression level after pH shift. It involves genes that play a role in nitrate assimilation, such as nirB, nirD and narB and the nitrate transporter smb20436 (Figure 4, Additional file 5).
Analysis of expression profiles of the S. meliloti rpoH1 mutant following an acidic pH shift in view of wild type results
In order to elucidate the role of RpoH1 in transcription dynamics during pH stress response, the time-course transcriptomic analyses of the rpoH1 mutant upon acidic pH shift were compared to those of the wild type. For a most effective comparative analysis, K-means clustering was performed for the 210 genes selected through the filtering of the wild type data, but this time the clustering was carried out with their log2 expression data in the rpoH1 mutant arrays. This approach enabled the identification of genes that, throughout the time-course, behaved in a similar fashion both in the rpoH1 mutant arrays and in the wild type, as well as the identification of genes that displayed no differential expression in the rpoH1 mutant arrays, even though they were differentially expressed, upon acidic pH shift, in the wild type.
Clusters J and K grouped genes that were downregulated throughout the time-course, with persistent and transient downregulation, respectively. Like in the wild type arrays, many flagellar genes were also downregulated in the mutant and grouped in cluster J. The phosphate transport system encoded in the phoCDET operon also grouped in this cluster. In E. coli, phoB is involved in the acid shock response . Among the transiently downregulated genes in cluster K were genes involved in nitrogen metabolism, such as those coding for nitrite and nitrate reductases, nirD, nirB and narB, which play a role in the conversion of nitrate to ammonia. Unlike the wild type, the clustering of the rpoH1 mutant data yielded the observation of a large cluster of genes whose expression changed very little throughout the time-course. For the genes in cluster L, the M-values remained close to zero at all time points (Figure 5B). Genes in cluster L include those coding for heat shock proteins and proteases, as well as the elongation factor tufAB operon and the gene coding for the putative chemotaxis protein cheW3. The complete lists of genes obtained from the clustering of the rpoH1 mutant data can be seen in Additional file 6. Additionally, in order to confirm the microarray results, quantitative reverse transcription PCR (qRT-PCR) analyses of six different genes were performed, for time points 10 and 60 minutes after pH shock (Additional file 7). The qRT-PCR results were very similar to those of the microarray expression data, for all genes analyzed, with the exception of the dctA gene, which presented a relatively higher expression value than that observed in the wild type microarrays at the 60-minute time point.
Identification of S. meliloti genes that are regulated in an RpoH1-independent manner following an acidic pH shift
Identification of S. meliloti genes that are regulated in an RpoH1-dependent manner following an acidic pH shift
Genes classified as RpoH1-dependent did not present significant differential expression after pH shift in the rpoH1 mutant arrays, having shown otherwise a threefold differential expression for at least one time point in the wild type arrays. They comprise as many as 101 genes of the S. meliloti genome whose transcription after pH shift seems to be dependent on rpoH1 expression (Additional file 4). A number of protein turnover and chaperone genes were upregulated in the wild type arrays, such as the ones coding for the heat shock proteins IbpA, GrpE and GroEL5 (Figure 6D), as the ones coding for the Clp proteases, which are involved in the degradation of misfolded proteins . No differential expression whatsoever was observed for those genes in the rpoH1 mutant arrays, characterizing thus an RpoH1-dependent expression of stress-response genes upon acid pH shift (Figure 5B, Additional file 6). Genes involved in translation, like tufA and tufB, rplC rplD and rplS, were downregulated, characterizing a seemingly RpoH1-dependent inhibition of translational activity in S. meliloti cells under pH stress. Genes cheW 3 and mcpT (Figure 6E), coding for proteins involved in chemotaxis, were also downregulated only in the wild type arrays.
Identification of S. meliloti genes that are regulated in a complex manner following an acidic pH shift
RpoH1 is also involved in the downregulation of specific transiently expressed genes. Interestingly, three genes from wild type cluster C were not grouped in cluster I as transiently upregulated in the rpoH1 mutant arrays. Those are the genes dctA, coding for a dicarboxylate transport protein, ndvA, coding for a beta glucan export protein, and the gene smc01505, which codes for the RpoE2 anti-sigma factor. These genes seem to have an RpoH1-independent upregulation, but an RpoH1-dependent downregulation as of 20 minutes following pH shift. In the wild type arrays, their expression is transient, but in the rpoH1 mutant arrays they remained upregulated throughout the entire time period analyzed (Figure 6C, F). For those genes, the RpoH1 sigma factor is likely to play a role in a more complex regulatory system with the involvement of a secondary regulator, for instance a repressor, which would be under the control of RpoH1, whereas the transcription activation of the genes themselves seems to be RpoH1-independent.
Functional classification of genes regulated in an RpoH1-dependent manner
The S. meliloti sigma factor RpoH1 is important for stress response at low pH
In the soil, S. meliloti deals with adverse environmental variations that could induce physiological stress responses. Alternative sigma factors, such as RpoH1, directly sense and respond with transcriptional activation to the presence of stress conditions in their environment. The relative lack of differential expression of genes at pH 7.0 most likely reflects the absence of an inhospitable environmental condition to activate the alternative rpoH1 transcriptional response. The differential expression of genes related to rhizobactin synthesis in the microarray analyses may indicate a need for increased iron uptake regulation at pH 7.0. Even though the rpoH1 mutation does not affect host invasion during the endosymbiotic process, rpoH1 mutant bacteroids are defective in nitrogen fixation (Fix-- phenotype) . However, we cannot explain the requirements for RpoH1 during symbiosis as a consequence of rhizobactin necessity, since rhizobactin is not expressed in the nodules .
The growth of the rpoH1 mutant was severely compromised at pH 5.75 and a growth defect was also observed after pH shock experiments. Growth inhibition probably occurs as a result of both lower internal pH and the differential ability of anions to inhibit metabolism. The fact that an rpoH1 mutant does not grow on LB plates containing acid pH gradient  corroborates our pH sensitivity phenotype. Previous studies have shown that an rpoH1 mutant is capable of eliciting the formation of nodules on alfalfa plants, but the rpoH1 mutation causes early senescence of bacteroids during the endosymbiotic process [23, 25]. The present work did not explore regulation within the nodule, another condition in which rpoH1 is expressed . Bearing in mind that the endosymbiotic process is affected by the ability of rhizobial cells to protect themselves against environmental stresses encountered within the host, it is possible that the early senescence observed for rpoH1 mutant nodules  is caused by an increased sensitivity to pH stress upon rhizosphere and plant acidification during nodulation. Within the plant cell, symbiotic bacteria have to face acid conditions . Transport of protons or ionized acids could acidify the symbiosomes and the low oxygen concentration in the nodules could be expected to alter pathways of carbon metabolism, leading to the production of organic acids that inhibit the regulation of cytoplasmic pH . In this case the role of RpoH1 during pH shift would be paramount not only at free-living growth, as shown in this work, but also during symbiosis, and sensitivity to low pH values is very likely the reason rpoH1 mutant cells cannot form functional nodules. Several stress responses are known to be linked with pH stress, including oxidative stress, heat shock, and envelope stress. Low pH usually accelerates acid consumption and proton export , and increases production of oxygen radicals, thus inducing a partial oxidative stress response. In this work, the expression of genes coding for ATP transporters that can work as proton pumps and proteins involved in osmotic stress response seem to be at least partially dependent on RpoH1. Likewise, the RpoH sigma factor has already been implicated in the oxidative stress response in other rhizobia [9, 11].
Moreover, our study revealed patterns of pH response and clarified the overlap of pH stress with heat shock response. The heat shock response in bacteria is characterized by the induction of a number of proteins in response to change in temperature. Since many of these proteins are also induced by a variety of other environmental stress conditions, it can be concluded that such response is a stress response and not only a heat shock response. RpoH1 has been described in S. meliloti as the heat shock response sigma factor [23–25]. The group of proteins shown to be involved in the heat shock response under the transcriptional control of RpoH1 includes chaperones, proteases, and regulatory factors. In the present study, we have seen that those groups of proteins are also involved in pH stress response. Hence, the pH stress response in S. meliloti, characterized in this work, is likewise not specific for pH stress, but also likely to be a response to other types of environmental stress.
Three groups of S. meliloti genes were found to be transcriptionally regulated upon pH stress in an RpoH1-independent, in an RpoH1-dependent and in a complex manner
Overall, gene expression following rapid acid shift revealed several patterns of acid stress response, characterized by the induction of heat shock regulons and exopolysaccharide production and the repression of energy-expensive flagellar and chemotaxis regulons. The observed response of the S. meliloti wild type following acid shift is in agreement with that described by Hellweg et al.. Though the nomenclature adopted in this manuscript is similar to that found in Hellweg et al., cluster distribution differs in that Hellweg divided the dataset in eight clusters and in the present study the dataset was divided into six clusters. Three classes of transcriptionally regulated S. meliloti genes could be identified: genes which were regulated in an RpoH1-independent, an RpoH1-dependent or in a complex manner upon pH stress. The first class of genes, which were regulated in an RpoH1-independent manner, comprises exopolysaccharide I biosynthesis genes, like exoQ, exoP, exoN and exoY, and also the group of genes involved in motility and flagellar biosynthesis like the flagellar genes flgA, flgL and mcpT. Those expression patterns further confirm the notion of an induced exopolysaccharide production and a hampered motility activity of S. meliloti upon pH shock , though the induction of exopolysaccharide production and the repression of motility is most seemingly an RpoH1-independent process. The vast majority of chemotaxis and flagellar genes was indeed downregulated in a similar fashion in both wild type and mutant arrays, even though the chemotaxis gene cheW3, for instance, was not repressed in the rpoH1 mutant. The genes included in this class of RpoH1-independently regulated genes do not, as a rule, comprise genes with a specific stress response function.
The second class of S. meliloti genes, which comprises those genes that responded in an RpoH1-dependent manner, is composed of genes known to be involved in heat shock, such as ibpA, grpE, clbP and groEL5, as well as some genes involved in translation like tufA and rplC. Our analysis strongly suggests that a transcriptional response to pH takes place in which cells reallocate resources by inhibiting energy-consuming processes and upregulating transcription of genes involved in chaperone mechanisms. The heat shock regulons were clearly under the control of RpoH1, and though genes belonging to diverse functional classes were transcriptionally modulated by rpoH1 expression, the most represented class of genes induced by pH shock stress was by far that of genes coding for chaperones. Those genes are likely to be paramount for an appropriate cellular response in fighting pH stress. The finding of genes coding for chaperone proteins such as groESL5 and clpB, already known to be RpoH1-dependent after temperature upshift  remarkably attests to the reliability of our results. The groEL5 mutant is able to fix nitrogen in the nodules . However, other important pH stress response genes such as lon, grpE and ibpA[39, 47, 48] are under the control of rpoH1 in S. meliloti and could be involved in dealing with the low pH environment in free-living conditions and within the nodule.
The third class was that of genes regulated in a complex manner. This was the case for the genes ndvA and smc01505, which were transiently upregulated only in the wild type arrays, whereas in the rpoH1 mutant arrays those genes were constantly upregulated. This lack of downregulation implies most likely that a secondary regulation takes place, in which a repression of the activities of some genes is then dependent on rpoH1 expression. Interestingly, smc01505 codes for the RpoE2 anti-sigma factor. RpoE2 is known to be involved in general stress response and in oxidative stress response in S. meliloti[41, 52], though it has been suggested that RpoE2 is not necessary for stress adaptation . Gene expression patterns are also influenced by sigma factor availability and activity. In the time-course comparison, smc01505 was regulated differently from the wild type in the rpoH1 mutant. It is likely that in a complex event such as stress response, extracytoplasmic sigma factors like RpoE2 act together with RpoH1, which is a sigma factor mostly responsible for stress response in the intracellular compartment. In E. coli, for instance, grpE expression is under the regulation of the sigma 70 and sigma 32  and rpoH transcription is controlled by sigma 70, sigma E and sigma 54 . Many stress genes are also regulated by transcriptional repressors and activators, a number of which were induced at the transcription level in our experiments. Those constitute a secondary activation and are important for responding to specific intracellular cues and for precisely coordinating transcription changes with the physiological state of the cell. Therefore, in order to understand how stress response in the periplasm and cytoplasm are coordinated, it is necessary to dissect the transcriptional regulatory network of sigma factors, considering not only that secondary regulation and cross-regulation take place, but also that there can be binding sites for more than one sigma factor in the promoter region of genes involved in stress response. Our primary focus with the time-course microarray analyses was to identify genes that are part of the regular pH stress response in S. meliloti wild type and from there to pinpoint genes whose expression is dependent on rpoH1 expression. This approach facilitated the comparison, for the genes that were differentially expressed only in the rpoH1 mutant arrays are probably under the control of more complex genetic circuits and require more extensive analyses for their role in stress response to be elucidated. Moreover, successful validation of the microarray data was obtained by qRT-PCR analyses performed for six different genes that were differentially expressed in the wild type. In the group of genes analyzed, RpoH1-dependent, RpoH1-independent and complex regulation could be observed, in accordance to the microarray expression data. The only dissimilarity in the qRT-PCR results was observed for the dctA gene, whose results were inconclusive for the wild type at the 60-minute time point. It may be that the upregulation of the dctA gene is sustained throughout the time-course. On the other hand, the available qRT-PCR data do not admit predictions about expression values between 10 and 60 minutes. Although the M-values were generally higher in the qRT-PCR analyses, the genes showed very similar expression patterns to those observed in the microarrays, indicating that the results can indeed be trusted (Additional file 7).
Time-course global gene expression is a powerful tool for the identification of S. meliloti genes regulated by the sigma factor RpoH1
The RpoH1-dependent pH stress response of S. meliloti was characterized with the aid of transcriptomic studies. Microarray hybridization was therefore employed to investigate the time-course response of S. meliloti to a sudden acid shift. Time-course experiments of gene expression facilitate the understanding of the temporal structure of regulatory mechanisms and the identification of gene networks involved in stress response . The time-series microarrays, followed by clustering, enabled us to capture multiple expression profiles at discrete time points of a continuous, but dynamic, cellular process. Also, it enabled us to extract the fundamental patterns of gene expression inherent in the data.
In S. meliloti, two RpoH-type sigma factors are annotated in the genome . RpoH1 and RpoH2 are involved in different stress responses, and this probably provides increased capacity for S. meliloti to adapt to different environments. We suggest for the first time that RpoH1 efficiently regulates the expression of specific heat shock genes in response to pH stress in S. meliloti. This type of regulation structure would also be efficient for adjustment to other stresses requiring rapid change of metabolic mode as well as thermal adaptation. We ultimately conclude that RpoH1 is necessary for the dynamic response of S. meliloti to sudden pH shift and it accounts for critical changes in gene expression during pH stress response. These findings form a basis for subsequent analyses of regulation and function of the stress response in S. meliloti. The time-course study provides efficient methodology for hypothesis-driven investigations to dissect the roles of sigma factors and other key players in transcription regulation not only in pH stress conditions, but in general stress response and adaptation. In addition to the recognition of individual genes with altered expressions, the proposed method for clustering of time-course data enabled us to identify gene clusters, each with a unique time-dependent expression pattern. Further biochemical and genetic studies on the regulatory events of S. meliloti cells undergoing environmental stress should continue to provide useful information for further understanding of the role of RpoH1 and other alternative sigma factors in stress response.
Our study indicated that sigma factor RpoH1 plays an important role in the response to low pH stress in S. meliloti. This role was efficiently unraveled by time-course microarray studies, in which key players involved in stress response whose transcription is under regulation of RpoH1 were identified. Clustering of time-course microarray data of S. meliloti wild type and rpoH1 mutant allowed for the classification of three groups of genes that were transcriptionally regulated upon pH stress in an RpoH1-independent, in an RpoH1-dependent or in a complex manner. Among the genes that showed an RpoH1-dependent regulation, there were several coding for heat shock and chaperone proteins. Time-course global gene expression analyses can be further employed to facilitate the temporal study of regulatory mechanisms and provide a more comprehensive framework for studying dynamic cellular processes, such as stress response.
Bacterial strains, plasmids, and growth conditions
Bacterial strains, plasmids and PCR primers used in this study
Spontaneous mutant of wild type strain RU47, Smr
Rm1021 derivative, rpoE1 mutant
Rm1021 derivative, rpoE2 mutant
Rm1021 derivative, rpoE5 mutant
Rm1021 derivative, rpoH1 mutant
Rm1021 derivative, fecI mutant
F- endA1 supE44 thi-1 λ- recA1 gyrA96 relA1 deoR Δ(lacZYA-argF)U169 ϕ80dlacZ ΔM15 mcrA Δ(mrr hsdRMS mcrBC)
E. coli 294::[RP4-2(Tc::Mu)(Km::Tn7)] pro res ΔrecA Tpr
pUC18 derivative, sacB lacZ α Kmr, mobilizable
pJN105 derivative, rpoH1, Gmr
Construction of sigma factor mutants
The protocols of Sambrook et al. were used for DNA manipulations. DNA fragments containing at least 500 base-pair deletions in the sigma factor genes were constructed by Gene Splicing by Overlap Extension or gene SOEing . In general, most of the coding sequence of the genes was deleted, and only the nucleotides coding for the first and last two amino acids of the genes are still present in the mutant strains. In a first Polymerase chain reaction (PCR), regions up- and downstream of the desired deletion were amplified, and then they were fused in a second PCR. The primers used for this purpose are listed in Table 1. The deletion constructs obtained were subsequently cloned into the suicide vector pK18mobsacB, which allows sucrose selection for vector loss . The resulting plasmids were conjugated into S. meliloti via E. coli S17-1 to introduce deletions by allelic exchange. Production of mutant strains was confirmed by PCR reactions designed to amplify DNA fragments spanning the gene of interest.
CAS siderophore assay
Chrome azurol S (CAS) assay mixtures for siderophore detection were prepared as described by Schwyn and Neilands . Supernatants of S. meliloti cultures grown in VMM were mixed 1:1 with a CAS assay solution. After equilibrium was reached, the absorbance at 630 nanometers was measured. The relative siderophore activity was determined by measuring optical density ratios of different cultures.
Procedures for continuous pH and pH shift growth experiments
S. meliloti strains were grown in Vincent minimal medium (VMM)  at 30°C at either pH 7.0 or pH 5.75 for growth tests at continuous pH values. VMM medium was composed of 14.7 mM K2HPO4, 11.5 mM KH2PO4, 0.46 mM CaCl2, 0.037 mM FeCl3, 1 mM MgSO4, 15.7 mM NH4Cl, 10 mM sodium succinate, 4.1 μM biotin, 48.5 μM H3BO3, 10 μM MnSO4, 1 μM ZnSO4, 0.5 μM CuSO4, 0.27 μM CoCl2, and 0.5 μM NaMoO4. Triplicate samples were measured for optical density at 580 nm, twice a day, for 7 days. For pH shift experiments cells of three independent cultures were grown in 30 ml of VMM with pH 7.0 to an O.D.580 of 0.8. Cell cultures of each flask were then centrifuged (10,000 × g, 2 min, 30°C) and the supernatant was discarded. The cell pellets were resuspended in 30 ml VMM with pH 5.75 or 30 ml VMM with pH 7.0 (control) and incubated at 30°C. At six time points cell suspension samples of 5 ml were harvested from each flask and immediately centrifuged (10000 × g, 1 min, 4°C). The resulting pellets were instantly frozen in liquid nitrogen for later RNA preparation. Cell suspension samples were harvested at 0, 5, 10, 15, 30, and 60 minutes following the pH shift. To determine the number of viable cells, dilutions of S. meliloti cultures grown 30 minutes after pH shift were plated on TY agar and incubated overnight at 30°C.
RNA was isolated according to the protocol published by Rüberg et al.. Total RNA was prepared using the RNeasy mini kit (QIAGEN, Hildesheim, Germany). By ribolysation (30 s; speed, 6.5; Hybaid, Heidelberg, Germany) cells were disrupted in the RLT buffer provided with the kit in Fast Protein Tubes (Qbiogene, Carlsbad, CA).
Transcriptional profiling using the SM14kOligo whole genome microarray
For microarray hybridization, three independent bacterial cultures from each condition were prepared as biological replicates for RNA isolation. Accordingly, for each time point, dual-fluorescence-labeled cDNA probes were prepared to hybridize with three slides, respectively. For each preparation of Cy3 and Cy5 labeled cDNAs, 10 μg of total RNA were used . To each microarray, the cDNA of the pH 7.0 and pH 5.75 grown cultures were mixed and hybridized. Slide processing, sample hybridization, and scanning procedures were performed applying the Sm14kOligo microarray, that carries 50 mer to 70 mer oligonucleotide probes directed against coding regions and intergenic regions . Analysis of microarray images was carried out applying the ImaGene 6.0 software (BioDiscovery) as described previously . Lowess normalization and significance test (fdr) were performed with the EMMA software . M-values (log2 experiment/control ratio), P-values (t test) and A-values were also calculated with EMMA. The M-value represents the logarithmic ratio between both channels. The A-value represents the logarithm of the combined intensities of both channels. The microarray results were verified for specific genes by quantitative reverse transcription-PCR using a QuantiTect SYBR Green reverse transcription-PCR kit (QIAGEN, Hildesheim, Germany) according to the manufacturer's instructions.
Filtering and clustering analysis of the microarray data
K-means clustering analysis of the microarray time-course data was performed with the aid of the Genesis software . After normalization, only genes with approximately threefold change in expression (M-value of ≥ 1.4 or ≤ -1.4) in at least one point of time in the wild type microarrays were considered for clustering analysis. Genes that did not present an evaluable expression value for at least 5 of the 6 points of time (missing values on the microarray flagged as empty spots) were not considered. K-means clustering was used for distributing differentially regulated genes into 6 groups, both with the wild type and with the rpoH1 mutant microarray data.
Quantitative RT-PCR analyses
Reverse transcription was performed using Superscript II reverse transcriptase (Invitrogen) with random hexamers as primers. RNA samples were tested for two time points, 10 and 60 minutes after pH shock. Real-time PCRs were run on an Opticon system (BioRad) using the FastStart DNA MasterPLUS SYBRGreen I kit (Roche) according to the manufacturer's instructions. The housekeeping gene rkpK was used as a reference for normalization. The sequences of the primers used are available at http://www.cebitec.uni-bielefeld.de/groups/brf/software/gendb_info/. Three independent cultures were analyzed, as well as three technical replicates, for each time point.
Microarray data accession numbers
The entire set of microarray data has been deposited in the ArrayLims database .
We thank Victoria Gödde, Manuela Meyer and Eva Schulte-Berndt for providing outstanding technical help. This work was supported by a scholarship from the NRW Graduate School in Bioinformatics and Genome Research, funded by the Ministry of Innovation, Science, Research and Technology of the state of North Rhine-Westphalia, Germany.
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