Global overview of gene expression
The R. etli CFN42 genome contains 6,030 annotated protein-encoding genes, 67 pseudo genes, 3 rRNA operons and 50 tRNA genes. Recently, we described an additional 89 ncRNA genes
32
. In both the wild type and rsh mutant, over 97% (or (683 + 870)/1,593) of protein-encoding genes that are transcribed above the detection limit (see Materials and methods) during early exponential growth are also expressed during late exponential growth. In addition, numerous genes are induced in the course of growth, as 20% (or (157 + 227)/1,937) of the genes expressed in late exponential phase are not transcribed during early growth (Figure 1).
<p>Figure 1</p>Detectable gene expression overview
Detectable gene expression overview. The number of genes expressed above the detection threshold in each condition and the overlap between the different conditions are shown in Venn diagrams. Upper and lower diagrams represent expression in the wild type and rsh mutant, respectively.
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We identified a large number of differentially expressed genes during exponential and stationary phase, both (p)ppGpp-dependent and independent, the former being consistent with the role of rsh as a global regulator described in other species
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34
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. The extent of differential expression is illustrated by the ratio/intensity MA plots in Additional file 2. Alarmone dependency was determined by comparing gene expression of the wild type and rsh mutant during each of the three sampled growth phases (Figure 2a). A total of 834 (p)ppGpp-dependent genes with an expression ratio of at least two-fold were found. Approximately half of these genes (520) were expressed exclusively during stationary phase and only a minority (36) were found to be (p)ppGpp-dependent during all growth conditions.
<p>Additional file 2</p>
Figure S2. MA plots comparing transcriptome data. Scatter plots of the microarray data that plot the distribution of the log2 intensity ratio (M-value) versus the log2 average intensity (A-value). Differentially expressed genes that are upregulated or downregulated are shown in red or green, respectively. The number of genes with a growth phase or (p)ppGpp-dependent expression profile are indicated by histogram bars at the right of the MA plot. (a) Wild type compared to rsh mutant in stationary phase. (b) Wild type compared to rsh mutant in exponential phase.
Click here for file
<p>Figure 2</p>(p)ppGpp-dependent gene expression
(p)ppGpp-dependent gene expression. (a) Venn diagram of all differentially expressed (p)ppGpp-dependent genes during early exponential phase, late exponential phase and stationary phase. (b) Venn diagram of all genes expressed during stationary phase (large ellipse). The overlap with (p)ppGpp-dependent genes (see (a)) shows all (p)ppGpp-dependent stationary phase genes (small ellipse). Upwards and downwards oriented arrows indicate gene induction and repression, respectively.
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By comparing expression in the wild type during stationary and early exponential phase, we identified 657 stationary phase genes (Figure 2b), representing 11% (or 657/6,030) of the annotated protein-coding genes. The overlap of (p)ppGpp-dependent genes and stationary phase genes shows that just over half (57% or (229 + 144)/657) of stationary phase genes are (p)ppGpp-dependent. Because 61% (or 229/373) of these were upregulated (Figure 2b), the alarmone (p)ppGpp seems to have a primarily inducing role in R. etli. A comparable number of (p)ppGpp-dependent genes were found in other bacteria: 490 (11%) of all genes in E. coli and 194 (6%) in Corynebacterium glutamicum after (p)ppGpp-induction by serine hydroxymate
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, 589 genes (7%) upon induction of (p)ppGpp synthesis in Streptomyces coelicolor
35
and 373 (18%) of all genes after treatment with mupirocin in Streptococcus pneumoniae
23
.
The microarray data were confirmed by analyzing the expression levels of 14 representative genes using reverse transcription-quantitative PCR (RT-qPCR; see Materials and methods). For each gene, expression during early exponential phase and stationary phase in the wild type and rsh mutant was measured so that three different ratios could be plotted versus the respective ratios obtained by microarray analysis (Figure 3), showing the array data to be in good agreement with the RT-qPCR data.
<p>Figure 3</p>RT-qPCR validation of the microarray data
RT-qPCR validation of the microarray data. Expression of 14 genes was determined using RT-qPCR for the wild type and rsh mutant in early exponential phase and stationary phase. The log2-transformed mean values of two biological replicates were used to report three different fold changes for each gene (Y-axis) compared to the respective microarray fold changes (X-axis). See Additional file 6 for a complete list of the plotted fold change values. Red dots, wild type stationary phase versus early exponential phase. Blue diamonds, wild type versus rsh mutant in stationary phase. Green squares, wild type versus rsh mutant in exponential phase. The fold changes for ecfG2/PF00052, CH00371 and prkA/CH02817 are indicated.
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The effect of (p)ppGpp on global gene expression during stationary phase
During stationary phase in E. coli, the alarmone (p)ppGpp induces a downregulation of processes involved in cell growth, such as DNA replication and translation, and an upregulation of specific metabolic pathways to cope with certain nutrient deficiencies as well as general stress responses to protect the cell against immediate and future harmful conditions. In order to better understand the role of (p)ppGpp in the global reprogramming of R. etli's transcriptome, we compared the expression of wild type and rsh mutant during stationary phase. As samples were taken approximately 6 hours after growth arrest, the observed differences in expression include both direct and indirect effects caused by a lack of alarmone. Of the 663 differentially expressed genes, 292 and 371 were upregulated and downregulated, respectively, in the wild type compared to the rsh mutant (Figure 2a). These genes were further grouped based on predicted functional role and category (Additional file 3). An overview of the functional categories (Figure 4a) shows the mutant to be less well adapted to the non-growing lifestyle as more growth-associated genes, involved in cell wall biosynthesis, energy production and intracellular trafficking and secretion, are induced in the mutant. Notably, the replication and recombination category is strongly represented in the mutant due to the high number of insertion sequence (IS)-related genes that show expression. An equal number of genes with unknown function were up- and downregulated. In the following paragraphs, selected functional categories, primarily focused on regulation and possible links with the pleiotropic stress phenotype, will be discussed in more detail.
<p>Additional file 3</p>
Table S1. The differentially expressed genes during stationary phase and exponential phase in the wild type compared to the rsh mutant.
Click here for file
<p>Figure 4</p>Differentially expressed genes grouped by functional categories
Differentially expressed genes grouped by functional categories. Up- and downregulated (wild type versus rsh mutant) genes are indicated by red and green bars, respectively, representing the number of genes per functional category. Functional categories of the RhizoBase database were used 92. (a) Stationary phase data of wild type versus rsh mutant. (b) Early exponential data of wild type versus rsh mutant.
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Transcriptional regulators and signal transduction
The link between changes in extracellular conditions and concomitant adaptation of genome expression involves a combination of sensors, transporters, phosphorylation cascades and the modulation of transcription factors
36
. Most of these belong to the 'transcription' and 'signal transduction' categories, of which 29 and 26 genes are differentially expressed, respectively, in the wild type compared to the (p)ppGpp-deficient mutant at onset of growth arrest (Additional file 3).
By clustering the differentially expressed genes of these two categories, we identified two main groups (Figure 5). The first group contains genes that are under negative (p)ppGpp control during primarily the stationary phase and include the LysR transcriptional regulators nocR and nodD3, the two-component sensor kinase virA and two diguanylate cyclases, PD00137 and PE00107. The second group contains genes that are under positive (p)ppGpp control during primarily the stationary phase, encoding among others the transcriptional regulators RirA and BolA-like CH02287, the CarD-like regulator CH04025, the two-component response regulators CH02556 and CH03335, and the N-acyl-L-homoserine lactone (AHL) synthase CinI.
<p>Figure 5</p>Clustering of differentially expressed signal transduction and transcription-related genes
Clustering of differentially expressed signal transduction and transcription-related genes. The heat map visualizes the expression profiles of all differentially expressed genes belonging to the transcription category and signal transduction category in the wild type and rsh mutant during stationary phase. The expression values in each row were standardized by subtraction of the mean and division by the standard deviation and hierarchically clustered. Expression values are reflected by red-green coloring as indicated. Genes showing similar expression patterns are grouped as follows: group 1, genes under negative (p)ppGpp control during stationary phase; group 2, genes under positive (p)ppGpp control during stationary phase. Exp., exponential; Stat., stationary.
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Several of these transcriptional regulators have previously been shown to play a role in the adaptation to adverse conditions in other species and can partly explain the pleiotropic stress phenotype of the rsh mutant. In E. coli, BolA controls expression of a number of cell wall proteins, is partially responsible for the coccoid morphology of stationary phase cells and is also expressed in a (p)ppGpp-dependent manner, being under control of RpoS
5
18
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. Reduced BolA levels may therefore contribute to the altered morphology of the R. etli rsh mutant. Furthermore, expression of the global iron-responsive regulator RirA that controls the synthesis of heme, FeS-clusters and bacterioferritin in rhizobia, is under positive (p)ppGpp control as well
37
38
. Accordingly, expression of bacterioferritin (bfr) was positively upregulated in the R. etli wild type, suggesting that (p)ppGpp contributes to iron homeostasis. Conversely, a lack of iron may cause an increase in the level of (p)ppGpp in order to regulate iron homeostasis in the cell as reported in E. coli and B. subtilis
39
40
. Since iron plays a crucial role in the oxidative stress response, incomplete iron sequestration may also contribute to the increased oxidative stress sensitivity of the rsh mutant
30
41
. Other regulators under positive (p)ppGpp control include two members of the cold shock protein family (CspA3, CspA4), a putative member of the UspA family (CH01233), the SOS response regulator LexA and the two-component regulator TcrX. TcrX is orthologous to PhyR of Methylobacterium extorquens, which regulates many stress response genes and was shown to play a role in the osmotic stress response in R. etli as well
42
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.
Sigma factors
R. etli CFN42 possesses 23 sigma factors that determine the promoter specificity of the RNAP holoenzyme by binding to the core enzyme. Therefore, differential expression and/or activity of sigma factors can redirect global gene expression. During exponential growth, transcription is largely under control of the housekeeping sigma factor σ70 as its binding affinity for RNAP and intracellular concentration are much higher compared to the other sigma factors. These alternative sigma factors have specific regulons and will redirect transcription upon unfavorable conditions. Bacteria like R. etli that have a complex lifestyle or encounter diverse environmental conditions usually display an increased number of sigma factors
5
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.
Upon transition to stationary phase, the reversible switch to a less σ70-dominated expression in E. coli is accomplished not solely by (p)ppGpp but also by DksA and the anti-σ70 factor Rsd. In R. etli, expression of dksA is reduced over eight-fold in stationary phase compared to early exponential phase in a (p)ppGpp-independent manner. The role of DksA in α-proteobacteria is so far unknown. Furthermore, no Rsd homolog is found in R. etli or other other α-proteobacteria. R. etli may compensate for the lack of a specific anti-σ70 factor, as we observed a (p)ppGpp-independent drop in expression of the housekeeping sigma factor sigA to below the detection limit while expression in E. coli of σ70 remains constant during stationary phase.
Of all the alternative sigma factors, only the extracytoplasmic function (ECF) sigma factor PF00052 was upregulated at least two-fold during stationary phase compared to early exponential phase in the wild type. The ECF sigma factor rpoE4 is expressed at the same level during all conditions in the wild type, but dropped below the expression threshold during stationary phase in the rsh mutant. Consequently, two ECF sigma factors, PF00052 and rpoE4, were upregulated over two-fold in the wild type compared to the rsh mutant during stationary phase (Figure 5). In E. coli, only the level of the stationary phase sigma factor rpoS (σS) increases with (p)ppGpp concentration and plays a crucial role as global regulator in the (p)ppGpp-dependent stress response
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. In contrast, ε- and α-proteobacteria, including R. etli, lack such a stationary phase sigma factor and, so far, it is unclear which system takes over this function.
Our data suggest that both PF00052 and RpoE4 may be important sigma factors in R. etli adaptation to stationary phase and possibly fulfill a role similar to RpoS in E. coli. First, both sigma factors are expressed during stationary phase. Second, both sigma factors are the most highly upregulated (p)ppGpp-dependent alternative sigma factors during stationary phase. Third, both share considerable sequence similarity and were recently classified in a group of proposed general stress response sigma factors that is exclusively found in α-proteobacteria
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. Fourth, it was recently shown in R. etli that RpoE4 regulates gene expression in response to several stress conditions including oxidative, saline and osmotic stress. Fifth, we found that PF00052 is also involved in the (p)ppGpp-dependent stress response and is in part functionally redundant with RpoE4 (see below).
Transcriptome analysis of an R. etli rpoE4 mutant and overexpression strain revealed 98 genes to be regulated by this sigma factor
42
. Since transcription of rpoE4 is (p)ppGpp-dependent, we investigated to what extent the reported RpoE4 regulon is (p)ppGpp-dependent. In total, 60 of the 98 genes belonging to the reported regulon are differentially expressed in our data (Additional file 4). Of these genes, 82% are (p)ppGpp-dependent and 92% are up- or downregulated during stationary phase compared to early exponential phase in the wild type. Upon rpoE4 overexpression, 74% of the reported upregulated genes were found to be (p)ppGpp-dependent.
<p>Additional file 4</p>
Table S2. The RpoE4-regulated genes according to Martinez-Salazar et al. (2009) that were found to be alarmone-dependent in this study
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.
Click here for file
Considering the RpoE4-regulated genes, all 16 genes predicted to encode proteins associated with cell envelope biogenesis are also (p)ppGpp-dependent. Similarly, E. coli's sole ECF sigma factor, σE, regulates many genes involved in the biogenesis and stress response of the cell envelope
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. Other RpoE4 and (p)ppGpp-dependent genes include a putative Mn-catalase (CH00462), a putative pyridoxine-phosphate oxidase (CH03474), an alpha-glucoside ABC transporter (algE), and a CarD-like transcriptional regulator (CH04025). The latter is a crucial regulator in Mycobacterium tuberculosis that is upregulated in response to oxidative stress, DNA damage and starvation
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. The above suggests that the pleiotropic stress phenotype of the R. etli rsh mutant can be explained, at least in part, by downregulation of (p)ppGpp-dependent sigma factors that play a crucial role in orchestrating the stress response.
Non-coding RNAs
Our data indicate that (p)ppGpp controls expression of many protein-coding genes. In addition, we identified 33 alarmone-dependent ncRNAs expressed during stationary phase. Of these, 28 were positively regulated by (p)ppGpp, including one glycine riboswitch, 17 novel ncRNAs, 4 previously identified but uncharacterized ncRNAs, and the 6 well characterized ncRNAs (6S RNA, tmRNA, signal recognition particle 4.5S RNA, RNase P, and ctRNA of plasmids p42d and p42e) (Additional file 5). Only five ncRNAs, all novel, were negatively regulated by (p)ppGpp.
<p>Additional file 5</p>
Table S3. The alarmone-dependent ncRNAs.
Click here for file
So far, no ncRNAs have been reported to be (p)ppGpp-dependent in any organism. However, in recent years, an increasing number of ncRNAs have been found to be regulated by alternative sigma factors in E. coli, Salmonella enterica serovar Typhimurium, L. monocytogenes, B. subtilis and S. coelicolor
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. Therefore, the (p)ppGpp-dependent ncRNAs of R. etli could be regulated by alternative sigma factors as well. Additionally, ncRNAs can also regulate sigma factors, as is the case for σS in E. coli whose translation is regulated by DsrA and RprA
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The level of 6S RNA was almost 14-fold lower in the alarmone-deficient mutant during stationary phase in R. etli. This is unlike in E. coli, where 6S RNA is not under (p)ppGpp control either in vitro or in vivo
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. However, 6S RNA transcription appears to be complexly regulated in E. coli as several stress regulators, such as Fis, H-NS, Lrp and StpA, were shown to be inhibitors under in vitro conditions
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. Recently, transcriptional analysis of a 6S RNA-deficient mutant showed 273 genes to be differentially expressed during stationary phase. Surprisingly, loss of 6S RNA in E. coli also resulted in an increase of the basal (p)ppGpp level mediated by an altered activity of SpoT and not RelA
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. Therefore, 6S RNA is clearly embedded in stationary phase adaptation, although its association with (p)ppGpp in R. etli and E. coli may differ.
Expression of bacterial RNase P and tmRNA was almost 13- and 6-fold downregulated, respectively, in the R. etli rsh mutant compared to the wild type. Although the synthesis and processing of tRNA is expected to be downregulated during growth arrest, 38% of the tRNAs were upregulated in the wild type during stationary phase compared to early exponential phase and 56% of the tRNAs were upregulated in an alarmone-dependent manner. The upregulation of bacterial RNase P during stationary phase in an alarmone-dependent manner is in line with the unexpected upregulation of several tRNAs as RNase P is required to process the 5' end of precursor tRNAs. Expression of tmRNA is also upregulated in R. etli. This alarmone-dependence of tmRNA expression has not been reported in E. coli, although a lack of 6S RNA results in a three-fold higher expression of the SmpB protein, which acts together with tmRNA
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. However, the expression level of tmRNA was not reported. Interestingly, the 6S RNA mutation is compensated for by an increase of the basal (p)ppGpp level, which indicates that the tmRNA/SmpB system might be alarmone-dependent in E. coli also. Still, (p)ppGpp is not needed for mRNA cleavage in the A site of the ribosome by tmRNA
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. In contrast, both tmRNA and smpB of Streptococcus pyogenes were shown to be upregulated in a relA-independent amino acid starvation response
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Translational apparatus
In addition to inducing general stress and nutrient scavenging regulons, the accumulation of (p)ppGpp upon growth arrest in E. coli is characterized by a stringent downregulation of expression of the translational apparatus as a mechanism to fine-tune the metabolically expensive process of protein synthesis according to the growth state of the cell
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. As expected, during the stationary phase all 56 genes encoding ribosomal proteins were downregulated in the R. etli wild type compared to the exponential phase. However, nearly all (53 out of 56) of these were downregulated in the rsh mutant as well. Although this (p)ppGpp-independent downregulation is in conflict with the established E. coli paradigm of the stringent response, a similar response was described in a rel mutant of Corynebacterium glutamicum upon addition of serine hydroxamate
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. Therefore, the difference in transcriptional regulation of ribosomal protein expression during growth arrest suggests that the stringent response in R. etli may deviate from the classical model in E. coli.
Other genes encoding parts of the translational machinery that were positively regulated by (p)ppGpp in R. etli include the homolog of E. coli yhbH (CH00406) and two EF-Tu elongation factors (tufA, tufB). In E. coli, YhbH is involved in the temporary storage or dimerization of ribosomes during stationary phase. This process was shown to contribute to the survival of E. coli
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. In accordance with our data, the YhbH ortholog of B. subtilis (yvyD) is also under positive (p)ppGpp control
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. However, in contrast to the positive (p)ppGpp-dependent regulation of tufA and tufB in R. etli, TE-Tu factors in E. coli and B. subtilis were previously shown to be under negative control of (p)ppGpp
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. Interestingly, translation factors such as TE-Tu are GTPases that can bind (p)ppGpp and associate with the ribosome, indicating that they may have a downstream role in (p)ppGpp-dependent gene regulation
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.
Post-translational modification, repair and recombination
The (p)ppGpp-dependent stress adaptation during stationary phase involves 20 genes belonging to the post-translational modification category, of which 15 were positively regulated. These include several components of the ATP-dependent Clp protease system, such as clpX, clpP2, clpP3, clpA and clpS, as well as the ATP-dependent proteases lon and ftsH
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. These proteases allow cells to cope with misfolded or denatured proteins, the abundance of which increases during stress conditions, such as heat stress, in order to prevent protein aggregation and to enable recycling of amino acids
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. A similar (p)ppGpp-dependent regulation was observed for clpA in E. coli as well as clpP1 and clpC in C. glutamicum
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. Thus, the (p)ppGpp-dependent increase of tmRNA in R. etli correlates with the increase in proteases as the Clp system and Lon are needed to degrade tmRNA-tagged polypeptides in E. coli
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.
Proteases and chaperones are also involved in regulating transcriptional regulators and other growth-phase regulated proteins, such as RpoS, Dps and GlnA in E. coli
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. Therefore, by controlling proteolysis, the alarmone (p)ppGpp mediates the cellular reprogramming of R. etli at the post-transcriptional level as well. Other positively controlled genes include the probable serine protease CH01273, the small heat shock protein PF00472 as well as genes required to cope with oxidative stress, such as osmC and grlA.
Rather unexpectedly, very few genes of the repair and recombination category were under positive stringent control. However, several IS-related genes were negatively controlled by (p)ppGpp, including 47 transposases, one resolvase, and one integrase. Therefore, these data suggest that the alarmone may assist in repressing insertional activity and mobility of IS-related elements.
Other processes
The impact of (p)ppGpp as a global regulator of transcription is further illustrated by its control of genes involved in diverse cellular processes. In E. coli, the alarmone plays a central role in restructuring metabolism upon nutrient starvation and growth arrest, thereby increasing the range of active metabolic pathways and nutrient scavenging potential
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. In R. etli, the alarmone likely has a similar role in metabolism as differential gene expression was detected for 22 genes involved in amino acid metabolism, 41 genes in carbohydrate metabolism, 9 in lipid metabolism and 22 in energy production.
(p)ppGpp was shown in E. coli to induce amino acid biosynthesis pathways depending on the availability of limiting amino acids. However, compared to exponential phase, no clear upregulation during stationary phase of one or more specific amino acid pathways was found in the R. etli wild type. Only a few genes involved in amino acid metabolism were positively controlled by (p)ppGpp (phhA, cysE1, glnA2, trpE). In addition, 13 amino acid synthesis genes (trpF, trpA, hisB, asnB, aroQ1, aroF, ilvI, aatA, lysC, argG2, tyrA, leuD, asd) along with the P-II regulator glnB, which regulates glutamine synthetase in response to nitrogen levels, were downregulated in a (p)ppGpp-independent manner during stationary phase compared to exponential phase. Therefore, during stationary phase, amino acid biosynthesis in R. etli is downregulated rather than upregulated as in E. coli.
Several genes encoding key enzymes of carbohydrate metabolism were induced by (p)ppGpp, including the transaldolase tal of the pentose pathway, glgC involved in starch and sucrose metabolism, the glycolytic gene fbaB and the gene encoding trehalose-6-phophatase, otsB. These genes were also shown to be under positive control by (p)ppGpp in E. coli upon amino acid starvation
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. FbaB is a fructose-bisphosphate aldolase whose reaction product can exert feedback control on the glycolytic flux and is also required for ribosome recycling during carbon starvation
6
. Moreover, OtsB produces the disaccharide trehalose from trehalose-6-phosphate, which is produced by OtsA using UDP-glucose and glucose-6-phosphate. Not only is trehalose an energy and carbon source, it also stabilizes and protects proteins and membranes from dehydration, oxidation and cold
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. Recently, it was shown that all three trehalose synthesis pathways known to date are present in S. meliloti. However, only the OtsA pathway is important for osmo-inducible trehalose synthesis
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. In R. etli, overexpressing otsA improves symbiotic efficiency and drought tolerance of its host P. vulgaris
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. During stationary phase, otsA and otsB have a different expression pattern; otsB is induced by (p)ppGpp while otsA is constitutively expressed in the wild type but under negative (p)ppGpp control upon growth arrest. It is possible that this (p)ppGpp-dependent regulation of trehalose synthesis contributes to the previously observed increased sensitivity of the rsh mutant to osmotic stress
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The link between the stringent response and the available carbon sources remains unclear. In E. coli, the (p)ppGpp synthetase/hydrolase SpoT interacts with acyl carrier proteins (ACPs) of fatty acid metabolism
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. R. etli contains four acyl carrier proteins, of which only two (acpP, acpXL) were expressed during growth and downregulated upon growth arrest independently of (p)ppGpp. In contrast to E. coli, no clear (p)ppGpp-dependent regulation of lipid metabolism genes was observed. Also, most of the nucleotide biosynthesis genes are downregulated during stationary phase compared to exponential phase in the wild type, reflecting the decreased need for nucleotides. Only six nucleotide biosynthesis genes were found to be under control of (p)ppGpp in R. etli. This is in accordance with the observed (p)ppGpp-independent downregulation of ribosomal proteins.
As well as regulating R. etli's biosynthetic potential, (p)ppGpp also controls its transport capacity during stationary phase. Twenty-one genes related to ABC transporters were under positive (p)ppGpp control, such as potF, dppA, proX, aglK, and gguB, while 12 were repressed. Most of these transporters allow for the uptake of amino acids, peptides and monosaccharides. In addition, two secretion-associated genes (secB and pilA) were upregulated and seven genes involved in type IV secretion were downregulated (virB1a, 2a, D4, B6a, B8a, B8d, B10). Interestingly, the pilin subunit pilA was the most highly expressed protein-encoding gene in R. etli during stationary phase.
Energy production drops during the stationary phase as more than 25 genes predicted to be involved in oxidative phosphorylation were downregulated compared to exponential phase in the wild type. In contrast to E. coli, 76% of the differentially expressed genes that belong to the energy production category, 95 in total, are not under (p)ppGpp control
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. During free-living growth, R. etli uses cytochrome aa3 terminal oxidases, encoded by ctaCDGE, coxPONM and CH00981-CH00985
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. The ctaCDGE terminal oxidase was downregulated during stationary phase in both the wild type and the rsh mutant. On the other hand, the coxPONM alternative terminal oxidase was upregulated during stationary phase in the wild type but not in the rsh mutant. The third probable terminal oxidase was not expressed. Therefore, the alternative terminal oxidase coxPONM is likely to play an important role during (p)ppGpp-dependent stationary phase adaptation.
In addition to the decrease in energy production, flagellum synthesis and motility is also downregulated during stationary phase, reflecting that it is a highly energy demanding process. In E. coli, flagellar genes are under positive (p)ppGpp control
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. Similarly in R. etli, (p)ppGpp positively regulates flagellar gene expression. However, this regulation occurs primarily during the exponential phase instead of the stationary phase, as 25 of the 35 flagellar genes were expressed above threshold during the exponential phase compared to 10 during the stationary phase. Of the latter, three flagellar hook-related genes (flgD, flgE, flgL) and two flagellin synthesis regulators (flaF, flbT) were upregulated in the wild type compared to the rsh mutant
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. FlgD forms a scaffold on which the hook subunit FlgE polymerizes on the envelope-embedded rod to form the flexible hook structure. FlgL is a junction protein connecting the rigid flagellar filament. In short, (p)ppGpp regulates several crucial flagellar genes in R. etli.
The effect of (p)ppGpp on global gene expression during early exponential phase
By comparing the expression data of the wild type and rsh mutant during early exponential growth, we identified 203 differentially expressed genes, of which 59 were under positive stringent control and 144 under negative stringent control. This is surprising as transcription during the exponential phase of a (p)ppGpp-deficient mutant and the wild type is generally thought to be very similar. The alarmone is considered to be a stationary phase or growth arrest-specific messenger that switches the cellular metabolism to a non-growing state. During favorable growth conditions, (p)ppGpp is produced at a low basal level and rapidly accumulates in response to growth-perturbing conditions. Furthermore, during the exponential phase, a (p)ppGpp-deficient mutant of E. coli is phenotypically very similar to the wild type, although a decreased growth phase-independent thermotolerance has been reported
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. However, to the best of our knowledge, to this date no detailed comparison of global transcription during exponential growth has been described for a wild type and relA spoT mutant of E. coli, which serves as the stringent response model organism. Still, it was recently shown that almost 300 genes were differentially expressed in an rpoS mutant of E. coli during exponential growth, even though RpoS is known as the stationary phase sigma factor
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. This would suggest that a difference in expression during logarithmic growth in a (p)ppGpp-deficient mutant could be expected as (p)ppGpp regulates the expression and activity of RpoS in E. coli. Moreover, a major difference in expression during growth in the absence of (p)ppGpp was also previously observed in M. tuberculosis and C. glutamicum
34
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. Our data are in agreement with these reports, showing that the low basal level of (p)ppGpp is functionally relevant during active growth. This additional function is also in agreement with the observed increase in sensitivity to several acute and chronic stresses of a R. etli rsh mutant during exponential growth
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.
A comparison of the (p)ppGpp-dependent genes during early exponential phase and stationary phase showed that only 50 genes were differentially expressed in both states. Of this fraction, only half of the genes showed similar positive or negative control during both phases. This suggests that the function of (p)ppGpp differs during active growth and growth arrest, possibly through involvement of other regulators. To further understand the impact and role of the alarmone during exponential growth, we again grouped the up- and downregulated genes in functional categories (Figure 4b). As 71% of these genes were under negative (p)ppGpp regulation, the alarmone plays a primarily repressing role during logarithmic growth, in contrast to the observed predominantly inducing role upon growth arrest. For example, the alarmone induces 19 transporters during stationary phase while it represses 12 during early exponential phase. Other genes under negative (p)ppGpp control include 10 conjugal transfer proteins, 5 IS-related transposases and 26 ribosomal proteins. In contrast, nine motility genes were upregulated by (p)ppGpp, such as three of the four basal-body rod proteins (flgBCG), one of the three flagellar switch proteins that interact with the chemotaxis system (fliN) and three chemotaxis proteins (motA, cheW5, cheY1). Therefore, (p)ppGpp has a similarly inducing role on flagellar genes during growth as observed upon growth arrest. A swimming test on 0.2% agar plates corroborates this observation (Figure 6). The (p)ppGpp-deficient mutant showed reduced swimming activity compared to the wild type, a phenotype that could be partially complemented by providing the rsh gene in trans. Hence, the alarmone is required for optimal motility, as was also previously reported for E. coli
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.
<p>Figure 6</p>Swimming motility test
Swimming motility test. Swimming halo diameter observed on 0.2% agar TY plates on three consecutive days for wild type, rsh mutant and complemented rsh mutant. The mean values and standard deviation of five biological replicates are shown. The differences over time are statistically significant between the different strains (P < 0.001).
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Remarkably, in addition to growth-related genes, many post-translational modification genes were under negative stringent control in the rsh mutant. These comprise numerous chaperones, including the three major ones, tig, dnaK and groEL-groES, involved in folding of new proteins as well as in proper assembly of unfolded proteins and refolding of misfolded proteins generated under stress conditions
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. DnaK is also involved in chromosomal DNA replication and is part of the osmotic stress response, in addition to osmC
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. Other upregulated heat shock proteins in the rsh mutant include four peptidases (hslV, lon, traF, htpX2) and one protease (ftsH). Although exponentially growing cells are considered to be less stressed, this increased expression of many heat shock proteins in actively growing cells in the absence of (p)ppGpp might indicate a defect or disruption in protein homeostasis, rather then merely an increase in translational activity. Therefore, this stress response during growth is in accordance with increased stress sensitivity of the rsh mutant as observed previously
30
.
Functional analysis of three (p)ppGpp-dependent regulators
To gain insight into the (p)ppGpp-controlled adaptation of R. etli to the stationary phase and diverse stresses as previously reported
30
, we selected three different types of previously uncharacterized regulators based on their strongly (p)ppGpp-dependent expression during stationary phase and belonging to the group of transcriptional regulators (ecfG2, phrR) or signal transduction (prkA). The microarray expression patterns of these regulators were confirmed using RT-qPCR (Figure 3). A phenotypical analysis was performed on the corresponding knockout strains to determine the regulators' contribution to the (p)ppGpp-regulated stress response.
Extracytoplasmic function sigma factor PF00052 or EcfG2
R. etli PF00052 is the most highly upregulated alternative sigma factor during stationary phase in the wild type and upregulated over two-fold compared to the rsh mutant. Analysis of the PF00052 knockout mutant showed decreased survival following oxidative stress, approximately three orders of magnitude lower compared to the wild type (Figure 7). In accordance, the rsh mutant also displays an increased oxidative stress phenotype
30
. In contrast to the rsh mutant, however, the PF00052 mutant does not show a decreased viability after osmotic or heat shock.
<p>Figure 7</p>Stress survival of (p)ppGpp-dependent regulator mutants
Stress survival of (p)ppGpp-dependent regulator mutants. Survival of the wild type, ecfG2 mutant, rpoE4 mutant, ecfG2-rpoE4 mutant and CH00371 mutant was determined by plating on TY medium after stress treatment and is shown as the mean log(colony forming units (CFU)/ml) of three biological replicates with error bars corresponding to standard deviations. Light gray bars represent control samples incubated at 30°C for the same time period as test samples. Dark gray bars represent samples incubated for 30 minutes in the presence of 10 mM H2O2 at 30°C. Black bars represent samples incubated for 30 minutes at 45°C. N.D., no colonies detected.
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Recently, a comprehensive phylogenetic analysis classified the ECF sigma factor family into 43 groups supported by domain architecture, genomic context conservation and potential targets
47
. R. etli contains 18 ECF sigma factors, of which three (rpoE4, sigK and PE00004), in addition to PF00052, were expressed during growth arrest as well. RpoE4 and PF00052 are 42% identical and both belong to theECF15/EcfG group, which exclusively contains α-proteobacterial ECFs, such as EcfG1 of Methylobacterium extorquens, RpoE2 of S. meliloti and SigT of C. crescentus. This group of proposed general stress response sigma factors is characterized by a conserved genomic context that encodes an EcfG-like sigma factor, a cytoplasmic NepR-like anti-sigma factor, a PhyR-like response regulator and a sensor histidine kinase. When the latter perceives a signal, it phosphorylates the regulator, which in turn binds to the anti-sigma factor, thereby releasing the sigma factor and initiating a signal transduction cascade
47
. In case of R. etli rpoE4, an anti-sigma factor (CH03274) and a sensor/regulator (tcrXY or CH03275-CH03276) are found upstream of rpoE4, and tcrX is transcribed in a strongly (p)ppGpp-dependent way (Additional file 3). Though PF00052 is also a member of the EcfG group, a similar genomic context was not recognized. Several other α-proteobacteria also have two EcfG representatives, one that is present in the conserved genomic context while the other is not - for example, S. meliloti 1021 and Agrobacterium tumefaciens str. C58
47
. A revised ECF nomenclature has been proposed
47
and has recently been adopted for EcfG-like ECF sigma factors in M. extorquens
43
and Bradyrhizobium japonicum
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. Accordingly, we will hereafter refer to PF00052 as EcfG2.
Due to the high similarity between RpoE4 and EcfG2, we also analyzed the stress sensitivity of an rpoE4 mutant. This revealed a decrease in survival of one order of magnitude upon oxidative and heat stress compared to the wild type (Figure 7). Hence, the rpoE4 mutant exhibits an oxidative stress phenotype less severe than the ecfG2 mutant but, in contrast to the latter, a significant heat stress phenotype. This suggests that RpoE4 and EcfG2 control expression of, at least in part, non-overlapping sets of target genes. To determine if both sigma factors function completely independently in these stress responses, an rpoE4-ecfG2 double mutant was constructed. After heat or oxidative stress treatment, the double mutant showed higher sensitivity than either of the single mutants separately (Figure 7). Moreover, survival of the double mutant is even lower than expected based upon the respective phenotypes of the single mutants, indicating a synergistic effect. Hence, we conclude that both sigma factors have partially overlapping functions in the (p)ppGpp-mediated stress response of R. etli to the tested stress conditions.
R. etli has two heat shock sigma factors that may contribute to the observed heat stress phenotype. RpoH1 was shown to be the main heat shock sigma factor, though a more complete response requires RpoH2
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. The promoter region of both sigma factors contains an EcfG-like binding site.
Recently, expression of R. etli rpoH2 was shown to be under positive control of RpoE4, while expression of rpoH1 is not
42
. To determine whether either or both rpoH sigma factors are regulated by EcfG2, their expression was analyzed by qPCR. The expression level of rpoH1 was not altered in the ecfG2 mutant compared to the wild type, while the transcription level of rpoH2 was reduced by approximately 25%. In the rpoE4-ecfG2 double mutant, expression of rpoH2 was reduced over 100-fold, confirming its RpoE4-dependency (data not shown). In contrast, the level of rpoH1 was upregulated over 2.5-fold in the double mutant. This increase is more likely a way to compensate for the impaired heat shock response, rather than a negative control of its expression.
Partial redundancy of EcfG-like sigma factors may occur in other α-proteobacteria as well. In S. meliloti, two EcfG-like proteins are encoded by rpoE2 and rpoE5. RpoE2 was previously reported to regulate many stress response genes during stationary phase. In agreement with our observations, an S. meliloti rpoE2 mutant showed increased sensitivity to H2O2 during stationary phase and rpoE5 is upregulated under heat stress
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.
Putative transcriptional regulator CH00371 or PhrR
CH00371 encodes a putative DNA-binding transcriptional regulator of unknown function belonging to the xenobiotic response element family. Expression of this gene is under positive (p)ppGpp-control during all growth phases, although most pronounced upon growth arrest. CH00371 is 80% identical to PhrR, a putative repressor protein of S. meliloti. This regulator was shown to be induced by low pH, hence designated PhrR for pH-regulated
79
. In order to investigate whether CH00371 plays a role in the acid stress response, growth of the R. etli wild type and CH00371 mutant was examined at pH levels ranging from pH 3.5 to 10. No growth difference was observed, either at acidic or basic pH (data not shown). In addition to low pH, oxidative stress agents and heat shock at neutral pH induce phrR in S. meliloti as well. Therefore, survival of the CH00371 mutant was determined under oxidative stress and after heat shock. Compared to the wild type, survival decreased by over four orders of magnitude upon oxidative shock following exposure to hydrogen peroxide (Figure 7). No survival was observed after heat treatment. Moreover, a plate assay demonstrated growth inhibition of a CH00371 mutant on medium containing H2O2 but not in the presence of the superoxide generators menadione and paraquat, nor of the organic hydroperoxide producer cumene hydroperoxide (data not shown).
In order to identify downstream elements in the regulatory cascade mediated by CH00371 during R. etli growth arrest, we carried out qPCR expression analysis of a selection of genes presumed to be associated with the oxidative and heat stress responses (Additional file 6). These candidate target genes were selected based on a literature search and sequence analysis. Several of these genes were downregulated. recA, a key regulator of the SOS response involved in DNA repair, and osmC, an osmotically induced peroxidase, were 70% and 30% downregulated in the CH00371 mutant compared to the wild type, respectively. The superoxide dismutase sodC was downregulated by 20%. Surprisingly, expression of katG was not significantly altered despite the oxidative stress phenotype. However, the expression level of katG was very low. This may indicate that KatG primarily exerts its function upon induction by oxidative shock. In addition, oxidative homeostasis is likely impaired in the CH00371 mutant as 14 genes related to oxidative stress resistance, such as gshB, sufBCD and cysK, showed increased expression of over 25% compared to the wild type. Interestingly, four genes of the EcfG2-RpoE4-regulon (CH00600, CH01778, CH01802 and CH02172) were also downregulated over 25%, possibly contributing to the observed heat stress phenotype.
<p>Additional file 6</p>
Table S4. The RT-qPCR fold changes compared to array fold changes and qPCR primers.
Click here for file
Furthermore, the expression level of CH00371 was not altered in the ecfG2 mutant and ecfG2 rpoE4 double mutant compared to the wild type, nor vice versa (data not shown). Hence, these novel regulators exert their role in the observed stress phenotypes of the respective mutants independently of each other.
Putative serine kinase CH02817 or PrkA
CH02817 or prkA is upregulated over 27-fold in the wild type compared to the rsh mutant during stationary phase, making it the most strongly (p)ppGpp-induced gene detected in our array. This was confirmed by RT-qPCR (Figure 3). PrkA belongs to the PrkA family of serine protein kinases and is highly conserved, with homologs in many eubacteria and archae suggesting a conserved function. E. coli and B. subtilis PrkAs were shown to phosphorylate serine residues of proteins
80
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and display 66% and 34% identity with the R. etli ortholog, respectively. Protein phosphorylation usually changes the function of the target by modulating its activity, its localization or interaction with other proteins, thereby converting extracellular signals into cellular responses, such as adaptation of the central metabolism, production of secondary metabolites and pathogenicity
82
. Although the specific regulatory function of PrkA remains unknown, the B. subtilis ortholog was shown to be an important inner spore coat protein under control of the developmental sigma factor σE
83
. Furthermore, prkA is part of a highly conserved gene cluster together with the two downstream genes CH02816 and CH02815. This suggests that prkA is likely the first gene of a three-gene operon in R. etli (Figure 8a), which we confirmed by RT-PCR (data not shown). The second operon gene encodes a protein containing a von Willebrand Factor type A domain and the third encodes a SpoVR-like protein. So far, these genes have not been functionally characterized.
<p>Figure 8</p>prkA genomic context and expression analysis
prkA genomic context and expression analysis. (a) R. etli prkA is the first gene of a three-gene operon. Open reading frames are represented by right facing arrows, genomic coordinates are indicated above. Restriction sites for the deletion insertion of the prkA mutant are depicted by downwards facing triangles, and primer sites for RT-PCR used to determine prkA operon structure are depicted by left and right facing triangles. (b) Expression of prkA-gusA transcriptional reporter fusion was monitored in different R. etli mutant backgrounds during growth in AMS succinate. The strains were the wild type R. etli CFN42, rsh mutant, prkA mutant, ntrC mutant and rpoN1 mutant. Expression levels are shown in Miller units and are the means of three biological replicates with error bars representing the standard deviation. Exp., exponential; Stat., stationary.
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To determine the function of prkA in R. etli, we constructed a non-polar deletion mutant. A phenotypical analysis of this mutant, including survival during stationary phase, osmotic stress, oxidative stress and heat stress, revealed no clear stress phenotype. Therefore, PrkA does not seem to play a crucial role in the stress response of R. etli. This is rather unexpected given the high level of (p)ppGpp-dependency and strong induction under stress conditions in other organisms. In E. coli and S. Typhimurium, the prkA homolog, annotated as yeaG, was also shown to be highly upregulated by (p)ppGpp upon entry into stationary phase as part of the RpoS regulon
81
. In addition, yeaG is upregulated by Lrp during stationary phase in E. coli
45
46
. Other stress conditions were also reported to induce yeaG expression, such as acid and osmotic stress in E. coli and sublethal concentrations of polymyxin in S. Typhimurium
6
.
Additionally, PrkA was postulated to be involved in nitrogen metabolism or the nitrogen starvation response in E. coli based on its potential association with NtrCB and GlnP
46
84
. To examine the transcriptional regulation of prkA in R. etli, we monitored expression of a transcriptional prkA-gusA promoter fusion in various genetic backgrounds (Figure 8b). β-Glucuronidase activity was measured during exponential and stationary phase under the same conditions used for microarray sampling, confirming that the expression of prkA is highly upregulated upon growth arrest in the wild type and positively controlled by (p)ppGpp. Moreover, increased expression of prkA was observed in a prkA mutant, indicating that prkA is negatively autoregulated. Expression of prkA was also shown to be regulated by NtrC and RpoN1. NtrC is a transcriptional regulator involved in nitrogen assimilation and growth in nitrogen-limited conditions, as well as a member of the σN-dependent activator family
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. RpoN1 codes for the main σN operating under free-living growth conditions in R. etli
86
. In the rpoN1 mutant background, prkA showed an even stronger downregulation than in the rsh mutant during stationary phase, showing prkA transcription to be strongly σN-dependent. Because NtrC is a common activator of σN-dependent genes, a similar downregulation of prkA in the ntrC mutant was expected. However, no downregulation of prkA was observed during growth and early stationary phase in the ntrC mutant. Instead, prkA was highly upregulated during late stationary phase compared to the wild type, suggesting that prkA is under negative control of NtrC.
To further analyze the role of PrkA in cellular metabolism, we compared growth of the wild type and prkA mutant on 384 different nitrogen sources using glucose as the sole carbon source. Even though transcriptional control of prkA expression by rpoN1 suggests an involvement for PrkA in nitrogen metabolism, no growth defects were detected. Therefore, the specific function of this highly conserved protein in the (p)ppGpp regulon remains to be identified.