Gibbs sampling was used to detect PmrA-binding motifs in the intergenic regions of three experimentally verified PmrAB targets (ugd, pmrC, pmrG). The logo of the statistically overrepresented motif detected is represented in Figure 1. This motif corresponded to the PmrA-binding site experimentally identified by Aguirre et al. 15 and partially overlapped the PmrA-binding site delineated by Wosten et al. 14. They detected this site upstream of the transcription start of pmrC, in the intergenic region between pmrG and pmrH, and upstream of ugd (on the plus strand) 1415. We used the obtained motif model in a genome-wide screening of the S. typhimurium intergenic sequences 38. Table 1 summarizes the results of our screening, using a threshold as described in Materials and methods. From experimentally verified examples, it appears that the PmrA motif can be biologically functional not only when present on the plus strand (as in the case of pmrH), but also when located on the minus strand (for example in pmrG) 14. Therefore, both strands of the genome sequence were screened.

We can expect to detect conserved biologically active PmrA motifs only in species that have a functional counterpart of the S. typhimurium PmrAB system. Of all the completely sequenced bacterial species, only the genomes of S. typhimurium, S. typhi, Escherichia coli, Shigella flexneri and Yersinia pestis contain the amino-acid motif that determines the specificity of the sensor protein PmrB (the amino acids suggested to be involved in binding Fe³⁺ 4). Also, the protein domains involved in the binding of PmrA to DNA were almost perfectly conserved in the PmrA orthologs in the species above (PF00486 domain, see supplementary information on our website 39). Therefore, these γ-proteobacterial species were used to perform phylogenetic footprinting analysis. For each gene containing a potential hit of the PmrA motif in the S. typhimurium genome sequence, close homologs were selected as described in Materials and methods.

For each dataset we aimed at constructing a local multiple alignment. We used Gibbs sampling to generate motifs that can be used as alignment seeds. Alignments were subsequently constructed based on the positions of these motif seeds. Potential seeds were selected using a heuristic described in the supplementary information on 39. Such multiple alignments summarize the motifs in the intergenic sequences that are conserved between species. We used the alignments to verify whether the putative PmrA motifs retrieved by the genome-wide screening were conserved in other species. Table 1 gives an overview of the results of the genome-wide screening and the phylogenetic footprinting approach (individual alignments are displayed in the supplementary information at 39).

Putative PmrA motifs were detected in the intergenic regions of genes encoding transcriptional regulators, outer-membrane and secreted proteins, proteins with functions involved in flagella and fimbria synthesis, proteins with a function related to the modification of cellular components, putative transport proteins, proteins involved in amino-acid synthesis and also in phage remnants. As mentioned above, if the putative PmrAB-regulated genes contained close homologs in other species, the intergenic sequences of these close homologs were locally aligned to check whether putative PmrA motifs were conserved in these other species as well. For some of the datasets, however, no local alignment could be identified (no motif detected). Closer inspection showed that most of these datasets contained highly homologous paralogs of the original sequence. The intergenic sequences of these paralogs showed an overall low degree of conservation (for example, STM0057) with the original intergenic sequence in S. typhimurium (data not shown). In some of the datasets, a local alignment of the respective intergenic regions could be detected, but the putative PmrA motif was not present within the conserved parts of the alignment (for example, leuO). For these putative PmrAB targets, phylogenetic footprinting could not strengthen the confidence in the prediction of the PmrA motif. If such putative motifs are biologically active, their activity will be restricted to Salmonella serovars or S. typhimurium.

Our analysis revealed that PmrA motifs, present in the intergenic sequences of known PmrAB-dependent S. typhimurium genes, were also conserved in the intergenic sequences of the orthologs of these genes in related species (Figure 2). An overview of the alignments of these known targets is given below.

pmrH (the first gene of an operon that contains the genes pmrHFIJKLM; Table 1) is the only known PmrAB-regulated gene for which the PmrA motif is conserved in all genome sequences analyzed (including that of Y. pestis). In pmrC, encoding a gene with unknown function 1522, the PmrA motif is conserved in the intergenic regions of its orthologs in E. coli strains, Salmonella species and Shigella. ugd encodes a UDP-D-glucose dehydrogenase required for the synthesis of Ara4N. Three two-component systems are involved in its regulation (PmrAB, PhoPQ and RcsCB) 1215 and this is reflected in the presence of the corresponding motifs: ugd contains PmrA, PhoP and RcsB motifs. The experimentally confirmed PmrA motif on the plus strand and part of the -10 sequence as determined by Aguirre et al. have been conserved in S. typhimurium, S. typhi and E. coli 15. The promoter of ugd also has a hit of the PmrA motif on the minus strand. This was, however, not confirmed by DNA footprint analysis 15 and might represent a false positive. The PhoP motif on the plus strand in ugd of Salmonella, although occurring as a dyad, is not conserved in close orthologs and was recently demonstrated to be non-functional 12. The recognition site for the RcsB protein 12 is also conserved in E. coli. Lastly, yibD encodes a putative glycosyltransferase. The PmrA motif is conserved in E. coli. yibD has recently been identified as a PmrAB target by a genome-wide mutagenesis study. Its actual function is still unknown 22.

Our in silico predictions pointed towards putative targets of the PmrAB regulatory system. Some of these have functions that were previously not associated with the PmrAB system. To prove the strength of our in silico approach, four potential targets were selected for biological validation: yibD (novel at the time of our analysis), aroQ (STM1269), mig-13 and sseJ. aroQ and yibD were selected because a perfect repeat of the previously described PmrA half-site (CTTAAT 15) was detected in their respective intergenic regions. mig-13 (Figure 2) was chosen because it has previously been reported as a gene selectively induced in macrophages, but with further unknown regulation 40. sseJ (Figure 2) was further analyzed because although PmrAB-regulated genes have been implicated in animal virulence 2, no direct link between SPI-2 (Salmonella pathogenicity island 2) gene regulation and PmrAB has been demonstrated yet.

For each of these targets, green fluorescent protein (GFP) reporter fusions were constructed and their expression was determined by fluorescence-activated cell sorter (FACS) analysis in wild-type S. typhimurium and a pmrA::Tn10d mutant. Because the PmrAB system is sensitive to Mg²⁺ and Fe³⁺ concentration, we tested the effect of these signals on the expression of the fusions 22 (Table 2). All experiments were performed at pH 5.8 and pH 7.7. All fusions tested exhibited the same PmrAB-dependent expression behavior at both pH levels. In all experiments, pmrC was used as a positive control.

The pmrC fusion showed a clear induction by either Mg²⁺ deprivation or Fe³⁺ excess. The observed level of induction was higher for the Fe³⁺-dependent signal than for the Mg²⁺-dependent signal and the combination of both signals seemed to act synergistically. For both signals, induction was abrogated in a pmrA::Tn10d background, indicating that induction by Mg²⁺ and Fe³⁺ is solely PmrAB dependent. For the mig-13 fusion, similar observations were made, although induction by low Mg²⁺ and the synergistic effect of both signals were less pronounced. mig-13 also exhibited a considerable background expression level both in a pmrA::Tn10d mutant and in the uninduced state in a wild-type background. aroQ was strongly induced by low Mg²⁺ and induction was abrogated in a pmrA::Tn10d background. The influence of Fe³⁺ was less pronounced. In the case of yibD, the opposite was found: the yibD gene was barely induced by low Mg²⁺ but Fe³⁺ excess resulted in a large induction. For the yibD fusion, although Fe³⁺ excess, but not Mg²⁺ deprivation, seemed to be a sufficient signal to trigger expression, both signals acted synergistically. Also, induction of yibD was abrogated in a pmrA::Tn10d background. Compared to the other fusions, the observed expression levels of the sseJ fusion were rather low in the test conditions. Because sseJ showed a higher overall expression level at pH 5.8, these data were considered most representative (see Table 2). Results show an upregulation of sseJ expression in elevated Fe³⁺ concentrations that was absent in the pmrA::Tn10d background. As observed for mig-13, sseJ was expressed at a background level in the mutant pmrA::Tn10d. Interestingly, even at low concentrations, Mg²⁺ seemed to counteract the Fe³⁺-dependent induction.

We constructed a set of mutant PmrA box sequences by site-directed mutagenesis of the PmrA box of yibD. AT → GC and GC → AT substitutions were introduced in the first half-site of the PmrA box (Figure 3a). We focused on the first half-site, as in the experimentally verified target pmrC, the second half-site overlaps with the -35 promoter site 14. Expression was compared in different mutagenized fusions and the nonmutated fusion in the wild type and in the pmrA::Tn10d strain in all conditions mentioned above. For simplicity, only the expression values for two inducing conditions are displayed in Figure 3b. One is induction by the combined action of high Fe³⁺ and low Mg²⁺ concentrations and the other is the induction by raised Fe³⁺ levels in the presence of high Mg²⁺. Observations under all other conditions allowed us to draw similar conclusions. Substitutions in the third and fifth positions of the motif box completely abrogated PmrAB-dependent expression. Mutations of the first, second, fourth or sixth position reduced PmrAB-dependent induction. Note that for the mutation in the second position, expression was very low but not completely abrogated. Results from this site-directed mutagenesis experiment of one representative PmrAB target allowed us to demonstrate unequivocally that the PmrA box we identified was responsible for PmrAB-dependent transcriptional activation. It also allowed us to further delineate the sequence requirements of the PmrA consensus.

On the basis of the instances of the PmrA motif in experimentally verified PmrAB targets of Salmonella (verified previously or validated in this study), a PmrA consensus was built (Figure 4). The motif consensus of PmrA was converted into a regular expression (A/C)(C/T)T(A/T)A(T/G/A) N₅NTT(A/T)A(T/A/G). To construct this regular expression we only considered the two conserved half-sites, because the PmrA motif is believed to be a dyad 15. We preferred the part between the conserved half-sites of the regular expression to be represented as degenerate (that is, N₅). Indeed, the observed degree of conservation in the intermediate part of the motif model (Figure 4b) is probably related to the restricted sample size of the training set rather than being an intrinsic property of the motif. Promising motifs (indicated in bold in Table 1) are, therefore, motifs that match this regular expression and thus contain nucleotides that occur in the conserved half-sites of one of the experimentally verified examples. Promising targets for which the putative PmrA motif was also conserved in species other than Salmonella were mig-13, yrbF, yjgD, ybdO, yejG, lasT and ybdN. Promising targets only present in S. typhimurium and/or S. typhi were STM1269 (aroQ), STM1273, sseJ and lpfA. Note that this listing is just based on an arbitrary selection criterion, that is, a preliminary PmrA motif consensus that will be improved as more PmrAB targets become experimentally validated. As well as the targets mentioned above, Table 1 contains other targets that are of interest because their annotation relates to the PmrAB system (such as yncD).

Genome sequences were obtained from GenBank 50. All intergenic regions used in this study were extracted using the modules of INCLUSive 51 to automatically parse GenBank entries 52. Here, we define an intergenic sequence as a region that contains the noncoding sequence between two coding regions. No overlap with coding regions is allowed. Intergenic regions with lengths smaller than 10 base-pairs (bp) were discarded because of computational reasons.

A motif model (a probabilistic representation of the consensus DNA pattern that is recognized by the respective regulatory protein) for PmrA was constructed using MotifSampler 53. The PmrA training set consisted of the promoter regions of three known PmrAB-regulated genes (ugd 71517, pmrH 7141719 and pmrC 214) for which the binding of the PmrA protein to the promoter regions was verified by DNA footprint analysis 1415.

The intergenic regions of the complete genome of S. typhimurium LT2 (NC_003197 38) were screened using MotifLocator 5455. The scoring scheme used by MotifLocator is extensively described in Thijs et al. 55 and uses an extension of the classical position-weight matrix scoring scheme 56. Given the motif model θ and the background model B_m a score W(x) is computed for each window x of length l in the sequence S. W(x) compares the score of the subsequence within the window being generated by the motif model to the score of the subsequence within the window being generated by the background model. b_j: nucleotide at position j in the segment.

Both the plus and minus strand were screened using a background model of order 3. The higher-order background allows implicit compensation for motifs that are located in a context highly resembling the global nucleotide composition of the genome. To apply a threshold on the scores, the scores of different motifs were normalized such that their values ranged between 0 and 1. The normalized scores are displayed in Table 1.

Hits with a score above 0.75 were retained (corresponding to a selection of the 0.003% top-scoring hits of the total number of possible motif positions in the genome. Possible positions are identified as overlapping windows of length l). To give a rough assessment of the number of hits with a score similar to the chosen threshold that could be expected from the specific nucleotide composition of the genome, we generated 100 random sets of intergenic sequences using a third-order background model. These random sets were scored with the same PmrA motif model. From these results it appeared that the true set contained three times more hits with a score above the threshold than an average random genome.

Highly similar homologs of the putative PmrAB-regulated genes were identified in the genome sequences of S. typhimurium (NC_003197), S. typhi (NC_003198), S. flexneri (NC_004337), E. coli O157:H7 (NC_002695), E. coli O157:H7 EDL933 (NC_002655), E. coli K12 (NC_000913), Y. pestis CO92 (NC_003143) and Y. pestis KIM (NC_004088). In general, only true orthologs are likely to have retained a similar function and therefore a similar mechanism of regulation 35. However, ortholog identification is a difficult problem and discriminating between true orthologs and paralogs is not always straightforward. Because our motif-detection algorithm is, to some extent, robust against the presence of noise and allows for the presence of sequences that do not contain the motif 57, we did not make an a priori distinction between true orthologs and paralogs if both appeared highly similar to the original protein. This motivated us to use the principle of clusters of orthologs for dataset construction 58. The pairwise BLAST scores obtained by mutually aligning the whole-genome sequences using BlastP 59 were used as input of the cluster program TRIBE-MCL 60. Stringent criteria were applied to retain only closely related orthologs and paralogs (cut-off of the BLAST hit was an E-value of 1e^-80). For those proteins that, when BLASTed against themselves, gave rise to an E-value higher than 1e^-80 (yjbE, STM1926, STM0344, yhcN, STM1868A, yceP, atpF, yjgD, csrA, ybfA) the threshold was relaxed (E-value 1e^-20). The choice of the stringent threshold was essential to maximally reduce the noise in the datasets.

We used a two-step procedure for phylogenetic footprinting. In the first step, Gibbs sampling is performed to generate a list of motifs. Subsequently, local alignments are generated by selecting motifs that can be used as alignment seeds and by assessing the relevance of the alignments by a test statistic.

Functional annotation was derived from the National Center for Biotechnology Information (NCBI) 3852 and from the Sanger annotation of S. typhi 64. Specific genomic context was derived from NCBI 3852. The distribution of the putative targets (unique for Salmonella species versus more widely distributed), as derived from our clusters of orthologous groups (COGs), was verified by comparison to the analysis of McClelland et al. 38, who included, in addition to the species we used, several subspecies of Salmonella (six genomes), and species more distantly related to Salmonella (Klebsiella pneumoniae).

The bacterial strains and plasmids used in this study are listed in Table 3. Bacteria were grown overnight at 37°C with aeration in Luria-Bertani (LB) broth or in the nitrogen minimal medium of Nelson and Kennedy 65 with modifications as previously described 66. The pH of the medium was buffered with 100 mM Tris-HCl, adjusted to pH 7.4 or pH 5.8. MgCl₂ was added at a final concentration of 10 μM or 10 mM. FeCl₃ was used at a final concentration of 100 μM from a freshly prepared 10 mM stock. Antibiotics were used, when appropriate, at the following concentrations: tetracycline, 30 μg/ml; and ampicillin, 100 μg/ml.

Plasmid DNA, after passage through S. typhimurium LB5010 67, was introduced into bacterial strains by electroporation. Polymerase chain reaction (PCR) was carried out in a Personal Mastercycler (Eppendorf, Hamburg, Germany) with Pfx DNA polymerase, using the manufacturer's instructions. The constructs containing the putative promoter regions of yibD, mig-13, aroQ, sseJ and pmrC and the site-directed mutated yibD promoter fragments were all verified by sequence analysis.

To construct the gfp reporter fusions of yibD, mig-13, aroQ, sseJ and pmrC, the primers listed in Table 4 were used in a PCR reaction (as described above) to amplify the respective promoter regions from the ATCC14028s genome. Restriction sites in the primers are indicated in bold face in Table 4. The promoter fragments were digested with EcoRI and BamHI and cloned into pCRII-TOPO that had been digested with EcoRI and BamHI. The promoter fragments were subcloned as EcoRI/BamHI fragments into the corresponding sites of pFPV25 40, resulting in the pCMPG plasmids listed in Table 3. These plasmids were electroporated into ATCC14028s and JSG421 21 after propagation through LB5010, as described above. Cloning steps were carried out in E. coli DH5α.

The single base-pair substitutions in the putative PmrA motif occurring in the yibD promoter sequence were introduced via a PCR approach using the QuickChange Site-Directed mutagenesis kit (Stratagene, La Jolla, CA), according to the manufacturer's instructions. The yibD promoter sequence introduced into pCRII-TOPO was used as the parent plasmid and appropriate primers were applied (sequences not shown). The site-directed mutated yibD promoter fragments were subcloned into pFPV25 (EcoRI/BamHI), resulting in plasmids pCMPG5615 → pCMPG5620, as listed in Table 3. These reporter plasmids were electroporated into ATCC14028s and JSG421.

Bacterial strains harboring the reporter constructs were grown overnight in nitrogen (N)-minimal medium pH 7.4 plus 10 mM MgCl₂, harvested, washed in N-minimal medium pH 7.4 without MgCl₂, and diluted 1:100 in N-minimal medium pH 7.4 plus 10 mM MgCl₂. Mid-log-phase bacteria were then inoculated into the indicated media and grown for 3 h to allow expression of GFP. Bacteria were diluted into PBS and analyzed by flow cytometry with a Becton Dickinson FACSCalibur and CellQuest acquisition and analysis software 40 with gates set to forward and side scatters characteristic of the bacteria.

As the gene names used in the annotation of the S. typhimurium genome sequence do not always match the 'common' names used in the PmrAB literature, we give a summary of the synonyms below. STM1269 (aroQ); ybjG (mig-13); pmrAB (basSR); ugd (udg, pagA, pmrE); pmrHFIJKLM (yfbE, pmrF, yfbG, STM2300, pqa, STM2302, STM2303); pmrC (yjdB); pmrG (ais); pbgP (yfbE,pmrH).

All additional information of our analysis is available on our supplementary website 39.