Skip to main content
  • Research article
  • Open access
  • Published:

Identification of chromosomal alpha-proteobacterial small RNAs by comparative genome analysis and detection in Sinorhizobium meliloti strain 1021

Abstract

Background

Small untranslated RNAs (sRNAs) seem to be far more abundant than previously believed. The number of sRNAs confirmed in E. coli through various approaches is above 70, with several hundred more sRNA candidate genes under biological validation. Although the total number of sRNAs in any one species is still unclear, their importance in cellular processes has been established. However, unlike protein genes, no simple feature enables the prediction of the location of the corresponding sequences in genomes. Several approaches, of variable usefulness, to identify genomic sequences encoding sRNA have been described in recent years.

Results

We used a combination of in silico comparative genomics and microarray-based transcriptional profiling. This approach to screening identified ~60 intergenic regions conserved between Sinorhizobium meliloti and related members of the alpha-proteobacteria sub-group 2. Of these, 14 appear to correspond to novel non-coding sRNAs and three are putative peptide-coding or 5' UTR RNAs (ORF smaller than 100 aa). The expression of each of these new small RNA genes was confirmed by Northern blot hybridization.

Conclusion

Small non coding RNA (sra) genes can be found in the intergenic regions of alpha-proteobacteria genomes. Some of these sra genes are only present in S. meliloti, sometimes in genomic islands; homologues of others are present in related genomes including those of the pathogens Brucella and Agrobacterium.

Background

Numerous DNA sequences giving rise to small non-coding RNAs (ncRNAs or sRNAs, ranging from size 50 to 250 nt for the vast majority of them) have been found in bacterial plasmids, phages, transposons and chromosomes. Estimates of the number of ncRNA genes in E. coli range from 50 to several hundred [1, 2]. The first ncRNAs were detected in the 1960s by chance, discovered by direct labelling as being associated with proteins on migration gels or identified after random mutations. The abundance of bacterial genome sequence data has allowed gene-finding computer programs to annotate a large number of prokaryote sequences. However, although de novo annotation programs successfully identify and map protein-coding genes, they are not designed to identify ncRNA genes. Recently, the intergenic regions (IGRs) of selected bacteria and yeast genomes were systematically searched for ncRNA genes. These computational screenings involved a combination of criteria, including large gaps between protein-coding genes [3, 4] even though in Sulfolobus solfataricus, 13 small RNAs (sRNAs) have been found encoded either within, or overlapping, annotated open reading frames [5]. Other criteria used are extended conservation between species [2, 4, 6], orphan promoter or terminator sequences [2, 4, 7], base-composition signatures [8, 9], and conserved secondary structures in deduced RNA sequences [10–13] even if not always significant [14]. Recently, ncRNA research algorithms have been developed including some or all of these criteria [15–18]. Supplementary in vivo experiments involving for example studies of expression patterns by Northern blotting or microarray testing are still essential to confirm that the sRNA candidate genes are indeed transcribed; such studies also provide information about temporal expression patterns, potential precursor forms and degradation products. In addition to in silico analysis, experimental in vivo RNomics were also developped (for example RACE and SELEX) [19–21].

ncRNAs are involved in a great variety of processes including chromosome replication and cell division (dicF [22]), transcriptional regulation (6S RNA [23]), RNA processing (RNase P or rnpB, [24]), mRNA stability and translation (antisense sequences such as spot42 [25]), protein stability (tmRNA, [26]) and transport (4.5S or ffs, [27]), stress adaptation (for example oxyS [28]), transition from growth to stationary phase (dsrA, rprA [29, 30]), quorum sensing and virulence (qrr [31]), plasmid copy number control (RNAI and RNAIII [32, 33]), carbon storage (csrBC [34]), and oligopeptide transport (gcvB [35]). Some provide housekeeping functions and others are regulators of stress gene expression, e.g. sRNAs modulating the bacterial cell surface by antisensing outer membrane protein (omp) genes (such as micF and micC, reviewed in [36, 37]). In many cases, ncRNAs are associated with proteins that enhance their function (Hfq [38], SmpB [39]). Their mechanisms of action can be grouped into three main categories: antisense by base-pairing with another RNA/DNA molecule (oxyS), RNA structure mimicry (6S, tmRNA) and catalytic functions (rnpB). These categories are not exclusive (some ncRNAs can be classified in more than one category). Also, not all mechanisms of action are known and it is likely that some ncRNAs act in ways that have not yet been described.

Sinorhizobium meliloti (formerly Rhizobium meliloti) is a common Gram-negative soil bacterium that lives symbiotically on the roots of certain genera of leguminous plants (including Medicago and Melilotus). The bacterium enters the root tissue through infection threads and forms nodules, inside which it converts atmospheric nitrogen into ammonia. In return, the plant provides an energy source for the bacteria. Excess nitrogen remains in the soil, potentially reducing the need for fertilisers. S. meliloti is one of the best known Rhizobia; it has been extensively studied by numerous groups worldwide and is readily amenable to genetic studies. Like many other members of the alpha-proteobacteria, this fast growing Rhizobium possesses a multipartite genome: a 3.65-Mb chromosome and two megaplasmids, pSymA (1.35 Mb) and pSymB (1.68 Mb) [40]. Its genome shares various fundamental similarities with those of some other symbiotic bacteria and various plant (Agrobacterium) and animal pathogens (Bartonella, Brucella). As for most sequenced prokaryotic genomes, the annotation of the S. meliloti genome has led to the prediction of protein-coding genes but yielded very little information about non-coding RNA genes. When the genome sequence of the S. meliloti strain 1021 was completed [40], its RNome was only composed of three identical rRNA operons, 54 tRNAs (53 decoding the standard 20 aa and one selenocysteine tRNA), and a single annotated ncRNA, ssrA (tmRNA or smc04478). The characterisation and expression patterns of this RNA gene were recently published [41]. Two other ncRNAs are described in dedicated databases [27, 42] one matching rnpB, the RNA component of the ubiquitous RNAse P ribonucleoprotein enzyme, and the other ffs (4.5S RNA), the RNA constituent of the signal recognition particle (SRP). Recent work by MacLellan with S. meliloti strain 1021 [43] and Izquierdo with strain GR4 [44] also describes ctRNAs (counter-transcribed-RNA) involved in plasmid incompatibility. In addition, 5' untranslated regions (UTR) of mRNAs that act as "riboswitches" have also been predicted in S. meliloti. Those cited by the Rfam database [45, 46] sense concentrations of vitamins B2 (RFN, upstream from ribH2) and B12 (cobalamin, upstream from cobP, smb20056, smc00982, smc00166 and between smb20555-smb20556), of thiamine (THI, in 5' of thiD, thiC and smc03869) and of glycine (5' end of gcvT). Corbino et al. [47] also describe riboswitches for methionine (SAM, in front of metA and metZ) and serine (serC), as well as elements upstream of suhB, smc02983 (speF) and smc03839 (ybhL). No lysine, leucine, threonine or tryptophan riboswitches have been predicted in S. meliloti or in related alpha-proteobacteria. Finally, a repression of heat shock gene expression (ROSE) element is also annotated in the RFAM database, in the 5' translated region of smb21295 (ibpA-like).

The purpose of this study was to discover unidentified small RNA genes in the chromosome of S. meliloti and related alpha-proteobacteria. We used computational comparative genomic prediction of sRNA gene candidates combined with expression profiling using dedicated microarrays, followed by Northern hybridization. This approach revealed 17 previously unidentified sRNAs, eight of which are widely conserved in the alpha-proteobacteria phylum. These analyses suggest that, like other free-living bacteria, alpha-proteobacteria encode numerous sRNAs, although their number and their nature may differ between species.

Results and discussion

Profile of small RNAs in S. meliloti

Staining of total RNA from bacteria resolved on gels reveals abundant sRNAs [48–52]. We used this method to analyse S. meliloti small RNA (<400 nt: Figure 1A). Four intense bands were detected, three of which correspond to the sizes predicted for 5S RNA (band 5), 4.5S RNA (band 2), and the 5' end of tmRNA (band 4, [41]). Band 6 (≈70 nt) corresponds to a length and migration profile compatible with tRNAs. No RNAs migrating faster than 70 nt were detected. Two less intense bands (1 and 3) were observed and were compatible with sizes predicted for rnpB RNA and for the 3' end of tmRNA [41]. Northern blotting confirmed the identity of each of these bands (Figure 1B). Surprisingly, no additional RNAs were visualized with either RNA extraction method (Trizol™ or Qiagen™, not shown) or stress (see conditions in Material and Methods section, data not shown). This experiment indicated that small RNAS do not constitute an abundant class of RNAs in S. meliloti, in contrast to what has been observed in marine Cyanobacteria and in Staphylococcus aureus [50–52]. As a consequence, we could not employ direct elution and sequencing to identify new sRNAs [53] in S. meliloti. We thus used computational prediction to identify candidates for further testing.

Figure 1
figure 1

Identification of small "known" RNAs in the S. meliloti chromosome. A: Migration of 10 μg of S. meliloti total RNA in a 2.5% high-resolution agarose gel (Sigma) stained with ethidium bromide. B: 5 μg of total RNA from S. meliloti strain 1021 was analyzed by Northern blotting hybridization with specific oligonucleotides [see Additional file 8]; the molecular sizes were calculated in nucleotides (nt): > rnpB (372 nt), > tmRNA 3' end (204 nt), > 5S (120 nt), > 4.5S (95 nt), and > tmRNA 5' end (82 nt) [39]. Band > was not hybridized but its size is consistent with it being a tRNA. Exposure times were optimized for each panel and signal intensity does not indicate relative abundance of ncRNAs.

Known sRNAs of S. meliloti: distinguishable biases?

ncRNAs in AT-rich hyperthermophiles can be located on the basis of local variations in genomic base composition [10, 11]. Although the S. meliloti chromosome is GC-rich (62.7%), we scanned the regions containing tmRNA, rnpB and ffs (Figure 2) for base composition signals. Unlike AT-rich genomes, no difference was observed between sRNA and background genomic sequences (Table 1). BLAST alignments of the three sRNAs against all sequenced bacteria revealed significant similarities with sequences from the alpha-2 subgroup of the class Proteobacteria. However maximum likelihood trees (see Additional file 1) showed that most identical sequences were from different genomes (R. etli and leguminosarum for ffs and tmRNA; Mezorhizobium for rnpB). To conclude, no apparent dominant bias was observed for the three known S. meliloti ncRNAs, except primary sequence conservation in IGRs of related alpha-proteobacteria genomes (especially subgroup-2).

Table 1 Selected features of "known" ncRNAs of S. meliloti
Figure 2
figure 2

Nucleotide bias analyses of known S. meliloti RNAs. Local variations of GC content (%) with a window size of 100 bp, in S. meliloti genomic regions around tmRNA, ffs and rnpB. The y-axis represents the minimal, maximal and mean values of the percentage of GC.

Selection of sRNA candidate genes in the S. meliloti chromosome

Most bacterial sRNA searches were conducted using the E. coli genome as a reference, so we first compiled the sRNAs available in the Rfam database for that organism (strain K12, riboswitch/cis-regulatory genes excluded) to try to identify sRNA orthologs using BLAST alignments (e-value < 1) against the complete S. meliloti chromosome sequence. No significant similarities were detected except for 4.5S and rnpB (see Additional file 2). ssrA (tmRNA) was not detected, presumably because the S. meliloti tmRNA is in a two-piece "permuted" form [41]. Surprisingly, the "ubiquitous" ssrS (6S RNA) was not detected either. Similar analysis with Bacillus and Pseudomonas sRNAs [RFAM] gave no further hits. This first approach confirmed a key point: most sRNAs cannot be detected by inter-phylum primary sequence identity.

RNA-specific tools described in the literature were then assessed. However, most rely on preliminary structural knowledge, knowledge which is poor for this phylum. Thus only a subset of these tools was tested: those reported to be able to detect new sRNA gene candidates in prokaryotic species. ISI (Intergenic Sequence Inspector, [54]) relies on inappropriate filters (in particular GC%), and was far too sensitive if the filters were disabled (close to 300 candidates). The use of QRNA [7] requires preliminary alignments. We tested it by aligning the 61 sRNAs annotated in the E. coli (K12) genome against S. meliloti's chromosome, but only 4.5S and rnpB were predicted by this tool. Finally, we assessed sRNApredict2 [18], which combines commonly sRNA-associated genetic features; it was used to search the S. meliloti chromosome IGRs for sRNAs, by comparison with A. tumefaciens and R. etli. As shown in the output tables (see Additional file 3), 13 sRNAs were predicted, seven being common to the two genomes compared. However, a detailed analysis of each candidate revealed that only one (pred1) was likely to correspond to a genuine small RNA gene whereas the others are almost certainly 5' UTRs (in view of the small distances and nature of the surrounding genes) or repeated elements (RIME, Sm- [55, 56]).

We ended up selecting for further analysis: the IGRs containing the origin of replication oriC (as a negative control) and the tmRNA, rnpB and 4.5S RNA genes; 22 IGRs longer than 450 nt; 13 IGRs showing short sequence identity in alpha-proteobacteria (see Additional file 10); and 28 IGRs selected using the Artemis Comparison Tool (ACT) with related genomes (see Additional file 11). Indeed, the sequence identities marked by the ACT were mostly confined to actual open reading frames (ORFs), even between two close chromosomes (S. meliloti and A. tumefaciens). Although hits in intergenic regions were extremely rare (less than 40), all three S. meliloti known sRNAs (tmRNA, 4.5S and rnpB) were included in these hits: we thus concluded similar ACT-visualized IGRs represented good sRNA gene candidates. Among these IGRs, those containing large repeats (Sm-1 to Sm-5) or RIMEs were however excluded, as were IGRs smaller than 50 nt (to avoid inclusion of 5' or 3' UTR elements).

This selection accounted for 67 candidate IGRs (see Additional file 4), which throughout this paper shall be referred to as sra, followed by a number corresponding to their order of apparition on the chromosome (starting from oriC).

Detection of expression using microarrays and Northern dotting

Microarray hybridization was the first method used to test for transcription of the sRNA candidates; an IGR-dedicated array was used (see Materials and Methods). The initial goal of the time-course microarray experiments was to detect ncRNA gene transcripts in various conditions. We first monitored gene expression over time during growth in minimal (MV) and rich (LB) media. The average log2 SNR of the three known ncRNAs (tmRNA, rnpB and 4.5S) and the ribosomal RNA 5S (included as a control) was very low (0.49) in MV medium, but was higher (4.13) in LB medium (see Additional file 5). We applied various stresses, as described in Materials and Methods, but detected no specific induction (not shown). We therefore used LB medium for expression analyses and the results are expressed as a heat map (Figure 3). We also checked the expression of all of the candidates by Northern dot blotting. Twenty-five candidates were found to give a strong hybridization signal (including rnpB and 4.5S RNA genes) and nine gave weak but detectable signals. Among the dot blot-"positive" IGRs, ten did not show significant expression on microarrays (Fig. 3, group B1), perhaps due to insufficient fluorescent labelling (e.g. the RNA was too small or labelling was hampered by secondary folding). Twenty-three IGRs gave no transcription signal either in Northern dot blots or in microarrays (Fig. 3, group B2). These included sra01, which corresponds to the S. meliloti origin of replication (oriC or smc04880) and was used as an internal negative control. Indeed, various methods (including qPCR and blotting) have been used to demonstrate that there is no transcription at this site (not shown). Lastly, 11 IGRs giving a transcription signal on microarrays were not confirmed by Northern dot blotting; in these cases the signal may have originated from surrounding coding genes.

Figure 3
figure 3

Heat map and Northern dot expression analysis of S. meliloti sra genes. Heat map visualizing the expression values for each sra gene at various stages of growth (in LB medium). Signal intensities are indicated as signal-to-noise SNR values (log2 scale), represented by a red panel. The position of each sra gene in the heat map is determined by its intensity. For the complementary Northern dot analysis, 10 μg of RNA, isolated from the most favourable expression condition, was spotted (in duplicate) onto a nylon membrane and hybridized with a radiolabelled specific probe [see Additional file 8].

Small RNA transcripts detected by Northern hybridization

Northern blotting was used to detect sRNAs. The same probes as for Northern dots were used but after hybridization of newly purified RNA from fresh cultures. For some candidates, probes were redrawn to target areas common to all considered subgroup-2 alpha-proteobacteria. sra15 was discarded because it appears to correspond to a pseudo phe-tRNA gene (not shown). This locus is possibly a vestige or a target of DNA insertion; indeed, a 500-kb symbiosis island has been shown to integrate into a phe-tRNA in the M. loti chromosome [57].

Four sRNA candidates (sra51, sra37, sra47, sra59) gave large transcripts (~1000 nt, not shown), inferred to be part of adjacent ORFs for three reasons: (i) they were larger than the intergenic region; (ii) they were large enough to encompass one of the flanking coding genes; and (iii) the strand detected corresponded to the orientation of at least one of the flanking genes. We did not pursue investigations to determine whether these 5'/3' UTRs encompass cis-regulatory RNA structures.

The signals detected for sra48, sra58 and sra62 were very strong and composed of multiple bands (data not shown). For sra48 and sra58, the explanation is sequence-specific hybridization of the probe to various transcripts due to small imperfect DNA repeats (sm-2 fragment in the case of sra58 and a previously undescribed repeat in sra48, data not shown). The sra62 candidate corresponds to a repeated region that coincides with the fixT loci, present in three copies in the genome of S. meliloti [40]. In the two first copies, fixT genes (fixT1 and fixT2) are co-located with fixK genes (fixK1 and fixK2). The third copy region of fixT gene (fixT3) encompasses sra62, which corresponds to a fixK3 pseudogene (not shown).

However, it cannot be concluded that the 23 candidates (group B2, Figure 3) for which no transcript was detected by microarray or Northern blot experiments correspond to false predictions: some of them may possibly be true sRNAs, but which are poorly or not expressed in the conditions tested.

Analysis of the 17 newly identified small RNAs

We further investigated the 17 sRNA candidates that yielded signals with a suitable size in Northern blots (<300 nt, Figure 4A). We excluded (Table 2) sra10, that contains a possible 101 amino acid ORF and sra29, which is a probable leader for rpsF (S6 ribosomal protein gene) [58, 59]; we also excluded sra24 that may encode a short peptide (38 aa long) rather rich in cysteine (10%). The 23 first aa (MALFFKPHCFLSLYCCLLSQRG...) correspond to a predicted transmembrane segment whereas 30% of the 14 other residues are positively charged amino acids. This biochemical configuration is found in small molecular peptide ion channels, such as defensins, involved in host-defences.

Table 2 Features and annotations of the 3 new small RNAs of S. meliloti potentially encoding proteins and peptides
Figure 4
figure 4

Detection and location of chromosomal S. meliloti sRNAs. A. Total RNA was extracted from cultures grown in LB (mid-exponential phase). Northern blots were hybridized with biotinylated DNA oligonucleotide probes [see Additional file 8] and exposed for various times (therefore the intensities of the signals do not correspond to the relative abundance of each sRNA). The positions of RNA size standards are shown on the left. B. Distribution of the sra genes along the S. meliloti chromosome. The origin of replication (oriC = sra01) and positions of tmRNA, rnpB and 4.5S are also indicated. Blue and red arrows represent genes on the reverse or forward strands, respectively. Genomic islands are indicated with grey boxes (Sme21T, Sme19T and Sme80S).

Of the 14 remaining RNAs, six correspond to S. meliloti-specific sRNAs (called orphan sRNAs, Table 3). All except sra61 lie within a genomic island [60] (sra14 in Smc19T; sra11, sra12a and sra12b in Smc21T; sra66 maps at the 5' end of Sme80s, just downstream from the insertion tRNAser gene smc03779). All these sRNAs are absent from Agrobacterium and other Rhizobium species, consistent with the absence of the three genomic islands from these related genomes. The "coding potential" of sra11, sra12a, sra12b and sra14 was assessed and only sra66 could translate a small non-conserved 16 aa peptide. There may be a relationship between their biological functions and their presence in genomic islands as bacterial islands are often related to eukaryotic host cell colonization (virulence or symbiosis). Indeed bacterial sRNAs were recently detected in the pathogenicity island of Staphylococcus [51] and in Salmonella (InvR [36]). Multiple 5' and 3' RACE mapping of these candidates was unsuccessful, possibly due to insufficient cDNA or because they are too small for satisfactory cloning. With no available orthologous sequences, determination of extremities through alignment and structure prediction based on covariations are not possible. The functions of these new non-coding genes are thus unknown. However, many small RNAs in bacteria act as post-transcritptional regulators via base-pairing action, so we used TargetRNA [61] to assess their capacity to act as antisense RNAs. No significant putative target was found for sra11, sra12a, sra14 or sra61, but sra12b and sra66 match with mRNA targets (see Additional file 12). One interesting TargetRNA prediction was the interaction between sra66 and a tolR-exbD-like gene (smc03957). TolR-ExbD proteins are membrane-bound transport proteins essential for ferric ion uptake in bacteria [62], and small RNAs modulating the free intracellular iron pool have indeed been identified in other bacteria (e.g RyhB, [63]).

Table 3 Features and annotations of the 6 new orphan (S. meliloti-specific) sRNAs of S. meliloti

In E. coli, sRNA genes were considered to be conserved if the alignment had an E-value lower than 0.001 [64]. On this basis, the sequences of the eight remaining expressed S. meliloti sra genes are highly conserved in related alpha-proteobacteria (e-value < 10-10; Table 4). sra56 is even an analog of Escherichia coli's 6S RNA (SsrS) that has recently been corroborated by RFAM. sra56 may thus be considered as a fortuitous positive control, validating our experimental approach. All these conserved sra genes we describe were then subjected to transcriptional element analysis, structure prediction using covariation, and potential mRNA target prediction.

Table 4 Features and annotations of the 8 new Alpha-proteobacterial sRNAs of S. meliloti

Genomic synteny for alpha-proteobacteria sra genes

S. meliloti chromosomal sRNA-encoding genes have a slight distribution preference, 70% of them being on the left replicore, but no preference was observed concerning the leading or the lagging strand (Figure 4B). The conservation of gene adjacency (synteny) may be associated with functional relationships (e.g. gcvB and ssrA are functionally associated to their conserved adjacent genes, respectively gcvA and smpB) [35, 65]. Therefore, we assessed the conservation of neighbouring genes for the eleven alpha-proteobacterial sra, including tmRNA, rnpB and 4.5S (see Additional files 10 and 11). We found only three (4.5S, tmRNA and sra41) where both flanking genes were conserved and four with one conserved flanking gene (including rnpB). Three display no synteny (including sra56 = 6S). However, our observations suggest that in alpha-proteobacteria, functional association between sRNAs and conserved adjacent genes is uncertain, as even smpB is not linked to tmRNA (separated by 1,1 Mb).

Conserved sra gene transcriptional signals

The computational identification of promoter sequences is difficult because signals are weak [4]. Consensus binding sites have been proposed for the S. meliloti σ70 and σ54-dependent promoters (CTTAGAC-n17-CTATAT [66] and TGGCACG-n4-TTGCW [67], respectively). Using relaxed regular expressions (i.e. pattern matching), we scanned the 5' UTR region of each sra gene to detect any such consensus (max. 4 mismatches). In the same way than for the orphan candidates, the end-mapping experiments remained unsuccessful for all new candidates but sra32 (5' end-AAACAGGCAGGAA and 3' end-CTTGTTTTTTT), thus the exact sites of the extremities of the sra genes are unknown. However, sequence alignment between several alpha-proteobacteria was informative. As for ORFS, no significant nucleotide identities were apparent in the 5' and 3' regions (not shown). Thus, the start and stop of the alignment and the sizes deduced from electrophoretic motility were used to define the ends of each sra gene. We only detected consensus σ70-promoters in the ubiquitous ncRNAs (ffs, tmRNA, rnpB and 6S) and the 5'-UTR mapped region of sra32 (Table 5). Even with a larger spacer between the -35 and -10 boxes (17 to 20), no consensus sequence was detected in the other sra genes. Similarly, only the ffs 5'-UTR matches a possible σ54 binding site. However, S. meliloti contains a large number of predicted sigma-factors (ca. 16), it is therefore possible that sra genes are dependent on them. Unfortunately, Melina-based [68] motif extraction from the promoter regions of these genes was inconclusive and did not show any consensus.

Table 5 Promoter detection in conserved S. meliloti sra genes

We also looked for potential classical L-shaped terminators (stable stem-loops followed by U-stretches) at the alignment-deduced 3' end of each sra. As most terminators in GC-rich bacteria have no long consecutive U-stretches [69], we also looked for I-shaped (stable stem-loop with no U-stretch) and V-shaped (two consecutive hairpins [69]) terminators (Table 6). Terminator structures could be predicted for all conserved sra genes, except sra30 and sra34, for which the alignments are too short for the ends to be accurately mapped. All three shapes were found, I-shapes being the most common. This supports the proposal that "orphan" terminators in IGRs may indicate the presence of an sra gene, although because of the high GC content of the S. meliloti genome, stable stem-loops are frequent and consequently not very informative.

Table 6 Terminator prediction for S. meliloti sra genes

Conserved sra genes predicted structure and mRNA targets

The structures of non-coding RNAs are important for their function. Consequently, we made a conserved secondary structure prediction for all alpha-proteobacteria sra genes (except sra30 and sra34 because of too short alignments).

We first compared the 4.5S and 6S Alifold [70, 71] and RNAz [72], outputs with the equivalent RFAM structure (Additional file 13). The two tools give different structures for 4.5S, the Alifold prediction being closer to that of RFAM than the RNAz prediction. However, bulge A, the minimal site required for binding to EF-G [73], is similarly folded in the three models. The three predicted structures of sra56 (6S) are similar, 6S being folded as a largely double-stranded RNA with a single-stranded central bulge. However, the 3' side of the central bulge can form a stable stem-loop in alpha-proteobacteria, as previously described [74].

The predicted structure of sra03 is well-conserved, composed of three long hairpins: the central one, ending with a 15 nt loop, is strictly conserved, and the 3' and 5' stem-loop structures present co-varying nucleotides. Analogous design (three stem-loops) was found for the E. coli sRNAs drsA, micC and qrr [46]. No significant target mRNA was found using the full RNA but the 15-nt loop presents complementarity with the 5'-UTR of the smc03977-smc03976 operon (not shown). These two genes have paralogs, mostly in alpha-proteobacteria genomes. The function of Smc03977 is unknown but Smc03976 belongs to the ZapA cell division family of proteins [75]. ZapA binds the ftsZ cell division gene, which has been reported to undergo antisense inhibition in E. coli [22], so sra03 is possibly implicated in cell division regulation.

sra25 was only identified in Rhizobia (meliloti, etli and leguminosarum), however with remarkable primary sequence identity. Its predicted secondary structure is also highly conserved, composed of a long stem with one central bulge and a small hairpin. The 3' end structure was predicted to act as a stabilization terminator. A possible pairing with the 5' UTR of a gene encoding a putative membrane protease protein (Smc04020) was proposed by TargetRNA, although with low significance (p-value > 10-3). This protein resembles the E. coli HflKC protein, known to interact with the cell division protease FtsH [76]. As for sra03, we propose that sra25 may have a role in the S. meliloti cell cycle.

Only Alifold proposed a consensus structure for sra33: it resembles other short bacterial sRNAs including RyeE [46]. Predictions for sra33 showed strong pairing ability with the 5' ends of smc00899 and of rkpJ. The first gene is organized in an operon structure with smc00900 (encoding a PilT-like toxin), defining a post-segregational killing toxin-antitoxin (TA) system. This type of mechanism, involving sRNAs in the inhibition of TA systems, has been extensively described in E. coli [77]. Finding such a mechanism in S. meliloti is interesting as we recently detected approximately 53 TA loci (accounting for 95 genes) in the complete genome sequence [78].

sra32 is the only small RNA predicted both by sRNApredict2 and ACT analysis. For this gene, hybridization was tested by Northern blot and a signal was obtained for two of the most distant members: A. tumefaciens (140 nt) and R. elti (132 nt) (Figure 5A and 5B). The secondary structures of sra32 were predicted by both Alifold and RNAz; 59% of the nucleotides can pair in seven conserved regions, those at the 3' and 5' ends (TB1 and TB7) possibly forming stabilization stem-loops. Only the primary sequence of TB3 is conserved, all other structures being supported by covariations. The search for potential mRNA targets yielded significant predictions for fliM (flagellar motor switch) and smc01800 (cytochrome C oxidase). The same sequence of sra32 (nt 60 to 95, TB4 to TB6) is predicted to pair with the 5' leader region of both mRNA targets. Discovery of a putative flagella antisense RNA in S. meliloti and related bacteria is interesting. Indeed, all these bacteria interact with plant or mammal cells and flagella are cell-surface components required for eukaryotic-prokaryotic cells interactions [37].

Figure 5
figure 5

Characterization of sra32. A. Distance tree of sra32 using the distance/NJ method (clustalW [90]). Numbers at the nodes represent bootstrap proportions (BP) of 1000 replicates. B. In northern blots, a signal for the predicted sra32 was detected corresponding to lengths of 144 and 106 nucleotides in total RNA from S. meliloti 1021 and to 140 and 132 nt in that from Agrobacterium tumefaciens and Rhizobium etli, respectively.

Finally, structure and target prediction of sra41 needed preliminary analysis as (i) two signals were detected by Northern hybridization (a major ~106 nt band and a minor ~68 nt species) and (ii) sra41 is present in three imperfect copies, two in tandem in the same chromosomal IGR and the third, with a more divergent primary sequence, maps in pSymA. Additionally, sra41 is well-conserved in alpha-proteobacteria and is present in two to three copies, on both chromosomes and (mega-)plasmids except in Agrobacterium (chromosomal loci only). Translatable small ORFs are predicted within some sra41 candidates (see Additional file 6) whereas others are devoid of complete coding frames. A similar conserved structure was proposed for the three S. meliloti copies, composed of three stem-loops as described for sra03. Target mRNAs were predicted separately for each of the three sra41 copies in S. meliloti. The only predicted target for the first chromosomal copy is smc02392, which encodes a hypothetical protein with a Sel1 repeat-containing domain. The second copy is predicted to interact with two mRNAs encoding Smc00317, a transmembrane protein with homologies to efflux carrier proteins, and Smc01118, a glucoprotease-like protein possibly involved in chaperoning processes. No significant target was predicted for the pSymA copy.

Conclusion

We used computational comparative genomic screening to search for small RNA genes in S. meliloti and related alpha-proteobacteria, as very few sRNAs had been identified in this phylum [46]. From a list of 64 S. meliloti candidate IGRs (excluding tmRNA, 4.5S and rnpB), we show that 17 encode small RNAs (14 non-coding RNAs, two small mRNAs and a 5' leader region). This work constitutes a significant advance in small RNAs studies in alpha-proteobacteria.

A possible antisense function was suggested for 57% of the sra genes, although these predictions remain based on TargetRNA estimations. To validate these antisense activities, further in vitro validation of predicted target genes will be necessary, even if TargetRNA's e-value was set to a highly significant threshold (see material and methods section). It is however interesting to notice that the functions of the predicted mRNA targets are various, including roles in transport, membranes and toxin-antitoxin systems. However, antisense RNAs may act on transcription termination, translation, mRNA degradation and can be activators and/or repressors. As a consequence, accurate in silico prediction of sra functions is difficult. The specific physiological roles of these newly discovered genes in alpha-proteobacteria regulatory pathways can only be determined by biological investigation. The initial regulation of each sra gene, i.e. the precise signalling conditions that trigger their expression should be analyzed, as this may give us clues about their roles. Monitoring the expression of each sra under various conditions would require numerous experiments, as many parameters can be changed alone or simultaneously to simulate oxidative, heat, cold, and osmotic stresses as well as nutrient and metal starvation. In E. coli, Hfq generally facilitates the pairing of ncRNAs [79]. Therefore the influence of the S. meliloti hfq homolog (nrfA or smc01048) in the sra-target mRNAs hybrid formation could be analyzed by constructing a mutant. In parallel, screening should be extended to additional replicons (megaplasmids and plasmids): we show that sequence conservation in closely related bacteria IGRs can indicate the presence of putative small sra genes.

Methods

Bacterial growth

In all experiments, S. meliloti strain 1021 (streptomycin resistant, StrR) was grown at 30°C in the presence of 25 μg.ml-1 of streptomycin. Bacteria were initially grown to the stationary phase in LB (Luria-Bertani) medium, collected, washed and then resuspended in MV (Vincent minimal medium, 1970 [80]) or LB medium. Stresses were applied in MV at mid-exponential phase (OD600 nm = 0.4) as follows: 10 minutes with a sub-lethal dose of hydrogen peroxide (10 mM); salt shock (0,4 M NaCl), pH 5 and pH 9 generated with 10 N HCl or NaOH were also applied during 10 minutes; cold (10°C) and heat shocks (40°C) lasted 15 minutes. The other alpha-proteobacteria used in Northern blot and sequencing experiments are listed in Additional file 7.

RNA purification and DNase treatment

Cells were harvested by centrifugation (5 min, 2600 × g, room temperature) and immediately frozen at -80°C. These pellets were subsequently re-suspended in 200 μl of TE buffer (10 mM Tris-HCl pH8 – 1 mM EDTA) containing lysozyme (1 mg.ml-1) and total RNA was extracted using the RNeasy® mini kit (Qiagen™) and treated with RQ1 Rnase free DNase (1 U.μg-1, GE Healthcare) in the presence of 6 mM of MgCl2 for 20 min at 37°C.

5' and 3' RACE mapping

RNAs shorter than 300 nt were eluted from a 2.5% high-resolution agarose gel (Sigma) in 0.5 × TBE buffer [81] and used to build a cDNA library using the MessageAmpII-Bacteria kit (Ambion). The RNAs were 3' end-polyadenylated and first strands were synthesized using oligo-T7-dT (AATACGACTCACTATAGGGCGAA dT25) then treated overnight at 37°C with terminal deoxynucleotidyl transferase in the presence of 1 mM of dTTP. The second strands were obtained with a 5'-primer (GGAATACTAGTGACACCAGACAAGTTG dA15). PCR was carried out at 55°C using 1 μl of the cDNAs and 4 pmoles of the appropriate specific primers (see Additional file 8): one corresponding to the targeted gene and the other specific to either the 5' or 3' tagged ends. The products obtained were inserted into pGEM-T (Promega) and sequenced using the BigDye terminator v3 protocol (Applied Biosystems). RNA genes of interest were amplified by PCR with a 50°C to 40°C touch-down program, using the 5' and 3' end primers designed after mapping, from 12 genomic DNA preparations from several Rhizobia (see Additional file 8). The resulting products were sequenced using the protocol described above and analyzed in silico for co-variation and conserved secondary structure.

Northern dot analysis

DNase-treated, S. meliloti total RNA (10 μg per dot) was denatured (by incubating for 10 min at 70°C then chilling on ice) and spotted under vacuum onto a nylon membrane (Zeta Probe) using Bio-Dot (Bio-rad). These dot membranes were baked for 30 min at 80°C, pre-hybridized, hybridized and washed according to Ambion's instructions (Oligoprobes), and hybridization was visualized on InstantImager (Packard). 20-mer oligonucleotides (see Additional File 3) were 5' P-end labelled with [gamma32P]ATP. For each candidate, two oligonucleotide probes (one per strand) were selected to identify the strand of transcription. Aliquots of 62 pmoles of each oligonucleotide probe were incubated for 1 hr at 37°C with 1 μl of T4 polynucleotide kinase, 2.5 μl of 10 × kinase buffer (Ambion) and 2 μl of 32P-ATP [5,550 KBq (222,000 KBq.mmol-1)]. The radiolabelled probes were then purified through MicroSpin G25 columns (GE Healthcare). The efficiency of probe labelling was monitored in a liquid scintillation analyser (1600 TR Packard).

Northern blot analysis

S. meliloti was grown in LB medium to mid-exponential phase (OD600 nm= 0.8). Total RNA (10 μg) was extracted, denatured, and subjected to electrophoresis on an 8% acrylamide/bis acrylamide (19:1) denaturing gel (8 M urea) in 0.5 × TBE buffer [81]. The RNA was then transferred to a nylon membrane (Ambion) in the same buffer and the membrane was baked for 30 min at 80°C. Biotinylated oligoprobes were used for hybridization and bound probes were detected according to Ambion's instructions (BrightStar® BioDetect™).

Construction of the DNA microarrays

A PCR-based microarray was designed (see Additional file 9) with primer3-designated oligonucleotides derived from the 67 IGRs (intergenic empty regions) identified by screening (see Additional File 4). Seventy bp were excluded at the 5' and 3' ends of each IGR to avoid expression contamination by adjacent genes. The IGRs with lengths >550 nt were amplified as more than one PCR fragment. Each PCR involved 200 ng of S. meliloti 1021 genomic DNA, 1.25 units of Taq DNA polymerase (Promega) and 4 pmol of each oligonucleotide in a final volume of 50 ml for 40 cycles (Peltier Thermal Cycler, MJ Research Inc). The PCR buffer contained 5 μl MgCl2 (25 mM), 1 × Taq buffer (Promega) and 4.3 μl dNTPs. The length and quality of each PCR product was assessed by electrophoresis on 2% agarose TBE (Tris-Borate EDTA 0.5 × final) gels. The IGRs-PCR probes were dried, resuspended in 30 μl betaine, 1.5 M-3 × SSC and spotted in triplicate onto GAPS II™-coated glass slides (Corning) through robotic arraying (Microgrid II, BioRobotics).

Microarray hybridization, data acquisition and statistical analysis

The labelled cDNA was resuspended in hybridization buffer (3 × SSC/0.1% SDS/50% formamide) and cohybridized with 10 μg of salmon sperm DNA to the microarray glass slides overnight at 55°C. The slides were washed for 5 min at 55°C in wash buffer (2 × SSC/0.1% SDS) then 2 min in high-stringency buffer (0.2 × SSC/0.1% SDS, twice), 2 min in 0.2 × SSC (twice) and 2 min in 0.1 × SSC, and dried by centrifugation (3 min, 210 g). Hybridized microarray slides were scanned (GenePix4000, Axon Instruments, Inc.) with independent excitation of the fluorophores Cy5 and Cy3 at 10-μm resolution. Our microarray time series experiment was planned with a dye-swap design; Dabney & Storey recently showed that a simple average dye-swap removes dye bias without affecting the biological signal and preserves the ordering of true expression means [82]. To determine if ncRNA candidates showed detectable expression as assessed by microarray analysis, we used log2 SNR (signal to noise ratios), the "noise" value being the average intensity of spots containing spotting buffer. All genes with log2 SNR lower than 2 (a signal less than 4-fold greater than the technological noise) were considered as untranscribed under the conditions tested and their value changed to 0 (filtering). The resulting expression profiles are illustrated as a heat map.

Bioinformatics

Intergenic regions (IGRs) were determined as genome areas with no gene annotation on either of the two strands. The S. meliloti database used [83] includes original annotations of all ORFs, as well as tRNA, rRNA and repetitive elements. The Artemis Comparison Tool (ACT [84]) from the Sanger Centre [85] was used for whole genome comparisons of IGRs between the S. meliloti chromosome, as the reference, and other alpha-proteobacteria genomes: Agrobacterium tumefaciens strain C58 Cereon, Rhizobium etli CFN42, Rhizobium leguminosarum bv. vicae 3841 and Mesorhizobium loti MAFF303099.

ISI [54] was used taking the initial embl record file corresponding to the S. meliloti chromosome (AL591688) as an input, and applying an IGR length threshold of 7 bp. Parameter 'w' in BLAST was set to 7 in order to refine word detection.

In order to produce the input alignment file for QRNA v.2.0.3.c [7], the 61 ncRNAs annotated in the E. coli K12 Refseq file (NC_000913) were extracted, and compared to the chromosomal IGRs of S. meliloti thanks to WU BLAST 2.0, with various e-value thresholds (10-5, 10-2, 0.1 and default: 10). QRNA was then run with scanning window set to 100 nt.

sRNAPredict2 [18] was tested using the S. meliloti chromosome ORF list (NC_003047.ptt) from the Refseq repository [86]. The ".coords" TIGR file is unavailable for S. meliloti. The t/rRNA database was compiled from data in the TIGR_CMR RNA list [87] and from the S. meliloti sequencing consortium website [83]. The terminator database was derived from TransTerm [88, 89]. The S. meliloti sRNA training set was generated from data available at the corresponding RFAM database page [46]. Two reference genomes were used: Agrobacterium tumefaciens str. C58 and Rhizobium etli CFN 42. Consequently, two blast output files were generated, where S. meliloti intergenic regions were compared to the cited genomes using WU BLAST 2.0 with same parameters as Livny [18] (E = 10e-5, V = 10000 et B = 10000). Finally, databases of regions of predicted conserved secondary structure were produced using QRNA, again with parameters set to the same values as in [18]. No input files corresponding to RNAMotif search results or to promoter/transcription binding sites were provided to sRNAPredict.

TargetRNA [61] was used (default parameters) to identify sra candidates' mRNA targets. Potential base pair binding interactions were considered significant only if their P-value fell below 0.001. Nucleotide sequences were analyzed by ClustalW [90] and resulting multiple alignments were used in ALIFOLD [71] to model RNA secondary structures. Similar predictions were realized using the RNAz program [72].

References

  1. Eddy SR: Non-coding RNA genes and the modern RNA world. Nature Rev Genet. 2001, 2: 919-10.1038/35103511.

    Article  CAS  PubMed  Google Scholar 

  2. Wassarman KM, Repoila F, Rosenow C, Storz G, Gottesman S: Identification of novel small RNAs using comparative genomics and microarrays. Genes Dev. 2001, 13: 1637-1651. 10.1101/gad.901001.

    Article  Google Scholar 

  3. Olivas WM, Muhlrad D, Parker R: Analysis of the yeast genome: identification of new non-coding and small ORF-containing RNAs. Nucleic Acids Res. 1997, 25: 4619-10.1093/nar/25.22.4619.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  4. Argaman L, Hershberg R, Vogel J, Bejerano G, Wagner EG, Margalit H, Altuvia S: Novel small RNA-encoding genes in the intergenic regions of Escherichia coli. Curr Biol. 2001, 2: 941-950. 10.1016/S0960-9822(01)00270-6.

    Article  Google Scholar 

  5. Zago MA, Dennis PP, Omer AD: The expanding world of small RNAs in the hyperthermophilic archaeon Sulfolobus solfataricus. Mol Microbiol. 2005, 6: 1812-1828. 10.1111/j.1365-2958.2005.04505.x.

    Article  Google Scholar 

  6. Axmann IM, Kensche P, Vogel J, Kohl S, Herzel H, Hess WR: Identification of cyanobacterial non-coding RNAs by comparative genome analysis. Genome Biol. 2005, 9: R73-10.1186/gb-2005-6-9-r73.

    Article  Google Scholar 

  7. Chen S, Lesnik EA, Hall TA, Sampath R, Griffey RH, Ecker DJ, Blyn LB: A bioinformatics based approach to discover small RNA genes in the Escherichia coli genome. Biosystems. 2002, 2–3: 157-177. 10.1016/S0303-2647(02)00013-8.

    Article  Google Scholar 

  8. Klein RJ, Misulovin Z, Eddy S: Noncoding RNA genes identified in AT-rich hyperthermophiles. Proc Natl Acad Sci USA. 2002, 11: 7542-7547. 10.1073/pnas.112063799.

    Article  Google Scholar 

  9. Schattner P: Searching for RNA genes using base-composition statistics. Nucleic Acids Res. 2002, 9: 2076-2082. 10.1093/nar/30.9.2076.

    Article  Google Scholar 

  10. Rivas E, Klein RJ, Jones TA, Eddy SR: Computational identification of noncoding RNAs in E. coli by comparative genomics. Curr Biol. 2001, 7: 1369-1373. 10.1016/S0960-9822(01)00401-8.

    Article  Google Scholar 

  11. Rivas E, Eddy SR: Noncoding RNA gene detection using comparative sequence analysis. BMC Bioinformatics. 2001, 2: 8-10.1186/1471-2105-2-8.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  12. Uzilov AV, Keegan JM, Mathews DH: Detection of non-coding RNAs on the basis of predicted secondary structure formation free energy change. BMC Bioinformatics. 2006, 7: 173-10.1186/1471-2105-7-173.

    Article  PubMed Central  PubMed  Google Scholar 

  13. Babak T, Blencowe BJ, Hughes TR: Considerations in the identification of functional RNA structural elements in genomic alignments. BMC Bioinformatics. 2007, 8: 33-10.1186/1471-2105-8-33.

    Article  PubMed Central  PubMed  Google Scholar 

  14. Rivas E, Eddy SR: Secondary structure alone is generally not statistically significant for the detection of noncoding RNAs. Bioinformatics. 2000, 7: 583-605. 10.1093/bioinformatics/16.7.583.

    Article  Google Scholar 

  15. Yachie N, Numata K, Saito R, Kanai A, Tomita M: Prediction of non-coding and antisense RNA genes in Escherichia coli with Gapped Markov Model. Gene. 2006, 372: 171-181. 10.1016/j.gene.2005.12.034.

    Article  CAS  PubMed  Google Scholar 

  16. Saetrom P, Sneve R, Kristiansen KI, Snøve O, Grünfeld T, Rognes T, Seeberg E: Predicting non-coding RNA genes in Escherichia coli with boosted genetic programming. Nucleic Acids Res. 2005, 33 (10): 3263-3270. 10.1093/nar/gki644.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  17. Livny J, Fogel MA, Davis BM, Waldor MK: sRNAPredict: an integrative computational approach to identify sRNAs in bacterial genomes. Nucleic Acids Res. 2005, 13: 4096-4105. 10.1093/nar/gki715.

    Article  Google Scholar 

  18. Livny J, Brencic A, Lory S, Waldor MK: Identification of 17 Pseudomonas aeruginosa sRNAs and prediction of sRNA-encoding genes in 10 diverse pathogens using the bioinformatic tool sRNAPredict2. Nucleic Acids Res. 2006, 12: 3484-3493. 10.1093/nar/gkl453.

    Article  Google Scholar 

  19. Vogel J, Bartels V, Tang TH, Churakov G, Slagter-Jager JG, Huttenhofer A, Wagner EG: RNomics in Escherichia coli detects new sRNA species and indicates parallel transcriptional output in bacteria. Nucleic Acids Res. 2003, 22: 6435-6443. 10.1093/nar/gkg867.

    Article  Google Scholar 

  20. Huttenhofer A, Vogel J: Experimental approaches to identify non-coding RNAs. Nucleic Acids Res. 2006, 2: 635-646. 10.1093/nar/gkj469.

    Article  Google Scholar 

  21. Willkomm DK, Minnerup J, Huttenhofer A, Hartmann RK: Experimental RNomics in Aquifex aeolicus: identification of small non-coding RNAs and the putative 6S RNA homolog. Nucleic Acids Res. 2005, 6: 1949-1960. 10.1093/nar/gki334.

    Article  Google Scholar 

  22. Bouche F, Bouche JP: Genetic evidence that DicF, a second division inhibitor encoded by the Escherichia coli dicB operon, is probably RNA. Mol Microbiol. 1989, 3: 991-994. 10.1111/j.1365-2958.1989.tb00249.x.

    Article  CAS  PubMed  Google Scholar 

  23. Wassarman KM, Storz G: 6S RNA regulates E. coli RNA polymerase activity. Cell. 2000, 101: 613-623. 10.1016/S0092-8674(00)80873-9.

    Article  CAS  PubMed  Google Scholar 

  24. Frank DN, Pace NR: Ribonuclease P: unity and diversity in a tRNA processing ribozyme. Annu Rev Biochem. 1998, 67: 153-180. 10.1146/annurev.biochem.67.1.153.

    Article  CAS  PubMed  Google Scholar 

  25. Moller T, Franch T, Udesen C, Gerdes K, Valentin-Hansen P: Spot 42 RNA mediates discoordinate expression of the E. coli galactose operon. Genes Dev. 2002, 16: 1696-1706. 10.1101/gad.231702.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  26. Zwieb C, Gorodkin J, Knudsen B, Burks J, Wower J: tmRDB (tmRNA database). Nucleic Acids Res. 2003, 31: 446-447. 10.1093/nar/gkg019.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  27. Rosenblad MA, Gorodkin J, Knudsen B, Zwieb C, Samuelsson T: SRPDB: Signal Recognition Particle Database. Nucleic Acids Res. 2003, 31: 363-364. 10.1093/nar/gkg107.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  28. Altuvia S, Zhang A, Argaman L, Tiwari A, Storz G: The Escherichia coli OxyS regulatory RNA represses fhlA translationby blocking ribosome binding. EMBO J. 1998, 17: 6069-6075. 10.1093/emboj/17.20.6069.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  29. Majdalani N, Cunning C, Sledjeski D, Elliott T, Gottesman S: DsrA RNA regulates translation of RpoS message by an anti-antisense mechanism, independent of its action as an antisilencer of transcription. Proc Natl Acad Sci USA. 1998, 95: 12462-12467. 10.1073/pnas.95.21.12462.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  30. Majdalani N, Hernandez D, Gottesman S: Regulation and mode of action of the second small RNA activator of RpoS translation, RprA. Mol Microbiol. 2002, 46: 813-826. 10.1046/j.1365-2958.2002.03203.x.

    Article  CAS  PubMed  Google Scholar 

  31. Lenz DH, Mok KC, Lilley BN, Kulkarni RV, Wingreen NS, Bassler BL: The Small RNA Chaperone Hfq and Multiple Small RNAs Control QuorumSensing in Vibrio harveyi and Vibrio cholerae. Cell. 2004, 118: 69-82. 10.1016/j.cell.2004.06.009.

    Article  CAS  PubMed  Google Scholar 

  32. He L, Soderbom F, Wagner EG, Binnie U, Binns N, Masters M: PcnB is required for the rapid degradation of RNAI, the antisense RNA that controls the copy number of ColE1-related plasmids. Mol Microbiol. 1993, 9: 1131-1142. 10.1111/j.1365-2958.1993.tb01243.x.

    Article  CAS  PubMed  Google Scholar 

  33. Benito Y, Kolb FA, Romby P, Lina G, Etienne J, Vandenesch F: Probing the structure of RNAIII, the Staphylococcus aureus agr regulatory RNA, and identification of the RNA domain involved in repression of protein A expression. RNA. 2000, 6: 668-679. 10.1017/S1355838200992550.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  34. Weilbacher T, Suzuki K, Dubey AK, Wang X, Gudapaty S, Morozov I, Baker CS, Georgellis D, Babitzke P, Romeo T: A novel sRNA component of the carbon storage regulatory system of Escherichia coli. Mol Microbiol. 2003, 48: 657-670. 10.1046/j.1365-2958.2003.03459.x.

    Article  CAS  PubMed  Google Scholar 

  35. Urbanowski ML, Stauffer LT, Stauffer GV: The gcvB gene encodes a small untranslated RNA involved in expression of the dipeptide and oligopeptide transport systems in Escherichia coli. Mol Microbiol. 2003, 37: 856-868. 10.1046/j.1365-2958.2000.02051.x.

    Article  Google Scholar 

  36. Vogel J, Papenfort K: Small non-coding RNAs and the bacterial outer membrane. Curr Opin Microbiol. 2006, 9: 605-611. 10.1016/j.mib.2006.10.006.

    Article  CAS  PubMed  Google Scholar 

  37. Guillier M, Gottesman S, Storz G: Modulating the outer membrane with small RNAs. Genes Dev. 2006, 20: 2338-2348. 10.1101/gad.1457506.

    Article  CAS  PubMed  Google Scholar 

  38. Zhang A, Wassarman KM, Ortega J, Steven AC, Storz G: The Sm-like Hfq protein increases OxyS RNA interaction with target mRNAs. Mol Cell. 2002, 9: 11-22. 10.1016/S1097-2765(01)00437-3.

    Article  PubMed  Google Scholar 

  39. Shin JH, Price CW: SsrA-SmpB Ribosome Rescue System is Important for Growth of Bacillus subtilis at Low and High Temperatures. J Bacteriol. 2007, 189 (10): 3729-37. 10.1128/JB.00062-07.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  40. Galibert F, et al: The composite genome of the legume symbiont Sinorhizobium meliloti. Science. 2001, 5530: 668-72. 10.1126/science.1060966.

    Article  Google Scholar 

  41. Ulve VM, Cheron A, Trautwetter A, Fontenelle C, Barloy-Hubler F: Characterization and expression patterns of Sinorhizobium meliloti tmRNA (ssrA). FEMS Microbio Lett. 2007, 269 (1): 117-123. 10.1111/j.1574-6968.2006.00616.x.

    Article  CAS  Google Scholar 

  42. Brown JW: The ribonuclease P Database. Nucleic Acids Res. 1999, 27: 314-10.1093/nar/27.1.314.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  43. MacLellan SR, Smallbone LA, Sibley CD, Finan TM: The expression of a novel antisense gene mediates incompatibility within the large repABC family of alpha-proteobacterial plasmids. Mol Microbiol. 2005, 55 (2): 611-623. 10.1111/j.1365-2958.2004.04412.x.

    Article  CAS  PubMed  Google Scholar 

  44. Izquierdo J, Venkova-Canova T, Ramirez-Romero MA, Tellez-Sosa J, Hernandez-Lucas I, Sanjuan J, Cevallos MA: An antisense RNA plays a central role in the replication control of a repC plasmid. Plasmid. 2005, 3: 259-277. 10.1016/j.plasmid.2005.05.003.

    Article  Google Scholar 

  45. Griffiths-Jones S, Moxon S, Marshall M, Khanna A, Eddy SR, Bateman A: Rfam: annotating non-coding RNAs in complete genomes. Nucleic Acids Res. 2005, 33: D121-D124. 10.1093/nar/gki081.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  46. The Rfam Database. [http://www.sanger.ac.uk/Software/Rfam/]

  47. Corbino KA, Barrick JE, Lim J, Welz R, Tucker BJ, Puskarz I, Mandal M, Rudnick ND, Breaker RR: Evidence for a second class of S-adenosylmethionine riboswitches and other regulatory RNA motifs in alpha-proteobacteria. Genome Biol. 2005, 8: R70-10.1186/gb-2005-6-8-r70.

    Article  Google Scholar 

  48. Suzuma S, Asari S, Bunai K, Yoshino K, Ando Y, Kakeshita H, Fujita M, Nakamura K, Yamane K: Identification and characterization of novel small RNAs in the aspS-yrvM intergenic region of the Bacillus subtilis genome. Microbiology. 2002, 148: 2591-2598.

    Article  CAS  PubMed  Google Scholar 

  49. Ando Y, Asari S, Suzuma S, Yamane K, Nakamura K: Expression of a small RNA, BS203 RNA, from the yocI-yocJ intergenic region of Bacillus subtilis genome. FEMS Microbiol Lett. 2002, 207: 29-33.

    CAS  PubMed  Google Scholar 

  50. Gohlmann HW, Weiner J, Schon A, Herrmann R: Identification of a small RNA within the pdh gene cluster of Mycoplasma pneumoniae and Mycoplasma genitalium. J Bacteriol. 2000, 182: 3281-3284. 10.1128/JB.182.11.3281-3284.2000.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  51. Pichon C, Felden B: Small RNA genes expressed from Staphylococcus aureus genomic and pathogenicity islands with specific expression among pathogenic strains. Proc Natl Acad Sci USA. 2005, 102: 14249-14254. 10.1073/pnas.0503838102.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  52. Axmann IM, Kensche P, Vogel J, Kohl S, Herze H, Hess WR: Identification of cyanobacterial non-coding RNAs by comparative genome analysis. Genome Biol. 2005, 6: R73-10.1186/gb-2005-6-9-r73.

    Article  PubMed Central  PubMed  Google Scholar 

  53. Trotochaud AE, Wassarman KM: A highly conserved 6S RNA structure is required for regulation of transcription. Nat Struct Mol Biol. 2005, 12: 313-319. 10.1038/nsmb917.

    Article  CAS  PubMed  Google Scholar 

  54. Pichon C, Felden B: Intergenic sequence inspector: searching and identifying bacterial RNAs. Bioinformatics. 19 (13): 1707-9. 10.1093/bioinformatics/btg235. 2003, Sep 1

  55. Osteras M, Stanley J, Finan TM: Identification of Rhizobium-specific intergenic mosaic elements within an essential two-component regulatory system of Rhizobium species. J Bacteriol. 1995, 177: 5485-5494.

    CAS  PubMed Central  PubMed  Google Scholar 

  56. Osteras M, Boncompagni E, Vincent N, Poggi MC, Le Rudulier D: Presence of a gene encoding choline sulfatase in Sinorhizobium meliloti bet operon: choline-O-sulfate is metabolized into glycine betaine. Proc Natl Acad Sci USA. 1998, 95: 11394-11399. 10.1073/pnas.95.19.11394.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  57. Sullivan JT, Ronson CW: Evolution of rhizobia by acquisition of a 500-kb symbiosis island that integrates into a phe-tRNA gene. Proc Natl Acad Sci USA. 1998, 9: 5145-5149. 10.1073/pnas.95.9.5145. Erratum in: Proc. Natl. Acad. Sci. USA 15:9059

    Article  Google Scholar 

  58. Zengel JM, Lindahl L: Diverse mechanisms for regulating ribosomal protein synthesis in Escherichia coli. Prog Nucleic Acid Res Mol Biol. 1994, 47: 331-370.

    Article  CAS  PubMed  Google Scholar 

  59. Benard L, Philippe C, Ehresmann B, Ehresmann C, Portier C: Pseudoknot and translational control in the expression of the S15 ribosomal protein. Biochimie. 1996, 78: 568-576. 10.1016/S0300-9084(96)80003-4.

    Article  CAS  PubMed  Google Scholar 

  60. Mantri Y, Williams KP: Islander: a database of integrative islands in prokaryotic genomes, the associated integrases and their DNA site specificities. Nucleic Acids Res. 2004, D55-8. 10.1093/nar/gkh059. 32 Database

  61. Tjaden B, Goodwin SS, Opdyke JA, Guillier M, Fu DX, Gottesman S, Storz G: Target prediction for small, noncoding RNAs in bacteria. Nucleic Acids Res. 2006, 34: 2791-2802. 10.1093/nar/gkl356.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  62. Wiggerich HG, Klauke B, Koplin R, Priefer UB, Puhler A: Unusual structure of the tonB-exb DNA region of Xanthomonas campestris pv. campestris: tonB, exbB, and exbD1 are essential for ferric iron uptake, but exbD2 is not. J Bacteriol. 1997, 179: 7103-7110.

    CAS  PubMed Central  PubMed  Google Scholar 

  63. Jacques JF, Jang S, Prevost K, Desnoyers G, Desmarais M, Imlay J, Masse E: RyhB small RNA modulates the free intracellular iron pool and is essential for normal growth during iron limitation in Escherichia coli. Mol Microbiol. 2006, 62: 1181-1190. 10.1111/j.1365-2958.2006.05439.x.

    Article  CAS  PubMed  Google Scholar 

  64. Hershberg R, Altuvia S, Margalit H: A survey of small RNA-encoding genes in Escherichia coli. Nucleic Acids Res. 2003, 31: 1813-20. 10.1093/nar/gkg297.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  65. Karzai AW, Susskind MM, Sauer RT: SmpB, a unique RNA-binding protein essential for the peptide-tagging activity of SsrA (tmRNA). EMBO J. 1999, 18: 3793-3799. 10.1093/emboj/18.13.3793.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  66. MacLellan SR, Smallbone LA, Sibley CD, Finan TM: The expression of a novel antisense gene mediates incompatibility within the large repABC family of alpha-proteobacterial plasmids. Mol Microbiol. 2005, 55: 611-623. 10.1111/j.1365-2958.2004.04412.x.

    Article  CAS  PubMed  Google Scholar 

  67. Dombrecht B, Marchal K, Vanderleyden J, Michiels J: Prediction and overview of the RpoN-regulon in closely related species of the Rhizobiales. Genome Biol. 2002, 3 (12):

  68. Okumura T, Makiguchi H, Makita Y, Yamashita R, Nakai K: Melina II: a web tool for comparisons among several predictive algorithms to find potential motifs from promoter regions. Nucleic Acids Res. 2007, 35: W227-231. 10.1093/nar/gkm362.

    Article  PubMed Central  PubMed  Google Scholar 

  69. Unniraman S, Prakash R, Nagaraja V: Conserved economics of transcription termination in eubacteria. Nucleic Acids Res. 2002, 30: 675-684. 10.1093/nar/30.3.675.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  70. Hofacker IL: Vienna RNA secondary structure server. Nucleic Acids Res. 2003, 31: 3429-3431. 10.1093/nar/gkg599.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  71. A Web Interface for the Prediction Consensus Structures of Aligned Sequences. [http://rna.tbi.univie.ac.at/cgi-bin/alifold.cgi]

  72. Gruber AR, Neubock R, Hofacker IL, Washietl S: The RNAz web server: prediction of thermodynamically stable and evolutionarily conserved RNA structures. Nucleic Acids Res. 2007, 35: W335-338. 10.1093/nar/gkm222.

    Article  PubMed Central  PubMed  Google Scholar 

  73. Nakamura K, Miyamoto H, Suzuma S, Sakamoto T, Kawai G, Yamane K: Minimal functional structure of Escherichia coli 4.5 S RNA required for binding to elongation factor G. J Biol Chem. 2001, 276: 22844-22849. 10.1074/jbc.M101376200.

    Article  CAS  PubMed  Google Scholar 

  74. Barrick JE, Sudarsan N, Weinberg Z, Ruzzo WL, Breaker RR: 6S RNA is a widespread regulator of eubacterial RNA polymerase that resembles an open promoter. RNA. 2005, 5: 774-784. 10.1261/rna.7286705.

    Article  Google Scholar 

  75. Small E, Marrington R, Rodger A, Scott DJ, Sloan K, Roper D, Dafforn TR, Addinall SG: FtsZ polymer-bundling by the Escherichia coli ZapA orthologue, YgfE, involves a conformational change in bound GTP. J Mol Biol. 2007, 369: 210-221. 10.1016/j.jmb.2007.03.025.

    Article  CAS  PubMed  Google Scholar 

  76. Kihara A, Akiyama Y, Ito K: Host regulation of lysogenic decision in bacteriophage lambda: transmembrane modulation of FtsH (HflB), the cII degrading protease, by HflKC (HflA). Proc Natl Acad Sci USA. 1997, 94: 5544-5549. 10.1073/pnas.94.11.5544.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  77. Gerdes K, Wagner EG: RNA antitoxins. Curr Opin Microbiol. 2007, 10: 117-124. 10.1016/j.mib.2007.03.003.

    Article  CAS  PubMed  Google Scholar 

  78. Sevin EW, Barloy-Hubler F: RASTA-Bacteria: a web-based tool for identifying toxin-antitoxin loci in prokaryotes. Genome Biol. 2007, 8: R155-10.1186/gb-2007-8-8-r155.

    Article  PubMed Central  PubMed  Google Scholar 

  79. Aiba H: Mechanism of RNA silencing by Hfq-binding small RNAs. Curr Opin Microbiol. 2007, 10: 134-139. 10.1016/j.mib.2007.03.010.

    Article  CAS  PubMed  Google Scholar 

  80. Vincent JM: A manual for the practical study of root-nodule bacteria. 1970, Blackwell Scientific Publications, Oxford

    Google Scholar 

  81. Sambrook J, Fritsch EF, Maniatis T: Molecular cloning. 1989, New York: Cold Spring Harbor Laboratory Press, 2

    Google Scholar 

  82. Dabney AR, Storey JD: A new approach to intensity-dependent normalization of two-channel microarrays. Biostatistics. 2007, 8 (1): 128-139. 10.1093/biostatistics/kxj038.

    Article  PubMed  Google Scholar 

  83. The Sinorhizobium meliloti strain 1021 Genome Project. [http://bioinfo.genopole-toulouse.prd.fr/annotation/iANT/bacteria/rhime/index.html]

  84. Carver TJ, Rutherford KM, Berriman M, Rajandream MA, Barrell BG, Parkhill J: ACT: the Artemis Comparison Tool. Bioinformatics. 2005, 21: 3422-3. 10.1093/bioinformatics/bti553.

    Article  CAS  PubMed  Google Scholar 

  85. The Artemis Comparison Tool. [http://www.sanger.ac.uk/Software/ACT]

  86. The Refseq Database. [ftp://ftp.ncbi.nih.gov/genomes/Bacteria/]

  87. The Comprehensive Microbial Resource. [http://pathema.tigr.org/tigr-scripts/CMR/shared/MakeFrontPages.cgi?page=rna_list]

  88. Jacobs GH, Stockwell PA, Tate WP, Brown CM: Transterm – extended search facilities and improved integration with other databases. Nucleic Acids Res. 2006, 34: D37-40. 10.1093/nar/gkj159.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  89. The Database of mRNA related information. [http://www.genomics.jhu.edu/TransTerm/transterm.html]

  90. Higgins D, Thompson J, Gibson T, Thompson JD, Higgins DG, Gibson TJ: CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 1994, 22: 4673-4680. 10.1093/nar/22.22.4673.

    Article  PubMed Central  PubMed  Google Scholar 

Download references

Acknowledgements

Vincent Ulvé and Emeric Sevin were supported by PRIR-ADAPTOME and RdC-PREDATOR Région Bretagne, respectively. This work was supported by the CNRS (Centre National de la Recherche Scientifique) and by the Université Européenne de Bretagne.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Frédérique Barloy-Hubler.

Additional information

Authors' contributions

VU and AC conceived the design and use of the microarrays and performed the isolation and blotting of the RNAs. AC performed 5'-3' RACE and sequencing of sra32 candidates in Rhizobiales. ES and FBH performed the bioinformatic analyses and IGRs annotation. FBH designed and coordinated all aspects of the project. All authors read and approved the final manuscript.

Vincent M Ulvé, Emeric W Sevin contributed equally to this work.

Electronic supplementary material

12864_2007_1180_MOESM1_ESM.pdf

Additional file 1: Phylogenetic maximum likelihood trees of alpha-proteobacteria ffs, rnpB and tmRNA sequences. The data provided shows the phylogenetic maximum likelihood trees in subgroup-2 alpha-proteobacteria of the canonical tmRNA, rnpB and ffs small RNAs. (PDF 83 KB)

12864_2007_1180_MOESM2_ESM.pdf

Additional file 2: BlastN detection of E. coli small genes in S. meliloti genome. The data provided describes the results of homology searches for E. coli small RNAs in the S. meliloti genome. (PDF 51 KB)

12864_2007_1180_MOESM3_ESM.pdf

Additional file 3: sRNAPredict outputs. The data provided presents the results obtained with sRNAPredict on S. meliloti's chromosome. (PDF 38 KB)

12864_2007_1180_MOESM4_ESM.xls

Additional file 4: Intergenic regions included in this study. The data provided lists the intergenic regions selected (sra candidates) for in vivo validation and their features. (XLS 79 KB)

12864_2007_1180_MOESM5_ESM.pdf

Additional file 5: Normalized expression levels (log2SNR) of IGRs candidates. The data provided compiles the normalized expression levels for the candidates. (PDF 34 KB)

12864_2007_1180_MOESM6_ESM.pdf

Additional file 6: sra41 multiple loci in S. meliloti and related alpha-proteobacteria. The data provided features the multiple loci of sra41 in subgroup-2 alpha-proteobacteria. (PDF 42 KB)

12864_2007_1180_MOESM7_ESM.pdf

Additional file 7: Strains used in this study.The data provided references the different bacteria used in this study. (PDF 57 KB)

12864_2007_1180_MOESM8_ESM.pdf

Additional file 8: Oligonucleotides used in RACE and Northern assays. The data provided presents the oligonucleotide sequences used in RACE and Northern assays. (PDF 67 KB)

12864_2007_1180_MOESM9_ESM.pdf

Additional file 9: Oligonucleotides used in microarray design. The data provided presents the oligonucleotide sequences used in the microarray design. (PDF 45 KB)

12864_2007_1180_MOESM10_ESM.pdf

Additional file 10: Short (FASTA) alignment and corresponding synteny results. The data provided shows the results of the search for small regions of homology between alpha-proteobacteria. (PDF 1 MB)

12864_2007_1180_MOESM11_ESM.pdf

Additional file 11: Artemis Comparison Tool (ACT) screenshots alignment and corresponding synteny results. The data provided presents the results of the ACT comparisons. (PDF 4 MB)

12864_2007_1180_MOESM12_ESM.pdf

Additional file 12: TargetRNA results. The data provided shows the results of the target analysis for each valid sra gene. (PDF 155 KB)

12864_2007_1180_MOESM13_ESM.pdf

Additional file 13: Alifold and RNAz secondary predictions. The data provided presents the alternative structures predicted for sra genes depending on the tools used. (PDF 2 MB)

Authors’ original submitted files for images

Rights and permissions

Open Access This article is published under license to BioMed Central Ltd. This is an Open Access article is distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and permissions

About this article

Cite this article

Ulvé, V.M., Sevin, E.W., Chéron, A. et al. Identification of chromosomal alpha-proteobacterial small RNAs by comparative genome analysis and detection in Sinorhizobium meliloti strain 1021. BMC Genomics 8, 467 (2007). https://doi.org/10.1186/1471-2164-8-467

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/1471-2164-8-467

Keywords