Transcriptomic profiling of Yersinia pseudotuberculosis reveals reprogramming of the Crp regulon by temperature and uncovers Crp as a master regulator of small RNAs.

One hallmark of pathogenic yersiniae is their ability to rapidly adjust their life-style and pathogenesis upon host entry. In order to capture the range, magnitude and complexity of the underlying gene control mechanisms we used comparative RNA-seq-based transcriptomic profiling of the enteric pathogen Y. pseudotuberculosis under environmental and infection-relevant conditions. We identified 1151 individual transcription start sites, multiple riboswitch-like RNA elements, and a global set of antisense RNAs and previously unrecognized trans-acting RNAs. Taking advantage of these data, we revealed a temperature-induced and growth phase-dependent reprogramming of a large set of catabolic/energy production genes and uncovered the existence of a thermo-regulated 'acetate switch', which appear to prime the bacteria for growth in the digestive tract. To elucidate the regulatory architecture linking nutritional status to virulence we also refined the CRP regulon. We identified a massive remodelling of the CRP-controlled network in response to temperature and discovered CRP as a transcriptional master regulator of numerous conserved and newly identified non-coding RNAs which participate in this process. This finding highlights a novel level of complexity of the regulatory network in which the concerted action of transcriptional regulators and multiple non-coding RNAs under control of CRP adjusts the control of Yersinia fitness and virulence to the requirements of their environmental and virulent life-styles.

Thermodynamic matchers for the construction of the cuckoo RNA family.

RNA family models describe classes of functionally related, non-coding RNAs based on sequence and structure conservation. The most important method for modeling RNA families is the use of covariance models, which are stochastic models that serve in the discovery of yet unknown, homologous RNAs. However, the performance of covariance models in finding remote homologs is poor for RNA families with high sequence conservation, while for families with high structure but low sequence conservation, these models are difficult to built in the first place. A complementary approach to RNA family modeling involves the use of thermodynamic matchers. Thermodynamic matchers are RNA folding programs, based on the established thermodynamic model, but tailored to a specific structural motif. As thermodynamic matchers focus on structure and folding energy, they unfold their potential in discovering homologs, when high structure conservation is paired with low sequence conservation. In contrast to covariance models, construction of thermodynamic matchers does not require an input alignment, but requires human design decisions and experimentation, and hence, model construction is more laborious. Here we report a case study on an RNA family that was constructed by means of thermodynamic matchers. It starts from a set of known but structurally different members of the same RNA family. The consensus secondary structure of this family consists of 2 to 4 adjacent hairpins. Each hairpin loop carries the same motif, CCUCCUCCC, while the stems show high variability in their nucleotide content. The present study describes (1) a novel approach for the integration of the structurally varying family into a single RNA family model by means of the thermodynamic matcher methodology, and (2) provides the results of homology searches that were conducted with this model in a wide spectrum of bacterial species.

Riboregulation in plant-associated α-proteobacteria.

The symbiotic α-rhizobia Sinorhizobium meliloti, Bradyrhizobium japonicum, Rhizobium etli and the related plant pathogen Agrobacterium tumefaciens are important model organisms for studying plant-microbe interactions. These metabolically versatile soil bacteria are characterized by complex lifestyles and large genomes. Here we summarize the recent knowledge on their small non-coding RNAs (sRNAs) including conservation, function, and interaction of the sRNAs with the RNA chaperone Hfq. In each of these organisms, an inventory of hundreds of cis- and trans-encoded sRNAs with regulatory potential was uncovered by high-throughput approaches and used for the construction of 39 sRNA family models. Genome-wide analyses of hfq mutants and co-immunoprecipitation with tagged Hfq revealed a major impact of the RNA chaperone on the physiology of plant-associated α-proteobacteria including symbiosis and virulence. Highly conserved members of the SmelC411 family are the AbcR sRNAs, which predominantly regulate ABC transport systems. AbcR1 of A. tumefaciens controls the uptake of the plant-generated signaling molecule GABA and is a central regulator of nutrient uptake systems. It has similar functions in S. meliloti and the human pathogen Brucella abortus. As RNA degradation is an important process in RNA-based gene regulation, a short overview on ribonucleases in plant-associated α-proteobacteria concludes this review.

Genome-wide profiling of Hfq-binding RNAs uncovers extensive post-transcriptional rewiring of major stress response and symbiotic regulons in Sinorhizobium meliloti.

The RNA chaperone Hfq is a global post-transcriptional regulator in bacteria. Here, we used RNAseq to analyze RNA populations from the legume symbiont Sinorhizobium meliloti that were co-immunoprecipitated (CoIP-RNA) with a FLAG-tagged Hfq in five growth/stress conditions. Hfq-bound transcripts (1315) were largely identified in stressed bacteria and derived from small RNAs (sRNAs), both trans-encoded (6.4%) and antisense (asRNAs; 6.3%), and mRNAs (86%). Pull-down with Hfq recovered a small proportion of annotated S. meliloti sRNAs (14% of trans-sRNAs and 2% of asRNAs) suggesting a discrete impact of this protein in sRNA pathways. Nonetheless, Hfq selectively stabilized CoIP-enriched sRNAs, anticipating that these interactions are functionally significant. Transcription of 26 Hfq-bound sRNAs was predicted to occur from promoters recognized by the major stress σ factors σ(E2) or σ(H1/2). Recovery rates of sRNAs in each of the CoIP-RNA libraries suggest a large impact of Hfq-assisted riboregulation in S. meliloti osmoadaptation. Hfq directly targeted 18% of the predicted S. meliloti mRNAs, which encode functionally diverse proteins involved in transport and metabolism, σ(E2)-dependent stress responses, quorum sensing, flagella biosynthesis, ribosome, and membrane assembly or symbiotic nitrogen fixation. Canonical targeting of the 5' regions of two of the ABC transporter mRNAs by the homologous Hfq-binding AbcR1 and AbcR2 sRNAs leading to inhibition of protein synthesis was confirmed in vivo. We therefore provide a comprehensive resource for the systems-level deciphering of hitherto unexplored S. meliloti stress and symbiotic post-transcriptional regulons and the identification of Hfq-dependent sRNA-mRNA regulatory pairs.

Global mapping of transcription start sites and promoter motifs in the symbiotic α-proteobacterium Sinorhizobium meliloti 1021.

BACKGROUND: Sinorhizobium meliloti is a soil-dwelling α-proteobacterium that possesses a large, tripartite genome and engages in a nitrogen fixing symbiosis with its plant hosts. Although much is known about this important model organism, global characterization of genetic regulatory circuits has been hampered by a lack of information about transcription and promoters. RESULTS: Using an RNAseq approach and RNA populations representing 16 different growth and stress conditions, we comprehensively mapped S. meliloti transcription start sites (TSS). Our work identified 17,001 TSS that we grouped into six categories based on the genomic context of their transcripts: mRNA (4,430 TSS assigned to 2,657 protein-coding genes), leaderless mRNAs (171), putative mRNAs (425), internal sense transcripts (7,650), antisense RNA (3,720), and trans-encoded sRNAs (605). We used this TSS information to identify transcription factor binding sites and putative promoter sequences recognized by seven of the 15 known S. meliloti σ factors σ70, σ54, σH1, σH2, σE1, σE2, and σE9). Altogether, we predicted 2,770 new promoter sequences, including 1,302 located upstream of protein coding genes and 722 located upstream of antisense RNA or trans-encoded sRNA genes. To validate promoter predictions for targets of the general stress response σ factor, RpoE2 (σE2), we identified rpoE2-dependent genes using microarrays and confirmed TSS for a subset of these by 5' RACE mapping. CONCLUSIONS: By identifying TSS and promoters on a global scale, our work provides a firm foundation for the continued study of S. meliloti gene expression with relation to gene organization, σ factors and other transcription factors, and regulatory RNAs.

Conservation and Occurrence of Trans-Encoded sRNAs in the Rhizobiales.

Post-transcriptional regulation by trans-encoded sRNAs, for example via base-pairing with target mRNAs, is a common feature in bacteria and influences various cell processes, e.g., response to stress factors. Several studies based on computational and RNA-seq approaches identified approximately 180 trans-encoded sRNAs in Sinorhizobium meliloti. The initial point of this report is a set of 52 trans-encoded sRNAs derived from the former studies. Sequence homology combined with structural conservation analyses were applied to elucidate the occurrence and distribution of conserved trans-encoded sRNAs in the order of Rhizobiales. This approach resulted in 39 RNA family models (RFMs) which showed various taxonomic distribution patterns. Whereas the majority of RFMs was restricted to Sinorhizobium species or the Rhizobiaceae, members of a few RFMs were more widely distributed in the Rhizobiales. Access to this data is provided via the RhizoGATE portal [1,2].

A genome-wide survey of sRNAs in the symbiotic nitrogen-fixing alpha-proteobacterium Sinorhizobium meliloti.

BACKGROUND: Small untranslated RNAs (sRNAs) are widespread regulators of gene expression in bacteria. This study reports on a comprehensive screen for sRNAs in the symbiotic nitrogen-fixing alpha-proteobacterium Sinorhizobium meliloti applying deep sequencing of cDNAs and microarray hybridizations. RESULTS: A total of 1,125 sRNA candidates that were classified as trans-encoded sRNAs (173), cis-encoded antisense sRNAs (117), mRNA leader transcripts (379), and sense sRNAs overlapping coding regions (456) were identified in a size range of 50 to 348 nucleotides. Among these were transcripts corresponding to 82 previously reported sRNA candidates. Enrichment for RNAs with primary 5'-ends prior to sequencing of cDNAs suggested transcriptional start sites corresponding to 466 predicted sRNA regions. The consensus sigma70 promoter motif CTTGAC-N17-CTATAT was found upstream of 101 sRNA candidates. Expression patterns derived from microarray hybridizations provided further information on conditions of expression of a number of sRNA candidates. Furthermore, GenBank, EMBL, DDBJ, PDB, and Rfam databases were searched for homologs of the sRNA candidates identified in this study. Searching Rfam family models with over 1,000 sRNA candidates, re-discovered only those sequences from S. meliloti already known and stored in Rfam, whereas BLAST searches suggested a number of homologs in related alpha-proteobacteria. CONCLUSIONS: The screening data suggests that in S. meliloti about 3% of the genes encode trans-encoded sRNAs and about 2% antisense transcripts. Thus, this first comprehensive screen for sRNAs applying deep sequencing in an alpha-proteobacterium shows that sRNAs also occur in high number in this group of bacteria.

Prediction of Sinorhizobium meliloti sRNA genes and experimental detection in strain 2011.

BACKGROUND: Small non-coding RNAs (sRNAs) have emerged as ubiquitous regulatory elements in bacteria and other life domains. However, few sRNAs have been identified outside several well-studied species of gamma-proteobacteria and thus relatively little is known about the role of RNA-mediated regulation in most other bacterial genera. Here we have conducted a computational prediction of putative sRNA genes in intergenic regions (IgRs) of the symbiotic alpha-proteobacterium S. meliloti 1021 and experimentally confirmed the expression of dozens of these candidate loci in the closely related strain S. meliloti 2011. RESULTS: Our first sRNA candidate compilation was based mainly on the output of the sRNAPredictHT algorithm. A thorough manual sequence analysis of the curated list rendered an initial set of 18 IgRs of interest, from which 14 candidates were detected in strain 2011 by Northern blot and/or microarray analysis. Interestingly, the intracellular transcript levels varied in response to various stress conditions. We developed an alternative computational method to more sensitively predict sRNA-encoding genes and score these predicted genes based on several features to allow identification of the strongest candidates. With this novel strategy, we predicted 60 chromosomal independent transcriptional units that, according to our annotation, represent strong candidates for sRNA-encoding genes, including most of the sRNAs experimentally verified in this work and in two other contemporary studies. Additionally, we predicted numerous candidate sRNA genes encoded in megaplasmids pSymA and pSymB. A significant proportion of the chromosomal- and megaplasmid-borne putative sRNA genes were validated by microarray analysis in strain 2011. CONCLUSION: Our data extend the number of experimentally detected S. meliloti sRNAs and significantly expand the list of putative sRNA-encoding IgRs in this and closely related alpha-proteobacteria. In addition, we have developed a computational method that proved useful to predict sRNA-encoding genes in S. meliloti. We anticipate that this predictive approach can be flexibly implemented in many other bacterial species.