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Computational methods can often facilitate the functional characterization of individual sRNAs and furthermore allow high-throughput analysis on large numbers of sRNA candidates. This chapter outlines a potential workflow for computational sRNA analyses and describes in detail methods for homolog detection, target prediction, and functional characterization based on enrichment analysis. The cyanobacterial sRNA IsaR1 is used as a specific example. All methods are available as webservers and easily accessible for nonexpert users.

Background: While NGS allows rapid global detection of transcripts, it remains difficult to distinguish ncRNAs from short mRNAs. To detect potentially translated RNAs, we developed an improved protocol for bacterial ribosomal footprinting (RIBOseq). This allowed distinguishing ncRNA from mRNA in EHEC. A high ratio of ribosomal footprints per transcript (ribosomal coverage value, RCV) is expected to indicate a translated RNA, while a low RCV should point to a non-translated RNA., Results: Based on their low RCV, 150 novel non-translated EHEC transcripts were identified as putative ncRNAs, representing both antisense and intergenic transcripts, 74 of which had expressed homologs in E. coli MG1655. Bioinformatics analysis predicted statistically significant target regulons for 15 of the intergenic transcripts; experimental analysis revealed 4-fold or higher differential expression of 46 novel ncRNA in different growth media. Out of 329 annotated EHEC ncRNAs, 52 showed an RCV similar to protein-coding genes, of those, 16 had RIBOseq patterns matching annotated genes in other enterobacteriaceae, and 11 seem to possess a Shine-Dalgarno sequence, suggesting that such ncRNAs may encode small proteins instead of being solely non-coding. To support that the RIBOseq signals are reflecting translation, we tested the ribosomal-footprint covered ORF of ryhB and found a phenotype for the encoded peptide in iron-limiting condition., Conclusion: Determination of the RCV is a useful approach for a rapid first-step differentiation between bacterial ncRNAs and small mRNAs. Further, many known ncRNAs may encode proteins as well.

Mechanisms adjusting replication initiation and cell cycle progression in response to environmental conditions are crucial for microbial survival. Functional characterization of the trans-encoded small non-coding RNA (trans-sRNA) EcpR1 in the plant-symbiotic alpha-proteobacterium Sinorhizobium meliloti revealed a role of this class of riboregulators in modulation of cell cycle regulation. EcpR1 is broadly conserved in at least five families of the Rhizobiales and is predicted to form a stable structure with two defined stem-loop domains. In S. meliloti, this trans-sRNA is encoded downstream of the divK-pleD operon. ecpR1 belongs to the stringent response regulon, and its expression was induced by various stress factors and in stationary phase. Induced EcpR1 overproduction led to cell elongation and increased DNA content, while deletion of ecpR1 resulted in reduced competitiveness. Computationally predicted EcpR1 targets were enriched with cell cycle-related mRNAs. Post-transcriptional repression of the cell cycle key regulatory genes gcrA and dnaA mediated by mRNA base-pairing with the strongly conserved loop 1 of EcpR1 was experimentally confirmed by two-plasmid differential gene expression assays and compensatory changes in sRNA and mRNA. Evidence is presented for EcpR1 promoting RNase E-dependent degradation of the dnaA mRNA. We propose that EcpR1 contributes to modulation of cell cycle regulation under detrimental conditions.

CopraRNA (Comparative prediction algorithm for small RNA targets) is the most recent asset to the Freiburg RNA Tools webserver. It incorporates and extends the functionality of the existing tool IntaRNA (Interacting RNAs) in order to predict targets, interaction domains and consequently the regulatory networks of bacterial small RNA molecules. The CopraRNA prediction results are accompanied by extensive postprocessing methods such as functional enrichment analysis and visualization of interacting regions. Here, we introduce the functionality of the CopraRNA and IntaRNA webservers and give detailed explanations on their postprocessing functionalities. Both tools are freely accessible at http://rna.informatik.uni-freiburg.de., (© The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.)

The small RNA AbcR1 regulates the expression of ABC transporters in the plant pathogen Agrobacterium tumefaciens, the plant symbiont Sinorhizobium meliloti, and the human pathogen Brucella abortus. A combination of proteomic and bioinformatic approaches suggested dozens of AbcR1 targets in A. tumefaciens. Several of these newly discovered targets are involved in the uptake of amino acids, their derivatives, and sugars. Among the latter is the periplasmic sugar-binding protein ChvE, a component of the virulence signal transduction system. We examined 16 targets and their interaction with AbcR1 in close detail. In addition to the previously described mRNA interaction site of AbcR1 (M1), the CopraRNA program predicted a second functional module (M2) as target-binding site. Both M1 and M2 contain single-stranded anti-SD motifs. Using mutated AbcR1 variants, we systematically tested by band shift experiments, which sRNA region is responsible for mRNA binding and gene regulation. On the target site, we find that AbcR1 interacts with some mRNAs in the translation initiation region and with others far into their coding sequence. Our data show that AbcR1 is a versatile master regulator of nutrient uptake systems in A. tumefaciens and related bacteria.