ReadRNA

The transcriptome corresponds to the RNA set present in a cell at a specific time; each profile is characteristic of the given growth condition. Transcriptome studies via tiling-array and RNAseq technologies are used to quantify a large number of genes and to identify novel transcripts such as antisense and non-coding regulatory RNAs. With these approaches, we characterized the interconnection of five regulatory pathways in an adaptive response in Escherichia coli (Bury-Mone et al. 2009) and showed that a riboregulator controls the central metabolism in Staphylococcus aureus (Bohn et al. 2010). The nature and timing of molecular events that affect the RNAs in eukaryotes and prokaryotes are different and confer different chemical properties to the RNAs. Eukaryotic cells are compartmentalized and RNAs are generally stable. Eukaryote transcriptome studies thus allowed a detailed analysis of transcriptional and post-transcriptional events and led to the discovery of networks of regulons. In contrast, prokaryotic RNAs are generally unstable and the native transcript 5'-end is a triphosphate nucleotide. In bacteria, transcriptome studies cannot distinguish between primary and processed RNAs. For these very reasons, current bacterial transcriptomes do not contain enough information to deduce the regulatory pathways that generated the observed RNAs, nor to infer transcriptional and post-transcriptional regulons. Only a few bacterial species known as "models" (mainly E. coli and Bacillus subtilis) can complement transcriptomic data by the genetic results accumulated over half a century. We have developed a 5’end tagging strategy, which discriminates, within a bacterial transcriptome, RNAs according to their origin; i.e. primary transcripts synthesized by the RNA polymerase, from matured transcripts that are generated by RNA cleavage (Fouquier d'Herouel et al. 2011). We recently adapted this method to associate it with deep RNA sequencing techniques (termed “tagRNAseq”). Our preliminary results allow for the first time, the detection and differentiation of all native and truncated RNAs of a bacterium, thus obtaining a picture of the primary and matured transcriptome. A main finding from our work is that eighty-five percent of bacterial transcripts correspond to processed RNAs. This startling observation is a driving and motivating force behind the ReadRNA project, as this suggest that the major RNA bulk affected by gene expression reprogramming could be due to post-transcriptional events. TagRNAseq i) enables to determine the specific contribution and the extent of RNA maturation in the control of bacterial gene expression during steady state conditions, ii) provides information on the relative abundance of each form of RNA during an adaptation process, iii) generates a database that can be used to identify new regulatory mechanisms that operate exclusively on the post-transcriptional level. The ReadRNA project will make use of the tagRNAseq method that was validated by our preliminary results. We propose to study the transcriptomes of three major pathogenic species: E. coli, S. aureus and Enterococcus faecalis. ReadRNA will establish two experimental pillars for these three species: i) Primary and mature transcriptomes and, ii) Transcriptional and post-transcriptional regulons in response to a signal associated with an environmental condition. The project will benefit from our expertise on transcriptome analysis of regulatory networks and knowledge on extracytoplasmic stress regulons. The impacts of ReadRNA are primarily cognitive: We can directly "see" the relative contribution of transcriptional and post-transcriptional events (maturation and stability) affecting RNAs; these observations will be used to generate a new “level” of information on control of gene expression and adaptation processes. ReadRNA will allow the study of gene regulation at the molecular level and at a genomic scale, even with genetically uncharacterized bacteria.