Recherche de cible pour des miRNAs chez l'Humain.

Leptospiral promoter regions are poorly characterized: experimentally proven transcription factor binding sites have not been described in the literature and promoter prediction algorithms and E. coli consensus sequences of DNA motifs are not appropriate for Leptospira. Identification of Transcription Start Sites (TSS) and promoters on a global scale will provide essential information on DNA motifs that are targets of RNA polymerases, sigma factors and transcription factors. RNA sequencing will also provide information on small regulatory RNAs. These small (~30-500 nt) non-coding RNAs (sRNAs) are an emerging class of post-transcriptional regulators which play a variety of important roles in many biological processes. Studies on sRNA regulation of gene expression in Leptospira are currently in their infancy. Our results will provide new insights into the transcriptional landscape of L. interrogans, including the repertoire of sRNA, and it will establish the foundation for future experimental work on gene regulation.    

In the context of the Swiss consortium InfectX (www.infectx.ch), Javier PIZARRO-CERDA previously performed siRNA, microRNA, drug screens and proteomic analyses to investigate signaling pathways modulating invasion of host cells by the bacterial pathogen Listeria monocytogenes. In a first consortium study, based on results from drug and siRNA screens targeting the human kinome, we identified major kinases which up- or down-regulate cell invasion by L. monocytogenes and by 7 additional bacterial and viral pathogens (Rämö et al. 2014). Subsequently, a siRNA genome-wide screen allowed us to revisit and redefine the role of cytoskeletal complexes required for L. monocytogenes cellular invasion and actin-based motility (Kühbacher et al. 2015). Applying a proteomic ‘surfaceome’ analysis, we also revealed that late endosomal compartments are recruited to L. monocytogenes infection foci to promote invasion (Kühbacher et al. Submitted). More recently, we have started the analysis of a microRNA screen which highlights novel gene clusters associated to regulation of phosphoinositide metabolism during L. monocytogenes cell entry (Kühbacher et al. Unpublished Results). These different projects have generated vast amounts of data that have been until now only independently analyzed. However, this information can now be exploited from a systems biology perspective to identify hidden connections between relevant signaling cascades and gene networks which may highlight novel cellular functions exploited by pathogens in the context of infection. The team of Benno SCHWIKOWSKI will perform two types of analysis on the data generated by Javier PIZARRO-CERDA. In both cases, p-values will be aggregated across gene sets using suitable statistical approaches. We will then

• Pathway-based analysis. This type of analysis considers genes in sets that have been recognized to operate together to perform certain biological functions (e.g.,

The Transcriptome & Epigenome Platform is dedicated to the development and use of high throughput approaches for transcriptomics and epigenomics studies. The platform is accessible to any research team from the Pasteur Institute (80% of the projects) as well as from outside. It is involved (most often as collaborator) in several projects funded by the ANR, AVIESAN and by the Pasteur Institute in the framework of the PTR programs. Next Generation Sequencing (NGS) based on the Illumina technology (HiSeq 2000/2500 sequencers) is used to perform RNA-sequencing experiments for which a large amount of data is generated. After a first step involving bioinformatics, specific statistical methods must be used be analyze rigorously the data. These analyses are most often performed by the statistician(s) of the platform. They are also in charge of bibliographical survey activity.