sRNARegNet - Comparative analysis of small RNA regulatory networks in Gammaproteobacteria

• Applicant: Professor Dr. Konrad Förstner
• Subject Area: Metabolism, Biochemistry and Genetics of Microorganisms ; Bioinformatics and Theoretical Biology ; Microbial Ecology and Applied Microbiology
• Term: from 2020 to 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 433110396

The efficient control of gene expression is essential for all living organisms. In addition to the extensively studied protein-based regulators (i.e. transcription factors (TFs) and bacterial RNA-polymerase sigma factors), small regulatory RNAs (sRNAs) are key agents to adjust cellular transcript levels to external cues. The advent of high-throughput sequencing technologies has revolutionized the identification of sRNAs in all phyla of life, including the bacteria. A typical bacterium expresses hundreds of sRNA species, however, their biological functions frequently are not known. In this project, we aim to identify, annotate and characterize novel sRNAs from a diverse set of microbes from the class of Gammaproteobacteria (a total of 20 species). Samples will be collected from four different growth conditions including iron-limitation and cell membrane stress to ensure that sRNAs expressed under a broad range of environmental settings will be detected. Focusing on sRNA regulators that depend on the RNA chaperon Hfq for their function and act through base-pairing with target mRNAs, we will study their distribution as well as their evolution. To this end, we have developed an integrated bioinformatics platform for the generation of high-resolution microbial transcriptome maps allowing for the genome-wide discovery of transcriptional start sites (TSSs) and sRNAs, as well as binding sites for transcription factors and sigma factors controlling expression from the corresponding promoters. We will use RIL-Seq analysis (RNA interaction by ligation and sequencing) to globally identify the targets of these base pairing sRNAs and to infer biologically-relevant gene expression regulation. The data will be integrated into a comprehensive network model of sRNA-mediated gene regulation allowing us to explore the evolutionary relationship of sRNAs, their transcriptional regulators, and targets. Based on these analyses, we will be able to address numerous biological questions such as whether the existence and regulons of sRNA are linked to the life style and physiologies of their host bacterium. Additionally, this consistent collection of TSSs, expression levels, and sRNA-interaction data will be a unique and highly valuable resource that can be used by other investigators with a wide range of research interests.

• DFG Programme: Research Grants
• International Connection: USA
• Cooperation Partner: Professorin Gisela Storz, Ph.D.