Cellular homeostasis pathways in bacteria



 DESCRIPTION (provided by applicant): Cellular Homeostasis Pathways in Bacteria Maintaining cellular homeostasis is critical for balanced cell growth. Yet remarkably little is known about the connections between processes that contribute to homeostasis. A number of transcription-focused studies have elucidated some of this wiring, especially for responses to specific stresses, but other contributions to homeostasis remain oblique. Here we focus on two understudied features of bacteria to understand their contributions to cellular homeostasis. First, we are teasing apart processes in the envelope compartment of the cell that interlock its complex functions, and coordinate with the cytoplasm. Second, we are exploring how the cell controls protein abundance both in response to differential conditions, and in response to cell differentiation. As protein production constitutes the majority of the energy expended by the bacterial cell, it is critical that protein production can change as needed. Our biological studies are powered by genome-scale technologies. We identify novel envelope pathways using chemical genomics, and also with our method, currently in development, for pooled genetic interaction analysis. This method is based on double knockdowns made with CRISPRi (CRISPR/Cas9 interference) technology. We are determining how protein abundance is controlled using global technologies to measure protein abundance (ribosome profiling + mRNAseq) coupled with a new method we are developing to measure mRNA decay at genome scale. In each case, we use the datasets we generate as a starting point for detailed mechanistic analysis of interesting findings. Importantly, because the methods powering our research are readily portable across bacteria, we are now studying the envelope both in E. coli and in B. subtilis, enabling evolutionary comparison across the Gram-positive/Gram- negative divide. We are also actively working to port these methods to medically and environmentally relevant non-model organisms. Finally, as our high quality datasets meet the standard necessary for providing a reliable entry point for mechanistic studies, they are an essential resource for the study of multiple cell processes by the scientific community.