Penunuri, G. (BMEB) – Genomic, Proteomic, and Computational Approaches to the Study of Host-Microbe Systems

Host-microbe systems are core to some of biology’s most consequential interactions, from the pathogens that drive infectious disease to symbionts affecting agricultural pest control and vector-borne disease transmission. Yet unlike the model organisms that have driven most of modern molecular biology, the microbes at the center of these interactions are rarely genetically tractable: many cannot be cultured outside a host, resist standard tools for genetic manipulation, and are annotated largely by homology to distantly related free-living relatives. This dissertation develops genomic, proteomic, and computational methods to work around this lack of infrastructure and contribute techniques and tools to the study and further understanding of host-microbe systems. Using Wolbachia cultured in Drosophila melanogaster cell lines, I demonstrate that chemical mutagenesis can be used to perturb intracellular genomes leaving a detectable mutational signal. I employ a low error rate sequencing technique to record and model the mutational landscape left by the mutagen ethyl methanesulfonate (EMS) demonstrating its use for mutagenesis screens of intracellular bacteria. I next utilize structural proteome datasets to screen host-microbe proteomes for strong candidates of molecular mimicry, microbe proteins that have coevolved a eukaryotic like domain or structure and suggest use for host manipulation or microbe survival in the host environment. Building off of this screen for novel effectors through structural alignments I develop and test a distributed computing system for performing large scale systematic literature reviews. Altogether these projects represent generalizable approaches to the study of host-microbe systems reaching from classically studied and thoroughly understood to novel and non-model systems.

Event Host: Gabriel Penunuri, Ph.D. Candidate, Biomolecular Engineering & Bioinformatics 

Advisor: Russell Corbett-Detig

Zoom: https://ucsc.zoom.us/j/98216883331?pwd=uqmUSQba2X6GVNBhOhAGRwgCZyjAyj.1

Passcode: 730377