Computational study of the evolution of bacterial DNA repair systems

Abstract

Bacteria thrive in dynamic environments with their DNA facing a constant onslaught of damage. To combat these damages, genomes code for a toolkit of cellular responses, including DNA repair. Making a choice of DNA repair pathway is critical to ensure genome stability versus accuracy. Comparative genomics based studies have highlighted a variability in the repertoires of repair pathways coded across bacterial genomes. Even though we have started to gain mechanistic insights of how these repair pathways work at a molecular level, we still lack an understanding of the factors that dictate the employment of a given repair pathway over the other. In this light, some of the outstanding questions that we do not have answers to, include, how, when and why repair pathways came to be distributed across bacteria. Towards addressing these questions, we included two different repair pathways as case studies: 1. Non-homologous end joining (NHEJ), a template-independent double strand break repair pathway and 2. AlkB, an oxidative demethylase employed in nucleotide alkylation damage repair. We developed a workflow to understand the evolution of these two repair pathways using computational approaches like comparative genomics, phylogenetic comparative methods and machine learning. We found that shared ancestry is not sufficient to explain the incidence of proteins involved in both the repair mechanisms. Our work supports the hypothesis that sources of genome instability play an important role in dictating the evolutionary history of these DNA repair pathways across bacteria.