A pan-genome method to determine core regions of the Bacillus subtilis and Escherichia coli genomes

Abstract

Synthetic engineering of bacteria to produce industrial products is a burgeoning field of research and application. In order to optimize genome design, designers need to understand which genes are essential, which are optimal for growth, and locations in the genome that will be tolerated by the organism when inserting engineered cassettes. We present a pan-genome based method for the identification of core regions in a genome that are strongly conserved at the species level. We show that these core regions are very likely to contain all or almost all essential genes. We assert that synthetic engineers should avoid deleting or inserting into these core regions unless they understand and are manipulating the function of the genes in that region. Similarly, if the designer wishes to streamline the genome, non-core regions and in particular low penetrance genes would be good targets for deletion. Care should be taken to remove entire cassettes with similar penetrance of the genes within cassettes as they may harbor toxin/antitoxin genes which need to be removed in tandem. The bioinformatic approach introduced here saves considerable time and effort relative to knockout studies on single isolates of a given species and captures a broad understanding of the conservation of genes that are core to a species. ImportanceThe pan-genome approach presented in this paper can be used to determine core regions of a genome and has many possible applications. Synthetic engineering design can be informed by which genes/regions are more conserved (core) versus less conserved. The level of conservation of adjacent non-core genes tends to define cassettes of genes which may be part of a pathway or system that can inform researchers about possible functional significance. The pattern of gene presence across the different genomes of a species can inform the understanding of evolution and horizontal gene acquisition. The approach saves considerable time and effort relative to laboratory methods used to identify essential genes in species.