Comparative whole-genome approach to identify traits underlying microbial interactions

Abstract

ABSTRACTInteractions among microorganisms affect the structure and function of microbial communities, potentially affecting ecosystem health and biogeochemical cycles. The functional traits mediating microbial interactions are known for several model organisms, but the prevalence of these traits across microbial diversity is unknown. We developed a new genomic approach to systematically explore the occurrence of metabolic functions and specific interaction traits, and applied it to 473 sequenced genomes from marine bacteria. The bacteria could be divided into coherent genome functional clusters (GFCs), some of which are consistent with known bacterial ecotypes (e.g. within pico-Cyanobacteria andVibriotaxa) while others suggest new ecological units (e.g.Marinobacter,AlteromonasandPseudoalteromonas). Some traits important for microbial interactions, such as the production of and resistance towards antimicrobial compounds and the production of phytohormones, are widely distributed among the GFCs. Other traits, such as the production of siderophores and secretion systems, as well as the production and export of specific B vitamins, are less common. Linked Trait Clusters (LTCs) include traits that may have evolved together, for example chemotaxis, motility and adhesion are linked with regulatory systems involved in virulence and biofilm formation. Our results highlight specific GFCs, such as those comprising Alpha- and Gammaproteobacteria, as particularly poised to interact both synergistically and antagonistically with co-occurring bacteria and phytoplankton. Similar efficient processing of multidimensional microbial information will be increasingly essential for translating genomes into ecosystem understanding across biomes, and identifying the fundamental rules that govern community dynamics and assembly.