Comparative whole-genome approach to identify bacterial traits for microbial interactions

Abstract

<jats:title>ABSTRACT</jats:title><jats:p>Interactions among microorganisms affect the structure and function of microbial communities, with potentially far-reaching effects on 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 (e.g. the production of vitamins, siderophores, antimicrobial compounds and phytohormones), and apply this approach to 473 sequenced genomes from marine bacteria. We identify 48 coherent genome functional clusters (GFCs), that are partly consistent with known bacterial ecotypes (e.g. within pico-Cyanobacteria and <jats:italic>Vibrio</jats:italic> taxa) and identify putative new ones (e.g. <jats:italic>Marinobacter, Alteromonas</jats:italic> and <jats:italic>Pseudoalteromonas</jats:italic>). Interaction traits such as the production of and resistance towards antimicrobial compounds and the production of phytohormones are widely distributed among the GFCs, while other traits are less common (e.g. siderophores and secretion systems are found in 32% of genomes or less). Several GFCs lack the ability to produce B vitamins, suggesting that these metabolites represent essential trading goods for many bacteria. Alpha- and Gammaproteobacteria encode many interaction traits, and appear particularly poised to interact both synergistically and antagonistically with co-occurring bacteria and phytoplankton. Linked Trait Clusters (LTCs) group chemotaxis, motility and adhesion with regulatory systems involved in virulence and biofilm formation, and suggest that type-4 secretion systems may be used to inject the hormone indole acetic acid into target phytoplankton cells. Similar efficient processing and representation of multidimensional microbial functional information will be increasingly essential for translating genomes into ecosystem understanding across biomes.</jats:p>

Phototroph-heterotroph interactions during growth and long-term starvation across Prochlorococcus and Alteromonas diversity

“…Finally, both the coarse-grained ecological classification of microbial interactions (e.g. positive/negative) and the high-resolution mechanistic view obtained using advanced physiology and omics approaches are difficult to translate into quantitative, predictive models of organismal growth and decline (Antoniewicz, 2020;Gralka et al, 2020;Zoccarato et al, 2020) . Therefore, we still face fundamental challenges in interpreting and understanding the increasingly diverse and mechanistic view of microbial interactions and translating these insights into conceptual and mathematical models of cell growth and death.…”