Metabolome-Proteome Differentiation Coupled to Microbial Divergence

Abstract

ABSTRACT Tandem high-throughput proteomics and metabolomics were employed to functionally characterize natural microbial biofilm communities. Distinct molecular signatures exist for each analyzed sample. Deconvolution of the high-resolution molecular data demonstrates that identified proteins and detected metabolites exhibit organism-specific correlation patterns. These patterns are reflective of the functional differentiation of two bacterial species that share the same genus and that co-occur in the sampled microbial communities. Our analyses indicate that the two species have similar niche breadths and are not in strong competition with one another. IMPORTANCE Natural microbial assemblages represent dynamic consortia that exhibit extensive complexity at all levels. In the present study, we demonstrate that correlations between protein and metabolite abundances allow the deconvolution of complex molecular data sets into shared and organism-specific contingents. We demonstrate that evolutionary divergence is associated with the restructuring of cellular metabolic networks, which in turn allows bacterial species to occupy distinct ecological niches. The apparent lack of interspecific competition may explain the extensive population-level genetic heterogeneity observed extensively within microbial communities. The reported findings have broad implications for the in-depth investigation of the ecology and evolution of distinct microbial community members and for leveraging the solution of cryptic metabolic processes in the future.