Identification of microbial metabolic functional guilds from large genomic datasets

Heterotrophic microbes play an important role in the Earth System as key drivers of major biogeochemical cycles. Specifically, the consumption rate of organic matter is set by the interaction between diverse microbial communities and the chemical and physical environment in which they reside. Modeling these dynamics requires reducing the complexity of microbial communities and linking directly with biogeochemical functions. Microbial metabolic functional guilds provide one approach for reducing microbial complexity and incorporating microbial biogeochemical functions into models. However, we lack a way to identify these guilds. In this study, we present a method for defining metabolic functional guilds from annotated genomes, which are derived from both uncultured and cultured organisms. This method utilizes an Aspect Bernoulli (AB) model and was tested on three large genomic datasets with 1,733–3,840 genomes each. Ecologically relevant microbial metabolic functional guilds were identified including guilds related to DMSP degradation, dissimilatory nitrate reduction to ammonia, and motile copiotrophy. This method presents a way to generate hypotheses about functions co-occurring within individual microbes without relying on cultured representatives. Applying the concept of metabolic functional guilds to environmental samples will provide new insight into the role that heterotrophic microbial communities play in setting rates of carbon cycling