Uncovering microbial life-history strategies under disturbance: a trait-based computational analysis of anaerobic systems

Abstract

Trait-based approaches are helpful in simplifying ecosystem complexity to explore disturbance-diversity-function relationships. These frameworks classify organisms based on their functional characteristics--traits that influence growth, survival and reproduction--providing a mechanistic basis to understand how communities respond to changes in their environment. The application of these approaches has been successful in ecology, but to date has only been tested in a few microbial ecosystems, namely, soil microbial communities and aerobic bioreactors treating wastewater. Here, we employed Grimes competitor-stress-tolerant-ruderal framework in replicated mesophilic anaerobic bioreactors exposed to a disturbance (biomass removal) with varied frequencies at a constant number of disturbance events for 90 days. Bioreactors were inoculated with sludge from full-scale anaerobic digesters and fed with a mixture of primary and waste activated sludge. A genome-resolved metagenomics approach was utilised to assess the microbial communities. We found that communities across the disturbance range were clustered into three groups, suggesting the adoption of a three-way life-history strategy. This study demonstrates, for the first time, the applicability of trait-based life-history strategies in anaerobic microbial systems under disturbance, providing a new perspective for understanding and managing microbial ecosystems under disturbance conditions.