Trait-based patterns of microbial dynamics in dormancy potential and heterotrophic strategy: case studies of resource-based and post-press succession
This work is published.
Kearns PJ and A Shade. 2018. Trait-based patterns of microbiome succession in dormancy and heterotrophic strategy. The ISME Journal. 12:2575–2581 https://doi.org/10.1038/s41396-018-0194-x
Understanding the relationship between microbial community structure and function is a major challenge in microbial ecology. Recent work has shown that community weighted mean 16S rRNA gene copies, as a proxy for heterotrophic growth strategy, is a microbial community trait that decreases predictably over successional trajectories that are underpinned by changes in resource availability. However, it has been challenging to identify other microbial traits that are predictive of community functions and have consistent patterns with succession. Trait-based patterns of secondary succession (e.g., after a disturbance) are less often considered, and these responses may be underpinned by abiotic drivers other than changes in resources. In this perspectives piece, we present hypotheses about microbial traits important for microbial succession in resource-based and post-press disturbance scenarios, as synthesized from previous works and extended within this work. Using four case studies, we compare two traits, heterotrophic strategy and dormancy potential, and two different types of succession, resource-based (endogenous heterotrophic) and post-press. There were decreases in weighted ribosomal operon counts and in dormancy genes over resource-based succession. Both traits also were lower in post-press succession as compared to reference conditions, but increased with time from disturbance. Thus, dormancy potential may be an additional trait that changes predictably with succession. Finally, considering changes in microbial community traits over post-press succession is as important as over resource-based succession. These patterns need to be interpreted carefully and reference and recovering samples can be collected to improve interpretation of changes in community traits over post-press succession.
This study was supported in part by the Michigan State University, the Michigan State Plant Resilience Institute, the US Department of Energy Joint Genome Institute’s Community Science Project #1834, the National Science Foundation DEB #1749544 and the Michigan State University computational resources provided by the Institute for Cyber-Enabled Research. The work conducted by the U.S. Department of Energy Joint Genome Institute, a DOE Office of Science User Facility, is supported under Contract No. DE-AC02-05CH11231.
Data analysis was performed in QIIME (v. 1.9.0), R (v. 3.4.1), and PICRUSt (Galaxy server: https://huttenhower.sph.harvard.edu/galaxy/).