Understanding how microbiomes influence the systems they inhabit

• Published in: Nature microbiology Vol. 3; no. 9; pp. 977 - 982
• Main Authors: Hall, Ed K., Bernhardt, Emily S., Bier, Raven L., Bradford, Mark A., Boot, Claudia M., Cotner, James B., del Giorgio, Paul A., Evans, Sarah E., Graham, Emily B., Jones, Stuart E., Lennon, Jay T., Locey, Kenneth J., Nemergut, Diana, Osborne, Brooke B., Rocca, Jennifer D., Schimel, Joshua P., Waldrop, Mark P., Wallenstein, Matthew D.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01-09-2018; Nature Publishing Group
• Subjects: 631/326/171; 631/326/2565/2134; 631/326/2565/855; 631/326/47; Biomedical and Life Sciences; Infectious Diseases; Life Sciences; Medical Microbiology; Microbiology; Microbiomes; Parasitology; Review Article; Virology
• ISSN: 2058-5276; 2058-5276
• DOI: 10.1038/s41564-018-0201-z

Translating the ever-increasing wealth of information on microbiomes (environment, host or built environment) to advance our understanding of system-level processes is proving to be an exceptional research challenge. One reason for this challenge is that relationships between characteristics of microbiomes and the system-level processes that they influence are often evaluated in the absence of a robust conceptual framework and reported without elucidating the underlying causal mechanisms. The reliance on correlative approaches limits the potential to expand the inference of a single relationship to additional systems and advance the field. We propose that research focused on how microbiomes influence the systems they inhabit should work within a common framework and target known microbial processes that contribute to the system-level processes of interest. Here, we identify three distinct categories of microbiome characteristics (microbial processes, microbial community properties and microbial membership) and propose a framework to empirically link each of these categories to each other and the broader system-level processes that they affect. We posit that it is particularly important to distinguish microbial community properties that can be predicted using constituent taxa (community-aggregated traits) from those properties that cannot currently be predicted using constituent taxa (emergent properties). Existing methods in microbial ecology can be applied to more explicitly elucidate properties within each of these three categories of microbial characteristics and connect them with each other. We view this proposed framework, gleaned from a breadth of research on environmental microbiomes and ecosystem processes, as a promising pathway with the potential to advance discovery and understanding across a broad range of microbiome science.
This Review Article discusses the importance of considering known microbial processes to inform our understanding of the role of microbial communities in ecosystem processes, and a move away from approaches based solely on correlation analyses.