Applying causal reasoning to investigate multicausality in microbial systems

• Published in: Ecosphere (Washington, D.C) D.C), 2024-05, Vol.15 (5), p.n/a
• Main Authors: Potter, Teal S., Zalewski, Zachary, Miao, Max, Allsup, Cassandra, Thompson, Kathleen M., Hayden, Daniel, George, Isabelle, Lankau, Richard A., Lankau, Emily W.
• Format: Article
• Language: English
• Subjects: Academic disciplines; animal ecology; Bradford Hill criteria; carbon; Carbon cycle; Case studies; Causality; causation; Ecological function; Ecologists; Ecology; Epidemiology; experimental design; Experiments; humans; Infectious diseases; Microbial activity; microbial ecology; microbiome; multicausality; Pathogens; phylogeny; soil
• ISSN: 2150-8925; 2150-8925
• DOI: 10.1002/ecs2.4782

Microbial communities contribute to many essential ecological functions, from carbon cycling in soil to healthy functioning of the human body. Yet, determining how the make‐up of microbial communities is causally linked to a particular function remains a huge challenge. Despite improved tools for characterizing microbiomes at increasingly finer phylogenetic and functional scales, researchers are still unable to perform direct experimental hypothesis testing as is performed in plant and animal ecology. However, microbial ecology is not the only scientific field tasked with drawing firm causal inferences from correlational data. Here we introduce microbial ecologists to a framework used by epidemiologists: the Bradford Hill Causal Criteria. Hill posited that as a field accrues different types of evidence to support a hypothesis, it increases confidence in claiming that the hypothesized relationship is causal. A set of nine criteria help distinguish different types of evidence. Our goal was to illustrate how these causal criteria can be used in microbial ecology to retrospectively evaluate a body of research to determine the strength of a causal claim and judge the value of future research directions. We illustrate how this framework can help researchers organize their understanding of a body of literature to reveal knowledge gaps and analytical approaches that have been underutilized. We then discuss the types of causality and illustrate how investigating multicausal systems requires an updated application of older frameworks that assume one causal agent is at play for each functional outcome. We also examine analytical approaches that are appropriate for distinguishing the types of causality.