Derek Skillings

Lynch et al., in an article in this issue, argue that an entire microbiome is rarely, if ever, the right target of analysis for causal explanations in microbiome research. They argue, using interventionist criteria of proportionality, specificity and stability, for restricting causal claims to the smallest subset of microbes—a causal core—that generate the effect of interest. A further question remains: what kind of interactions generate a consortium of microbes that can operate as causal agents in this manner? Here I introduce two possible kinds of such consortia: ‘trojan horses’ and ‘syntrophic’ individuals.

Lynch et al., in an article in this issue, argue that an entire microbiome is rarely, if ever, the right target of analysis for causal explanations in microbiome research. They argue, using interventionist criteria of proportionality, specificity and stability, for restricting causal claims to the smallest subset of microbes—a causal core—that generate the effect of interest. A further question remains: what kind of interactions generate a consortium of microbes that can operate as causal agents in this manner? Here I introduce two possible kinds of such consortia: ‘trojan horses’ and ‘syntrophic’ individuals.

. Early microbiome research found numerous associations between microbial community patterns and host physiological states. These findings hinted at community-level explanations. “Top-down” experiments, working with whole communities, strengthened these explanatory expectations. Now, “bottom-up” mechanism-seeking approaches are dissecting communities to focus on specific microbes carrying out particular biochemical activities. To understand the interplay between methodological and explanatory scales, we examine claims of “dysbiosis,” when host illness is proposed as the consequence of a community state. Our analysis concludes with general observations about how methodologies relate to explanations, and the implications for microbiome research.

It is now widely accepted that microorganisms play many important roles in the lives of plants and animals. Every macroorganism has been shaped in some way by microorganisms. The recognition of the ubiquity and importance of microorganisms has led some to argue for a revolution in how we understand biological individuality and the primary units of natural selection. The term “holobiont” was introduced as a name for the biological unit made up by a host and all of its associated microorganisms, and much of this new debate about biological individuality has focused on whether holobionts are integrated individuals or communities. In this paper, I show how parts of the holobiont can span both characterizations. I argue that most holobionts share more affinities with communities than they do with organisms, and that, except for maybe in rare cases, holobionts do not meet the criteria for being organisms, evolutionary individuals, or units of selection.

Biological processes are often explained by identifying the underlying mechanisms that generate a phenomenon of interest. I characterize a basic account of mechanistic explanation and then present three challenges to this account, illustrated with examples from molecular biology. The basic mechanistic account is insufficient for explaining nonsequential and nonlinear dynamic processes, is insufficient for explaining the inherently stochastic nature of many biological mechanisms, and fails to give a proper framework for analyzing organization. I suggest that biological processes are best approached as a multidimensional gradient—with some processes being paradigmatic cases of mechanisms and some being marginal cases