We argue that microbiome research should be more reflective on the methods that it relies on to build its datasets due to the danger of facing a methodological problem which we call “epistemic misalignment.” An epistemic misalignment occurs when the method used to answer specific scientific questions does not track justified answers, due to the material constraints imposed by the very method. For example, relying on 16S rRNA to answer questions about the function of the microbiome generates epistemic misalignments, due (...) to the different temporal scales that 16S rRNA provides information about and the temporal scales that are required to know about the functionality of some microorganisms. We show how some of these exist in contemporary microbiome science and urge microbiome scientists to take some measures to avoid them, as they may question the credibility of the field as a whole. (shrink)

A distinction between different notions of “structure” and “function” is suggested for interpreting the overwhelming amount of data on microbiome structure and function. Sequence data, biochemical agents, interaction networks, taxonomic communities, and their dynamics can be linked to potential or actual biochemical activities, causal roles, and selected effects, respectively. This conceptual clarification has important methodological consequences for how to interpret existing data and approach open questions in contemporary microbiome research practice. In particular, the field will have to start thinking about (...) notions of function more directly. Also see the video abstract here https://youtu.be/j5pq5uGld1k. (shrink)