Correlations in microbial abundance data reveal host-bacteria and bacteria-bacteria interactions jointly shaping the C. elegans microbiome

Abstract

Compositional structure of host-associated microbiomes is potentially affected by interactions among the microbes and between the microbes and the host. To quantify the relative importance of these contributions to the microbiome composition and variation, here we analyze absolute abundance (count) data for a minimal eight-species native microbiome in the intestine. We find that a simple neutral model only considering migration, birth, death, and competition for space among the bacteria can capture the means and variances of bacterial abundance, but not the experimental bacteria-bacteria covariances. We find that either bacteria-bacteria interactions or correlations among bacterial population dynamics parameters induced by the host can qualitatively recapitulate the observed correlations among bacterial taxa. However, both models are underdetermined and not unique, and the combination of both mechanisms likely contributes. This highlights that single time-point measurements on their own are not sufficient to distinguish between two distinct biological mechanisms. Further, we observe that different interactions are required to explain (co)variance data in microbiota associated with different host genotypes, suggesting different community dynamics associated with these host types. Finally, we find that many of these signals are obscured when data are converted to proportions from counts, consistent with a growing literature on the limitations of compositional data for inference of population dynamics. We end with a discussion of the limitations of Lotka-Volterra type assumptions for microbial community data analysis revealed by our results. Published by the American Physical Society 2024