Stochastic microbiome assembly depends on context


Individuals are constantly exposed to microbial organisms that may or may not colonize their gut microbiome, and newborns assemble their microbiomes through a number of these acquisition events. Since microbiome composition has been shown to influence host physiology, a mechanistic understanding of community assembly has potentially therapeutic applications. In this article, we investigate microbiome acquisition in a highly controlled setting using germ-free fruit flies inoculated with specific bacterial species at known abundances. Our approach revealed that acquisition events are stochastic and that the probabilities of colonization of different species in different contexts encode ecological information about the interactions. These findings have implications for microbiome-based therapies like faecal microbiota transplantation that attempt to alter a person’s gut microbiome by deliberately introducing foreign microbes.


Observational studies reveal substantial variability in microbiome composition between individuals. Targeted studies in gnotobiotic animals highlight this variability by showing that some bacterial strains colonize deterministically, while others colonize stochastically. Although some of this variability can be explained by external factors such as environmental, dietary and genetic differences between individuals, in this paper we show that for the model organism Drosophila melanogaster, interactions between bacteria can affect the process of microbiome assembly, contributing to a baseline level of microbiome variability even among isogenic organisms that are reared, housed, and fed identically. In germ-free flies fed known combinations of bacterial species, we find that some species colonize more frequently than others, even when fed at the same high concentration. We are developing an ecological technique that infers the presence of interactions between bacterial species based on their probabilities of colonization in different contexts, requiring only presence/absence data from two-species experiments. We use a stepwise sequence of probabilistic models, in which colonization of each bacterial species is treated as an independent stochastic process, to reproduce empirical distributions of colonization outcomes across experiments. We find that incorporating context-dependent interactions significantly improves model performance. Stochastic and context-dependent microbiome assembly underpins clinical therapies such as faecal microbiota transplantation and probiotic administration and should inform the design of synthetic faecal transplantations and dosing regimens.


    • Accepted January 10, 2022.
  • Author contributions: research designed by EWJ, JMC, DAS and WBL; EWJ did some research; EWJ provided new analytical reagents/tools; WBL provided data; EWJ analyzed the data; EWJ wrote the paper; and EWJ, JMC, DAS and WBL edited the article.

  • The authors declare no competing interests.

  • This article is a direct PNAS submission.

  • This article contains additional information online at

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