Stability and diversity of interactions in complex microbiomes

Complex microbial communities abound in nature, yet designing robust and stable microbial consortia for use in biotechnology and One Health applications remains a major challenge. Inspired by a large body of work on community ecology, we used mathematical models to investigate what makes a microbiome stable. Our approach integrates three factors that characterize many free-living and host-associated microbial communities but have seldom been jointly considered: sustained growth, high-order interactions, and a broad diversity of interaction profiles. We derived a simple expression that relates community stability to basic statistical properties of the underlying interaction networks. Analytical and numerical results show that synergistic high-order interactions, such as those derived from complex auxotrophies, play a critical role in stabilizing species-rich microbial communities with highly diverse interaction profiles. In contrast, in the absence of high-order interactions, viability is restricted to communities with very sparse or fully mutualistic interaction networks. Our findings have the potential to inform microorganism-based interventions in areas in which sustained growth and long-term stability are desirable properties. We propose that incorporating high-order mutualism into engineered microbial consortia could improve their robustness by buffering design uncertainty about the underlying interaction networks.