Laboratoire Matière et Systèmes Complexes

Emergent Simplicity in Microbial Communities

Pankaj Mehta

A major unresolved question in microbiome research is whether the complex ecological patterns observed in surveys of natural communities can be explained and predicted by fundamental, quantitative principles. Bridging theory and experiment is hampered by the multiplicity of ecological processes that simultaneously affect community assembly and a lack of theoretical tools for modeling diverse ecosystems. In the first part of the talk, I will present a simple ecological model of microbial communities that can predict and reproduce large-scale ecological patterns observed across multiple natural and laboratory settings (Science 2018; Scientific Reports 2020; PLoS One 2021; PRE 2019; American Naturalist in press). Surprisingly, our model works despite having a “random” metabolisms and “random” taxonomical structure. This raises the natural of question of why random ecosystems can describe real-world experimental data. In the second, more theoretical part of the talk, I will answer this question by using methods from statistical physics (Cavity Method, Random Matrix Theory) to show that when a community becomes diverse enough, it will always self-organize into a stable state whose properties are well captured by a “typical random ecosystems”. This phase transition to typicality suggests that the ecological patterns observed in nature maybe generic, emergent properties of diverse microbial communities, explaining their ubiquity in natural microbiomes.