Spatial microbial community dynamics using a continuous species interaction model
2021
Comprehending the assembly and maintenance of microbial diversity in natural communities, despite the abundance of antagonistic interactions, is a major problem of interest in biology. A common framework to study the problem is through cyclic dominance games over pairwise interactions. Recent papers incorporating higher-order interactions in these models have successfully explained high diversity of microbes, especially in communities where antibiotic producing, sensitive, and resistant strains co-exist. But most of these models are based on a small number of discrete species, assume a notion of pure cyclic dominance, and focus on low mutation rate regimes, none of which best represents the highly interlinked, quickly evolving and continuous nature of microbial phenotypic space. Here, we present a model of species in a continuous space, with mutual higher order interactions, to examine the assembly and stability of microbial communities. Specifically, we focus on toxin production, vulnerability, and inhibition among the simulated species. We observe intricate interaction between certain parameters that generates highly divergent patterns of diversity and spatial community dynamics. We find that spatial properties are better predicted by species interaction constraints rather than mobility, and that community formation time, mobility, and mutation rate best explain the patterns of diversity. Significance StatementUnderstanding the assembly and maintenance of diverse microbial communities in nature is a question of great interest to theoretical biologists. Previous works, utilizing evolutionary game theory and other techniques, have explained the role of higher order interactions for the coexistence of diverse microbes in different kinds of environments. But these models are usually based on a small number of discrete species and low//no mutation rate, which is not how many natural microbial communities function. In this work, we explore a new framework which incorporates a continuous species model along with a wide range of mutation rates to comprehend the process of microbial community formation.
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