Diversity, Stability, and Reproducibility in Stochastically Assembled Microbial Ecosystems

Goyal, Akshit; Maslov, Sergei

doi:10.1103/physrevlett.120.158102

Cited by 86 publications

(109 citation statements)

References 28 publications

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“…Ref. 57 , where it was employed to describe the colonization dynamics of an ecosystem with cross-feeding). In the case of non-substitutable essential resources of two (or more) types, that is the subject of this study, this simple rule is replaced with the following two competitive exclusion rules:…”

Section: Model and Resultsmentioning

confidence: 99%

Alternative stable states in a model of microbial community limited by multiple essential nutrients

Dubinkina

Fridman²,

Pandey³

et al. 2018

Preprint

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Microbial communities routinely have several alternative stable states observed for the same environmental parameters. Sudden and irreversible transitions between these states make external manipulation of these systems more complicated. To better understand the mechanisms and origins of multistability in microbial communities, we introduce and study a model of a microbial ecosystem colonized by multiple specialist species selected from a fixed pool. Growth of each species can be limited by essential nutrients of two types, e.g. carbon and nitrogen, each represented in the environment by multiple metabolites. We demonstrate that our model has an exponentially large number of potential stable states realized for different environmental parameters. Using game theoretical methods adapted from the stable marriage problem we predict all of these states based only on ranked lists of competitive abilities of species for each of the nutrients. We show that for every set of nutrient influxes, several mutually uninvadable stable states are generally feasible and we distinguish them based upon their dynamic stability. We further explore an intricate network of discontinuous transitions (regime shifts) between these alternative states both in the course of community assembly, or upon changes of nutrient influxes.

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Section: Model and Resultsmentioning

confidence: 99%

Alternative stable states in a model of microbial community limited by multiple essential nutrients

Dubinkina

Fridman²,

Pandey³

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Some considered special cases when the system parameters satisfy certain constraints [2,18]. The rest considered aspects such as cross-feeding [19][20][21], toxin [22], rock-paper-scissors relation [23,24,26], complex interactions [24][25][26] or co-evolution [27], etc. (see SI Sec.II.A for details).…”

Section: Introductionmentioning

confidence: 99%

Overcome Competitive Exclusion in Ecosystems

Wang

Liu

2020

iScience

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Explaining biodiversity in nature is a fundamental problem in ecology. An outstanding challenge is embodied in the so-called Competitive Exclusion Principle: two species competing for one limiting resource cannot coexist at constant population densities, or more generally, the number of consumer species in steady coexistence cannot exceed that of resources. The fact that competitive exclusion is rarely observed in natural ecosystems has not been fully understood. Here we show that by forming chasing triplets among the consumers and resources in the consumption process, the Competitive Exclusion Principle can be naturally violated. The modeling framework developed here is broadly applicable and can be used to explain the biodiversity of many consumer-resource ecosystems and hence deepens our understanding of biodiversity in nature.I.

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“…Furthermore, we find that the quadratic SSI model, usually called the "generalized Lotka-Volterra (gLV) model", is not capable of recapitulating the entire set of pair and trio growth outcomes using a single parameterization. Although the gLV model may be useful when fit to whole communities [19,20,21], our work suggests that this model lacks the necessary complexity to be predictive when built from building blocks assumed to be universal.Alternatively, the microbiome can be modeled by species-metabolite interaction (SMI) models, which are constructed using the interactions of individual microbes with a shared metabolite pool [28,29,30,14,11]. SMI models follow from networks which include both microbiota and metabolites, which may be inferred from literature [30] or from genome-scale metabolic networks [31].…”

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confidence: 99%

Metabolite-mediated modelling of microbial community dynamics captures emergent behaviour more effectively than species–species modelling

Brunner

Chia

2019

J. R. Soc. Interface.

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Personalized models of the gut microbiome are valuable for disease prevention and treatment. For this, one requires a mathematical model that predicts microbial community composition and the emergent behaviour of microbial communities. We seek a modelling strategy that can capture emergent behaviour when built from sets of universal individual interactions. Our investigation reveals that species–metabolite interaction (SMI) modelling is better able to capture emergent behaviour in community composition dynamics than direct species–species modelling. Using publicly available data, we examine the ability of species–species models and species–metabolite models to predict trio growth experiments from the outcomes of pair growth experiments. We compare quadratic species–species interaction models and quadratic SMI models and conclude that only species–metabolite models have the necessary complexity to explain a wide variety of interdependent growth outcomes. We also show that general species–species interaction models cannot match the patterns observed in community growth dynamics, whereas species–metabolite models can. We conclude that species–metabolite modelling will be important in the development of accurate, clinically useful models of microbial communities.

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Diversity, Stability, and Reproducibility in Stochastically Assembled Microbial Ecosystems

Cited by 86 publications

References 28 publications

Alternative stable states in a model of microbial community limited by multiple essential nutrients

Alternative stable states in a model of microbial community limited by multiple essential nutrients

Overcome Competitive Exclusion in Ecosystems

Metabolite-mediated modelling of microbial community dynamics captures emergent behaviour more effectively than species–species modelling

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