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Ecological modelling approaches for predicting emergent properties in microbial communities

Abstract

Recent studies have brought forward the critical role of emergent properties in shaping microbial communities and the ecosystems of which they are a part. Emergent properties—patterns or functions that cannot be deduced linearly from the properties of the constituent parts—underlie important ecological characteristics such as resilience, niche expansion and spatial self-organization. While it is clear that emergent properties are a consequence of interactions within the community, their non-linear nature makes mathematical modelling imperative for establishing the quantitative link between community structure and function. As the need for conservation and rational modulation of microbial ecosystems is increasingly apparent, so is the consideration of the benefits and limitations of the approaches to model emergent properties. Here we review ecosystem modelling approaches from the viewpoint of emergent properties. We consider the scope, advantages and limitations of Lotka–Volterra, consumer–resource, trait-based, individual-based and genome-scale metabolic models. Future efforts in this research area would benefit from capitalizing on the complementarity between these approaches towards enabling rational modulation of complex microbial ecosystems.

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Fig. 1: Examples of emergent properties arising from community complexity.
Fig. 2: Model types commonly used for studying emergent properties of microbial communities.
Fig. 3: Choosing a suitable modelling approach.

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Acknowledgements

This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant no. 866028) and from the UK Medical Research Council (project no. MC_UU_00025/11). S.M. thanks the Swiss National Science Foundation for funding the Swiss National Centre of Competence in Research Microbiomes and an Eccellenza project and the ERC for starting grant no. 715097. W.H. received funding from the National Institutes of Health through grant no. R01-GM121498. S.S. received funding from the Portuguese Foundation for Science and Technology under the scope of a PhD grant (no. SFRH/BD/121695/2016) and the strategic funding of the UIDB/04469/2020 unit.

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N.I.V.D.B. conceived the review, carried out the literature survey and wrote the manuscript. D.M., S.S. and I.R. contributed to the section on the genome-scale metabolic models. J.C., W.H. and S.M. helped with the literature survey and contributed to the manuscript structuring and writing. K.R.P. conceived the review, helped with the literature survey and wrote the manuscript.

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Correspondence to Kiran R. Patil.

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van den Berg, N.I., Machado, D., Santos, S. et al. Ecological modelling approaches for predicting emergent properties in microbial communities. Nat Ecol Evol 6, 855–865 (2022). https://doi.org/10.1038/s41559-022-01746-7

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