Ecological modelling approaches for predicting emergent properties in microbial communities.

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Serval ID
serval:BIB_9CB7EA70CD91
Type
Article: article from journal or magazin.
Publication sub-type
Review (review): journal as complete as possible of one specific subject, written based on exhaustive analyses from published work.
Collection
Publications
Institution
Title
Ecological modelling approaches for predicting emergent properties in microbial communities.
Journal
Nature ecology & evolution
Author(s)
van den Berg N.I., Machado D., Santos S., Rocha I., Chacón J., Harcombe W., Mitri S., Patil K.R.
ISSN
2397-334X (Electronic)
ISSN-L
2397-334X
Publication state
Published
Issued date
07/2022
Peer-reviewed
Oui
Volume
6
Number
7
Pages
855-865
Language
english
Notes
Publication types: Journal Article ; Review
Publication Status: ppublish
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.
Keywords
Microbiota, Models, Biological, Models, Theoretical
Pubmed
Web of science
Create date
23/05/2022 12:39
Last modification date
18/07/2022 5:35
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