Contribution of genome-scale metabolic modelling to niche theory.

Antoine Régimbeau, Marko Budinich, Abdelhalim Larhlimi, Juan José Pierella Karlusich, Olivier Aumont, Laurent Memery, Chris Bowler, Damien Eveillard

Journal: Ecology letters 2022;25(6):1352-1364

PMID: 35384214

Abstract

Standard niche modelling is based on probabilistic inference from organismal occurrence data but does not benefit yet from genome-scale descriptions of these organisms. This study overcomes this shortcoming by proposing a new conceptual niche that resumes the whole metabolic capabilities of an organism. The so-called metabolic niche resumes well-known traits such as nutrient needs and their dependencies for survival. Despite the computational challenge, its implementation allows the detection of traits and the formal comparison of niches of different organisms, emphasising that the presence-absence of functional genes is not enough to approximate the phenotype. Further statistical exploration of an organism's niche sheds light on genes essential for the metabolic niche and their role in understanding various biological experiments, such as transcriptomics, paving the way for incorporating better genome-scale description in ecological studies.

© 2022 The Authors. Ecology Letters published by John Wiley & Sons Ltd.

Address: Université de Nantes, CNRS, LS2N, Nantes, France.; Département de Biologie, Institut de Biologie de l'ENS, École Normale supérieure, CNRS, INSERM, Université PSL, Paris, France.; Laboratoire d'Océanographie et du Climat: Expérimentations et Approches Numériques (LOCEAN), IRD-IPSL, Paris, France.; Université de Brest (UBO), CNRS, IRD, Ifremer, Laboratoire des Sciences de l'Environnement Marin, Plouzané, France.; Département de Biologie, Institut de Biologie de l'ENS, École Normale supérieure, CNRS, INSERM, Université PSL, Paris, France.; Research Federation for the study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GO-SEE, Paris, France.; Université de Nantes, CNRS, LS2N, Nantes, France.; Research Federation for the study of Global Ocean Systems Ecology and Evolution, FR2022/Tara GO-SEE, Paris, France.

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MeSH Terms: Ecosystem, Phenotype
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