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Contribution of genome‐scale metabolic modelling to niche theory
Author(s) -
Régimbeau Antoine,
Budinich Marko,
Larhlimi Abdelhalim,
Pierella Karlusich Juan José,
Aumont Olivier,
Memery Laurent,
Bowler Chris,
Eveillard Damien
Publication year - 2022
Publication title -
ecology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.852
H-Index - 265
eISSN - 1461-0248
pISSN - 1461-023X
DOI - 10.1111/ele.13954
Subject(s) - niche , organism , ecological niche , biology , genome , ecology , model organism , computational biology , inference , environmental niche modelling , evolutionary biology , scale (ratio) , gene , computer science , genetics , geography , habitat , artificial intelligence , cartography
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.