Emerging methods for genome-scale metabolic modeling of microbial communities.
genome-scale
metabolic modeling
metagenome
microbial communities
model reconstruction
systems biology
Journal
Trends in endocrinology and metabolism: TEM
ISSN: 1879-3061
Titre abrégé: Trends Endocrinol Metab
Pays: United States
ID NLM: 9001516
Informations de publication
Date de publication:
03 Apr 2024
03 Apr 2024
Historique:
received:
28
11
2023
revised:
28
02
2024
accepted:
29
02
2024
medline:
5
4
2024
pubmed:
5
4
2024
entrez:
4
4
2024
Statut:
aheadofprint
Résumé
Genome-scale metabolic models (GEMs) are consolidating as platforms for studying mixed microbial populations, by combining biological data and knowledge with mathematical rigor. However, deploying these models to answer research questions can be challenging due to the increasing number of available computational tools, the lack of universal standards, and their inherent limitations. Here, we present a comprehensive overview of foundational concepts for building and evaluating genome-scale models of microbial communities. We then compare tools in terms of requirements, capabilities, and applications. Next, we highlight the current pitfalls and open challenges to consider when adopting existing tools and developing new ones. Our compendium can be relevant for the expanding community of modelers, both at the entry and experienced levels.
Identifiants
pubmed: 38575441
pii: S1043-2760(24)00062-6
doi: 10.1016/j.tem.2024.02.018
pii:
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of interests The authors declare no conflicts of interest.