Emerging methods for genome-scale metabolic modeling of microbial communities

Chaimaa Tarzi, Guido Zampieri, Neil Sullivan, Claudio Angione

Research output: Contribution to journalReview articlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)533-548
Number of pages16
JournalTrends in Endocrinology and Metabolism
Volume35
Issue number6
DOIs
Publication statusE-pub ahead of print - 3 Apr 2024

Bibliographical note

Publisher Copyright:
© 2024 The Author(s)

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