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Multi-dimensional experimental and computational exploration of metabolism pinpoints complex probiotic interactions

Zampieri, Guido; Efthimiou, Georgios; Angione, Claudio

Authors

Guido Zampieri

Claudio Angione



Abstract

Multi-strain probiotics are widely regarded as effective products for improving gut microbiota stability and host health, providing advantages over single-strain probiotics. However, in general, it is unclear to what extent different strains would cooperate or compete for resources, and how the establishment of a common biofilm microenvironment could influence their interactions. In this work, we develop an integrative experimental and computational approach to comprehensively assess the metabolic functionality and interactions of probiotics across growth conditions. Our approach combines co-culture assays with genome-scale modelling of metabolism and multivariate data analysis, thus exploiting complementary data- and knowledge-driven systems biology techniques. To show the advantages of the proposed approach, we apply it to the study of the interactions between two widely used probiotic strains of Lactobacillus reuteri and Saccharomyces boulardii, characterising their production potential for compounds that can be beneficial to human health. Our results show that these strains can establish a mixed cooperative-antagonistic interaction best explained by competition for shared resources, with an increased individual exchange but an often decreased net production of amino acids and short-chain fatty acids. Overall, our work provides a strategy that can be used to explore microbial metabolic fingerprints of biotechnological interest, capable of capturing multifaceted equilibria even in simple microbial consortia.

Citation

Zampieri, G., Efthimiou, G., & Angione, C. (2023). Multi-dimensional experimental and computational exploration of metabolism pinpoints complex probiotic interactions. Metabolic Engineering, 76, 120-132. https://doi.org/10.1016/j.ymben.2023.01.008

Journal Article Type Article
Acceptance Date Jan 21, 2023
Online Publication Date Jan 28, 2023
Publication Date Mar 1, 2023
Deposit Date Mar 13, 2023
Publicly Available Date Mar 13, 2023
Journal Metabolic Engineering
Print ISSN 1096-7176
Electronic ISSN 1096-7184
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 76
Pages 120-132
DOI https://doi.org/10.1016/j.ymben.2023.01.008
Keywords Probiotics; Metabolic modelling; Biofilms; Microbial interactions; Multivariate analysis
Public URL https://hull-repository.worktribe.com/output/4234179

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