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Learning beyond-pairwise interactions enables the bottom-up prediction of microbial community structure.

ABSTRACT: Understanding the assembly of multispecies microbial communities represents a significant challenge in ecology and has wide applications in agriculture, wastewater treatment, and human healthcare domains. Traditionally, studies on the microbial community assembly focused on analyzing pairwise relationships among species; however, neglecting higher-order interactions, i.e., the change of pairwise relationships in the community context, may lead to substantial deviation from reality. Herein, we have proposed a simple framework that incorporates higher-order interactions into a bottom-up prediction of the microbial community assembly and examined its accuracy using a seven-member synthetic bacterial community on a host plant, duckweed. Although the synthetic community exhibited emergent properties that cannot be predicted from pairwise coculturing results, our results demonstrated that incorporating information from three-member combinations allows the acceptable prediction of the community structure and actual interaction forces within it. This reflects that the occurrence of higher-order effects follows consistent patterns, which can be predicted even from trio combinations, the smallest unit of higher-order interactions. These results highlight the possibility of predicting, explaining, and understanding the microbial community structure from the bottom-up by learning interspecies interactions from simple beyond-pairwise combinations.

SUBMITTER: Ishizawa H

PROVIDER: S-EPMC10873592 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

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Learning beyond-pairwise interactions enables the bottom-up prediction of microbial community structure.

Ishizawa Hidehiro H Tashiro Yosuke Y Inoue Daisuke D Ike Michihiko M Futamata Hiroyuki H

Proceedings of the National Academy of Sciences of the United States of America 20240205 7

Understanding the assembly of multispecies microbial communities represents a significant challenge in ecology and has wide applications in agriculture, wastewater treatment, and human healthcare domains. Traditionally, studies on the microbial community assembly focused on analyzing pairwise relationships among species; however, neglecting higher-order interactions, i.e., the change of pairwise relationships in the community context, may lead to substantial deviation from reality. Herein, we ha ...[more]

PMID: 38315845

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Project description:Humans have used high salinity for the production of bean-based fermented foods over thousands of years. Although high salinity can inhibit the growth of harmful microbes and select functional microbiota in an open environment, it also affects fermentation efficiency of bean-based fermented foods and has a negative impact on people's health. Therefore, it is imperative to develop novel defined starter cultures for reduced-salt fermentation in a sterile environment. Here, we explored the microbial assembly and function in the fermentation of traditional Chinese broad bean paste with 12% salinity. The results revealed that the salinity and microbial interactions together drove the dynamic of community and pointed out that five dominant genera (Staphylococcus, Bacillus, Weissella, Aspergillus, and Zygosaccharomyces) may play different key roles in different fermentation stages. Then, core species were isolated from broad bean paste, and their salinity tolerance, interactions, and metabolic characteristics were evaluated. The results provided an opportunity to validate in situ predictions through in vitro dissection of microbial assembly and function. Last, we reconstructed the synthetic microbial community with five strains (Aspergillus oryzae, Bacillus subtilis, Staphylococcus gallinarum, Weissella confusa, and Zygosaccharomyces rouxii) under different salinities and realized efficient fermentation of broad bean paste for 6 weeks in a sterile environment with 6% salinity. In general, this work provided a bottom-up approach for the development of a simplified microbial community model with desired functions to improve the fermentation efficiency of bean-based fermented foods by deconstructing and reconstructing the microbial structure and function.IMPORTANCE Humans have mastered high-salinity fermentation techniques for bean-based fermented product preparation over thousands of years. High salinity was used to select the functional microbiota and conducted food fermentation production with unique flavor. Although a high-salinity environment is beneficial for suppressing harmful microbes in the open fermentation environment, the fermentation efficiency of functional microbes is partially inhibited. Therefore, application of defined starter cultures for reduced-salt fermentation in a sterile environment is an alternative approach to improve the fermentation efficiency of bean-based fermented foods and guide the transformation of traditional industry. However, the assembly and function of self-organized microbiota in an open fermentation environment are still unclear. This study provides a comprehensive understanding of microbial function and the mechanism of community succession in a high-salinity environment during the fermentation of broad bean paste so as to reconstruct the microbial community and realize efficient fermentation of broad bean paste in a sterile environment.

Dataset Information

Learning beyond-pairwise interactions enables the bottom-up prediction of microbial community structure.

Publications

Learning beyond-pairwise interactions enables the bottom-up prediction of microbial community structure.

Similar Datasets

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