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Revealing interactions between microbes, metabolites, and dietary compounds using genome-scale analysis

生物 微生物生态学 计算生物学 微生物代谢 变化(天文学) 系统生物学 生物信息学 肠道微生物群 生态学 生物化学 冗余(工程) 外温 微生物群 基因组 新陈代谢 肠道菌群 肠道细菌 生物技术
作者
Tong Wang,Benjamin M. Gyori,Scott T. Weiss,Giulia Menichetti,Yang-Yu Liu
出处
期刊:Microbiome [BioMed Central]
卷期号:14 (1)
标识
DOI:10.1186/s40168-025-02312-6
摘要

The role of gut microbiome in predicting diet response and developing personalized dietary recommendations has been increasingly recognized. Yet, we still lack comprehensive, genome-based insights into which gut microbes metabolize specific dietary compounds. Here, we leveraged the metabolic networks constructed from well-annotated microbial genomes to characterize the potential interactions between microbes and metabolites, specifically emphasizing the interactions between microbes and dietary compounds. We revealed a substantial, approximately fourfold variation in both the number of metabolites and dietary compounds in the microbial genome-scale metabolic networks across different genera, whereas species within the same genus showed a high metabolic similarity (mean coefficient of variation in microbial network degree $$\overline{CV }$$ = 0.023 for metabolites and 0.015 for dietary compounds). We found that the number of species that can utilize a metabolite drastically varies, ranging from 1 to 818 species, with some metabolites being used by a wide range of species (211 out of 1390 metabolites used by more than 95% of species) and others only by a few species (435 metabolites used by less than 5% of species). Leveraging a longitudinal microbiome study, we observed that microbial taxa with similar metabolic capacity tend to have positively correlated abundances, and the gut microbiome’s capacity to process dietary compounds is functionally stable. Finally, we propose a network-based method to identify the dietary compounds that are specific to no more than 10 microbial species, offering a new strategy for combining a dietary compound and its linked microbial species to design synbiotics. Our results quantitatively reveal large-scale variation and redundancy in gut microbial metabolism and identify dietary compounds linked to only a few microbial species. These findings improve understanding of microbe-metabolite interactions and provide a foundation for the rational design of microbiome-based interventions for healthy benefits.
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