Linking dietary fiber to human malady through cumulative profiling of microbiota disturbance
Xin Zhang,
Huan Liu,
Yu Li,
Yanlong Wen,
Tianxin Xu,
Chen Chen,
Shuxia Hao,
Jielun Hu,
Shaoping Nie,
Fei Gao,
Gengjie Jia
Affiliations
Xin Zhang
Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen China
Huan Liu
State Key Laboratory of Food Science and Resources China‐Canada Joint Lab of Food Science and Technology (Nanchang), Key Laboratory of Bioactive Polysaccharides of Jiangxi Province, Nanchang University Nanchang China
Yu Li
Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong China
Yanlong Wen
State Key Laboratory of Food Science and Resources China‐Canada Joint Lab of Food Science and Technology (Nanchang), Key Laboratory of Bioactive Polysaccharides of Jiangxi Province, Nanchang University Nanchang China
Tianxin Xu
Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen China
Chen Chen
Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen China
Shuxia Hao
Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen China
Jielun Hu
State Key Laboratory of Food Science and Resources China‐Canada Joint Lab of Food Science and Technology (Nanchang), Key Laboratory of Bioactive Polysaccharides of Jiangxi Province, Nanchang University Nanchang China
Shaoping Nie
State Key Laboratory of Food Science and Resources China‐Canada Joint Lab of Food Science and Technology (Nanchang), Key Laboratory of Bioactive Polysaccharides of Jiangxi Province, Nanchang University Nanchang China
Fei Gao
Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen China
Gengjie Jia
Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen China
Abstract Dietary fiber influences the composition and metabolic activity of microbial communities, impacting disease development. Current understanding of the intricate fiber‐microbe‐disease tripartite relationship remains fragmented and elusive, urging a systematic investigation. Here, we focused on microbiota disturbance as a robust index to mitigate various confounding factors and developed the Bio‐taxonomic Hierarchy Weighted Aggregation (BHWA) algorithm to integrate multi‐taxonomy microbiota disturbance data, thereby illuminating the complex relationships among dietary fiber, microbiota, and disease. By leveraging microbiota disturbance similarities, we (1) classified 32 types of dietary fibers into six functional subgroups, revealing correlations with fiber solubility; (2) established associations among 161 diseases, uncovering shared microbiota disturbance patterns that explain disease co‐occurrence (e.g., type II diabetes and kidney diseases) and distinct microbiota patterns that discern symptomatically similar diseases (e.g., inflammatory bowel disease and irritable bowel syndrome); (3) designed a body‐site‐specific microbiota disturbance scoring scheme, computing a disturbance score (DS) for each disease and highlighting the pronounced capacity of Crohn's disease to disturb gut microbiota (DS = 14.01) in contrast with food allergy's minimal capacity (DS = 0.74); (4) identified 1659 fiber‐disease associations, predicting the potential of dietary fiber to modulate specific microbiota changes associated with diseases of interest; (5) established murine models of inflammatory bowel disease to validate the preventive and therapeutic effects of arabinoxylan that notably perturbed the Bacteroidetes and Firmicutes phyla, as well as the Bacteroidetes and Lactobacillus genera, aligning with our model predictions. To enhance data accessibility and facilitate targeted dietary intervention development, we launched an interactive webtool—mDiFiBank at https://mdifibank.org.cn/.