Construction method and application of a response score of a bacterial community dietary fiber

By constructing a gut microbiota dietary fiber response scoring method and utilizing techniques such as equidistant logarithmic ratio transformation and Wasserstein distance, the problem of nonlinear coupling between gut microbiota and metabolites was solved, achieving high-precision multi-omics feature analysis and optimization of individual nutritional intervention strategies.

CN122240989APending Publication Date: 2026-06-19YUNNAN AGRICULTURAL UNIVERSITY

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
YUNNAN AGRICULTURAL UNIVERSITY
Filing Date
2026-03-26
Publication Date
2026-06-19

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Abstract

This invention relates to the field of bioinformatics data processing, and particularly to a method and application for constructing a gut microbiota dietary fiber response score. The method includes: acquiring gut microbiome sequencing data from multiple time points of a target individual; extracting relative abundance data of key bacterial genera and performing an isometric logarithmic ratio transformation to obtain an abundance vector sequence; simultaneously acquiring metabolomics data, extracting short-chain fatty acid concentration data, and normalizing it to obtain a metabolic concentration vector sequence; calculating the distance covariance and distance variance between the two sequences and calculating the distance correlation coefficient accordingly; concatenating the abundance vector and metabolic concentration vector at the current time point with the coefficient to construct a multidimensional state vector; constructing a single-point supported empirical distribution function and calculating its Wasserstein distance to the health baseline probability distribution function; and using an exponential decay mapping function to calculate the distance and output the response score. This invention captures the nonlinear coupling mechanism between the gut microbiota and metabolites, improving the biological realism and assessment accuracy of multi-omics feature analysis.
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