Background Functional redundancy (FR) in the human gut microbiome is crucial for maintaining stability and resilience, exhibiting a hierarchical structure. However, the precise configuration and functional implications of this hierarchy remain elusive and limited by single-metric measurements. We aimed to develop a method that comprehensively characterizes the hierarchical organization of functional redundancy in personalized microbiomes. Results We represented functional redundancy as a network and developed a structural entropy (SE)-based approach to elucidate FR hierarchy, revealing functional redundancy clusters (FRCs)—groups of species capable of independently executing specific metabolic pathways. Through controlled simulations and cross-cohort analyses spanning 4912 gut metagenomes across 28 disease cohorts, we established that our approach offers higher resolution, more comprehensive measurement, and greater robustness in detecting disease-associated functional patterns than traditional FR methods. In healthy individuals, we observed FR network polycentric structure, which shifted to monocentric structure in non-alcoholic steatohepatitis patients. Vitamin biosynthesis FRCs correlated with microbiota transplantation efficiency, while FRCs specialized in short-chain fatty acid production predicted immunotherapy response and patient survival. Permutation tests validated the causal relationship between SE differences and disease phenotypes, while perturbation experiments revealed that FR keystone species exert disproportionate influence on the system’s resilience. Conclusions Our SE-based approach to functional redundancy analysis provides superior sensitivity compared to conventional metrics by integrating multiple hierarchical levels of functional organization. This methodology establishes a novel perspective for understanding microbiome stability through personalized FR networks, positioning FRCs as promising diagnostic markers and therapeutic targets for microbiome-associated diseases. <MediaObject ID="MOESM2"> <VideoObject FileRef="MediaObjects/40168_2025_2273_MOESM2_ESM.mp4" VideoID="3tj5Gpqq95q5ba7JhsEYAT"> <Caption Language="En" xml:lang="en"> <CaptionContent> Video Abstract </CaptionContent> </Caption> </VideoObject> </MediaObject>

Deciphering the personalized functional redundancy hierarchy in the gut microbiome

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发表日期：

2025年12月4日

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Yiqi Jiang,
Lijia Che,
Shuai Cheng Li

摘要

Background

Functional redundancy (FR) in the human gut microbiome is crucial for maintaining stability and resilience, exhibiting a hierarchical structure. However, the precise configuration and functional implications of this hierarchy remain elusive and limited by single-metric measurements. We aimed to develop a method that comprehensively characterizes the hierarchical organization of functional redundancy in personalized microbiomes.

Results

We represented functional redundancy as a network and developed a structural entropy (SE)-based approach to elucidate FR hierarchy, revealing functional redundancy clusters (FRCs)—groups of species capable of independently executing specific metabolic pathways. Through controlled simulations and cross-cohort analyses spanning 4912 gut metagenomes across 28 disease cohorts, we established that our approach offers higher resolution, more comprehensive measurement, and greater robustness in detecting disease-associated functional patterns than traditional FR methods. In healthy individuals, we observed FR network polycentric structure, which shifted to monocentric structure in non-alcoholic steatohepatitis patients. Vitamin biosynthesis FRCs correlated with microbiota transplantation efficiency, while FRCs specialized in short-chain fatty acid production predicted immunotherapy response and patient survival. Permutation tests validated the causal relationship between SE differences and disease phenotypes, while perturbation experiments revealed that FR keystone species exert disproportionate influence on the system’s resilience.

Conclusions

Our SE-based approach to functional redundancy analysis provides superior sensitivity compared to conventional metrics by integrating multiple hierarchical levels of functional organization. This methodology establishes a novel perspective for understanding microbiome stability through personalized FR networks, positioning FRCs as promising diagnostic markers and therapeutic targets for microbiome-associated diseases.

Video Abstract