Abstract

The gut microbiome plays a critical role in chronic liver disease, yet quantitative methods that integrate microbial community structure with clinical indices remain limited. Here, we applied an energy landscape analysis (ELA)-based framework to characterize transitions in gut microbiota along a clinical gradient of liver disease severity, as measured by the FibroScan-AST (FAST) score. The analysis revealed characteristic community states corresponding to low, intermediate, and high FAST scores, indicating that liver disease progression is associated with structured transitions in microbial community organization rather than simple changes in overall diversity. To further dissect community-level organization, we developed the community shaping index (CSI), which quantifies how strongly individual taxa are associated with specific community structures. Integrating CSI with species-environment association parameters identified key taxa with distinct ecological roles, including unclassified Subdoligranulum taxon, an unclassified Ruminococcus gnavus group taxon, and Streptococcus salivarius, that link host environmental conditions with community composition. Exploratory causal discovery suggested that Streptococcus salivarius and the unclassified Subdoligranulum may play distinct, potentially active roles in linking liver health with gut microbial organization, but with contrasting associations: S. salivarius was linked to disease-related liver deterioration and dysbiotic states, whereas the unclassified Subdoligranulum was associated with healthier liver function and coherent community organization. Overall, this ecologically grounded framework provides a unified and mechanistic foundation for analyzing microbiome structure and disease-associated transitions.