Imbalance in gut microbial interactions as a marker of health and disease

Abstract

Imbalances in the human gut microbiome (dysbioses) are linked to multiple diseases but remain poorly understood. Current biomarkers to identify dysbiosis are inconsistent and fail to capture the ecological mechanisms differentiating healthy from diseased microbiomes. We propose a general dysbiosis biomarker, inspired by phenomenology observed in a gut-microbiome theoretical model introduced here. The emergent communities show complex interaction networks and two distinct collective states, corresponding to healthy and dysbiotic microbiomes. Our robust metric for dysbiosis, by quantifying the balance between cooperation and competition, differentiates these states in both simulated and real datasets across diverse diseases. Moreover, it reveals that dysbiosis results from a shift toward greater cooperation in the community. Our metric further correlates with disease progression, highlighting its potential as a diagnostic tool.