Differential Analysis of Microbial Interaction Networks

TL;DR

This paper introduces a network-based framework to analyze microbiome reorganization across different conditions, revealing functional interaction shifts associated with diseases and sex differences.

Contribution

The study presents a novel approach combining network inference, differential analysis, and pathway enrichment to uncover microbiome rewiring beyond abundance changes.

Findings

Extensive microbial network rewiring observed across diseases and sexes.

Pathway enrichment uncovers functional signals not visible in individual networks.

Framework applied successfully to IBD, T2D, and cardiovascular disease.

Abstract

Microbiome studies increasingly indicate that disease-associated shifts cannot be understood from compositional changes alone. The functional architecture of microbial communities encoded in patterns of association among microbial gene families may reveal how these systems reorganize across biological conditions. Here, we present a network-based framework for characterizing microbiome rewiring across conditions. The approach combines condition-specific network inference, differential network analysis and pathway enrichment to identify interactions that are gained, lost or altered between groups, with a specific focus on sex-dependent differences. We apply the framework to inflammatory bowel disease, type 2 diabetes and atherosclerotic cardiovascular disease, comparing male and female specific microbial gene-family networks within each disease context. Across these settings, differential networks reveal extensive rewiring of microbial functional interactions, suggesting that microbiome alterations are shaped not only by changes in abundance but also by shifts in community organization. Importantly, pathway enrichment of rewired interactions uncovers functional signals that are not apparent from individual networks alone, highlighting latent disease and sex associated mechanisms. Code, data and supplementary information are available on the web site.