The French Gut (FG) cohort is a large-scale citizen science initiative that provides a unique opportunity to explore gut microbiome (GM) heterogeneity within the French population, identifying key environmental and lifestyle factors as well as deviations linked to chronic diseases. The discovery of robust microbial patterns is a major challenge because of the high-dimension and inter-individual variability of the data. Enterosignatures (ES) address this by grouping microbiome compositions into a few groups which weighted combination accurately describe the original sample composition, revealing variations in GM and improving our understanding of its structural organization. While ES help explain inter-individual differences, microbial guilds -groups of microorganisms coexisting in similar ecological niches- offer another layer of insight. The relationship between ES and guilds remains largely unexplored, yet combining both could enhance our understanding of latent structures in the GM that are relevant in terms of metabolic functionality.To address this, we built a meta-cohort of approximately 6,000 individuals from nine large curated cohorts spanning ten countries, applying strict inclusion criteria such as minimal metadata (age, sex, body mass index, health status) and sequencing depth (&gt; 20,000,000 reads), and analyzed it for comparison with the FG cohort pilot-phase (~ 3,000 individuals). Using NeighborFinder, a microbial network inference approach, we identified significant differences. Bacterial network topology varied across ES, with denser and more connected structures associated with individuals primarily represented by ES_Prev rather than ES_Bact. The metabolic potential of the individuals grouped by their primary ES also showed differences, with lower metabolic potential for the ES_Bact group.The topology of microbial network is specific for each ES, suggesting that the stratification of the cohort based on the microbial composition is an important preliminary step before analyzing the guilds composition and functions. This approach enhances our understanding of GM structure and its link to health and diseases.Read less <