METAGENOME-ASSEMBLED GENOMES FROM A POPULATION-BASED COHORT UNCOVER NOVEL GUT SPECIES AND STRAIN DIVERSITY, REVEALING PREVALENT DISEASE ASSOCIATIONS

Metagenomic profiling has advanced understanding of microbe-host interactions. However, widely used read-based approaches are limited by incomplete reference databases and the inability to resolve strain-level variation. Here, we present a scalable, genome-resolved framework that integrates population-specific metagenome-assembled genomes (MAGs) to discover novel species, strain diversity, and disease associations. From 1,878 deeply sequenced samples in the Estonian microbiome cohort (EstMB-deep), we reconstructed 84,762 MAGs representing 2,257 species, including 353 (15.6%) previously uncharacterized species reaching up to 30% relative abundances in some individuals. We integrated these MAGs with the Unified Human Gastrointestinal Genome (UHGG) collection to create an expanded reference (GUTrep), enabling profiling of 2,509 EstMB individuals and testing associations with 33 prevalent diseases. Of 25 diseases with significant associations, 8 involved newly identified species, underscoring the value of population-specific MAGs. To quantify within-species diversity, we developed the Strain Richness Index (SRI), a novel MAG-based metric that informed strain-level analyses. Based on SRI, we prioritized Odoribacter splanchnicus, a prevalent species with the lowest strain heterogeneity, yielding sufficient power for strain-level analysis. We identified two dominant strains, N1 and N2, with distinct gene repertoires and divergent disease associations. Notably, strain N1 was negatively associated with gastritis and duodenitis and hypertensive heart disease, associations undetected at the species level. Our study expands the human gut reference landscape, demonstrates the importance of population-specific MAGs for uncovering novel microbial diversity, and reveals strain-level disease associations obscured at higher taxonomic levels, highlighting the need for genome-resolved approaches in microbiome research.