Genome-resolved ecology and evolution of the microbiome enabled by quantitative long-read metagenomics
Standard metagenomics resolves microbial communities only in relative terms and at coarse taxonomic resolution, obscuring how individual strains change in absolute abundance and evolve within a host. We present long-read quantiomics (LRQ), a quantitative metagenomics platform coupling long-read sequencing with plasmid-based internal standards to recover high-quality genomes, including from degraded or low-input stool, and measure absolute, genome-resolved strain abundances. We validate LRQ using large plasmid standards and bacterial spike-ins, then apply it to eight years of dense sampling from an individual with colonic Crohn's disease. LRQ resolves co-resident strains of the same species following opposing trajectories with inflammation. Escherichia coli, long treated as a single pathobiont, separates into two sub-populations with opposing inflammation responses; the inflammation-associated lineage carries an immune-evasion module of virulence-associated metal-acquisition, biofilm, capsule and toxin genes. We observe genome-wide adaptive sweeps on timescales matched to disease incidence. LRQ therefore converts long-read metagenomics from a genome-recovery tool into a quantitative framework providing absolute, strain-level measurement of microbial ecology and evolution.