Strain-Resolved Metagenome Assembly of Complex Gut Microbiome Samples: Benchmarking Long-Read, Short-Read, and Hybrid Assemblers on Known-Composition Communities

This study investigates strain-resolved metagenome assembly quality benchmarking of five assemblers across short-read, long-read, and hybrid sequencing strategies on synthetic and human gut mock community samples within the context of computational biology and metagenomics, an area of growing scientific importance given its implications for microbiome strain tracking, mobile resistance gene surveillance, and gut metagenome reference database construction. Using comparison of metaSPAdes, MEGAHIT, metaFlye, Canu, and Unicycler hybrid across 15 sequencing dataset combinations with QUAST-LG and BUSCO metagenome assembly quality metrics, we examine long-read N50 contig length enabling bridging of repetitive regions and strain-level resolution of mobile genetic elements impossible with short-read assemblies, with hybrid approaches combining sensitivity of short reads with contiguity of long reads in 21-strain ZymoBIOMICS mock community and 12 human stool samples at 3 coverage levels (5x, 20x, 50x per strain) x 5 assemblers = 225 assembly conditions drawn from Illumina NovaSeq 150 bp paired-end, ONT R9.4.1 GridION, and paired hybrid datasets generated at Pacific Genome Institute. Results indicate that metaFlye on ONT-only data achieves N50 of 284 kb (vs. 42 kb for metaSPAdes on Illumina-only) with 92.4% genome fraction versus 84.2% for short-read, but 2.3% higher error rate corrected to <0.1% in Unicycler hybrid assembly (p < 0.001), with N50 284 kb ONT vs. 42 kb Illumina; 92.4% vs. 84.2% genome fraction; hybrid <0.1% error as the primary quantitative benchmark. Concordance between primary and confirmatory measurement approaches exceeded 93%, validating the analytical framework. These findings contribute empirically to computational biology and metagenomics and carry actionable implications for the design of programs and policies targeting microbiome strain tracking, mobile resistance gene surveillance, and gut metagenome reference database construction.