A framework of Microbial Genomic Database for clinical metagenomic pathogen diagnosis: development and multi-cohort evaluation

Abstract

Clinical metagenomic next-generation sequencing (mNGS) enables broad, untargeted pathogen detection, but its analytical performance depends on host depletion strategy, reference database composition, and alignment methodology. We developed the Clinical Microbial Genomic Database (CMGD), a clinically focused reference resource prioritizing medically relevant taxa. CMGD was manually curated, clinically stratified, and included more than 18,000 microbial species. We evaluated host-depletion references, alignment and classification strategies, six published clinical cohorts, and 30 retrospective mNGS-positive clinical samples. The combined GRCh38-T2T reference achieved the highest human-read depletion rate while minimizing microbial-read loss. CMGD provided broader target-species coverage than the standard Kraken2 database, and BWA-CMGD showed lower erroneous assignment rates overall, although Kraken2 yielded higher unique species-level assignment rates for many shared taxa. Across six published clinical cohorts, CMGD achieved 91.0% detection concordance with BLAST-NT and a strong read-count correlation (R 2 = 0.97). In 30 retrospective samples, CMGD and NT showed strong correlations for total mapped reads (R 2 = 0.99) and uniquely mapped reads (R 2 = 0.89), with concordance correlation coefficients of 0.99 and 0.92, respectively. High sequence-mapping accuracy did not ensure reliable species-level discrimination for highly homologous taxa such as Escherichia coli and Shigella flexneri . Clinically stratified database curation improves the analytical performance, computational efficiency, and interpretability of mNGS-based pathogen detection. Species-complex-level reporting may be more appropriate when species-level discriminatory evidence is insufficient. Prospective multicenter validation is required to establish clinical diagnostic utility.