ArticleFunctional & integrative genomics2026
Comparative genomic analysis of hypervirulent and classical Klebsiella pneumoniae isolates from respiratory samples: A computational assessment of virulence genes.
Article in Functional & integrative genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Hypervirulent Klebsiella pneumoniae (hvKp) has emerged as a major cause of severe respiratory infections worldwide; however, its genomic distinction from classical K. pneumoniae (cKp), particularly within respiratory isolates, remains incompletely understood. In this study, we conducted a large-scale comparative genomic analysis of 1,293 respiratory Kp genomes retrieved from the BV-BRC database, of which 538 were classified as hvKp and 755 as cKp based on established marker genes. Comprehensive profiling of 127 virulence-associated genes revealed distinct virulence architectures between the two groups. HvKp isolates exhibited significantly higher prevalence of key virulence determinants, particularly iron acquisition systems (aerobactin and yersiniabactin) and capsule-associated loci (p < 0.001), reflecting a specialized and optimized virulence strategy. In contrast, cKp isolates showed greater overall virulence gene diversity, as indicated by higher Shannon diversity indices despite lower marker prevalence. Notably, dominant lineages such as ST11-K64 displayed hybrid virulence profiles, suggesting ongoing genomic convergence. Phylogenetic and PCoA analyses demonstrated clustering driven by functional gene repertoires rather than strict lineage relationships, highlighting functional convergence. To improve predictive resolution, a weighted virulence scoring framework was developed, integrating key determinants such as siderophores, capsule regulators, and hypervirulence-associated genes. This model enabled stratification of isolates into low-, intermediate-, and high-risk categories, with high-risk clusters strongly associated with hvKp signatures. The scoring system demonstrated excellent discriminatory performance (AUC = 0.987) and improved classification accuracy compared to single-marker approaches. Overall, this study provides a robust framework for genomic risk stratification and enhances surveillance of emerging hvKp lineages.
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