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A central hub for convergence: multi-layer genomic networks reveal lineage-specific plasmid compatibility driving hypervirulence and carbapenem resistance in ST11 Klebsiella pneumoniae

Sep 2026 · Frontiers in Microbiology · 0 citations · 41 references

Abstract

The convergence of hypervirulence and carbapenem resistance in Klebsiella pneumoniae represents a critical threat to global public health. However, the genomic mechanisms underlying this convergence, particularly the interplay between chromosomal background and mobile genetic elements, remain incompletely understood. Here, we integrated complete genome data from 102 clinical isolates from Qujing, China, with a global dataset of 4,262 genomes to construct a multi-layer population genomic framework. Using comparative genomics and sequence-similarity network analyses, we characterized the structural organization of the core genome and the population structures of plasmids and prophages. We show that the ST11 lineage serves as a central hub for the convergence of hypervirulence and carbapenem resistance. Plasmids are organized into discrete, functionally specialized communities, among which a dominant community is strongly enriched for hypervirulence and multidrug resistance determinants and preferentially associates with ST11. In contrast, the core genome exhibits a highly constrained structural organization, with most core genes embedded within conserved synteny modules, indicating strong evolutionary constraints on chromosomal architecture. Furthermore, prophages form structured yet more conserved communities that show non-random associations with plasmid types and selectively contribute to the dissemination of resistance genes. Notably, we identified a previously unreported plasmid harboring multiple copies of key virulence loci, underscoring the ongoing modular evolution of high-risk elements. Together, these findings reveal that the convergence of hypervirulence and resistance is driven by lineage-specific plasmid compatibility within a structurally constrained chromosomal background, and they establish a network-based framework for understanding the evolution of high-risk K. pneumoniae lineages.

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