An exploratory profiling of defense system signatures in Klebsiella pneumoniae clonal populations

Bacterial defense systems against bacteriophages are critical for bacterial genome stability and fitness, yet their distribution and epidemiological relevance in Klebsiella pneumoniae remain unexplored. We aimed to characterize defense system signatures across major K. pneumoniae clonal lineages and evaluate their utility as genomic signatures for tracking clonal dissemination. Here, we analyzed 6,346 genomes to characterize population structure, defense system signatures, and their coevolution with resistance determinants and plasmid backbones. PopPUNK clustering resolved 146 lineages that stratified into major clonal lineages (G-ST-KL combinations) with distinct resistance and virulence profiles. DefenseFinder and PADLOC identified 320 distinct defense systems, revealing that each clonal lineage harbors a unique defensotype characterized by systematic module replacement rather than stochastic gene loss. Co-occurrence networks further showed that these systems are organized into lineage-specific functional modules, with contrasting architectures even among lineages sharing the same sequence type. Integration of defense, resistance, and plasmid data uncovered strong lineage-specific associations, whereby broad-host-range plasmid backbones acquired distinct defense-resistance payloads in different clonal backgrounds. Geographic and host-niche analyses demonstrated that defense system distribution reflects clonal lineage expansion rather than independent geographic selection, and analysis of 689 Chinese genomes confirmed vertical inheritance of lineage-specific signatures along transmission chains. Collectively, defense systems in K. pneumoniae are organized into lineage-specific defensotypes shaped by synergistic modules and clonal evolutionary dynamics. Defense system profiling provides an additional layer of epidemiological resolution beyond conventional typing and offers practical utility for genomic surveillance, particularly in resource-limited settings where PCR-based detection of conserved systems could serve as a rapid proxy for identifying high-risk K. pneumoniae clones.