Regional Distribution of Klebsiella pneumoniae Virulence Genes: Insights from a Comparative Genome Analysis

Regional Distribution of Klebsiella pneumoniae Virulence Genes: Insights from a Comparative Genome Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report Regional Distribution of Klebsiella pneumoniae Virulence Genes: Insights from a Comparative Genome Analysis Sanika Mahesh Kulkarni, Jobin John Jacob, Subbulakshmi R, Venkatesh N, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7763903/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract The hypervirulent Klebsiella pneumoniae (hvKp) is a clinically significant pathotype. HvKp-related pathotypes are characterized by the presence of multiple key virulence determinants, contributing to severe infections across diverse geographic regions. In contrast, certain carbapenem-resistant K. pneumoniae (CRKp) lineages carry only a subset of these virulence genes, representing virulence marker-associated CRKp that may acquire additional determinants over time. Several virulence markers, including rmpA , rmpA2 , iucA , iroB , clb , ybt , and peg-344 , have been identified as potential diagnostic biomarkers for hvKp detection. This study examines the global distribution of five key hvKp virulence genes ( iucA, rmpA, rmpA2, iroB , and peg-344 ), comparing classical hvKp lineages with nonclassical hvKp/virulence-marker-associated CRKp lineages. Analysis revealed substantial ST- and region-specific variation in the retention of these markers. These findings underscore the need for multigene, region-specific surveillance strategies to facilitate early detection and guide effective clinical and infection control measures. Hypervirulent Klebsiella pneumoniae (hvKp) Virulence genes Diagnostic biomarkers Carbapenem resistance regional variability Figures Figure 1 Figure 2 Figure 3 Impact Statement The convergence of virulence and resistance in Klebsiella pneumoniae is still being explored. While virulence plasmids have been decoded, their integration into resistance plasmids remains an ongoing area of investigation. Mosaic plasmids, formed by the integration of virulence and resistance-carrying amplicons, tend to retain or lose certain virulence genes. This dynamic evolution makes it challenging to define a universal set of hypervirulence markers, as Kp rapidly diversifies into distinct strains across different regions. To address this challenge, our study leveraged publicly available genomic data to provide a panoramic view of the diverse virulence profiles of representative genomes from various regions. The gene distribution highlighted significant variations in the proportions of markers such as rmpADC and rmpA2 across lineages and geographic locations. Notably, aerobactin ( iucA ) remains a highly specific and stable biomarker for hypervirulence. These observations provide a current perspective on virulence markers, and given the plasticity of the Klebsiella genome, continuous monitoring is essential for refining detection assays and enhancing surveillance strategies. Introduction Carbapenem-resistant Klebsiella pneumoniae (CRKp) is a major health threat in health settings across the globe, particularly in Asia, where over half of Kp infections exhibit carbapenem resistance [ 1 ]. Increasing resistance complicates treatment, increases mortality rates, and limits therapeutic options. Moreover, the emergence of hypervirulent K. pneumoniae (hvKp) has raised additional concerns because of its enhanced virulence and potential for severe, invasive infections [ 2 – 5 ]. In this study, hvKp was defined as K. pneumoniae strains carrying at least four of the following biomarkers: rmpA, rmpA2, iucA, iroB , and peg344 , which is consistent with recent experimental evidence that strongly associates these markers with hypervirulence [ 6 , 7 ]. These genes are commonly plasmid-borne and contribute to increased pathogenic potential, distinguishing hvKp from classical K. pneumoniae (cKp). The distinct clinical presentation and phenotypic characteristics distinguish the hypervirulent pathotype from classical K. pneumoniae (cKp) [ 8 ]. Notably, hvKp can cause severe infections in otherwise healthy individuals and can be readily disseminated from the primary infection site to multiple organs [ 9 , 10 ]. While many hvKp strains exhibit a hypermucoid phenotype, not all are string positive. The string test is a phenotypic marker commonly used to indicate hypermucoviscosity. However, its absence does not rule out hypervirulence, as some hvKp strains may lack rmpA and rmpA2 but may exhibit other virulence traits. Genotypic analysis associated the virulence of hvkp to plasmid-borne genes, including iucABDC and iutA (siderophores), rmpADC , rmpA2 (mucoid regulators), clb (colibactin) [ 6 ], and peg-344 , a gene encoding a putative inner membrane transporter present on large virulence plasmids that has emerged as a sensitive and specific biomarker for hypervirulence [ 11 ]. Chromosomal acquisition of ICEKp10, which carries the ybt cluster for yersiniabactin biosynthesis, further enhances the pathogenicity of hvKp. Although these genetic markers aid in hvKp detection, many clinical laboratories rely solely on the string test. In recent years, bidirectional genetic exchange has driven the convergence of multidrug-resistant (MDR-Kp) and hypervirulent (hvKp) pathotypes. Classical multidrug-resistant strains have acquired virulence plasmids, either entirely or through partial integration (hv-MDR/CRKp). Conversely, hypervirulent strains have incorporated resistance determinants, including carbapenemase-producing genes via horizontal gene transfer (CR-hvKp). This convergence has generated diverse virulence profiles among convergent strains, depending on the specific virulence plasmids (e.g., pK2044, pLVPK) or resistance elements (e.g., bla KPC , bla NDM , bla OXA−48−like ) that are acquired [ 12 , 13 ]. Strains harboring only partial virulence genes can be classified as virulence marker-positive cKp/CRKp. While the acquisition of the complete plasmid enhances virulence traits such as increased siderophore production and capsule formation [ 6 ], partial integration often leads to the truncation or loss of key genes such as rmpA and rmpA2 , thereby altering hypermucoid phenotypes [ 6 , 14 ]. Convergent Kp isolates, defined as strains harboring four or more core virulence markers ( rmpA, rmpA2, iucA, iroB , and peg344 ) in combination with resistance determinants, are relatively rare compared with virulence marker–positive cKp/CRKp isolates that carry fewer virulence genes. Although these isolates may not always meet the strict criteria for hvKp or CR-hvKp classification, monitoring their emergence and spread is crucial for understanding the dynamics of virulence and resistance convergence. The variable retention of individual virulence genes across strains underscores the limitations of relying on single markers and highlights the importance of a combinatorial definition for robust hvKp detection. Given the increase in reports of converging isolates, a systematic analysis of virulence gene distribution is crucial for identifying robust biomarkers for hvKp detection. This study aims to address this gap by leveraging large-scale genomic data to assess the variability and retention of key virulence genes across diverse sequence types (STs) and geographic regions to better understand the genetic dynamics underlying virulence marker retention and loss. This study systematically compares genomes available in the NCBI database and examines evolving trends in virulence gene composition across different STs, geographic regions, and K-loci. Materials and Methods In our study, we selected the Kp genomes on the basis of the presence of the key virulence markers iucA, rmpADC, rmpA2, iroB, and peg‑344 , as annotated in the metadata available via NCBI Pathogen Detection. The genomes were filtered using available metadata tags. Additionally, we excluded entries lacking valid GCA accession numbers, SRA identifiers (ERR/SRR), or essential metadata such as collection dates and geographic locations. This approach enabled the curation of a dataset suitable for regional comparative analysis of virulence marker distribution. A comprehensive data analysis was conducted via Kleborate v.3.1.0 ( https://github.com/klebgenomics/Kleborate.git ) to investigate the global distributions of virulence-associated genes, STs, and AMR genes. While other genes, such as ybt and clb , contribute to virulence, they are also frequently found in classical Kp strains, making them less specific markers for hypervirulence. A dataset of ~ 12,000 hvKp genomes from the NCBI database (as of 14-10-2024) ( https://www.ncbi.nlm.nih.gov/pathogens/isolates/#taxgroup_name:%22Klebsiella%20pneumoniae%22 ) was analysed to examine the presence and spread of known virulence determinants. The distribution of peg-344 was determined via BLAST alignment against the reference sequence from the NTUH-K2044 Kp plasmid pK2044 (GenBank accession: AP006726.1). The analysis was conducted with a minimum coverage threshold of 100% and an identity threshold of 90%, considering only the highest-scoring hits. The kleborate-derived data for rmpA, rmpA2, iucA and iroB were stratified by geographic region, including Europe, South Asia, East Asia, Southeast Asia, Middle East Asia, Africa, North America, South America, and Oceania, to examine regional variations in the prevalence of these markers. Additionally, strains were classified into two groups: Group A, consisting of STs previously established in multiple studies as strongly associated with hvKp (ST23, ST25, ST375, ST65, and ST86) [ 15 – 17 ], and Group B, comprising all other STs that are primarily CRKps but can acquire virulence factors over time. This classification distinguishes intrinsically hypervirulent lineages from those that secondarily acquire virulence factors. Using this classification, we analysed the prevalence of strains in each group to understand the extent of convergence between virulence and resistance. To further investigate the distribution of virulence genes among STs, we visualized the presence of key markers ( rmpA, rmpA2, iucA, iroB and peg-344 ) across different STs via a heatmap. The visualization was generated via Python (version 3.12.3) with several libraries: Masilea (version 0.5.3; https://doi.org/10.1186/s13059-024-03469-3 ) for creating structured heatmaps, Pillow (version 11.2.1) for image processing, Pandas (version 2.3.0; https://doi.org/10.5281/zenodo.3509134 ) for data manipulation, and Matplotlib (version 3.10; https://doi.org/10.1109/MCSE.2007.55 ) for plotting. The regional distribution of these STs was also analysed to assess geographical variations, and capsular (K) locus diversity was examined, given its association with hypervirulent and resistant isolates. A combination of virulence genes has been widely accepted as a biomarker of hvKp; therefore, multiple genes were cooccurring to understand the prevalence within the dataset. To assess the regional distribution of virulence-associated genes, a chi-square (χ²) test of independence was performed to evaluate whether the observed gene frequencies across geographic regions significantly deviated from those expected under random distribution. The expected values were calculated on the basis of the total number of isolates per region and the overall prevalence of each virulence gene in the dataset. Separate tests were performed for each geographic region, and to account for multiple comparisons across nine regions, the Benjamini–Hochberg procedure was applied to control the false discovery rate at 5%. The significance threshold was set at adjusted p < 0.05. Statistical analysis was performed via SPSS (v 29), with multiple testing correction carried out in R (v 4.5.1). Results Analysis revealed that the distribution of core virulence-associated genes varied significantly across geographic regions (Fig. 1 ). The prevalence percentages represent the proportion of genomes from each region that carried the respective virulence gene. The final dataset included 12,961 genomes (see Supplementary Table S1 ), with the following regional breakdown: East Asia (n = 7004), North America (n = 1967), Europe (n = 1869), South Asia (n = 803), Southeast Asia (n = 661), the Middle East (n = 356), Oceania (n = 143), Africa (n = 85), and South America (n = 73) (see Supplementary Table S2 ). On the basis of virulence marker profiles, the majority of isolates (10,064/12,489; 80.5%) presented partial profiles with fewer than five core markers, whereas 2,425 isolates (18.7% of the total 12,961) presented all five markers ( rmpADC, rmpA2, iucA, iroB, and peg-344 ). Notably, aerobactin ( iucA ) exhibited the highest prevalence across all regions, consistently exceeding 90%, as expected because the dataset was filtered for iucA -positive genomes, with the highest occurrence in South Asia (99.1%). The rmpA2 gene had the highest prevalence in the Middle East (83.7%) and East Asia (83.5%) but was markedly lower in South America (15.1%). The rmpADC locus followed a similar trend, being most common in East Asia (61.7%) and Oceania (68.5%), whereas its occurrence was minimal in the Middle East (23.6%) and South Asia (22.2%). The prevalence of iroB varies widely. The highest percentages were observed in South America (70%), Oceania (62.2%) and Southeast Asia (51.7%), whereas the percentages were particularly low in the Middle East (5.0%) and North America (9.5%). The BLAST results for Peg-344 revealed substantial regional variation, peaking in North America (82.9%), the Middle East (80.6%), and Africa (83.5%), whereas it was lower in South Asia (49.3%) and South America (26%). These findings suggest distinct regional patterns of virulence gene distribution, with certain markers such as iucA consistently present at high frequencies. In contrast, others, including peg-344 , rmpADC, rmpA2 , and iroB , exhibited greater localized prevalence (Fig. 1 and Supplementary Table 3 ). Among other virulence determinants, ybt was widespread, particularly in East Asia, South Asia, and the Middle East. In contrast, clb , encoding colibactin, was the least detected virulence factor, with the prevalence remaining below 25% across all regions. These distributions highlight that while iucA is nearly ubiquitous, markers such as peg-344, rmpADC, rmpA2 , and iroB , which are critical to the updated definition of convergent isolates, exhibit highly uneven regional representation. The χ² analysis revealed significant regional variations in the distribution of virulence genes, with deviations assessed against expected frequencies under a random distribution. iucA, as expected owing to the selection criterion, along with iro, rmpADC , and rmpA2 , showed statistically significant differences in most regions after Benjamini–Hochberg correction for multiple testing (adjusted p < 0.05), except for Oceania (adjusted p = 0.222), where no significant difference was observed. The iucA prevalence was highest in South Asia (53.1%) and North America (50.8%), whereas it peaked in South America (32.9%) and Southeast Asia (22.8%). rmpADC and rmpA2 had the highest prevalence in East Asia (22.1% and 29.9%) and North America (35.2%), respectively. These results highlight pronounced regional disparities in the distribution of core virulence markers, which likely influence the geographic patterns of convergent isolates carrying four or more markers in combination with resistance determinants (see Supplementary Table S9). Furthermore, hvKp strains harboring all five virulence genes (n = 2425) were categorized into two groups. Group A comprised STs historically and strongly associated with intrinsic hvKp (ST23, ST25, ST65, ST86, ST375, and ST1660), whereas Group B included all other STs, primarily classical CR-Kp, with the potential to acquire virulence determinants. This classification allowed us to investigate the pathotype distribution of hvKp and hv-CRKp/CR-hvKp isolates across different geographic regions ( Fig. 2 ) . Group A, representing intrinsic hvKp lineages, constituted the majority of cases across most regions. Group B, which included convergent hv-CRKp/CR-hvKp isolates, accounted for a relatively small proportion, with relatively high frequencies in North America, Europe, and South Asia (see Supplementary Tables S4 and S5 ). These findings indicate that Group A lineages, such as ST23, which harbour the complete set of virulence determinants, represent the true hypervirulent clones. In contrast, Group B lineages, including high-risk CR-Kps such as ST147, do not carry the full virulence gene repertoire but are increasingly acquiring subsets of virulence markers and can thus be described as virulence marker-associated CR-Kps. To complement the geographic and prevalence analyses, we performed a detailed STwise assessment of virulence gene distribution (Fig. 3 B), providing insights into lineage-specific patterns. To further investigate convergence globally, we analysed the STs of K. pneumoniae genomes across nine regions. A total of 20 predominant STs were identified ( Supplementary Table S6 ), with representative counts including ST11 (n = 3,665, East Asia), ST23 (n = 760, East Asia), and ST147 (n = 737, North America) ( Supplementary Table S7 ). These STs were further grouped into (1) classical hypervirulent STs (e.g., ST23, ST65, and ST86) and (2) high-risk carbapenem-resistant STs (e.g., ST11, ST15, ST147, and ST2096), enabling assessment of virulence marker acquisition across both categories. Figure 3 A–C provides an integrated view of the STwise virulence gene distribution, geographic prevalence, and K locus diversity across both groups. As expected, Group A lineages (e.g., ST23, ST65, ST86, ST375, and ST1660) consistently carried the full complement of virulence determinants ( rmpADC, iroB, and iucA ). The Group B lineages, while not classical hvKp types, also harboured all five virulence genes, indicating that multiple nonclassical STs have acquired the complete hypervirulence repertoire. This framework allowed us to examine whether classical hvKp lineages are more prone to acquiring resistance or, conversely, whether nonclassical STs are increasingly taking up full virulence, either alone or in combination with carbapenem resistance. The heatmap further highlights that aerobactin ( iucA) is conserved across both groups, emphasizing its central role in hypervirulence. Geographic analysis revealed lineage-specific enrichment: ST11 in East Asia, ST147 in North America and Europe, ST231 in South and Southeast Asia, ST2096 in the Middle East, and ST86 in Oceania. Capsule types KL1 and KL2 were predominantly associated with classical hvKp lineages (Group A), which is consistent with their complete virulence gene load and established links to community-acquired infections. In contrast, KL64 and KL51 were more common among nonclassical hvKp lineages (Group B), including ST231 and ST147, reflecting lineages where hypervirulence coexists with emerging resistance traits (Fig. 3 C, Supplementary Table S8 ). Analysis of virulence marker combinations further reinforced these distinctions. Among the isolates carrying two markers, rmpA2 and iucA were the most common, whereas the isolates with three markers predominantly carried rmpA, rmpA2 , and iucA ( Supplementary Fig. 1 ). Together, these findings underscore a strong correlation between lineage, virulence gene carriage, and capsular diversity: classical hvKp lineages retain conserved virulence signatures, whereas nonclassical hvKp/virulence marker-associated CRKp lineages exhibit greater genomic plasticity, likely driven by selective pressures in healthcare environments. Discussion Our findings underscore that classical hvKp lineages maintain conserved virulence traits, whereas certain nonclassical lineages have also acquired the full set of hypervirulence genes and can be classified as hvKp as per the recent definition. The distribution of these lineages is region specific, and several high-risk STs show simultaneous carriage of virulence determinants and carbapenem resistance, highlighting the need for vigilant surveillance, particularly in hospital settings. These results underscore the importance of detecting complete virulence gene repertoires across Kp strains, including both classical and nonclassical hvKp, in the context of geographic variability and plasmid-mediated gene integration. Understanding these distribution patterns is crucial for early diagnosis, as hypervirulence traits can significantly impact disease severity and patient outcomes, particularly in regions with a high burden of multidrug-resistant strains [ 6 , 18 – 20 ]. Among these markers, genes encoding siderophores, such as aerobactin ( iucA ), remain consistently conserved across both classical and nonclassical hvKp lineages, highlighting their central role in pathogenic potential [ 21 ]. While iucA alone does not define hypervirulence, its presence is a stable component of the hvKp signature and serves as a useful target for molecular diagnostics [ 22 ]. In contrast, the loss of peg-344 , or mutations in key hypervirulence regulators such as rmpADC and rmpA2 in certain carbapenem-resistant lineages, indicates shifts in the genetic architecture of virulence marker-associated CRKps. Table 1 provides a detailed summary of the defining features of these pathotypes. Table 1 Table 1 Features of the significant characteristics of Kp, hvKp, hv-CRKp, and CR-hvKp on the basis of plasmid type, virulence genes, antibiotic resistance, and STs Feature Kp hvKp CR-hvKp hv-CRKp Mucoid/String Test Mucoid (String Negative) Hypermucoid (String Positive) String Positive or Negative String Positive or Negative Plasmid Types Resistance plasmids (e.g., IncFII, IncL/M, IncR, IncHI1B, IncFIB and IncFIIK, ColKp3) Large virulence plasmids (pLVPK, SGH10) pLVPK, resistance plasmids (e.g., IncFII, IncN, IncHI1B, IncFIB and IncFIIK) Resistance plasmids (e.g., IncFII, IncL/M, IncR, IncHI1B, IncFIB and IncFIIK) with or without pLVPK K Locus Regionally varies K1, K2, K20, K57 K1, K2, K64 K64, others Sequence Types E.g., ST11, ST14, ST258, ST231, ST147 E.g., ST23, ST25, ST65, ST86, ST375, ST1660 E.g., ST23, ST65, ST86 ST11, ST15, ST2096, ST231, ST147 Prevalence Global East Asia (China), South East Asia, Europe Global, with notable cases in North America, the Middle East, East Asia (China) Global, with notable cases in South Asia (India), Europe and East Asia In silico analyses confirmed that iucA is structurally stable, highlighting it as a key determinant of virulence in Kp [ 18 , 23 ]. Other key virulence genes ( rmpA, rmpA2, iroB , and peg-344 ) display relatively low stability, and their presence contributes to pathogenicity. While aerobactin is stable and often present, strains carrying only a subset of the five virulence markers likely exhibit lower overall virulence and reduced metastatic potential than strains harboring the complete hvKp signature. The functional impact of incomplete virulence profiles requires further in vivo validation, particularly to assess their pathogenicity and potential for dissemination. The incorporation of all five markers into multigene surveillance frameworks enables more accurate detection of hypervirulent and carbapenem-resistant strains, supporting targeted monitoring in clinical and epidemiologic contexts. The vaccine candidates, such as Kleb4V (LimmaTech Biologicals AG/GSK), a P. aeruginosa exotoxin protein A recombinant bioconjugate that targets O-antigens (O1, O2a, O2afg, O3b), KlebVax (SSVI and WRAIR), a 24-valent K antigen unconjugated vaccine that targets capsular polysaccharides and vaccines that target the K2, K3, K10 and K55 mixtures, and unconjugated capsular polysaccharides, have shown promising immunogenicity in phase 1/2 trials [ 24 – 28 ]. However, our genomic analysis revealed significant regional variability in virulence marker distribution; with the increasing convergence of resistance and virulence plasmids in high-risk STs (e.g., ST147 and ST2096), KL loci, which are responsible for capsular synthesis and immune evasion, are becoming critical contributors to increased pathogenicity. However, these loci are not adequately targeted by current vaccine formulations. In regions such as South Asia and the Middle East, where KL64 and KL51 dominate, and in China, where KL47 and KL64 are prevalent, the current vaccine targets, K1 and K2, offer limited coverage. The incorporation of KL-specific targets in future vaccine strategies is essential for enhancing protection against CR-hvKp in these high-burden regions. A key limitation of this study is the uneven distribution of genomes across geographic regions, particularly from South America and Africa, where the number of available sequences is limited. Since our findings are based on publicly available genomes in NCBI at the time of analysis, they may not fully represent the global epidemiology of hvKp. Additionally, we did not verify whether rmpADC was chromosomally encoded or plasmid encoded, which is crucial, as plasmid-borne rmpA is prone to loss, potentially affecting hypervirulence expression. Furthermore, our analysis focused on known virulence-associated genes, and emerging or unidentified genetic variants contributing to hypervirulence may not have been captured. Future studies incorporating experimental validation in vitro, followed by animal model studies to confirm the virulence genes or their function in regional isolates, would complement the genomic data, which are needed to address these gaps. Conclusion Our study presents a comprehensive analysis of hvkp and its convergence with carbapenem-resistant strains, highlighting the presence of virulence determinants and its increasing nonendemic nature. We observed substantial geographic and ST-specific variation in the distribution of the key virulence marker iucA , which was consistently present across all lineages, whereas genes such as rmpADC, rmpA2, peg-344 , and iroB exhibited differential retention, particularly in the virulence marker-associated CRKps, indicating ongoing genomic adaptations. The increasing prevalence of CR-hvKps in hospital settings represents a serious clinical threat, as multidrug-resistant, hypervirulent strains complicate treatment and infection control. Early detection via multigene, region-specific biomarkers is essential for identifying disseminated infections and guiding effective clinical management. These findings underscore the urgent need for enhanced genomic surveillance, refined molecular diagnostics, and targeted therapeutic strategies to mitigate the growing epidemiological and clinical impact of hvKp and CR-hvKp. Declarations Conflicts of interest All the authors declare that they have no conflicts of interest. Author Contribution S.M.K.: Conceptualization; Data curation; Formal analysis; Methodology; Project administration; Resources; Validation; Visualization; Roles/Writing - original draft; Writing - review & editing, J.J.J.: Conceptualization; Project administration; Validation; Visualization; Writing - review & editing, Monisha Priya T: Data analysis; S.R.: Data Curation and analysis, V.N.: Data visualization; Statistical Analysis;K. G.: Formal analysis; Validation;A.B.: Formal analysis; Validation;K.W.: Supervision; Validation; Critical revision. B.V. : Conceptualization; Funding acquisition; Supervision; Validation; Visualization; Review & editing. All authors read and approved the final manuscript. Acknowledgement The authors thank the Department of Clinical Microbiology, Christian Medical College and Hospital, Vellore, for providing us with all the necessary facilities to conduct our study. 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Nat Commun 14:7962 Edelman R, Taylor DN, Wasserman SS, McClain JB, Cross AS, Sadoff JC et al (1994) Phase 1 trial of a 24-valent Klebsiella capsular polysaccharide vaccine and an eight-valent Pseudomonas O-polysaccharide conjugate vaccine administered simultaneously. Vaccine 12(14):1288–1294 Campbell WN, Hendrix E, Cryz SJ Jr, Cross AS (1996) Immunogenicity of a 24-valent Klebsiella capsular polysaccharide vaccine and an eight-valent Pseudomonas O-polysaccharide conjugate vaccine administered to victims of acute trauma. Clin Infect Dis 23(1):179–181 Donta ST, Peduzzi P, Cross AS, Sadoff J, Haakenson C, Cryz SJ Jr et al (1996) Immunoprophylaxis against Klebsiella and Pseudomonas aeruginosa infections: the Federal Hyperimmune Immunoglobulin Trial Study Group. J Infect Dis 174(3):537–543 Cryz SJ Jr, Mortimer P, Cross AS, Fürer E, Germanier R (1986) Safety and immunogenicity of a polyvalent Klebsiella capsular polysaccharide vaccine in humans. Vaccine 4(1):15–20 Dangor Z, Benson N, Berkley JA, Bielicki J, Bijsma MW, Broad J et al (2024) Vaccine value profile for Klebsiella pneumoniae . Vaccine 42(19S1):S125–S141. 10.1016/j.vaccine.2024.02.072 Additional Declarations No competing interests reported. Supplementary Files SupplementaryFile1.xlsx SupplementaryFile1.xlsx FigureLegends.docx SupplementaryFigure1.pdf Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 01 Apr, 2026 Reviews received at journal 26 Mar, 2026 Reviewers agreed at journal 12 Mar, 2026 Reviews received at journal 07 Dec, 2025 Reviewers agreed at journal 04 Dec, 2025 Reviewers agreed at journal 03 Dec, 2025 Reviewers invited by journal 02 Dec, 2025 Editor assigned by journal 06 Oct, 2025 Submission checks completed at journal 04 Oct, 2025 First submitted to journal 02 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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1","display":"","copyAsset":false,"role":"figure","size":808848,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGeographic distribution of virulence-associated genes in Kp.\u003cbr\u003e\nBar plots depict the percentage prevalence of five hypervirulence-associated genes (\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eiucA, iroB, rmpADC, rmpA2,\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003epeg-344\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e) across different global regions.\u003cbr\u003e\nThe height of each bar represents the proportion (%) of genomes from that region positive for each gene, as determined via Kleborate analysis. The total number of genomes analysed per region is indicated as (n).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure1finalpage0001.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7763903/v1/7e5531b23b130750c86a6268.jpg"},{"id":97471725,"identity":"bf4e3a1e-b3ce-45b1-b7a0-157c5091e388","added_by":"auto","created_at":"2025-12-04 17:43:08","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":268531,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of isolates with convergence of hypervirulence and carbapenem resistance in Kp. (A) Geographic distribution of all the convergence (in orange) and only hvKp (in brown) values; the percentages are shown across different regions.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(B) Furthermore, the data were distributed into two groups based on STs to determine which group had abundant converging isolates. Group A primarily comprised STs usually associated with hypervirulence, whereas Group B consisted of STs linked to multidrug resistance.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure20210page0001.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7763903/v1/a93d901fed7f046fb5fbc3a3.jpg"},{"id":97669164,"identity":"98776424-74b8-493e-a146-5157a9076e01","added_by":"auto","created_at":"2025-12-08 09:27:27","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1182913,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSTwise distribution of virulence genes, antimicrobial resistance, and capsular (K) locus diversity in the study set. (A) Heatmap representation showing the distribution of virulence-associated genes (\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ermpA, rmpA2, iucA, iroB,\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003epeg-344\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e) across major STs. (B) Distribution of virulence genes (e.g., \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ermpA, rmpA2, iucA, iroB \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eand \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003epeg-344\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e) among the same STs. (C) Capsular (K) locus diversity across STs, with a focus on dominant capsule types such as KL1, KL2, KL51, and KL64. The percentage values represent the proportion of genomes within each ST that harbor the respective gene or K-locus type.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure3finalpage0001.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7763903/v1/dab249d885dbc33c4b9acd1c.jpg"},{"id":97677687,"identity":"bc66cdfa-f0eb-4fbf-af29-f0b4710fbf6a","added_by":"auto","created_at":"2025-12-08 09:54:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3499188,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7763903/v1/cb7b3597-f98c-43c5-ab0d-a1b424725915.pdf"},{"id":97669770,"identity":"b657d72c-0eb1-4b17-9fa2-104202aa241c","added_by":"auto","created_at":"2025-12-08 09:28:51","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":784403,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7763903/v1/6515030e35fefa188d4aab04.xlsx"},{"id":97668834,"identity":"584fae20-127c-4492-8b8b-1223bcbc0895","added_by":"auto","created_at":"2025-12-08 09:26:21","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":784403,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7763903/v1/74720f40fbac711702761206.xlsx"},{"id":97669160,"identity":"d387882d-f011-49f7-9484-05cd8101d208","added_by":"auto","created_at":"2025-12-08 09:27:26","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":19661,"visible":true,"origin":"","legend":"","description":"","filename":"FigureLegends.docx","url":"https://assets-eu.researchsquare.com/files/rs-7763903/v1/b5f69bfbfc4bb1bc10725e61.docx"},{"id":97471732,"identity":"62abdadf-e928-496e-bcf0-22591e807aeb","added_by":"auto","created_at":"2025-12-04 17:43:08","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":153764,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7763903/v1/dbe285026e02983e9f55a93e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Regional Distribution of Klebsiella pneumoniae Virulence Genes: Insights from a Comparative Genome Analysis","fulltext":[{"header":"Impact Statement","content":"\u003cp\u003eThe convergence of virulence and resistance in \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e is still being explored. While virulence plasmids have been decoded, their integration into resistance plasmids remains an ongoing area of investigation. Mosaic plasmids, formed by the integration of virulence and resistance-carrying amplicons, tend to retain or lose certain virulence genes. This dynamic evolution makes it challenging to define a universal set of hypervirulence markers, as Kp rapidly diversifies into distinct strains across different regions.\u003c/p\u003e\u003cp\u003eTo address this challenge, our study leveraged publicly available genomic data to provide a panoramic view of the diverse virulence profiles of representative genomes from various regions. The gene distribution highlighted significant variations in the proportions of markers such as \u003cem\u003ermpADC\u003c/em\u003e and \u003cem\u003ermpA2\u003c/em\u003e across lineages and geographic locations. Notably, aerobactin (\u003cem\u003eiucA\u003c/em\u003e) remains a highly specific and stable biomarker for hypervirulence. These observations provide a current perspective on virulence markers, and given the plasticity of the \u003cem\u003eKlebsiella\u003c/em\u003e genome, continuous monitoring is essential for refining detection assays and enhancing surveillance strategies.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eCarbapenem-resistant \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (CRKp) is a major health threat in health settings across the globe, particularly in Asia, where over half of Kp infections exhibit carbapenem resistance [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Increasing resistance complicates treatment, increases mortality rates, and limits therapeutic options. Moreover, the emergence of hypervirulent \u003cem\u003eK. pneumoniae\u003c/em\u003e (hvKp) has raised additional concerns because of its enhanced virulence and potential for severe, invasive infections [\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In this study, hvKp was defined as \u003cem\u003eK. pneumoniae\u003c/em\u003e strains carrying at least four of the following biomarkers: \u003cem\u003ermpA, rmpA2, iucA, iroB\u003c/em\u003e, and \u003cem\u003epeg344\u003c/em\u003e, which is consistent with recent experimental evidence that strongly associates these markers with hypervirulence [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These genes are commonly plasmid-borne and contribute to increased pathogenic potential, distinguishing hvKp from classical \u003cem\u003eK. pneumoniae\u003c/em\u003e (cKp). The distinct clinical presentation and phenotypic characteristics distinguish the hypervirulent pathotype from classical \u003cem\u003eK. pneumoniae\u003c/em\u003e (cKp) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Notably, hvKp can cause severe infections in otherwise healthy individuals and can be readily disseminated from the primary infection site to multiple organs [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. While many hvKp strains exhibit a hypermucoid phenotype, not all are string positive. The string test is a phenotypic marker commonly used to indicate hypermucoviscosity. However, its absence does not rule out hypervirulence, as some hvKp strains may lack \u003cem\u003ermpA\u003c/em\u003e and \u003cem\u003ermpA2\u003c/em\u003e but may exhibit other virulence traits. Genotypic analysis associated the virulence of hvkp to plasmid-borne genes, including \u003cem\u003eiucABDC\u003c/em\u003e and \u003cem\u003eiutA\u003c/em\u003e (siderophores), \u003cem\u003ermpADC\u003c/em\u003e, \u003cem\u003ermpA2\u003c/em\u003e (mucoid regulators), \u003cem\u003eclb\u003c/em\u003e (colibactin) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], and \u003cem\u003epeg-344\u003c/em\u003e, a gene encoding a putative inner membrane transporter present on large virulence plasmids that has emerged as a sensitive and specific biomarker for hypervirulence [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Chromosomal acquisition of ICEKp10, which carries the \u003cem\u003eybt\u003c/em\u003e cluster for yersiniabactin biosynthesis, further enhances the pathogenicity of hvKp. Although these genetic markers aid in hvKp detection, many clinical laboratories rely solely on the string test.\u003c/p\u003e\u003cp\u003eIn recent years, bidirectional genetic exchange has driven the convergence of multidrug-resistant (MDR-Kp) and hypervirulent (hvKp) pathotypes. Classical multidrug-resistant strains have acquired virulence plasmids, either entirely or through partial integration (hv-MDR/CRKp). Conversely, hypervirulent strains have incorporated resistance determinants, including carbapenemase-producing genes via horizontal gene transfer (CR-hvKp). This convergence has generated diverse virulence profiles among convergent strains, depending on the specific virulence plasmids (e.g., pK2044, pLVPK) or resistance elements (e.g., \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eKPC\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eNDM\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003eOXA\u0026minus;48\u0026minus;like\u003c/sub\u003e) that are acquired [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Strains harboring only partial virulence genes can be classified as virulence marker-positive cKp/CRKp. While the acquisition of the complete plasmid enhances virulence traits such as increased siderophore production and capsule formation [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], partial integration often leads to the truncation or loss of key genes such as \u003cem\u003ermpA\u003c/em\u003e and \u003cem\u003ermpA2\u003c/em\u003e, thereby altering hypermucoid phenotypes [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Convergent Kp isolates, defined as strains harboring four or more core virulence markers (\u003cem\u003ermpA, rmpA2, iucA, iroB\u003c/em\u003e, and \u003cem\u003epeg344\u003c/em\u003e) in combination with resistance determinants, are relatively rare compared with virulence marker\u0026ndash;positive cKp/CRKp isolates that carry fewer virulence genes. Although these isolates may not always meet the strict criteria for hvKp or CR-hvKp classification, monitoring their emergence and spread is crucial for understanding the dynamics of virulence and resistance convergence. The variable retention of individual virulence genes across strains underscores the limitations of relying on single markers and highlights the importance of a combinatorial definition for robust hvKp detection. Given the increase in reports of converging isolates, a systematic analysis of virulence gene distribution is crucial for identifying robust biomarkers for hvKp detection. This study aims to address this gap by leveraging large-scale genomic data to assess the variability and retention of key virulence genes across diverse sequence types (STs) and geographic regions to better understand the genetic dynamics underlying virulence marker retention and loss. This study systematically compares genomes available in the NCBI database and examines evolving trends in virulence gene composition across different STs, geographic regions, and K-loci.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eIn our study, we selected the Kp genomes on the basis of the presence of the key virulence markers \u003cem\u003eiucA, rmpADC, rmpA2, iroB, and peg‑344\u003c/em\u003e, as annotated in the metadata available via NCBI Pathogen Detection. The genomes were filtered using available metadata tags. Additionally, we excluded entries lacking valid GCA accession numbers, SRA identifiers (ERR/SRR), or essential metadata such as collection dates and geographic locations. This approach enabled the curation of a dataset suitable for regional comparative analysis of virulence marker distribution. A comprehensive data analysis was conducted via Kleborate v.3.1.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/klebgenomics/Kleborate.git\u003c/span\u003e\u003cspan address=\"https://github.com/klebgenomics/Kleborate.git\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to investigate the global distributions of virulence-associated genes, STs, and AMR genes. While other genes, such as \u003cem\u003eybt\u003c/em\u003e and \u003cem\u003eclb\u003c/em\u003e, contribute to virulence, they are also frequently found in classical Kp strains, making them less specific markers for hypervirulence. A dataset of ~\u0026thinsp;12,000 hvKp genomes from the NCBI database (as of 14-10-2024) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/pathogens/isolates/#taxgroup_name:%22Klebsiella%20pneumoniae%22\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/pathogens/isolates/#taxgroup_name:%22Klebsiella%20pneumoniae%22\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was analysed to examine the presence and spread of known virulence determinants. The distribution of \u003cem\u003epeg-344\u003c/em\u003e was determined via BLAST alignment against the reference sequence from the NTUH-K2044 Kp plasmid pK2044 (GenBank accession: AP006726.1). The analysis was conducted with a minimum coverage threshold of 100% and an identity threshold of 90%, considering only the highest-scoring hits. The kleborate-derived data for \u003cem\u003ermpA, rmpA2, iucA\u003c/em\u003e and \u003cem\u003eiroB\u003c/em\u003e were stratified by geographic region, including Europe, South Asia, East Asia, Southeast Asia, Middle East Asia, Africa, North America, South America, and Oceania, to examine regional variations in the prevalence of these markers. Additionally, strains were classified into two groups: Group A, consisting of STs previously established in multiple studies as strongly associated with hvKp (ST23, ST25, ST375, ST65, and ST86) [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], and Group B, comprising all other STs that are primarily CRKps but can acquire virulence factors over time. This classification distinguishes intrinsically hypervirulent lineages from those that secondarily acquire virulence factors. Using this classification, we analysed the prevalence of strains in each group to understand the extent of convergence between virulence and resistance.\u003c/p\u003e\u003cp\u003eTo further investigate the distribution of virulence genes among STs, we visualized the presence of key markers (\u003cem\u003ermpA, rmpA2, iucA, iroB\u003c/em\u003e and \u003cem\u003epeg-344\u003c/em\u003e) across different STs via a heatmap. The visualization was generated via Python (version 3.12.3) with several libraries: Masilea (version 0.5.3; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s13059-024-03469-3\u003c/span\u003e\u003cspan address=\"10.1186/s13059-024-03469-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) for creating structured heatmaps, Pillow (version 11.2.1) for image processing, Pandas (version 2.3.0; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5281/zenodo.3509134\u003c/span\u003e\u003cspan address=\"10.5281/zenodo.3509134\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) for data manipulation, and Matplotlib (version 3.10; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1109/MCSE.2007.55\u003c/span\u003e\u003cspan address=\"10.1109/MCSE.2007.55\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) for plotting. The regional distribution of these STs was also analysed to assess geographical variations, and capsular (K) locus diversity was examined, given its association with hypervirulent and resistant isolates. A combination of virulence genes has been widely accepted as a biomarker of hvKp; therefore, multiple genes were cooccurring to understand the prevalence within the dataset.\u003c/p\u003e\u003cp\u003eTo assess the regional distribution of virulence-associated genes, a chi-square (χ\u0026sup2;) test of independence was performed to evaluate whether the observed gene frequencies across geographic regions significantly deviated from those expected under random distribution. The expected values were calculated on the basis of the total number of isolates per region and the overall prevalence of each virulence gene in the dataset. Separate tests were performed for each geographic region, and to account for multiple comparisons across nine regions, the Benjamini\u0026ndash;Hochberg procedure was applied to control the false discovery rate at 5%. The significance threshold was set at adjusted p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Statistical analysis was performed via SPSS (v 29), with multiple testing correction carried out in R (v 4.5.1).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eAnalysis revealed that the distribution of core virulence-associated genes varied significantly across geographic regions (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). The prevalence percentages represent the proportion of genomes from each region that carried the respective virulence gene. The final dataset included 12,961 genomes (see \u003cstrong\u003eSupplementary Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/strong\u003e), with the following regional breakdown: East Asia (n\u0026thinsp;=\u0026thinsp;7004), North America (n\u0026thinsp;=\u0026thinsp;1967), Europe (n\u0026thinsp;=\u0026thinsp;1869), South Asia (n\u0026thinsp;=\u0026thinsp;803), Southeast Asia (n\u0026thinsp;=\u0026thinsp;661), the Middle East (n\u0026thinsp;=\u0026thinsp;356), Oceania (n\u0026thinsp;=\u0026thinsp;143), Africa (n\u0026thinsp;=\u0026thinsp;85), and South America (n\u0026thinsp;=\u0026thinsp;73) (see \u003cstrong\u003eSupplementary Table \u003cspan class=\"InternalRef\"\u003eS2\u003c/span\u003e\u003c/strong\u003e). On the basis of virulence marker profiles, the majority of isolates (10,064/12,489; 80.5%) presented partial profiles with fewer than five core markers, whereas 2,425 isolates (18.7% of the total 12,961) presented all five markers (\u003cem\u003ermpADC, rmpA2, iucA, iroB, and peg-344\u003c/em\u003e). Notably, aerobactin (\u003cem\u003eiucA\u003c/em\u003e) exhibited the highest prevalence across all regions, consistently exceeding 90%, as expected because the dataset was filtered for \u003cem\u003eiucA\u003c/em\u003e-positive genomes, with the highest occurrence in South Asia (99.1%). The \u003cem\u003ermpA2\u003c/em\u003e gene had the highest prevalence in the Middle East (83.7%) and East Asia (83.5%) but was markedly lower in South America (15.1%). The \u003cem\u003ermpADC\u003c/em\u003e locus followed a similar trend, being most common in East Asia (61.7%) and Oceania (68.5%), whereas its occurrence was minimal in the Middle East (23.6%) and South Asia (22.2%). The prevalence of \u003cem\u003eiroB\u003c/em\u003e varies widely. The highest percentages were observed in South America (70%), Oceania (62.2%) and Southeast Asia (51.7%), whereas the percentages were particularly low in the Middle East (5.0%) and North America (9.5%). The BLAST results for \u003cem\u003ePeg-344\u003c/em\u003e revealed substantial regional variation, peaking in North America (82.9%), the Middle East (80.6%), and Africa (83.5%), whereas it was lower in South Asia (49.3%) and South America (26%). These findings suggest distinct regional patterns of virulence gene distribution, with certain markers such as \u003cem\u003eiucA\u003c/em\u003e consistently present at high frequencies. In contrast, others, including \u003cem\u003epeg-344\u003c/em\u003e, \u003cem\u003ermpADC, rmpA2\u003c/em\u003e, and \u003cem\u003eiroB\u003c/em\u003e, exhibited greater localized prevalence (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cstrong\u003eand Supplementary Table\u0026nbsp;3\u003c/strong\u003e). Among other virulence determinants, \u003cem\u003eybt\u003c/em\u003e was widespread, particularly in East Asia, South Asia, and the Middle East. In contrast, \u003cem\u003eclb\u003c/em\u003e, encoding colibactin, was the least detected virulence factor, with the prevalence remaining below 25% across all regions. These distributions highlight that while \u003cem\u003eiucA\u003c/em\u003e is nearly ubiquitous, markers such as \u003cem\u003epeg-344, rmpADC, rmpA2\u003c/em\u003e, and \u003cem\u003eiroB\u003c/em\u003e, which are critical to the updated definition of convergent isolates, exhibit highly uneven regional representation.\u003c/p\u003e\n\u003cp\u003eThe \u0026chi;\u0026sup2; analysis revealed significant regional variations in the distribution of virulence genes, with deviations assessed against expected frequencies under a random distribution. iucA, as expected owing to the selection criterion, along with \u003cem\u003eiro, rmpADC\u003c/em\u003e, and \u003cem\u003ermpA2\u003c/em\u003e, showed statistically significant differences in most regions after Benjamini\u0026ndash;Hochberg correction for multiple testing (adjusted p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), except for Oceania (adjusted p\u0026thinsp;=\u0026thinsp;0.222), where no significant difference was observed. The \u003cem\u003eiucA\u003c/em\u003e prevalence was highest in South Asia (53.1%) and North America (50.8%), whereas it peaked in South America (32.9%) and Southeast Asia (22.8%). \u003cem\u003ermpADC\u003c/em\u003e and \u003cem\u003ermpA2\u003c/em\u003e had the highest prevalence in East Asia (22.1% and 29.9%) and North America (35.2%), respectively. These results highlight pronounced regional disparities in the distribution of core virulence markers, which likely influence the geographic patterns of convergent isolates carrying four or more markers in combination with resistance determinants (see Supplementary Table S9).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurthermore, hvKp strains harboring all five virulence genes (n\u0026thinsp;=\u0026thinsp;2425) were categorized into two groups. Group A comprised STs historically and strongly associated with intrinsic hvKp (ST23, ST25, ST65, ST86, ST375, and ST1660), whereas Group B included all other STs, primarily classical CR-Kp, with the potential to acquire virulence determinants. This classification allowed us to investigate the pathotype distribution of hvKp and hv-CRKp/CR-hvKp isolates across different geographic regions \u003cstrong\u003e(\u003c/strong\u003eFig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cstrong\u003e)\u003c/strong\u003e. Group A, representing intrinsic hvKp lineages, constituted the majority of cases across most regions. Group B, which included convergent hv-CRKp/CR-hvKp isolates, accounted for a relatively small proportion, with relatively high frequencies in North America, Europe, and South Asia (see \u003cstrong\u003eSupplementary Tables S4\u003c/strong\u003e and \u003cstrong\u003eS5\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThese findings indicate that Group A lineages, such as ST23, which harbour the complete set of virulence determinants, represent the true hypervirulent clones. In contrast, Group B lineages, including high-risk CR-Kps such as ST147, do not carry the full virulence gene repertoire but are increasingly acquiring subsets of virulence markers and can thus be described as virulence marker-associated CR-Kps. To complement the geographic and prevalence analyses, we performed a detailed STwise assessment of virulence gene distribution (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB), providing insights into lineage-specific patterns. To further investigate convergence globally, we analysed the STs of \u003cem\u003eK. pneumoniae\u003c/em\u003e genomes across nine regions. A total of 20 predominant STs were identified (\u003cstrong\u003eSupplementary Table S6\u003c/strong\u003e), with representative counts including ST11 (n\u0026thinsp;=\u0026thinsp;3,665, East Asia), ST23 (n\u0026thinsp;=\u0026thinsp;760, East Asia), and ST147 (n\u0026thinsp;=\u0026thinsp;737, North America) (\u003cstrong\u003eSupplementary Table S7\u003c/strong\u003e). These STs were further grouped into (1) classical hypervirulent STs (e.g., ST23, ST65, and ST86) and (2) high-risk carbapenem-resistant STs (e.g., ST11, ST15, ST147, and ST2096), enabling assessment of virulence marker acquisition across both categories.\u003c/p\u003e\n\u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA\u0026ndash;C provides an integrated view of the STwise virulence gene distribution, geographic prevalence, and K locus diversity across both groups. As expected, Group A lineages (e.g., ST23, ST65, ST86, ST375, and ST1660) consistently carried the full complement of virulence determinants (\u003cem\u003ermpADC, iroB, and iucA\u003c/em\u003e). The Group B lineages, while not classical hvKp types, also harboured all five virulence genes, indicating that multiple nonclassical STs have acquired the complete hypervirulence repertoire. This framework allowed us to examine whether classical hvKp lineages are more prone to acquiring resistance or, conversely, whether nonclassical STs are increasingly taking up full virulence, either alone or in combination with carbapenem resistance.\u003c/p\u003e\n\u003cp\u003eThe heatmap further highlights that aerobactin (\u003cem\u003eiucA)\u003c/em\u003e is conserved across both groups, emphasizing its central role in hypervirulence. Geographic analysis revealed lineage-specific enrichment: ST11 in East Asia, ST147 in North America and Europe, ST231 in South and Southeast Asia, ST2096 in the Middle East, and ST86 in Oceania. Capsule types KL1 and KL2 were predominantly associated with classical hvKp lineages (Group A), which is consistent with their complete virulence gene load and established links to community-acquired infections. In contrast, KL64 and KL51 were more common among nonclassical hvKp lineages (Group B), including ST231 and ST147, reflecting lineages where hypervirulence coexists with emerging resistance traits (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eC, \u003cstrong\u003eSupplementary Table S8\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003eAnalysis of virulence marker combinations further reinforced these distinctions. Among the isolates carrying two markers, \u003cem\u003ermpA2\u003c/em\u003e and \u003cem\u003eiucA\u003c/em\u003e were the most common, whereas the isolates with three markers predominantly carried \u003cem\u003ermpA, rmpA2\u003c/em\u003e, and \u003cem\u003eiucA\u003c/em\u003e (\u003cstrong\u003eSupplementary Fig.\u0026nbsp;1\u003c/strong\u003e). Together, these findings underscore a strong correlation between lineage, virulence gene carriage, and capsular diversity: classical hvKp lineages retain conserved virulence signatures, whereas nonclassical hvKp/virulence marker-associated CRKp lineages exhibit greater genomic plasticity, likely driven by selective pressures in healthcare environments.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur findings underscore that classical hvKp lineages maintain conserved virulence traits, whereas certain nonclassical lineages have also acquired the full set of hypervirulence genes and can be classified as hvKp as per the recent definition. The distribution of these lineages is region specific, and several high-risk STs show simultaneous carriage of virulence determinants and carbapenem resistance, highlighting the need for vigilant surveillance, particularly in hospital settings. These results underscore the importance of detecting complete virulence gene repertoires across Kp strains, including both classical and nonclassical hvKp, in the context of geographic variability and plasmid-mediated gene integration. Understanding these distribution patterns is crucial for early diagnosis, as hypervirulence traits can significantly impact disease severity and patient outcomes, particularly in regions with a high burden of multidrug-resistant strains [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Among these markers, genes encoding siderophores, such as aerobactin (\u003cem\u003eiucA\u003c/em\u003e), remain consistently conserved across both classical and nonclassical hvKp lineages, highlighting their central role in pathogenic potential [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. While \u003cem\u003eiucA\u003c/em\u003e alone does not define hypervirulence, its presence is a stable component of the hvKp signature and serves as a useful target for molecular diagnostics [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In contrast, the loss of \u003cem\u003epeg-344\u003c/em\u003e, or mutations in key hypervirulence regulators such as \u003cem\u003ermpADC\u003c/em\u003e and \u003cem\u003ermpA2\u003c/em\u003e in certain carbapenem-resistant lineages, indicates shifts in the genetic architecture of virulence marker-associated CRKps. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e provides a detailed summary of the defining features of these pathotypes.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFeatures of the significant characteristics of Kp, hvKp, hv-CRKp, and CR-hvKp on the basis of plasmid type, virulence genes, antibiotic resistance, and STs\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFeature\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKp\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ehvKp\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCR-hvKp\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehv-CRKp\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMucoid/String Test\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMucoid (String Negative)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHypermucoid (String Positive)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eString Positive or Negative\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eString Positive or Negative\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePlasmid Types\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eResistance plasmids (e.g., IncFII, IncL/M, IncR, IncHI1B, IncFIB and IncFIIK, ColKp3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLarge virulence plasmids (pLVPK, SGH10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003epLVPK, resistance plasmids (e.g., IncFII, IncN, IncHI1B, IncFIB and IncFIIK)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eResistance plasmids (e.g., IncFII, IncL/M, IncR, IncHI1B, IncFIB and IncFIIK) with or without pLVPK\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eK Locus\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRegionally varies\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eK1, K2, K20, K57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eK1, K2, K64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eK64, others\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSequence Types\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eE.g., ST11, ST14, ST258, ST231, ST147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eE.g., ST23, ST25, ST65, ST86, ST375, ST1660\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eE.g., ST23, ST65, ST86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eST11, ST15, ST2096, ST231, ST147\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePrevalence\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGlobal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEast Asia (China), South East Asia, Europe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGlobal, with notable cases in North America, the Middle East, East Asia (China)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eGlobal, with notable cases in South Asia (India), Europe and East Asia\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eIn silico analyses confirmed that \u003cem\u003eiucA\u003c/em\u003e is structurally stable, highlighting it as a key determinant of virulence in Kp [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Other key virulence genes (\u003cem\u003ermpA, rmpA2, iroB\u003c/em\u003e, and \u003cem\u003epeg-344\u003c/em\u003e) display relatively low stability, and their presence contributes to pathogenicity. While aerobactin is stable and often present, strains carrying only a subset of the five virulence markers likely exhibit lower overall virulence and reduced metastatic potential than strains harboring the complete hvKp signature. The functional impact of incomplete virulence profiles requires further in vivo validation, particularly to assess their pathogenicity and potential for dissemination. The incorporation of all five markers into multigene surveillance frameworks enables more accurate detection of hypervirulent and carbapenem-resistant strains, supporting targeted monitoring in clinical and epidemiologic contexts.\u003c/p\u003e\u003cp\u003eThe vaccine candidates, such as Kleb4V (LimmaTech Biologicals AG/GSK), a \u003cem\u003eP. aeruginosa\u003c/em\u003e exotoxin protein A recombinant bioconjugate that targets O-antigens (O1, O2a, O2afg, O3b), KlebVax (SSVI and WRAIR), a 24-valent K antigen unconjugated vaccine that targets capsular polysaccharides and vaccines that target the K2, K3, K10 and K55 mixtures, and unconjugated capsular polysaccharides, have shown promising immunogenicity in phase 1/2 trials [\u003cspan additionalcitationids=\"CR25 CR26 CR27\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. However, our genomic analysis revealed significant regional variability in virulence marker distribution; with the increasing convergence of resistance and virulence plasmids in high-risk STs (e.g., ST147 and ST2096), KL loci, which are responsible for capsular synthesis and immune evasion, are becoming critical contributors to increased pathogenicity. However, these loci are not adequately targeted by current vaccine formulations. In regions such as South Asia and the Middle East, where KL64 and KL51 dominate, and in China, where KL47 and KL64 are prevalent, the current vaccine targets, K1 and K2, offer limited coverage. The incorporation of KL-specific targets in future vaccine strategies is essential for enhancing protection against CR-hvKp in these high-burden regions.\u003c/p\u003e\u003cp\u003eA key limitation of this study is the uneven distribution of genomes across geographic regions, particularly from South America and Africa, where the number of available sequences is limited. Since our findings are based on publicly available genomes in NCBI at the time of analysis, they may not fully represent the global epidemiology of hvKp. Additionally, we did not verify whether \u003cem\u003ermpADC\u003c/em\u003e was chromosomally encoded or plasmid encoded, which is crucial, as plasmid-borne \u003cem\u003ermpA\u003c/em\u003e is prone to loss, potentially affecting hypervirulence expression. Furthermore, our analysis focused on known virulence-associated genes, and emerging or unidentified genetic variants contributing to hypervirulence may not have been captured. Future studies incorporating experimental validation in vitro, followed by animal model studies to confirm the virulence genes or their function in regional isolates, would complement the genomic data, which are needed to address these gaps.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study presents a comprehensive analysis of hvkp and its convergence with carbapenem-resistant strains, highlighting the presence of virulence determinants and its increasing nonendemic nature. We observed substantial geographic and ST-specific variation in the distribution of the key virulence marker \u003cem\u003eiucA\u003c/em\u003e, which was consistently present across all lineages, whereas genes such as \u003cem\u003ermpADC, rmpA2, peg-344\u003c/em\u003e, and \u003cem\u003eiroB\u003c/em\u003e exhibited differential retention, particularly in the virulence marker-associated CRKps, indicating ongoing genomic adaptations. The increasing prevalence of CR-hvKps in hospital settings represents a serious clinical threat, as multidrug-resistant, hypervirulent strains complicate treatment and infection control. Early detection via multigene, region-specific biomarkers is essential for identifying disseminated infections and guiding effective clinical management. These findings underscore the urgent need for enhanced genomic surveillance, refined molecular diagnostics, and targeted therapeutic strategies to mitigate the growing epidemiological and clinical impact of hvKp and CR-hvKp.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflicts of interest\u003c/h2\u003e\u003cp\u003eAll the authors declare that they have no conflicts of interest.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eS.M.K.: Conceptualization; Data curation; Formal analysis; Methodology; Project administration; Resources; Validation; Visualization; Roles/Writing - original draft; Writing - review \u0026amp; editing, J.J.J.: Conceptualization; Project administration; Validation; Visualization; Writing - review \u0026amp; editing, Monisha Priya T: Data analysis; S.R.: Data Curation and analysis, V.N.: Data visualization; Statistical Analysis;K. G.: Formal analysis; Validation;A.B.: Formal analysis; Validation;K.W.: Supervision; Validation; Critical revision. B.V. : Conceptualization; Funding acquisition; Supervision; Validation; Visualization; Review \u0026amp; editing. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors thank the Department of Clinical Microbiology, Christian Medical College and Hospital, Vellore, for providing us with all the necessary facilities to conduct our study. Ms Sanika Mahesh Kulkarni (First author) would also like to extend gratitude to The Tamil Nadu Dr. M.G.R. Medical University, as a registered PhD institution, and acknowledge its support.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGlobal and Regional Prevalence of Hospital-Acquired Carbapenem-Resistant Klebsiella pneumoniae Infection: A Systematic Review and Meta-analysis | Open Forum Infectious Diseases | Oxford Academic [Internet]. 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Vaccine 42(19S1):S125\u0026ndash;S141. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.vaccine.2024.02.072\u003c/span\u003e\u003cspan address=\"10.1016/j.vaccine.2024.02.072\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":false,"email":"","identity":"current-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Current Microbiology","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":false,"inReviewRevisionsEnabled":false},"keywords":"Hypervirulent Klebsiella pneumoniae (hvKp), Virulence genes, Diagnostic biomarkers, Carbapenem resistance, regional variability","lastPublishedDoi":"10.21203/rs.3.rs-7763903/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7763903/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe hypervirulent \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (hvKp) is a clinically significant pathotype. HvKp-related pathotypes are characterized by the presence of multiple key virulence determinants, contributing to severe infections across diverse geographic regions. In contrast, certain carbapenem-resistant \u003cem\u003eK. pneumoniae\u003c/em\u003e (CRKp) lineages carry only a subset of these virulence genes, representing virulence marker-associated CRKp that may acquire additional determinants over time. Several virulence markers, including \u003cem\u003ermpA\u003c/em\u003e, \u003cem\u003ermpA2\u003c/em\u003e, \u003cem\u003eiucA\u003c/em\u003e, \u003cem\u003eiroB\u003c/em\u003e, \u003cem\u003eclb\u003c/em\u003e, \u003cem\u003eybt\u003c/em\u003e, and \u003cem\u003epeg-344\u003c/em\u003e, have been identified as potential diagnostic biomarkers for hvKp detection.\u003c/p\u003e\u003cp\u003eThis study examines the global distribution of five key hvKp virulence genes (\u003cem\u003eiucA, rmpA, rmpA2, iroB\u003c/em\u003e, and \u003cem\u003epeg-344\u003c/em\u003e), comparing classical hvKp lineages with nonclassical hvKp/virulence-marker-associated CRKp lineages. Analysis revealed substantial ST- and region-specific variation in the retention of these markers. These findings underscore the need for multigene, region-specific surveillance strategies to facilitate early detection and guide effective clinical and infection control measures.\u003c/p\u003e","manuscriptTitle":"Regional Distribution of Klebsiella pneumoniae Virulence Genes: Insights from a Comparative Genome Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-04 17:43:03","doi":"10.21203/rs.3.rs-7763903/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-01T12:17:47+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-26T09:11:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"50835376340561168572252447150077072030","date":"2026-03-12T17:33:00+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-07T15:19:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"274931593368757369405521272380484694183","date":"2025-12-04T15:24:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"230072490534197837443066377352606072117","date":"2025-12-03T06:46:36+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-02T12:41:39+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-06T20:06:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-04T08:10:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"Current Microbiology","date":"2025-10-02T05:26:49+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":false,"email":"","identity":"current-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Current Microbiology","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":false,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6eca0f77-8ca2-420c-a6a3-8ab3e47c2c35","owner":[],"postedDate":"December 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-19T02:23:10+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-04 17:43:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7763903","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7763903","identity":"rs-7763903","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}