Genomic Characterization of Multidrug-Resistant Klebsiella pneumoniae Strains from Bovine Mastitis Reveals Extensive Resistome and Virulome Arsenals

Genomic Characterization of Multidrug-Resistant Klebsiella pneumoniae Strains from Bovine Mastitis Reveals Extensive Resistome and Virulome Arsenals | 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 Research Article Genomic Characterization of Multidrug-Resistant Klebsiella pneumoniae Strains from Bovine Mastitis Reveals Extensive Resistome and Virulome Arsenals Kh. Yeashir Arafat, Md Abu Ahsan Gilman, Md. Morshedur Rahman, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7912731/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Klebsiella pneumoniae , a major bovine clinical mastitis (CM) pathogen, carries multidrug resistance (MDR) and virulence factor genes (VFGs), posing serious animal and public health threats. This study screened 27 K. pneumoniae isolates (19 from CM milk and 8 from feces) through culture, biochemical tests, and 16S rRNA -gene sequencing. An overall prevalence of K. pneumoniae was 22.5% (27/120), with a higher rate in milk (27.14%) than feces (16.0%). Antibiogram profiling revealed that all isolates were multidrug-resistant, with high resistance to doxycycline, tetracycline, nalidixic acid, and ampicillin. Three highly resistant isolates (MBBL2, MNH_G2C5, MNH_G2C5F) underwent whole-genome sequencing for comprehensive genomic analysis. Sequence typing (ST), phylogenetic and pangenome analyses assigned MBBL2 and MNH_G2C5F to ST273 and MNH_G2C5 to ST101, clustering with global human- and animal-derived K. pneumoniae strains, and carrying notable strain-specific accessory genes (MNH_G2C5:123; MBBL2/MNH_G2C5F:826). Functional annotation identified abundant genes for carbohydrate metabolism (~ 10%), amino acid transport (~ 9%), and transcription (~ 9%). Resistome analysis identified 29–41 resistance genes, covering 12 antibiotic classes, metals, biocides, and acid stress. Virulence profiling identified 44–60 VFGs involved in adherence, biofilm formation, effector delivery, immune modulation, and metabolism. Genomic plasticity analysis revealed 27–34 variable regions, multiple prophages, 46–58 insertion sequences, and four plasmid replicons. Conserved exopolysaccharide/capsule clusters, secondary metabolites, and high pathogenicity scores (> 0.9) underscored both animal and human pathogenic potential. This study demonstrates that dairy cattle are a reservoir for high-risk MDR clones of K. pneumoniae carrying an extensive resistome and virulome arsenal, highlighting the urgent need for strengthened surveillance and control measures. Animal Science General Microbiology Bacteriology Epigenetics & Genomics Bioinformatics Bovine mastitis K. pneumoniae sequence type pangenome resistome virulence Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction Bovine mastitis, characterized by the inflammation of the mammary gland, stands as one of the most prevalent and economically devastating diseases affecting the global dairy industry [ 1 ]. The condition leads to significant reductions in milk yield and quality, increased veterinary costs, and premature culling, imposing substantial financial losses to the dairy farmers [ 2 , 3 ]. The etiology of bovine mastitis is complex and multifactorial, involving interactions between host, environment, and a diverse range of pathogens [ 1 , 4 ]. Among these pathogens, bacterial agents are the most predominant, with contagious and environmental bacteria being the primary culprits [ 5 ]. Within the spectrum of bacterial pathogens, Gram-negative coliforms, particularly Escherichia coli and K. pneumoniae , are frequently isolated from CM cases [ 6 , 7 ]. While E. coli is often reported as the most common cause, infections with K. pneumoniae are typically more severe, leading to massive udder inflammation, tissue necrosis, and a significantly prolonged recovery period for milk production [ 8 – 10 ]. The host immune response to K. pneumoniae is also notably intense, marked by elevations in pro-inflammatory cytokines [ 8 ]. The challenges in managing K. pneumoniae mastitis are compounded by its ubiquitous presence in the dairy environment, including soil, water, feed, bedding materials, and feces, which serve as reservoirs for udder contamination [ 11 – 15 ]. Furthermore, the bacterium can transmit laterally from infected to healthy cows, facilitating herd-level outbreaks [ 16 , 17 ]. The extensive and often indiscriminate use of antibiotics in livestock has fueled the selection of MDR strains, rendering conventional therapies ineffective [ 18 ]. A critical factor exacerbating the threat of K. pneumoniae is its exceptional ability to develop AMR, which greatly elevates treatment costs and imposes a significant economic burden [ 15 , 19 , 20 ]. While the recent development of a K. pneumoniae mastitis vaccine marks a significant step toward prevention, the continued emergence and persistence of MDR strains highlight the urgent need for comprehensive genomic surveillance and a deeper understanding of their evolution and transmission dynamics [ 11 , 14 , 21 , 22 ]. The pathogenicity of K. pneumoniae is mediated by an arsenal of virulence factors, including capsular polysaccharides, fimbriae for adhesion, and efficient iron-scavenging systems [ 15 , 23 – 25 ]. Of particular concern is the global emergence of MDR and hypervirulent K. pneumoniae clones, posing a serious challenge to both animal and human health. Sequence types ST273 and ST101 are recognized as high-risk lineages combining MDR with enhanced transmissibility and virulence [ 26 , 27 ]. For instance, ST273 strains frequently carry carbapenemases and other resistance genes on mobile plasmids, facilitating rapid dissemination [ 28 ]. Simultaneously, the bacterium’s capsular/exopolysaccharide (EPS/CPS) layer plays a central role in pathogenesis by shielding cells from phagocytosis, complement killing, and antimicrobial peptides, and by promoting persistence and tissue invasion [ 29 ]. Despite extensive research on K. pneumoniae , the genetic basis of virulence and resistance in bovine strains remains poorly understood. This gap is mainly due to their high genomic diversity, frequent gene acquisition and mutation events, and limited inclusion in livestock genomic surveillance, all of which hinder effective monitoring and control measures. Recent advances in high-throughput sequencing, particularly WGS, have provided unprecedented resolution for exploring bacterial genomes. These technologies enable comprehensive analyses of antimicrobial resistance genes (ARGs), virulence factors, sequence types, metabolic pathways, genomic diversity, pangenome dynamics, and mobile genetic elements (MGEs), essential for understanding pathogen evolution, transmission, and adaptation [ 30 – 32 ]. Therefore, this study aimed to comprehensively characterize the genomes of K. pneumoniae isolates associated with bovine CM in Bangladesh. By integrating conventional microbiological techniques with whole-genome sequencing, we sought to (i) determine the prevalence and AMR profiles of K. pneumoniae from milk and fecal samples, and (ii) conduct in-depth genomic analyses to investigate their relatedness, plasticity, resistome, and virulome. The findings will offer valuable insights into the evolution, dissemination, and pathogenic potential of MDR K. pneumoniae within dairy herds, contributing to the development of more effective surveillance and targeted control strategies against this critical mastitis pathogen. Methodology Sample collection, processing and identification of K. pneumoniae A total of 120 samples comprising 70 milk and 50 fecal samples were collected from 70 lactating cows diagnosed with CM. Samples were collected based on visible clinical symptoms, including changes in milk color (reddish or yellowish), udder swelling, redness, and increased temperature, along with a California Mastitis Test (CMT) score of 3, indicating numerous clots [ 33 ]. Sampling was conducted across 50 small-holding dairy farms (each with 5–15 cows) in the Gazipur district (24.09° N, 90.41° E), Bangladesh. The study was conducted during January 2022 to June 2024. The study strictly complied with animal welfare guidelines during sample collection. All procedures were carried out with minimal stress to the animals and under aseptic conditions to ensure hygiene and prevent discomfort. Before milk sampling, teat ends were disinfected to minimize infection risks. Samples (milk and feces) were collected non-invasively, ensuring no harm or undue stress to the cows [ 30 ]. Although formal ethical approval was not required under local regulations in Bangladesh for non-invasive sampling, internationally recognized standards for animal welfare, including the OIE Terrestrial Animal Health Code and FAO guidelines on responsible antimicrobial use in livestock, were followed. Verbal consent was obtained from farmers prior to sample collection, and no interventions beyond routine farm practices were applied. During the morning milking period (8:00–10:00 a.m.), all the samples were collected randomly and approximately 10 mL of milk was aseptically collected from each cow, while 5 g of feces was collected from each farm, using sterile Falcon tubes. Teat ends were disinfected prior to milk sampling, and strict hygiene protocols were maintained throughout the process to ensure sample integrity and minimize contamination [ 34 ]. The fecal samples were homogenized in distilled water at 1:1 ratio. For the isolation and phenotypic identification of K. pneumoniae , samples were first enriched in nutrient broth (Oxoid, UK) and incubated overnight at 37°C. The enriched broth was serially diluted up to 10⁻³ and plated onto Muller Hinton agar (Oxoid, UK) for overnight incubation at 37°C. Subsequently, a single pure colony was streaked onto MacConkey Agar (HiMedia, India) at 37°C for 24 h. Based on colony morphology (pink color, circular) the phenotypic characterization was conducted [ 18 , 35 ]. Gram negative bacilli were identified through Gram straining and series of biochemical tests ( Table S1 ) such as indole, catalase, oxidase, citrate, methyl red, lactose fermentation and Voges-Proskauer (VP) test [ 31 , 36 ]. Gram positive Staphylococcus warneri (Accession: JAQPCE000000000 used as a positive control for biochemical test. Species level identification was performed by using 16S rRNA gene sequencing using 27F (5′-AGAGTTTGATCCTGGCTCAG-3′) and U1492R (5′-CTA-CGGCTACCTTGTTACGA-3′) primers [ 18 , 37 ]. Antimicrobial susceptibility profile of the K. pneumoniae isolates Antimicrobial susceptibility testing (AST) of K. pneumoniae isolates (n = 27) was performed using the Kirby–Bauer disc diffusion method [ 1 ], following Clinical and Laboratory Standards Institute (CLSI) guidelines, M100, 34th edition [ 38 ]. In brief, pure cultures of K. pneumoniae isolates were swabbed onto Mueller–Hinton agar plates (Oxoid, UK), and antibiotic discs were aseptically placed on the inoculated agar. Plates were incubated at 37°C overnight, and the diameters of inhibition zones were measured [ 39 ]. Each assay was conducted in triplicate. The isolates were tested against 15 antibiotics commonly used to treat bacterial infections in humans and animals, including bovine mastitis in Bangladesh. The tested antibiotics included: Tetracyclines (doxycycline, 30 µg; tetracycline, 30 µg), Aminoglycosides (gentamicin, 10 µg; streptomycin, 10 µg), Beta-lactams (ampicillin, 10 µg; oxacillin, 1 µg), Monobactams (aztreonam, 30 µg), Fluoroquinolones (ciprofloxacin, 10 µg; nalidixic acid, 30 µg), Nitrofurans (nitrofurantoin, 300 µg), Carbapenems (imipenem, 10 µg), Chloramphenicol (30 µg), Macrolides (azithromycin, 15 µg), Sulphonamides (sulphonamide compound, 300 µg), and Cephalosporins (cefoxitin, 30 µg). Isolates were classified as resistant (R), intermediate (I), or susceptible (S) according to CLSI guidelines ( File S1 ). Isolates exhibiting resistance to three or more antibiotic classes were defined as multidrug-resistant (MDR). Whole genome sequencing, assembly and annotation of the K. pneumoniae isolates Based on the AST results, three MDR isolates of K. pneumoniae comprising two from milk (MNH_G2C5 and MBBL2) and one from feces (MNH_G2C5F) were selected for subsequent genomic investigation. The high-quality genomic DNA was obtained from nutrient broth cultures using the QIAamp DNA Mini Kit (QIAGEN, Germany) in accordance with the manufacturer’s instructions. DNA libraries were constructed from 1 ng of input DNA using the Nextera XT Kit (Illumina, USA). Whole-genome sequencing (WGS) was then performed on the Illumina MiSeq platform with a 2 × 250 bp paired-end run [ 40 , 41 ]. The quality of raw sequencing reads was assessed using FastQC v0.11.7 [ 42 ], and Illumina adapters, known sequencing artifacts, and phiX reads were removed using Trimmomatic v0.39 [ 43 ]. Genome assembly was carried out with SPAdes v3.15.5 [ 44 ], and annotation was performed using the NCBI Prokaryotic Genome Annotation Pipeline (PGAP) v6.6 [ 45 ] and RAST v2.0 server [ 46 ]. Genome completeness was estimated using CheckM v1.2.3 [ 47 ], while PathogenFinder v1.1 [ 48 ] was employed to estimate the probability of the isolates being human pathogens. Functional genome visualization and annotation were conducted using Genovi v0.2.16 [ 49 ]. All software tools were executed with default parameters unless stated otherwise. Sequence typing and phylogenetic analysis of the K. pneumoniae strains Multi-locus sequence typing (MLST) and core genome MLST (cgMLST) analyses were performed in-silico using BacWGSTdb 2.0 [ 50 ] to determine sequence types and trace the bacterial origin. A grapeTree ( http://achtman-lab.github.io/GrapeTree/MSTree_holder.html ) was used to produce and visualize a minimum spanning tree (MST) based on findings of the cgMLST. Based on cgMLST results, three study genomes (MBBL2, MNH_G2C5, and MNH_G2C5F), along with 49 reference K. pneumoniae genomes from NCBI ( File S2 ), were isolated from 41 humans, 4 domestic dogs, 3 bovines, 3 environmental sources, and 1 pangolin, used for phylogenetic analysis. Single nucleotide polymorphism (SNP) based phylogenetic analysis was performed using Parsnp [ 51 ], where K. pneumoniae strain 11227-1 (Accession: JDWN00000000.1) served as the reference genome. The phylogenetic tree was visualized, and annotated using the Interactive Tree of Life web-tool [ 52 ]. Furthermore, average nucleotide identity (ANI) was calculated using ANIclustermap [ 53 ], with the study genomes (MBBL2, MNH_G2C5, and MNH_G2C5F) and nine closely related K. pneumoniae genomes identified from the phylogenetic analysis (Table S2) . Pangenome analysis of the K. pneumoniae strains To explore the complete genetic repertoire of K. pneumoniae , we performed pangenome analysis using Roary v3.11.2 [ 54 ] on 12 phylogenetically related genomes ( Table S2 ). The genes were categorized into four groups: core (present in 99–100% of strains), soft core (95–99%), shell (15–95%), and cloud (< 15%). Furthermore, pangenome and core genome accumulation curves were constructed these genomes using the PanGP v1.0.1 software [ 55 ]. The analysis modeled new gene discovery as genomes were sequentially added, applying the distance guide algorithm with 100 replicates and 3,000 random genome order permutations. To estimate pangenome size, PanGP [ 55 ] employs a power-law regression model (y = Ax^B + C), where y denotes the total number of gene families, x is the number of genomes, and A, B, and C are model parameters. A value of B between 0 and 1 indicates an open pangenome. For core genome estimation, an exponential decay model (y = Ae^(Bx) + C) was used, with y representing the core genome size and x the number of genomes. Similarly, the rate of new gene acquisition was fitted using a least-squares power-law model (y = Ax^B), where y corresponds to the number of newly identified genes, x to the number of genomes, and A and B are fitting parameters [ 56 ]. Genome plasticity analysis of the K. pneumoniae strains To investigate the mobile genetic elements (MGEs) in MBBL2, MNH_G2C5, MNH_G2C5F, and nine closely related K. pneumoniae genomes ( Table S2 ), multiple bioinformatics tools were employed. Regions of genomic plasticity (RGPs) were identified using panRGP [ 57 ], insertion sequences (ISs) were detected with ISEscan [ 58 ], while prophage regions and plasmids were predicted with PHASTEST [ 59 ] and Platon [ 60 ], respectively. Prediction of antimicrobial resistance and virulence in K. pneumoniae strains To characterize the antimicrobial resistance and virulence potential of the 12 closely related K. pneumoniae genomes ( Table S2 ), including the study genomes, multiple specialized databases and tools were applied. Antibiotic resistance genes (ARGs) were predicted using the Comprehensive Antibiotic Resistance Database (CARD) [ 61 ] and AMRFinderPlus [ 62 ]. Virulence-associated genes (VFGs) were identified against the Virulence Factor Database (VFDB) [ 63 ] implemented in ABRicate ( https://github.com/tseemann/abricate ) with default settings. Genomic islands, representing horizontally acquired regions, were detected using IslandViewer4 [ 64 ]. In addition, plasmid replicons were identified with the staramr tool [ 65 ] which integrates PlasmidFinder [ 66 ] to scan genome assemblies for plasmid-derived sequences. Genomic functional analysis in K. pneumoniae strains The genomes of MBBL2, MNH_G2C5, and MNH_G2C5F were functionally annotated, and their metabolic pathways were classified using the KEGG database [ 67 ] via the KEGG Automatic Annotation Server [ 68 ]. Secondary metabolite biosynthetic gene clusters were identified with antiSMASH v7.0 [ 69 ]. In addition, antimicrobial proteins and their corresponding genes were predicted using the BAGEL4 web server [ 70 ], and the predicted bacteriocin domains were validated by BLASTp [ 71 ] searches against the non-redundant protein (nr) database. Prediction of the EPS gene operons The sequence of K. pneumoniae genomes was aligned with known EPS coding manipulators through the Basic Local Alignment Search Tool (BLAST) program ( https://blast.ncbi.nlm.nih.gov/Blast.cgi ) to identify the presence of the genes and map the EPS synthesis gene cluster. Statistical analysis We randomly selected 120 samples and prevalence was determined from the observed frequencies without applying any statistical analyses. Descriptive statistics were used to examine the distribution of antimicrobial resistance profile of the study isolates, ARGs and VFGs repertoire of the MBBL2, MNH_G2C5 and MNH_G2C5F genomes. The data from the ASTs were analyzed using one-way analysis of variance (ANOVA) followed by Tukey’s multiple-comparison test. Both ARGs and VFGs data were normalized by Total Sum Scaling (TSS) that uses the total read count for each gene in each sample [ 72 ]. Statistical significance was set for all tests at p ≤ 0.05. Results Prevalence of K. pneumoniae associated with bovine mastitis A total of 27 isolates were confirmed as K. pneumoniae using selective culture media, a series of biochemical tests and 16S rRNA gene sequencing. In biochemical assays, the isolates were positive for catalase, citrate utilization, and lactose fermentation, and negative for indole, oxidase, and methyl red identified as K. pneumoniae . Source-specific evaluation showed a higher prevalence in milk samples (27.1%, 19 isolates) compared to fecal samples (16.0%, 8 isolates). The prevalence was calculated directly from observed frequencies. Antibiogram profile of the K. pneumoniae isolates A total of 27 isolates were tested against fifteen antimicrobial agents, and all isolates demonstrated MDR, exhibiting resistance to 3 ≥ antibiotics ( File S1 ). The highest resistance was recorded for doxycycline (DO) with 21/27 (77.8%) resistant isolates, followed by ampicillin (AMP) and tetracycline (TE), each showing 20/27 (74.1%) resistance. Moderate resistance frequencies of 18/27 (66.7%) were observed for ciprofloxacin (CIP), nalidixic acid (NA), and sulfonamides (S3). Resistance to chloramphenicol (C) and cefoxitin (FOX) was also substantial, observed in 17/27 (63.0%) isolates. Similarly, azithromycin (AZM) and ceftriaxone (CRO) displayed resistance in 16/27 (59.3%) isolates each, while nitrofurantoin (F), oxacillin (OX), and imipenem (IPM) exhibited resistance in 15/27 (55.6%) isolates. Moderate resistance was seen with Streptomycin (S) (14/27, 51.9%), whereas gentamicin (CN) showed the lowest resistance level (9/27, 33.3%) and the highest susceptibility (14/27, 51.9%) ( File S1 ). Notably, three isolates (MBBL2, MNH_G2C5, and MNH_G2C5F) exhibited extensive multidrug resistance, with resistance to 13 of the 15 antibiotics tested. These three MDR isolates were selected for detailed genomic characterization, and their resistance profiles are summarized in Fig. 1 . Genomic features of K. pneumoniae strains The assembled genomes of K. pneumoniae strains MBBL2, MNH_G2C5, and MNH_G2C5F were approximately 5.39 Mbp, 4.59 Mbp, and 5.38 Mbp in size, respectively, each with a GC content of 57.5%. Genome quality assessment indicated high completeness (> 98%) and low contamination (0.82%) for MBBL2 and MNH_G2C5F, whereas MNH_G2C5 exhibited reduced completeness (80.93%) and slightly elevated contamination (2.35%). We predicted 5,341 coding sequences in MBBL2, 4,478 in MNH_G2C5, and 5,311 in MNH_G2C5F. Additionally, the genomes contained 89, 63, and 87 RNA genes, respectively. Further genomic characterization revealed the presence of a single CRISPR array in MBBL2 and MNH_G2C5F, while no CRISPR elements were detected in MNH_G2C5. Functional subsystem classification assigned 393 subsystems to MBBL2, 341 to MNH_G2C5, and 395 to MNH_G2C5F. A detailed summary on the genomic features of these genomes is provided in Table S3 . The circular genome representations of K. pneumoniae strains MBBL2, MNH_G2C5, and MNH_G2C5F, together with their COG-based functional annotations, are shown in Figure S1A and S1B . COG classification assigned genes into 27 functional categories across four major groups. The most abundant category was G (carbohydrate transport and metabolism), comprising 10.3%, 10.0%, and 10.4% of the genes in MBBL2, MNH_G2C5, and MNH_G2C5F, respectively. This was followed by category E (amino acid transport and metabolism; 8.8–9.4%), category K (transcription; 8.9–9.0%), category R (general function prediction only; 6.9–7.2%), and category P (inorganic ion transport and metabolism; ~6%). Additional enriched categories included C (energy production and conversion; 5.0–5.9%), M (cell wall/membrane/envelope biogenesis; 5.8%), and J (translation, ribosomal structure, and biogenesis; 4.7–5.4%). Molecular typing and genomic epidemiology of K. pneumoniae strains To elucidate the global genomic epidemiology of K. pneumoniae , we reconstructed the phylogenetic relationships among three study isolates (MBBL2, MNH_G2C5, and MNH_G2C5F) and 591 global genomes from NCBI GenBank using a seven-gene MLST scheme ( gapA, infB, mdh, pgi, phoE, rpoB, tonB ) (Fig. 2 ). K. pneumoniae strains MBBL2 and MNH_G2C5F were assigned to sequence type 273 (ST273), differing by 97 core genome MLST (cgMLST) alleles, whereas MNH_G2C5 formed a distinct clade within ST101, separated by 747 alleles (Figs. 2 A–C). cgMLST analysis revealed that MBBL2 and MNH_G2C5F clustered with 18 MDR ST273 strains from nine countries, while MNH_G2C5 showed close relatedness to 273 ST101 strains from 32 countries. All study strains exhibited genetic links to both human and animal-derived isolates ( File S1 ). An SNP-based phylogeny, constructed from 50,138 core SNPs across 52 genomes (including 49 reference genomes), placed MBBL2, MNH_G2C5F, and MNH_G2C5 in a clade predominantly composed of human-derived strains, except for one environmental isolate (STIN_94). MBBL2 and MNH_G2C5F co-clustered with clinical strains KP_NORM_BLD_116392 and ARLG-3223, while MNH_G2C5 grouped with C17KP0052, a human bloodstream infection isolate (Fig. 3 , File S2 ). This topology suggested recent common ancestry for MBBL2 and MNH_G2C5F, with MNH_G2C5 representing an earlier divergence. Genomic diversity and strain-specific genes in K. pneumoniae strains To substantiate the phylogenetic relationships and provide high-resolution genomic demarcation of the study isolates, we performed ANI analysis on a curated panel of 12 closely related strains (including study strains), selected based on their phylogenetic proximity from an initial set of 52 global genomes ( Table S2 , Figure S2 ). This analysis robustly confirmed the species-level identity of all three study strains (MBBL2, MNH_G2C5, and MNH_G2C5F), each demonstrating > 98% ANI with established K. pneumoniae reference strains, far exceeding the 95% threshold for species delineation [ 53 ]. The ANI results provided precise quantification of the genetic distances inferred from phylogeny. MBBL2 and MNH_G2C5F were nearly identical (99.9% ANI), whereas MNH_G2C5 showed slightly lower similarity (98.9%), reflecting its more distant phylogenetic position. MBBL2 and MNH_G2C5F exhibited the highest ANI (99.8%) with Kpn223 and KP_NORM_BLD_116392. In contrast, MNH_G2C5 was most closely related (98.9% ANI) to a broader set of strains, including ARLG-3223, Kpn223, KP_NORM_BLD_116392, MNH_G2C5F, MBBL2, 032D, 7008.20, and 5844 ( Table S2 , Figure S2 ). A pangenome analysis was performed on the study genomes (MBBL2, MNH_G2C5, and MNH_G2C5F) together with nine reference genomes ( Table S2 ) to explore their gene repertoire. The pangenome dendrogram revealed that MBBL2 and MNH_G2C5F were closely related to reference K. pneumoniae strains 5844, 032D, and 7008.20, while MNH_G2C5 showed the highest similarity to strains 6072, 11383, and 4254 (Fig. 4 A). We identified 7,873 genes across the 12 K. pneumoniae genomes (Fig. 4 B, Table S4 ). Strain-specific analysis further showed that MBBL2 possessed 1 unique gene and 826 accessory genes, MNH_G2C5 carried 123 unique genes and 234 accessory genes, whereas MNH_G2C5F, notably, contained no unique genes but shared 826 accessory genes (Fig. 4 C, Table S4 ). The new gene accumulation curve (Fig. 4 D) followed a power-law decay ( y = 312.947x − 1.19 , R² = 0.981963), indicating that the number of novel genes declines steadily with the addition of more genomes but does not reach a plateau, consistent with an open genome concept. Similarly, the pangenome expansion curve (Fig. 4 E) also supported an open pangenome model, as the total number of gene clusters continued to rise with each additional genome ( y = 200124x 0 , R² = 0.1), reflecting high genetic diversity. In contrast, the core genome displayed a progressive reduction, best fitted by an exponential decay model ( y = 1358.75e − 0.08x + 2343.19, R² = 0.994518), suggesting gene loss with the inclusion of additional genomes. Genomic plasticity and mobile genetic elements in K. pneumoniae strains To assess the genomic plasticity of 12 phylogenetically related K. pneumoniae genomes, we employed a pangenome-based approach to predict regions of genomic plasticity (RGPs), defined as gene clusters located within highly variable genomic regions. The number of RGPs varied widely across genomes, ranging from 11 in KP_NORM_BLD_116392 to 34 in MNH_G2C5, which harbored the highest count. Notably, MBBL2 and MNH_G2C5F carried an equal number of RGPs (27 each) (Fig. 5 ). The sizes of these regions spanned from approximately 0.26 Mb to 1.061 Mb ( File S3 ). To further explore contributors to genomic plasticity, we examined MGEs, including plasmids, prophages, and ISs. Plasmid profiling revealed four distinct replicon types among the three isolates. Both MBBL2 and MNH_G2C5F harbored IncFIB(K)(pCAV1099-114), IncFII(K), and IncHI1B(pNDM-MAR) plasmids while MNH_G2C5 carried only an IncR plasmid. Prophage counts varied across strains, with some harboring only intact prophages and others carrying a mixture of intact and questionable ones. MNH_G2C5 contained four prophage regions, whereas MBBL2 and MNH_G2C5F each carried two. Across the 12 K. pneumoniae genomes, a total of 816 IS elements were detected, of which 58, 52, and 46 were present in MBBL2, MNH_G2C5F, and MNH_G2C5, respectively ( File S3 ). Resistome repertoire in K. pneumoniae strains Comprehensive resistome analysis of 12 closely related K. pneumoniae genomes highlighted the genomic diversity and adaptability of these strains to multiple stressors, including acid, AMR, biocides, and metals. The three study genomes viz. MNH_G2C5, MBBL2, and MNH_G2C5F carried 41, 30, and 29 resistome genes, respectively (Fig. 6 , File S4 ), all of which included a strong core of acid resistance genes (e.g., asr ). A total of 48 AMR genes, conferring resistance to 12 antibiotic classes, were identified across the three genomes. The AMR gene count was highest in MNH_G2C5F (18), followed by MBBL2 (17) and MNH_G2C5 (13). These genes conferred resistance to aminoglycosides (e.g., aac(3)-IId , aadA5 ), beta-lactams (e.g., blaCTX-M-15 , blaLAP-2 , blaSHV-1 , blaSHV-11 , blaTEM-1 ), trimethoprim (e.g., dfrA1 , dfrA14 , dfrA17 ), phenicols (e.g., oqxA , oqxB , oqxB20 ), tetracyclines (e.g., tet(A) , tet(D) ), sulfonamides (e.g., sul1 , sul2 ), fluoroquinolones (e.g., qnrS1 ), fosfomycin (e.g., fosA ), rifamycin (e.g., arr ), macrolides (e.g., mph(A) ), and efflux pumps (e.g., emrD ), representing a shared resistance core (Fig. 6 ). The qacEdelta1 gene, conferring resistance to quaternary ammonium compounds, was detected in all three strains, suggesting tolerance to common chemical disinfectants. In addition, 34 metal resistance genes were detected in the three genomes. Arsenic resistance genes (e.g., arsC ) were present in all strains, while mercury resistance genes (e.g., merA/C/P/R/T ) were found in MBBL2 and MNH_G2C5F. Notably, copper resistance genes (e.g., pcoA/B/C/D/R/S ) and silver resistance genes (e.g., silA/B/C/E/F/P/R/S ) were exclusive to MNH_G2C5. Furthermore, MNH_G2C5 harbored nine heat resistance genes (e.g., psi-GI , kefB-GI , trxLHR , hdeD-GI , yfdX1/2 , shsP , clpK , hsp20 ) (Fig. 6 , File S4 ). Virulence gene arsenal and mechanistic insights in K. pneumoniae strains Virulence factor gene (VFG) profiles of the three study genomes were analyzed to assess their pathogenic potential. MBBL2 and MNH_G2C5F each harbored 60 VFGs, whereas MNH_G2C5 contained 44. These VFGs were found to facilitate virulence through several distinct mechanisms, including nutritional/metabolic factor, regulation, biofilm, adherence, effector delivery system, antimicrobial activity, immune modulation (Figure S3, File S4) . In all genomes, adherence-related genes represented the largest category, accounting for 26.67% in MBBL2 and MNH_G2C5F and 34.1% in MNH_G2C5. Moreover, MBBL2 and MNH_G2C5F genomes possessed 14 effector delivery system genes (23.33%), 13 nutritional/metabolic genes (21.67%), eight biofilm-related genes (13.33%), four immune modulation genes (6.67%), three regulatory genes (5%), and two antimicrobial activity genes (3.33%). In contrast, MNH_G2C5 contained 13 effector delivery system genes (29.54%), eight biofilm-related genes (18.18%), four genes each for regulation and antimicrobial activity (4.54% each), and lacked immune modulation genes ( Figure S3, File S4 ). Prediction of genomic islands in K. pneumoniae strains Genomic islands (GIs), which are gene clusters frequently acquired through horizontal gene transfer (HGT), were predicted in all three genomes and were found to harbor multiple VFGs and pathogen-associated genes, underscoring their potential role in pathogenicity. In the MBBL2 strain, 37 putative GIs were identified, of which 25 were predicted by SIGI-HMM and 12 by IslandPath-DIMOB, with sizes ranging from 4,035 to 291,727 bp. Among them, ten GIs carried genes associated with either virulence factors (VFs) or AMR. Notably, MBBL2 harbored curated AMR genes, including aac(3)-IId (WP_000557454.1), dfrA17 (WP_001389366.1), mrxA (WP_000004159.1), sul1 (WP_000259031.1), sul2 (WP_001043260.1), ACHL6M_RS25720 (WP_001516695.1), ACHL6M_RS25995 (WP_000503573.1), and ACHL6M_RS26045 (WP_000219391.1). In addition, homologs of resistance genes such as alaS (WP_004174700.1), floR (WP_023300759.1), kexD (WP_004200176.1), tetA (WP_000804064.1), ugd (WP_023328477.1), and ACHL6M_RS08150 (WP_023341379.1) were also identified (Fig. 7 ). In comparison, the MNH_G2C5 strain harbored 38 GIs, with 25 predicted by the SIGI-HMM method and 13 by IslandPath-DIMOB, ranging from 3,010 bp to 46,746 bp in length. Four of these islands contained genes associated with VFs or AMR. MNH_G2C5 carried multiple curated resistance genes, such as PGZ78_RS07210 (WP_001516695.1), PGZ78_RS07200 (WP_000027057.1), dfrA1 (WP_000777554.1), and sul1 (WP_000259031.1), as well as homologs of resistance genes, including tetA (WP_000804064.1), and PGZ78_RS00380 (WP_032419057.1). Notably, one pathogen-associated gene, PGZ78_RS16620 (WP_000376623.1) was also identified (Fig. 7 ). Similarly, MNH_G2C5F contained 39 GIs, comprising 25 predicted by the SIGI-HMM method and 14 by IslandPath-DIMOB, spanning 4,035–190,576 bp, with ten GIs carrying VFs or AMR-related genes. This strain encoded multiple curated resistance genes such as Q2T98_RS25690 (WP_001516695.1), Q2T98_RS25965 (WP_000503573.1), dfrA17 (WP_001389366.1), Q2T98_RS26015 (WP_000219391.1), mrxA (WP_000004159.1), aac(3)-IId (WP_000557454.1), sul1 (WP_000259031.1), and sul2 (WP_001043260.1). It also harbored homologs of resistance genes, including alaS (WP_004174700.1), floR (WP_023300759.1), kexD (WP_004200176.1), tetA (WP_000804064.1), ugd (WP_023328477.1), and Q2T98_RS08145 (WP_023341379.1) (Fig. 7 ). K. pneumoniae strains utilized diverse metabolic pathways to facilitate adaptation and survival The systemic metabolic pathways of gene products in the MBBL2, MNH_G2C5, and MNH_G2C5F genomes were analyzed to better understand how these strains utilized nutrients, interacted with their environment, and influenced health and disease processes. A total of 3,524 genes (68.7%) from MBBL2, 2,973 genes (68.9%) from MNH_G2C5, and 3,514 genes (68.8%) from MNH_G2C5F were successfully annotated and mapped to KEGG pathways, spanning six major categories and forty-one subcategories ( Figure S4 ). Among the major categories, metabolism-related genes were the most abundant (MBBL2 = 1,712; MNH_G2C5 = 1,492; MNH_G2C5F = 1,711), followed by those associated with environmental information processing, genetic information processing, cellular processes, human diseases, and organismal systems. Additionally, 58, 56, and 58 drug (antimicrobial) resistance genes were identified in MBBL2, MNH_G2C5, and MNH_G2C5F, respectively. All three genomes carried a complete biosynthesis of amino acids pathway that contributed to biogenic amine production. Seventeen complete modules related to production of biogenic amine identified in MNH_G2C5, while both MBBL2 and MNH_G2C5F genomes have 21 complete modules which correspond to serine biosynthesis, methionine biosynthesis, histidine biosynthesis and shikimate pathway respectively ( Figure S5 , File S5 ). Further analysis revealed that the three genomes harbored multiple genes influencing cellular community, including 71 quorum sensing genes in MBBL2 and MNH_G2C5F and 63 in MNH_G2C5 (e.g., luxS , qseC , qseB , lsrA , hfq , etc.), as well as biofilm-associated genes homologous to those characterized in Vibrio cholerae (e.g., cysE , wecB , csrA , etc.), Pseudomonas aeruginosa (e.g., gacS , crp , barA , etc.), and Escherichia coli (e.g., glgA , bcsA , rpoS , etc.) ( File S5 ). In addition, both MBBL2 and MNH_G2C5F genomes possessed 45 beta-lactam resistance genes while MNH_G2C5 contained 44 beta-lactam resistance genes. All three genomes also carried five vancomycin resistance genes and five platinum drug resistance genes. Moreover, MBBL2 and MNH_G2C5F harbored 58 cationic antimicrobial peptide (CAMP) resistance genes and seven antifolate resistance genes, compared with 57 and five, respectively, in MNH_G2C5. Moreover, all three genomes possessed 19 genes (e.g., dxr , ACAT , atoB , ispA , uppS , ispE , ispD , dxs ) associated with terpenoid backbone biosynthesis, along with 15 genes (e.g., entA , entB , dhbB , vibB , mxcF , entC , entD , pptT ) related to the biosynthesis of siderophore group nonribosomal peptides. Secondary metabolite gene clusters and human pathogenic potential in K. pneumoniae strains The genomes of MBBL2, MNH_G2C5, and MNH_G2C5F harbored multiple biosynthetic gene clusters (BGCs) linked to secondary metabolites (Fig. 8 ). MBBL2 and MNH_G2C5 contained a redox-cofactor gene cluster, including pqqC , pqqD , and pqqE , involved in pyrroloquinoline quinone (PQQ) biosynthesis. Both genomes also encoded two azole-containing RiPPs (ribosomally synthesized and post-translationally modified peptides) encoded by pflA and ycaO (Figs. 8 A and 8 C). Moreover, MBBL2 and MNH_G2C5F genomes carried an NRP (non-ribosomal peptide)-metallophore gene cluster for enterobactin biosynthesis ( entF , entC , entA ) and a terpene-precursor which is encoded by ispA gene (Figs. 8 A and 8 B). Importantly, all of three genomes possessed a RiPP-like protein dsbA involved in disulfide bond formation (Figs. 8 A-C). Additionally, BAGEL4 analysis identified rlmN ( BmbF ) in K. pneumoniae MNH_G2C5 (Protein ID: MDB1120801.1), a conserved bifunctional rRNA/tRNA methyltransferase experimentally validated at the protein level (PE = 3). The protein showed 100% sequence identity with characterized methyltransferases across multiple K. pneumoniae strains. Besides, MNH_G2C5 genome harbored BmbF (dual-specificity RNA methyltransferase RlmN) protein (Protein Id = MDB1120801.1) (Fig. 8 D). Simultaneously, the pathogenicity prediction analysis suggested that all three K. pneumoniae genomes possess a high likelihood of being human pathogens, as evidenced by PathogenFinder scores of 0.901 for MBBL2 and MNH_G2C5F, and 0.911 for MNH_G2C5. These values corresponded to the identification of 322, 255, and 322 pathogenic gene families across these genomes, respectively. EPS and capsule biosynthesis gene clusters in K. pneumoniae strains Further analysis of EPS and capsule biosynthesis clusters in three K. pneumoniae genomes revealed a largely conserved architecture with minor variations (Fig. 9 ). All genomes harbored two EPS/capsule biosynthesis clusters, with the MBBL2 and MNH_G2C5F clusters showing relative similarity. Both MBBL2-C1 and MNH_G2C5F_C1 contained a canonical EPS/capsule cluster, including genes involved in sugar-nucleotide biosynthesis ( ugd, gndA ), glycosyltransferases and tailoring enzymes ( GT, GT2, GT4, wbaP ), regulation and signaling ( wzc, wzb, wcaJ, galF ), and export/translocation (wza, Wzi, EpsG) ( Table S5 ). Notably, MNH_G2C5F_C1 shared nearly all genes with MBBL2-C1, differing only by one or two hypothetical or accessory genes. Conversely, MBBL2-C2 and MNH_G2C5F_C2 contained a distinct EPS-like cluster comprising glycosyltransferases ( wecA, wecF, wecG, rffC, rffM ), polymerization and chain-length control genes ( wzyE, wzzE ), sugar-nucleotide biosynthesis genes ( rffA, rffG, rfbA, wecB, wecC ), and export-associated genes ( wzxE ). These clusters were highly conserved between the genomes, suggesting functional equivalence in polysaccharide assembly. Additionally, MNH_G2C5_C1 carried genes for regulation and signaling (rho), glycosyltransferases (wecA, wecF, rffM), polymerization/chain-length control ( wzyE, wzzE ), sugar-nucleotide biosynthesis ( wecB, wecC, rffG, rfbA, rffA ), and export ( wzxE ). MNH_G2C5_C2 featured a cluster including glycosyltransferases ( GT, GT2, GT4, GT9, kbl, rfaC, rfaF, waaZ, waaA ), accessory enzymes ( tdh ), sugar-nucleotide biosynthesis ( rfaD ), and export ( waaL ) (Fig. 9 , Table S5 ). Discussion The emergence of K. pneumoniae as a major pathogen in bovine mastitis [ 1 , 14 , 23 ] represents a significant challenge to both animal welfare and public health due to its potential for zoonotic transmission and MDR [ 23 , 73 ]. This study provides a comprehensive genomic characterization of three MDR K. pneumoniae strains isolated from CM milk (MBBL2, MNH_G2C5) and feces (MNH_G2C5F) in the dairy farms of Bangladesh, revealing a complex interplay of AMR, virulence, and genomic plasticity. The high prevalence of K. pneumoniae (22.5%), particularly in milk samples (27.14%), underscores its role as a primary mastitis pathogen. This is consistent with studies from China and the USA, which have reported an increasing incidence of Klebsiella species in bovine CM, often linked to environmental contamination and poor udder hygiene [ 11 , 13 ]. Subsequent AST profiling revealed an alarming resistance scenario, with 86.67% of tested antibiotics ineffective and all 27 isolates classified as MDR. The high resistance to first-line antibiotics like ampicillin, tetracycline, and nalidixic acid mirrors trends observed in human and veterinary medicine worldwide, driven by the selective pressure of antimicrobial misuse [ 20 , 74 ]. To unveil the genetic basis of this high MDR, three isolates (MBBL2, MNH_G2C5, MNH_G2C5F), resistant to 13 (out of 15) antibiotics, were subjected to WGS to characterize their resistome and virulence repertoire. One of the noteworthy findings was the co-circulation of two high-risk K. pneumoniae clones, ST273 (MBBL2, MNH_G2C5F) and ST101 (MNH_G2C5), within the dairy herds of Bangladesh, underscoring their direct relevance to the One Health framework. While ST101 is a well-documented global MDR clone associated with hospital outbreaks in humans and increasingly reported in livestock [ 25 , 75 ], ST273 is less commonly reported but has been linked to severe infections in both humans and animals in Asia [ 76 ]. The phylogenetic proximity of these bovine-derived ST273 isolates to human clinical strains provides compelling evidence for recent cross-species transmission [ 77 ]. Furthermore, the pangenome analysis revealed an open genome, characterized by a large accessory gene pool and a decaying core, a hallmark of K. pneumoniae that facilitates niche adaptation [ 24 ]. The substantial number of strain-specific genes in MNH_G2C5 (ST101) and the nearly identical accessory genome of the ST273 isolates (MBBL2, MNH_G2C5F) underscore how clonal background shapes genomic plasticity. This open pangenome structure promotes the acquisition of MGEs, effectively turning the farm environment into a potential crucible for the evolution of new MDR and virulent variants through HGT [ 27 ]. The diverse resistome observed among the K. pneumoniae strains through integrated phenotypic and genomic analyses reflects strong selective pressures driving genomic plasticity and adaptation. Such heterogeneity suggests frequent HGT and exposure to varied antimicrobial and environmental stressors [ 27 ]. Both MBBL2 and MNH_G2C5F genomes harbored a more extensive arsenal of AMR genes, conferring resistance to critically important beta-lactams and fluoroquinolones. This genetic repertoire is critical for successful MDR clones, and has been extensively documented in human clinical isolates [ 78 ]. The presence of oqxAB and fosA in all three genomes, conferring resistance to chloramphenicol and fosfomycin, is noteworthy as these are often considered last-resort treatments for MDR infections. A recent study from India similarly identified a high prevalence of oqxAB in bovine K. pneumoniae , suggesting a widespread and potentially overlooked resistance mechanism in livestock reservoirs [ 79 ]. Furthermore, the detection of metal and biocide resistance genes ( qacEdelta1 , ars , mer ) indicates adaptation to farm environments where disinfectants and heavy metals are commonly used, a trait increasingly recognized as co-selected with AMR in agricultural settings [ 80 ]. Beyond their resistance traits, the pathogenic potential of these strains is notable, as all genomes were predicted with a high probability (> 0.90) of being human pathogens. The high number of VFGs, particularly those related to adherence and biofilm formation, is crucial for establishing infections in both the bovine udder and human tissues [ 1 , 12 , 15 , 81 ]. The abundance of adherence genes in MNH_G2C5 and the effector delivery system genes in all strains suggest multiple strategies for host colonization and immune evasion. The presence of complete siderophore systems ( e.g. , enterobactin) is a key virulence factor for systemic infection, as recently demonstrated in hypervirulent K. pneumoniae strains of livestock origin [ 82 ]. The high genomic plasticity observed in the study strains underscores their remarkable ability to adapt and evolve in response to selective pressures. The identification of numerous AMR, drug resistance and virulence genes within predicted GIs strongly suggests their acquisition via HGT [ 83 ]. A recent study on K. pneumoniae from dairy farms similarly found that GI-carried genes were major contributors to the strain-specific adaptation and resistance profiles [ 22 ]. The metabolic versatility of the strains, evidenced by the extensive KEGG pathway annotations for amino acid biosynthesis, quorum sensing, and biofilm formation, further explains their ability to thrive in diverse niches, from the bovine gut to the udder [ 1 , 81 ] and potentially the humans [ 12 , 15 ]. The distinct plasmid profiles further highlight the dynamic nature of MGEs; the presence of IncHI1B(pNDM-MAR) and IncFIB(K) plasmids in the ST273 isolates is particularly concerning, as these replicon types are frequently associated with the global dissemination of carbapenem resistance, even though no carbapenem resistance was phenotypically detected in this study [ 26 ]. Analysis of EPS and capsule biosynthesis clusters in the three K. pneumoniae genomes revealed a largely conserved architecture with minor variations, emphasizing their key role in virulence and environmental adaptation [ 84 ]. Core genes involved in capsule export and regulation ( e.g., wza, wzxE ) are essential for assembling a protective capsule that shields the bacterium from phagocytosis, while the extensive repertoire of glycosyltransferases supports biofilm formation [ 1 ]. This is further corroborated by virulence factor analysis, which showed that all three isolates harbor numerous biofilm-associated genes. Collectively, the observed genomic plasticity within EPS clusters underscores the strains’ potential for persistent infections through enhanced immune evasion and biofilm-mediated survival [ 84 , 85 ]. The genomic insights from this study are limited by the small number of sequenced isolates and the absence of in-vitro or in-vivo validation of the predicted resistance and virulence determinants. Further investigations are necessary to confirm the pathogenic potential and zoonotic risk posed by these high-risk K. pneumoniae clones. Conclusions This in-depth genomic investigation reveals that K. pneumoniae strains from bovine CM-associated milk and feces are important pathogens harboring high-risk MDR clones (ST101 and ST273). The convergence of a broad resistome, a rich virulome, and significant genomic plasticity in these strains poses a significant threat not only for animal health and production but also a potential reservoir for human infections. These findings emphasize the role of dairy animals in the evolution and dissemination of MDR and hyper-virulent superbugs like K. pneumoniae . This study underscores the urgent need for integrated One Health surveillance strategies that combine genomic epidemiology with robust antimicrobial stewardship in both veterinary and human medicine to mitigate the spread of these ever-challenging pathogens. Declarations Ethical approval The Animal Research Ethics Committee (AREC) of the Gazipur Agricultural University (Gazipur, Bangladesh) reviewed and approved the experimental procedures of this study (reference number FVMAS/AREC/2023/6679 [16 January 2023]). Written informed consent was obtained from each participating dairy farmer prior to the inclusion of their animals in this study, ensuring ethical compliance and voluntary participation. Clinical trial number Not applicable. Consent for publication Not applicable. Conflict of interest The authors declare no conflict of interest. Funding This research was supported by a grant from the Bangladesh Bureau of Educational Information and Statistics (BANBEIS), Ministry of Education, Government of the People’s Republic of Bangladesh (Grant No. LS20221764, duration 2023–2025). Authors contributions M.N.H. conceived and designed the study. K.Y.A, M.A.A.G., M.M.R., N.S. and F.H. performed experiment, curated, analyzed and visualized data, interpreted results, and wrote original draft. M.N.H. critically reviewed and edited the manuscript. The final manuscript was read and approved by all authors. Data availability The 16S rRNA gene sequences of K. pneumoniae strains MBBL2, MNH_G2C5 and MNH_G2C5F have been deposited in NCBI GenBank under accession numbers PX447844, PX447845 and PX447846, respectively. 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BMC Genomics 16(1):964 Hoque MN et al (2022) Induction of mastitis by cow-to-mouse fecal and milk microbiota transplantation causes microbiome dysbiosis and genomic functional perturbation in mice. Anim microbiome 4(1):43 Russo TA et al (2018) Identification of biomarkers for differentiation of hypervirulent Klebsiella pneumoniae from classical K. pneumoniae. J Clin Microbiol 56(9). p. 10.1128/jcm 00776 – 18 Hoque MN et al (2024) Genomic features and pathophysiological impact of a multidrug-resistant Staphylococcus warneri variant in murine mastitis. Microbes Infect 26(3):105285 Follador R et al (2016) The diversity of Klebsiella pneumoniae surface polysaccharides. Microb genomics 2(8):e000073 Xu L et al (2024) Klebsiella pneumoniae capsular polysaccharide: Mechanism in regulation of synthesis, virulence, and pathogenicity. Virulence 15(1):2439509 Additional Declarations The authors declare potential competing interests as follows: The authors declare no conflict of interest. Supplementary Files FigureS1.jpg FigureS1 FigureS2.jpg FigureS2 FigureS3.jpg FigureS3 FigureS4.jpg FigureS4 SupplementaryMaterials.docx Supplementaty Tables S1-S5 FileS1.xlsx File S1 FileS2.xlsx File S2 FileS3.xlsx File S3 FileS4.xlsx File S4 FileS5.xlsx File S5 Cite Share Download PDF Status: Posted Version 1 posted 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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04:14:01","extension":"html","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":189615,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7912731/v1/68a536c27bf452841eb47464.html"},{"id":94056695,"identity":"344a3c06-ac94-43fe-8d75-17f283e5c406","added_by":"auto","created_at":"2025-10-22 04:22:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":124161,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverall antibiotic resistance profile of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eK. pneumoniae\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e strains MBBL2, MNH_G2C5, and MNH_G2C5F.\u003c/strong\u003e Antibiotics tested include: NA (Nalidixic Acid), F (Nitrofurantoin), S (Streptomycin), CN (Gentamicin), OX (Oxacillin), AZM (Azithromycin), TE (Tetracycline), CIP (Ciprofloxacin), AMP (Ampicillin), CRO (Ceftriaxone), IPM (Imipenem), FOX (Cefoxitin), C (Chloramphenicol), DO (Doxycycline), and S3 (Sulfonamides). Color codes represent susceptibility patterns: green = susceptible, dark blue = intermediate, and red = resistant.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7912731/v1/fef8e2fa1605355bb8a9b1a5.png"},{"id":94056987,"identity":"b12418d9-3542-49c4-ba18-873c2e694755","added_by":"auto","created_at":"2025-10-22 04:38:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2587765,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCore genome multi-locus sequence typing (cgMLST) phylogenetic tree of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eKlebsiella pneumoniae\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e strains MBBL2, MNH_G2C5, and MNH_G2C5F and their nearest relatives.\u003c/strong\u003e The closest relatedness of MBBL2 and MNH_G2C5F was defined at a cgMLST allele threshold of 97, whereas MNH_G2C5 was assigned at a threshold of 747. White circles outlined in purple denote the three study isolates, with sequence types (STs) represented by distinct colors. The white circles outlined in purple correspond to MBBL2, MNH_G2C5 and MNH_G2C5F strains and the ST of each isolate is denoted by different colors. Numbers within the circles indicate the STs, and circle size reflects allelic differences.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7912731/v1/8d1c40269d17c9357ff8013b.png"},{"id":94057140,"identity":"ff8761f6-7bf9-43a9-8df5-e00c52710881","added_by":"auto","created_at":"2025-10-22 04:46:01","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":8362833,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEvolutionary phylogenetic relationship of the \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eK. pneumoniae\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e strains. Maximum-likelihood phylogenetic tree depicting the evolutionary relationships among 52 \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eK. pneumoniae\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e strains based on 50,138 high-quality SNPs derived from concatenated core-genome alignments\u003c/strong\u003e. Recombinant regions were excluded to ensure accurate phylogenetic inference. Genomes were aligned against the reference strain \u003cem\u003eK. pneumoniae\u003c/em\u003e11227-1 (NCBI Accession: JDWN00000000.1). The outer annotation ring illustrates strain-specific metadata, including isolation source, plasmid replicon types, host species, and country of origin, highlighting the genetic diversity and epidemiological distribution of the isolates.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7912731/v1/ee374ceb67071a342c3a4650.jpg"},{"id":94056609,"identity":"7a2da635-601c-4d28-afbb-828a41589bce","added_by":"auto","created_at":"2025-10-22 04:14:01","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2872750,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePangenome analysis of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eK. pneumoniae\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e strains MBBL2, MNH_G2C5, and MNH_G2C5F compared with nine closely related reference genomes. \u003c/strong\u003e(A) Gene presence/absence matrix based on pangenome clustering, with red squares indicating the three strains of interest. (B) Distribution of gene counts across the 12 genomes. (C) Flower plot showing the core genome (center), accessory genome (outer ring), and strain-specific unique genes (petals), with the three focal strains boxed in red. (D) Bar plot illustrating the number of novel genes added with each additional genome. (E) Gene accumulation curves depicting the expansion of the pangenome (blue) and reduction of the core genome (orange) as more genomes were included; blue and orange boxes denote estimated pangenome and core genome sizes at each step.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7912731/v1/fe8a25b1c807c257562af0ea.jpg"},{"id":94056701,"identity":"bf319164-b2e2-4898-9cf3-75cf26540c38","added_by":"auto","created_at":"2025-10-22 04:22:01","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":92946,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverview of genomic plasticity regions (RGPs) and mobile genetic elements (MGEs) in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eKlebsiella pneumoniae \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003estrains.\u003c/strong\u003e Genomes of MBBL2, MNH_G2C5, and MNH_G2C5F were compared with nine closely related \u003cem\u003eK. pneumoniae\u003c/em\u003e genomes. For each genome, the figure shows (left to right) total genome size, plasmid size, number of prophages, count of RGPs, and insertion sequence (IS) elements. The three focal genomes (MBBL2, MNH_G2C5, and MNH_G2C5F) are highlighted with a red box.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7912731/v1/0ac9f18d2e074077bb6eab82.png"},{"id":94056705,"identity":"7dbe7252-0f6f-4b8f-83d5-2579645b1bc1","added_by":"auto","created_at":"2025-10-22 04:22:01","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":671741,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHeatmap illustrating antimicrobial resistance determinants, along with acid, biocide, and metal resistance genes across 12 \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eK. pneumoniae \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003egenomes\u003c/strong\u003e. The first row indicates color codes for the resistome repertoire: yellow for acid resistance, mint blue for antimicrobial resistance (AMR), dark blue for biocide resistance, and red for metal resistance. Antibiotic and metal classes are color-coded in the legend (right column). The three focal genomes (MBBL2, MNH_G2C5, and MNH_G2C5F) are highlighted with red boxes in the left column.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7912731/v1/704b95c45ebc6cd673733572.jpg"},{"id":94056640,"identity":"da39a6a6-27fd-4ee9-8f7a-6571a750ebc7","added_by":"auto","created_at":"2025-10-22 04:14:02","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":4388811,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverview of predicted genomic islands (GIs) and their functional gene annotations in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eK. pneumoniae\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e strains MBBL2, MNH_G2C5, and MNH_G2C5F. \u003c/strong\u003eGenomic islands identified by the integrated method are shown in red, while predictions from IslandPath-DIMOB and SIGI-HMM are indicated in blue and orange, respectively. Functional genes are represented by colored circles: curated virulence factors (VFGs) in purple, VFG homologues in lavender, curated resistance genes (AMR) in red, AMR homologues in pink, and pathogen-associated genes (PAGs) in yellow.\u003c/p\u003e","description":"","filename":"Figure7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7912731/v1/3fee0f86e86ff8e3a3f0649c.jpg"},{"id":94056900,"identity":"44e85229-1c54-4787-a9ac-a9a016b08978","added_by":"auto","created_at":"2025-10-22 04:30:01","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":845840,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverview of the secondary metabolites biosynthesis gene clusters in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eK. pneumoniae\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e (A) MBBL2, (B) MNH_G2C5 and (C) MNH_G2C5F genomes.\u003c/strong\u003e Different colors represent genes involved in different functions: red color for core biosynthesis genes, dark pink color for additional biosynthesis genes, sky blue color for transport-related genes, dark green color for regulatory genes, gray color for other genes and ash color for resistance. (D) Overview of the BmbF (Dual-specificity RNA Methyltransferase RlmN) protein in \u003cem\u003eK. pneumoniae \u003c/em\u003eMNH_G2C5.\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-7912731/v1/f85e45230937e28c4f142079.png"},{"id":94056709,"identity":"f850667c-8713-424c-b51d-9ce449250fa2","added_by":"auto","created_at":"2025-10-22 04:22:01","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":149740,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEPS gene clusters of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eK. pneumoniae \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003estrains\u003c/strong\u003e MBBL2 (MBBL2_C1 and MBBL2_C1), MNH_G2C5 (MNH_G2C5_C1 and MNH_G2C5_C2), and MNH_G2C5F (MNH_G2C5F_C1 and MNH_G2C5F_C1). Different colors indicate the different functions of genes.\u003c/p\u003e","description":"","filename":"Figure9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7912731/v1/4245e2c38b28db0fe245a407.jpg"},{"id":94333920,"identity":"3e815f88-8271-4a0e-9b4c-f07d933546dc","added_by":"auto","created_at":"2025-10-27 12:23:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":18773585,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7912731/v1/41ef59b6-10dd-41c3-b26e-cff5e0c0e589.pdf"},{"id":94056988,"identity":"c3fc05a4-cdcb-4180-a2c2-fc45fcf8645e","added_by":"auto","created_at":"2025-10-22 04:38:01","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":4655702,"visible":true,"origin":"","legend":"\u003cp\u003eFigureS1\u003c/p\u003e","description":"","filename":"FigureS1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7912731/v1/8f3296e02a107f2cffab092c.jpg"},{"id":94056893,"identity":"5d3c2051-7b72-492f-9d16-1e442095a55c","added_by":"auto","created_at":"2025-10-22 04:30:01","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":537409,"visible":true,"origin":"","legend":"\u003cp\u003eFigureS2\u003c/p\u003e","description":"","filename":"FigureS2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7912731/v1/39672a044dfd73ca211f6b4e.jpg"},{"id":94056891,"identity":"98cd69a1-02bc-436c-9c7f-ea25acdf7fcb","added_by":"auto","created_at":"2025-10-22 04:30:01","extension":"jpg","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":147077,"visible":true,"origin":"","legend":"\u003cp\u003eFigureS3\u003c/p\u003e","description":"","filename":"FigureS3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7912731/v1/15919dfff668be0cc6cab78e.jpg"},{"id":94056711,"identity":"867d310c-b8f1-45a8-92a3-2948e7d4b08e","added_by":"auto","created_at":"2025-10-22 04:22:01","extension":"jpg","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":14012240,"visible":true,"origin":"","legend":"\u003cp\u003eFigureS4\u003c/p\u003e","description":"","filename":"FigureS4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7912731/v1/547dcd6f48b645523b321e29.jpg"},{"id":94056617,"identity":"9ece6bd4-ca06-4944-b1d2-7ad90d8e1a29","added_by":"auto","created_at":"2025-10-22 04:14:01","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":1031020,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementaty Tables S1-S5\u003c/p\u003e","description":"","filename":"SupplementaryMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-7912731/v1/4a2236bdb9e8f231d60f8baa.docx"},{"id":94056895,"identity":"cbc2a8eb-f31c-4145-b214-30e9e1f9227f","added_by":"auto","created_at":"2025-10-22 04:30:01","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":69057,"visible":true,"origin":"","legend":"\u003cp\u003eFile S1\u003c/p\u003e","description":"","filename":"FileS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7912731/v1/c08198d97d115178b8e4041d.xlsx"},{"id":94056897,"identity":"b686e433-9b3c-484f-9d68-fc0e5c67a6ac","added_by":"auto","created_at":"2025-10-22 04:30:01","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":23327,"visible":true,"origin":"","legend":"\u003cp\u003eFile S2\u003c/p\u003e","description":"","filename":"FileS2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7912731/v1/f4d5b518c74196d936a45e48.xlsx"},{"id":94056622,"identity":"a9a99c76-d2e0-440a-ad8c-54c47966cc0b","added_by":"auto","created_at":"2025-10-22 04:14:01","extension":"xlsx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":44336,"visible":true,"origin":"","legend":"\u003cp\u003eFile S3\u003c/p\u003e","description":"","filename":"FileS3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7912731/v1/6ed0a7eb9db18c7d697bb609.xlsx"},{"id":94056714,"identity":"556b7ee5-46d9-429b-9616-3f5b52465e5d","added_by":"auto","created_at":"2025-10-22 04:22:02","extension":"xlsx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":20703,"visible":true,"origin":"","legend":"\u003cp\u003eFile S4\u003c/p\u003e","description":"","filename":"FileS4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7912731/v1/ed751a8516ae2d7b49d0a836.xlsx"},{"id":94056990,"identity":"d41e0f7c-89b4-445b-bcc1-4877b2c69bd0","added_by":"auto","created_at":"2025-10-22 04:38:01","extension":"xlsx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":31277,"visible":true,"origin":"","legend":"\u003cp\u003eFile S5\u003c/p\u003e","description":"","filename":"FileS5.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7912731/v1/455ad9a41cfccc6b1b2e3949.xlsx"}],"financialInterests":"The authors declare potential competing interests as follows: The authors declare no conflict of interest.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eGenomic Characterization of Multidrug-Resistant \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eKlebsiella pneumoniae \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eStrains from Bovine Mastitis Reveals Extensive Resistome and Virulome Arsenals\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBovine mastitis, characterized by the inflammation of the mammary gland, stands as one of the most prevalent and economically devastating diseases affecting the global dairy industry [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The condition leads to significant reductions in milk yield and quality, increased veterinary costs, and premature culling, imposing substantial financial losses to the dairy farmers [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The etiology of bovine mastitis is complex and multifactorial, involving interactions between host, environment, and a diverse range of pathogens [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Among these pathogens, bacterial agents are the most predominant, with contagious and environmental bacteria being the primary culprits [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Within the spectrum of bacterial pathogens, Gram-negative coliforms, particularly \u003cem\u003eEscherichia coli\u003c/em\u003e and \u003cem\u003eK. pneumoniae\u003c/em\u003e, are frequently isolated from CM cases [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. While \u003cem\u003eE. coli\u003c/em\u003e is often reported as the most common cause, infections with \u003cem\u003eK. pneumoniae\u003c/em\u003e are typically more severe, leading to massive udder inflammation, tissue necrosis, and a significantly prolonged recovery period for milk production [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The host immune response to \u003cem\u003eK. pneumoniae\u003c/em\u003e is also notably intense, marked by elevations in pro-inflammatory cytokines [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The challenges in managing \u003cem\u003eK. pneumoniae\u003c/em\u003e mastitis are compounded by its ubiquitous presence in the dairy environment, including soil, water, feed, bedding materials, and feces, which serve as reservoirs for udder contamination [\u003cspan additionalcitationids=\"CR12 CR13 CR14\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Furthermore, the bacterium can transmit laterally from infected to healthy cows, facilitating herd-level outbreaks [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe extensive and often indiscriminate use of antibiotics in livestock has fueled the selection of MDR strains, rendering conventional therapies ineffective [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. A critical factor exacerbating the threat of \u003cem\u003eK. pneumoniae\u003c/em\u003e is its exceptional ability to develop AMR, which greatly elevates treatment costs and imposes a significant economic burden [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. While the recent development of a \u003cem\u003eK. pneumoniae\u003c/em\u003e mastitis vaccine marks a significant step toward prevention, the continued emergence and persistence of MDR strains highlight the urgent need for comprehensive genomic surveillance and a deeper understanding of their evolution and transmission dynamics [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The pathogenicity of \u003cem\u003eK. pneumoniae\u003c/em\u003e is mediated by an arsenal of virulence factors, including capsular polysaccharides, fimbriae for adhesion, and efficient iron-scavenging systems [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Of particular concern is the global emergence of MDR and hypervirulent \u003cem\u003eK. pneumoniae\u003c/em\u003e clones, posing a serious challenge to both animal and human health. Sequence types ST273 and ST101 are recognized as high-risk lineages combining MDR with enhanced transmissibility and virulence [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. For instance, ST273 strains frequently carry carbapenemases and other resistance genes on mobile plasmids, facilitating rapid dissemination [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Simultaneously, the bacterium\u0026rsquo;s capsular/exopolysaccharide (EPS/CPS) layer plays a central role in pathogenesis by shielding cells from phagocytosis, complement killing, and antimicrobial peptides, and by promoting persistence and tissue invasion [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Despite extensive research on \u003cem\u003eK. pneumoniae\u003c/em\u003e, the genetic basis of virulence and resistance in bovine strains remains poorly understood. This gap is mainly due to their high genomic diversity, frequent gene acquisition and mutation events, and limited inclusion in livestock genomic surveillance, all of which hinder effective monitoring and control measures. Recent advances in high-throughput sequencing, particularly WGS, have provided unprecedented resolution for exploring bacterial genomes. These technologies enable comprehensive analyses of antimicrobial resistance genes (ARGs), virulence factors, sequence types, metabolic pathways, genomic diversity, pangenome dynamics, and mobile genetic elements (MGEs), essential for understanding pathogen evolution, transmission, and adaptation [\u003cspan additionalcitationids=\"CR31\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Therefore, this study aimed to comprehensively characterize the genomes of \u003cem\u003eK. pneumoniae\u003c/em\u003e isolates associated with bovine CM in Bangladesh. By integrating conventional microbiological techniques with whole-genome sequencing, we sought to (i) determine the prevalence and AMR profiles of \u003cem\u003eK. pneumoniae\u003c/em\u003e from milk and fecal samples, and (ii) conduct in-depth genomic analyses to investigate their relatedness, plasticity, resistome, and virulome. The findings will offer valuable insights into the evolution, dissemination, and pathogenic potential of MDR \u003cem\u003eK. pneumoniae\u003c/em\u003e within dairy herds, contributing to the development of more effective surveillance and targeted control strategies against this critical mastitis pathogen.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003e\u003cb\u003eSample collection, processing and identification of\u003c/b\u003e \u003cb\u003eK. pneumoniae\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA total of 120 samples comprising 70 milk and 50 fecal samples were collected from 70 lactating cows diagnosed with CM. Samples were collected based on visible clinical symptoms, including changes in milk color (reddish or yellowish), udder swelling, redness, and increased temperature, along with a California Mastitis Test (CMT) score of 3, indicating numerous clots [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Sampling was conducted across 50 small-holding dairy farms (each with 5\u0026ndash;15 cows) in the Gazipur district (24.09\u0026deg; N, 90.41\u0026deg; E), Bangladesh. The study was conducted during January 2022 to June 2024. The study strictly complied with animal welfare guidelines during sample collection. All procedures were carried out with minimal stress to the animals and under aseptic conditions to ensure hygiene and prevent discomfort. Before milk sampling, teat ends were disinfected to minimize infection risks. Samples (milk and feces) were collected non-invasively, ensuring no harm or undue stress to the cows [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Although formal ethical approval was not required under local regulations in Bangladesh for non-invasive sampling, internationally recognized standards for animal welfare, including the OIE Terrestrial Animal Health Code and FAO guidelines on responsible antimicrobial use in livestock, were followed. Verbal consent was obtained from farmers prior to sample collection, and no interventions beyond routine farm practices were applied. During the morning milking period (8:00\u0026ndash;10:00 a.m.), all the samples were collected randomly and approximately 10 mL of milk was aseptically collected from each cow, while 5 g of feces was collected from each farm, using sterile Falcon tubes. Teat ends were disinfected prior to milk sampling, and strict hygiene protocols were maintained throughout the process to ensure sample integrity and minimize contamination [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The fecal samples were homogenized in distilled water at 1:1 ratio. For the isolation and phenotypic identification of \u003cem\u003eK. pneumoniae\u003c/em\u003e, samples were first enriched in nutrient broth (Oxoid, UK) and incubated overnight at 37\u0026deg;C. The enriched broth was serially diluted up to 10⁻\u0026sup3; and plated onto Muller Hinton agar (Oxoid, UK) for overnight incubation at 37\u0026deg;C. Subsequently, a single pure colony was streaked onto MacConkey Agar (HiMedia, India) at 37\u0026deg;C for 24 h. Based on colony morphology (pink color, circular) the phenotypic characterization was conducted [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Gram negative bacilli were identified through Gram straining and series of biochemical tests (\u003cb\u003eTable S1\u003c/b\u003e) such as indole, catalase, oxidase, citrate, methyl red, lactose fermentation and Voges-Proskauer (VP) test [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Gram positive \u003cem\u003eStaphylococcus warneri\u003c/em\u003e (Accession: JAQPCE000000000 used as a positive control for biochemical test. Species level identification was performed by using \u003cem\u003e16S rRNA\u003c/em\u003e gene sequencing using 27F (5\u0026prime;-AGAGTTTGATCCTGGCTCAG-3\u0026prime;) and U1492R (5\u0026prime;-CTA-CGGCTACCTTGTTACGA-3\u0026prime;) primers [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eAntimicrobial susceptibility profile of the\u003c/b\u003e \u003cb\u003eK. pneumoniae\u003c/b\u003e \u003cb\u003eisolates\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAntimicrobial susceptibility testing (AST) of \u003cem\u003eK. pneumoniae\u003c/em\u003e isolates (n\u0026thinsp;=\u0026thinsp;27) was performed using the Kirby\u0026ndash;Bauer disc diffusion method [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], following Clinical and Laboratory Standards Institute (CLSI) guidelines, M100, 34th edition [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In brief, pure cultures of \u003cem\u003eK. pneumoniae\u003c/em\u003e isolates were swabbed onto Mueller\u0026ndash;Hinton agar plates (Oxoid, UK), and antibiotic discs were aseptically placed on the inoculated agar. Plates were incubated at 37\u0026deg;C overnight, and the diameters of inhibition zones were measured [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Each assay was conducted in triplicate. The isolates were tested against 15 antibiotics commonly used to treat bacterial infections in humans and animals, including bovine mastitis in Bangladesh. The tested antibiotics included: Tetracyclines (doxycycline, 30 \u0026micro;g; tetracycline, 30 \u0026micro;g), Aminoglycosides (gentamicin, 10 \u0026micro;g; streptomycin, 10 \u0026micro;g), Beta-lactams (ampicillin, 10 \u0026micro;g; oxacillin, 1 \u0026micro;g), Monobactams (aztreonam, 30 \u0026micro;g), Fluoroquinolones (ciprofloxacin, 10 \u0026micro;g; nalidixic acid, 30 \u0026micro;g), Nitrofurans (nitrofurantoin, 300 \u0026micro;g), Carbapenems (imipenem, 10 \u0026micro;g), Chloramphenicol (30 \u0026micro;g), Macrolides (azithromycin, 15 \u0026micro;g), Sulphonamides (sulphonamide compound, 300 \u0026micro;g), and Cephalosporins (cefoxitin, 30 \u0026micro;g). Isolates were classified as resistant (R), intermediate (I), or susceptible (S) according to CLSI guidelines (\u003cb\u003eFile S1\u003c/b\u003e). Isolates exhibiting resistance to three or more antibiotic classes were defined as multidrug-resistant (MDR).\u003c/p\u003e\u003cp\u003e\u003cb\u003eWhole genome sequencing, assembly and annotation of the\u003c/b\u003e \u003cb\u003eK. pneumoniae\u003c/b\u003e \u003cb\u003eisolates\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBased on the AST results, three MDR isolates of \u003cem\u003eK. pneumoniae\u003c/em\u003e comprising two from milk (MNH_G2C5 and MBBL2) and one from feces (MNH_G2C5F) were selected for subsequent genomic investigation. The high-quality genomic DNA was obtained from nutrient broth cultures using the QIAamp DNA Mini Kit (QIAGEN, Germany) in accordance with the manufacturer\u0026rsquo;s instructions. DNA libraries were constructed from 1 ng of input DNA using the Nextera XT Kit (Illumina, USA). Whole-genome sequencing (WGS) was then performed on the Illumina MiSeq platform with a 2 \u0026times; 250 bp paired-end run [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The quality of raw sequencing reads was assessed using FastQC v0.11.7 [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], and Illumina adapters, known sequencing artifacts, and phiX reads were removed using Trimmomatic v0.39 [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Genome assembly was carried out with SPAdes v3.15.5 [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], and annotation was performed using the NCBI Prokaryotic Genome Annotation Pipeline (PGAP) v6.6 [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] and RAST v2.0 server [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Genome completeness was estimated using CheckM v1.2.3 [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], while PathogenFinder v1.1 [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] was employed to estimate the probability of the isolates being human pathogens. Functional genome visualization and annotation were conducted using Genovi v0.2.16 [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. All software tools were executed with default parameters unless stated otherwise.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSequence typing and phylogenetic analysis of the\u003c/b\u003e \u003cb\u003eK. pneumoniae\u003c/b\u003e \u003cb\u003estrains\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMulti-locus sequence typing (MLST) and core genome MLST (cgMLST) analyses were performed \u003cem\u003ein-silico\u003c/em\u003e using BacWGSTdb 2.0 [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] to determine sequence types and trace the bacterial origin. A grapeTree (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://achtman-lab.github.io/GrapeTree/MSTree_holder.html\u003c/span\u003e\u003cspan address=\"http://achtman-lab.github.io/GrapeTree/MSTree_holder.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used to produce and visualize a minimum spanning tree (MST) based on findings of the cgMLST. Based on cgMLST results, three study genomes (MBBL2, MNH_G2C5, and MNH_G2C5F), along with 49 reference \u003cem\u003eK. pneumoniae\u003c/em\u003e genomes from NCBI (\u003cb\u003eFile S2\u003c/b\u003e), were isolated from 41 humans, 4 domestic dogs, 3 bovines, 3 environmental sources, and 1 pangolin, used for phylogenetic analysis. Single nucleotide polymorphism (SNP) based phylogenetic analysis was performed using Parsnp [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], where \u003cem\u003eK. pneumoniae\u003c/em\u003e strain 11227-1 (Accession: JDWN00000000.1) served as the reference genome. The phylogenetic tree was visualized, and annotated using the Interactive Tree of Life web-tool [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Furthermore, average nucleotide identity (ANI) was calculated using ANIclustermap [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], with the study genomes (MBBL2, MNH_G2C5, and MNH_G2C5F) and nine closely related \u003cem\u003eK. pneumoniae\u003c/em\u003e genomes identified from the phylogenetic analysis \u003cb\u003e(Table S2)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePangenome analysis of the\u003c/b\u003e \u003cb\u003eK. pneumoniae\u003c/b\u003e \u003cb\u003estrains\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo explore the complete genetic repertoire of \u003cem\u003eK. pneumoniae\u003c/em\u003e, we performed pangenome analysis using Roary v3.11.2 [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e] on 12 phylogenetically related genomes (\u003cb\u003eTable S2\u003c/b\u003e). The genes were categorized into four groups: core (present in 99\u0026ndash;100% of strains), soft core (95\u0026ndash;99%), shell (15\u0026ndash;95%), and cloud (\u0026lt;\u0026thinsp;15%). Furthermore, pangenome and core genome accumulation curves were constructed these genomes using the PanGP v1.0.1 software [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. The analysis modeled new gene discovery as genomes were sequentially added, applying the distance guide algorithm with 100 replicates and 3,000 random genome order permutations. To estimate pangenome size, PanGP [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] employs a power-law regression model (y\u0026thinsp;=\u0026thinsp;Ax^B\u0026thinsp;+\u0026thinsp;C), where y denotes the total number of gene families, x is the number of genomes, and A, B, and C are model parameters. A value of B between 0 and 1 indicates an open pangenome. For core genome estimation, an exponential decay model (y\u0026thinsp;=\u0026thinsp;Ae^(Bx)\u0026thinsp;+\u0026thinsp;C) was used, with y representing the core genome size and x the number of genomes. Similarly, the rate of new gene acquisition was fitted using a least-squares power-law model (y\u0026thinsp;=\u0026thinsp;Ax^B), where y corresponds to the number of newly identified genes, x to the number of genomes, and A and B are fitting parameters [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eGenome plasticity analysis of the\u003c/b\u003e \u003cb\u003eK. pneumoniae\u003c/b\u003e \u003cb\u003estrains\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo investigate the mobile genetic elements (MGEs) in MBBL2, MNH_G2C5, MNH_G2C5F, and nine closely related \u003cem\u003eK. pneumoniae\u003c/em\u003e genomes (\u003cb\u003eTable S2\u003c/b\u003e), multiple bioinformatics tools were employed. Regions of genomic plasticity (RGPs) were identified using panRGP [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], insertion sequences (ISs) were detected with ISEscan [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e], while prophage regions and plasmids were predicted with PHASTEST [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e] and Platon [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e], respectively.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePrediction of antimicrobial resistance and virulence in\u003c/b\u003e \u003cb\u003eK. pneumoniae\u003c/b\u003e \u003cb\u003estrains\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo characterize the antimicrobial resistance and virulence potential of the 12 closely related \u003cem\u003eK. pneumoniae\u003c/em\u003e genomes (\u003cb\u003eTable S2\u003c/b\u003e), including the study genomes, multiple specialized databases and tools were applied. Antibiotic resistance genes (ARGs) were predicted using the Comprehensive Antibiotic Resistance Database (CARD) [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e] and AMRFinderPlus [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Virulence-associated genes (VFGs) were identified against the Virulence Factor Database (VFDB) [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e] implemented in ABRicate (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/tseemann/abricate\u003c/span\u003e\u003cspan address=\"https://github.com/tseemann/abricate\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) with default settings. Genomic islands, representing horizontally acquired regions, were detected using IslandViewer4 [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. In addition, plasmid replicons were identified with the staramr tool [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e] which integrates PlasmidFinder [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e] to scan genome assemblies for plasmid-derived sequences.\u003c/p\u003e\u003cp\u003e\u003cb\u003eGenomic functional analysis in\u003c/b\u003e \u003cb\u003eK. pneumoniae\u003c/b\u003e \u003cb\u003estrains\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe genomes of MBBL2, MNH_G2C5, and MNH_G2C5F were functionally annotated, and their metabolic pathways were classified using the KEGG database [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e] via the KEGG Automatic Annotation Server [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. Secondary metabolite biosynthetic gene clusters were identified with antiSMASH v7.0 [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. In addition, antimicrobial proteins and their corresponding genes were predicted using the BAGEL4 web server [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e], and the predicted bacteriocin domains were validated by BLASTp [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e] searches against the non-redundant protein (nr) database.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003ePrediction of the EPS gene operons\u003c/h2\u003e\u003cp\u003eThe sequence of \u003cem\u003eK. pneumoniae\u003c/em\u003e genomes was aligned with known EPS coding manipulators through the Basic Local Alignment Search Tool (BLAST) program (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://blast.ncbi.nlm.nih.gov/Blast.cgi\u003c/span\u003e\u003cspan address=\"https://blast.ncbi.nlm.nih.gov/Blast.cgi\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to identify the presence of the genes and map the EPS synthesis gene cluster.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eWe randomly selected 120 samples and prevalence was determined from the observed frequencies without applying any statistical analyses. Descriptive statistics were used to examine the distribution of antimicrobial resistance profile of the study isolates, ARGs and VFGs repertoire of the MBBL2, MNH_G2C5 and MNH_G2C5F genomes. The data from the ASTs were analyzed using one-way analysis of variance (ANOVA) followed by Tukey\u0026rsquo;s multiple-comparison test. Both ARGs and VFGs data were normalized by Total Sum Scaling (TSS) that uses the total read count for each gene in each sample [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. Statistical significance was set for all tests at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003ePrevalence of\u003c/b\u003e \u003cb\u003eK. pneumoniae\u003c/b\u003e \u003cb\u003eassociated with bovine mastitis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA total of 27 isolates were confirmed as \u003cem\u003eK. pneumoniae\u003c/em\u003e using selective culture media, a series of biochemical tests and \u003cem\u003e16S rRNA\u003c/em\u003e gene sequencing. In biochemical assays, the isolates were positive for catalase, citrate utilization, and lactose fermentation, and negative for indole, oxidase, and methyl red identified as \u003cem\u003eK. pneumoniae\u003c/em\u003e. Source-specific evaluation showed a higher prevalence in milk samples (27.1%, 19 isolates) compared to fecal samples (16.0%, 8 isolates). The prevalence was calculated directly from observed frequencies.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAntibiogram profile of the\u003c/b\u003e \u003cb\u003eK. pneumoniae\u003c/b\u003e \u003cb\u003eisolates\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA total of 27 isolates were tested against fifteen antimicrobial agents, and all isolates demonstrated MDR, exhibiting resistance to 3\u0026thinsp;\u0026ge;\u0026thinsp;antibiotics (\u003cb\u003eFile S1\u003c/b\u003e). The highest resistance was recorded for doxycycline (DO) with 21/27 (77.8%) resistant isolates, followed by ampicillin (AMP) and tetracycline (TE), each showing 20/27 (74.1%) resistance. Moderate resistance frequencies of 18/27 (66.7%) were observed for ciprofloxacin (CIP), nalidixic acid (NA), and sulfonamides (S3). Resistance to chloramphenicol (C) and cefoxitin (FOX) was also substantial, observed in 17/27 (63.0%) isolates. Similarly, azithromycin (AZM) and ceftriaxone (CRO) displayed resistance in 16/27 (59.3%) isolates each, while nitrofurantoin (F), oxacillin (OX), and imipenem (IPM) exhibited resistance in 15/27 (55.6%) isolates. Moderate resistance was seen with Streptomycin (S) (14/27, 51.9%), whereas gentamicin (CN) showed the lowest resistance level (9/27, 33.3%) and the highest susceptibility (14/27, 51.9%) (\u003cb\u003eFile S1\u003c/b\u003e). Notably, three isolates (MBBL2, MNH_G2C5, and MNH_G2C5F) exhibited extensive multidrug resistance, with resistance to 13 of the 15 antibiotics tested. These three MDR isolates were selected for detailed genomic characterization, and their resistance profiles are summarized in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eGenomic features of\u003c/b\u003e \u003cb\u003eK. pneumoniae\u003c/b\u003e \u003cb\u003estrains\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe assembled genomes of \u003cem\u003eK. pneumoniae\u003c/em\u003e strains MBBL2, MNH_G2C5, and MNH_G2C5F were approximately 5.39 Mbp, 4.59 Mbp, and 5.38 Mbp in size, respectively, each with a GC content of 57.5%. Genome quality assessment indicated high completeness (\u0026gt;\u0026thinsp;98%) and low contamination (0.82%) for MBBL2 and MNH_G2C5F, whereas MNH_G2C5 exhibited reduced completeness (80.93%) and slightly elevated contamination (2.35%). We predicted 5,341 coding sequences in MBBL2, 4,478 in MNH_G2C5, and 5,311 in MNH_G2C5F. Additionally, the genomes contained 89, 63, and 87 RNA genes, respectively. Further genomic characterization revealed the presence of a single CRISPR array in MBBL2 and MNH_G2C5F, while no CRISPR elements were detected in MNH_G2C5. Functional subsystem classification assigned 393 subsystems to MBBL2, 341 to MNH_G2C5, and 395 to MNH_G2C5F. A detailed summary on the genomic features of these genomes is provided in \u003cb\u003eTable S3\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eThe circular genome representations of \u003cem\u003eK. pneumoniae\u003c/em\u003e strains MBBL2, MNH_G2C5, and MNH_G2C5F, together with their COG-based functional annotations, are shown in \u003cb\u003eFigure S1A\u003c/b\u003e and \u003cb\u003eS1B\u003c/b\u003e. COG classification assigned genes into 27 functional categories across four major groups. The most abundant category was G (carbohydrate transport and metabolism), comprising 10.3%, 10.0%, and 10.4% of the genes in MBBL2, MNH_G2C5, and MNH_G2C5F, respectively. This was followed by category E (amino acid transport and metabolism; 8.8\u0026ndash;9.4%), category K (transcription; 8.9\u0026ndash;9.0%), category R (general function prediction only; 6.9\u0026ndash;7.2%), and category P (inorganic ion transport and metabolism; ~6%). Additional enriched categories included C (energy production and conversion; 5.0\u0026ndash;5.9%), M (cell wall/membrane/envelope biogenesis; 5.8%), and J (translation, ribosomal structure, and biogenesis; 4.7\u0026ndash;5.4%).\u003c/p\u003e\u003cp\u003e\u003cb\u003eMolecular typing and genomic epidemiology of\u003c/b\u003e \u003cb\u003eK. pneumoniae\u003c/b\u003e \u003cb\u003estrains\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo elucidate the global genomic epidemiology of \u003cem\u003eK. pneumoniae\u003c/em\u003e, we reconstructed the phylogenetic relationships among three study isolates (MBBL2, MNH_G2C5, and MNH_G2C5F) and 591 global genomes from NCBI GenBank using a seven-gene MLST scheme (\u003cem\u003egapA, infB, mdh, pgi, phoE, rpoB, tonB\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). \u003cem\u003eK. pneumoniae\u003c/em\u003e strains MBBL2 and MNH_G2C5F were assigned to sequence type 273 (ST273), differing by 97 core genome MLST (cgMLST) alleles, whereas MNH_G2C5 formed a distinct clade within ST101, separated by 747 alleles (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA\u0026ndash;C). cgMLST analysis revealed that MBBL2 and MNH_G2C5F clustered with 18 MDR ST273 strains from nine countries, while MNH_G2C5 showed close relatedness to 273 ST101 strains from 32 countries. All study strains exhibited genetic links to both human and animal-derived isolates (\u003cb\u003eFile S1\u003c/b\u003e). An SNP-based phylogeny, constructed from 50,138 core SNPs across 52 genomes (including 49 reference genomes), placed MBBL2, MNH_G2C5F, and MNH_G2C5 in a clade predominantly composed of human-derived strains, except for one environmental isolate (STIN_94). MBBL2 and MNH_G2C5F co-clustered with clinical strains KP_NORM_BLD_116392 and ARLG-3223, while MNH_G2C5 grouped with C17KP0052, a human bloodstream infection isolate (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cb\u003eFile S2\u003c/b\u003e). This topology suggested recent common ancestry for MBBL2 and MNH_G2C5F, with MNH_G2C5 representing an earlier divergence.\u003c/p\u003e\u003cp\u003e\u003cb\u003eGenomic diversity and strain-specific genes in\u003c/b\u003e \u003cb\u003eK. pneumoniae\u003c/b\u003e \u003cb\u003estrains\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo substantiate the phylogenetic relationships and provide high-resolution genomic demarcation of the study isolates, we performed ANI analysis on a curated panel of 12 closely related strains (including study strains), selected based on their phylogenetic proximity from an initial set of 52 global genomes (\u003cb\u003eTable S2\u003c/b\u003e, \u003cb\u003eFigure S2\u003c/b\u003e). This analysis robustly confirmed the species-level identity of all three study strains (MBBL2, MNH_G2C5, and MNH_G2C5F), each demonstrating\u0026thinsp;\u0026gt;\u0026thinsp;98% ANI with established \u003cem\u003eK. pneumoniae\u003c/em\u003e reference strains, far exceeding the 95% threshold for species delineation [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. The ANI results provided precise quantification of the genetic distances inferred from phylogeny. MBBL2 and MNH_G2C5F were nearly identical (99.9% ANI), whereas MNH_G2C5 showed slightly lower similarity (98.9%), reflecting its more distant phylogenetic position. MBBL2 and MNH_G2C5F exhibited the highest ANI (99.8%) with Kpn223 and KP_NORM_BLD_116392. In contrast, MNH_G2C5 was most closely related (98.9% ANI) to a broader set of strains, including ARLG-3223, Kpn223, KP_NORM_BLD_116392, MNH_G2C5F, MBBL2, 032D, 7008.20, and 5844 (\u003cb\u003eTable S2\u003c/b\u003e, \u003cb\u003eFigure S2\u003c/b\u003e).\u003c/p\u003e\u003cp\u003eA pangenome analysis was performed on the study genomes (MBBL2, MNH_G2C5, and MNH_G2C5F) together with nine reference genomes (\u003cb\u003eTable S2\u003c/b\u003e) to explore their gene repertoire. The pangenome dendrogram revealed that MBBL2 and MNH_G2C5F were closely related to reference \u003cem\u003eK. pneumoniae\u003c/em\u003e strains 5844, 032D, and 7008.20, while MNH_G2C5 showed the highest similarity to strains 6072, 11383, and 4254 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). We identified 7,873 genes across the 12 \u003cem\u003eK. pneumoniae\u003c/em\u003e genomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB, \u003cb\u003eTable S4\u003c/b\u003e). Strain-specific analysis further showed that MBBL2 possessed 1 unique gene and 826 accessory genes, MNH_G2C5 carried 123 unique genes and 234 accessory genes, whereas MNH_G2C5F, notably, contained no unique genes but shared 826 accessory genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC, \u003cb\u003eTable S4\u003c/b\u003e). The new gene accumulation curve (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD) followed a power-law decay (\u003cem\u003ey\u003c/em\u003e\u0026thinsp;=\u0026thinsp;312.947x\u003csup\u003e\u0026minus;\u0026thinsp;1.19\u003c/sup\u003e, \u003cem\u003eR\u0026sup2;\u003c/em\u003e = 0.981963), indicating that the number of novel genes declines steadily with the addition of more genomes but does not reach a plateau, consistent with an open genome concept. Similarly, the pangenome expansion curve (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE) also supported an open pangenome model, as the total number of gene clusters continued to rise with each additional genome (\u003cem\u003ey\u003c/em\u003e\u0026thinsp;=\u0026thinsp;200124x\u003csup\u003e0\u003c/sup\u003e, \u003cem\u003eR\u0026sup2;\u003c/em\u003e = 0.1), reflecting high genetic diversity. In contrast, the core genome displayed a progressive reduction, best fitted by an exponential decay model (\u003cem\u003ey\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1358.75e\u003csup\u003e\u0026minus;\u0026thinsp;0.08x\u003c/sup\u003e + 2343.19, \u003cem\u003eR\u0026sup2;\u003c/em\u003e = 0.994518), suggesting gene loss with the inclusion of additional genomes.\u003c/p\u003e\u003cp\u003e\u003cb\u003eGenomic plasticity and mobile genetic elements in\u003c/b\u003e \u003cb\u003eK. pneumoniae\u003c/b\u003e \u003cb\u003estrains\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo assess the genomic plasticity of 12 phylogenetically related \u003cem\u003eK. pneumoniae\u003c/em\u003e genomes, we employed a pangenome-based approach to predict regions of genomic plasticity (RGPs), defined as gene clusters located within highly variable genomic regions. The number of RGPs varied widely across genomes, ranging from 11 in KP_NORM_BLD_116392 to 34 in MNH_G2C5, which harbored the highest count. Notably, MBBL2 and MNH_G2C5F carried an equal number of RGPs (27 each) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The sizes of these regions spanned from approximately 0.26 Mb to 1.061 Mb (\u003cb\u003eFile S3\u003c/b\u003e). To further explore contributors to genomic plasticity, we examined MGEs, including plasmids, prophages, and ISs. Plasmid profiling revealed four distinct replicon types among the three isolates. Both MBBL2 and MNH_G2C5F harbored IncFIB(K)(pCAV1099-114), IncFII(K), and IncHI1B(pNDM-MAR) plasmids while MNH_G2C5 carried only an IncR plasmid. Prophage counts varied across strains, with some harboring only intact prophages and others carrying a mixture of intact and questionable ones. MNH_G2C5 contained four prophage regions, whereas MBBL2 and MNH_G2C5F each carried two. Across the 12 \u003cem\u003eK. pneumoniae\u003c/em\u003e genomes, a total of 816 IS elements were detected, of which 58, 52, and 46 were present in MBBL2, MNH_G2C5F, and MNH_G2C5, respectively (\u003cb\u003eFile S3\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eResistome repertoire in\u003c/b\u003e \u003cb\u003eK. pneumoniae\u003c/b\u003e \u003cb\u003estrains\u003c/b\u003e\u003c/p\u003e\u003cp\u003eComprehensive resistome analysis of 12 closely related \u003cem\u003eK. pneumoniae\u003c/em\u003e genomes highlighted the genomic diversity and adaptability of these strains to multiple stressors, including acid, AMR, biocides, and metals. The three study genomes \u003cem\u003eviz.\u003c/em\u003e MNH_G2C5, MBBL2, and MNH_G2C5F carried 41, 30, and 29 resistome genes, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, \u003cb\u003eFile S4\u003c/b\u003e), all of which included a strong core of acid resistance genes (e.g., \u003cem\u003easr\u003c/em\u003e). A total of 48 AMR genes, conferring resistance to 12 antibiotic classes, were identified across the three genomes. The AMR gene count was highest in MNH_G2C5F (18), followed by MBBL2 (17) and MNH_G2C5 (13). These genes conferred resistance to aminoglycosides (e.g., \u003cem\u003eaac(3)-IId\u003c/em\u003e, \u003cem\u003eaadA5\u003c/em\u003e), beta-lactams (e.g., \u003cem\u003eblaCTX-M-15\u003c/em\u003e, \u003cem\u003eblaLAP-2\u003c/em\u003e, \u003cem\u003eblaSHV-1\u003c/em\u003e, \u003cem\u003eblaSHV-11\u003c/em\u003e, \u003cem\u003eblaTEM-1\u003c/em\u003e), trimethoprim (e.g., \u003cem\u003edfrA1\u003c/em\u003e, \u003cem\u003edfrA14\u003c/em\u003e, \u003cem\u003edfrA17\u003c/em\u003e), phenicols (e.g., \u003cem\u003eoqxA\u003c/em\u003e, \u003cem\u003eoqxB\u003c/em\u003e, \u003cem\u003eoqxB20\u003c/em\u003e), tetracyclines (e.g., \u003cem\u003etet(A)\u003c/em\u003e, \u003cem\u003etet(D)\u003c/em\u003e), sulfonamides (e.g., \u003cem\u003esul1\u003c/em\u003e, \u003cem\u003esul2\u003c/em\u003e), fluoroquinolones (e.g., \u003cem\u003eqnrS1\u003c/em\u003e), fosfomycin (e.g., \u003cem\u003efosA\u003c/em\u003e), rifamycin (e.g., \u003cem\u003earr\u003c/em\u003e), macrolides (e.g., \u003cem\u003emph(A)\u003c/em\u003e), and efflux pumps (e.g., \u003cem\u003eemrD\u003c/em\u003e), representing a shared resistance core (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The \u003cem\u003eqacEdelta1\u003c/em\u003e gene, conferring resistance to quaternary ammonium compounds, was detected in all three strains, suggesting tolerance to common chemical disinfectants. In addition, 34 metal resistance genes were detected in the three genomes. Arsenic resistance genes (e.g., \u003cem\u003earsC\u003c/em\u003e) were present in all strains, while mercury resistance genes (e.g., \u003cem\u003emerA/C/P/R/T\u003c/em\u003e) were found in MBBL2 and MNH_G2C5F. Notably, copper resistance genes (e.g., \u003cem\u003epcoA/B/C/D/R/S\u003c/em\u003e) and silver resistance genes (e.g., \u003cem\u003esilA/B/C/E/F/P/R/S\u003c/em\u003e) were exclusive to MNH_G2C5. Furthermore, MNH_G2C5 harbored nine heat resistance genes (e.g., \u003cem\u003epsi-GI\u003c/em\u003e, \u003cem\u003ekefB-GI\u003c/em\u003e, \u003cem\u003etrxLHR\u003c/em\u003e, \u003cem\u003ehdeD-GI\u003c/em\u003e, \u003cem\u003eyfdX1/2\u003c/em\u003e, \u003cem\u003eshsP\u003c/em\u003e, \u003cem\u003eclpK\u003c/em\u003e, \u003cem\u003ehsp20\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, \u003cb\u003eFile S4\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eVirulence gene arsenal and mechanistic insights in\u003c/b\u003e \u003cb\u003eK. pneumoniae\u003c/b\u003e \u003cb\u003estrains\u003c/b\u003e\u003c/p\u003e\u003cp\u003eVirulence factor gene (VFG) profiles of the three study genomes were analyzed to assess their pathogenic potential. MBBL2 and MNH_G2C5F each harbored 60 VFGs, whereas MNH_G2C5 contained 44. These VFGs were found to facilitate virulence through several distinct mechanisms, including nutritional/metabolic factor, regulation, biofilm, adherence, effector delivery system, antimicrobial activity, immune modulation \u003cb\u003e(Figure S3, File S4)\u003c/b\u003e. In all genomes, adherence-related genes represented the largest category, accounting for 26.67% in MBBL2 and MNH_G2C5F and 34.1% in MNH_G2C5. Moreover, MBBL2 and MNH_G2C5F genomes possessed 14 effector delivery system genes (23.33%), 13 nutritional/metabolic genes (21.67%), eight biofilm-related genes (13.33%), four immune modulation genes (6.67%), three regulatory genes (5%), and two antimicrobial activity genes (3.33%). In contrast, MNH_G2C5 contained 13 effector delivery system genes (29.54%), eight biofilm-related genes (18.18%), four genes each for regulation and antimicrobial activity (4.54% each), and lacked immune modulation genes (\u003cb\u003eFigure S3, File S4\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003ePrediction of genomic islands in\u003c/b\u003e \u003cb\u003eK. pneumoniae\u003c/b\u003e \u003cb\u003estrains\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGenomic islands (GIs), which are gene clusters frequently acquired through horizontal gene transfer (HGT), were predicted in all three genomes and were found to harbor multiple VFGs and pathogen-associated genes, underscoring their potential role in pathogenicity. In the MBBL2 strain, 37 putative GIs were identified, of which 25 were predicted by SIGI-HMM and 12 by IslandPath-DIMOB, with sizes ranging from 4,035 to 291,727 bp. Among them, ten GIs carried genes associated with either virulence factors (VFs) or AMR. Notably, MBBL2 harbored curated AMR genes, including \u003cem\u003eaac(3)-IId\u003c/em\u003e (WP_000557454.1), \u003cem\u003edfrA17\u003c/em\u003e (WP_001389366.1), \u003cem\u003emrxA\u003c/em\u003e (WP_000004159.1), \u003cem\u003esul1\u003c/em\u003e (WP_000259031.1), \u003cem\u003esul2\u003c/em\u003e (WP_001043260.1), \u003cem\u003eACHL6M_RS25720\u003c/em\u003e (WP_001516695.1), \u003cem\u003eACHL6M_RS25995\u003c/em\u003e (WP_000503573.1), and \u003cem\u003eACHL6M_RS26045\u003c/em\u003e (WP_000219391.1). In addition, homologs of resistance genes such as \u003cem\u003ealaS\u003c/em\u003e (WP_004174700.1), \u003cem\u003efloR\u003c/em\u003e (WP_023300759.1), \u003cem\u003ekexD\u003c/em\u003e (WP_004200176.1), \u003cem\u003etetA\u003c/em\u003e (WP_000804064.1), \u003cem\u003eugd\u003c/em\u003e (WP_023328477.1), and \u003cem\u003eACHL6M_RS08150\u003c/em\u003e (WP_023341379.1) were also identified (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn comparison, the MNH_G2C5 strain harbored 38 GIs, with 25 predicted by the SIGI-HMM method and 13 by IslandPath-DIMOB, ranging from 3,010 bp to 46,746 bp in length. Four of these islands contained genes associated with VFs or AMR. MNH_G2C5 carried multiple curated resistance genes, such as \u003cem\u003ePGZ78_RS07210\u003c/em\u003e (WP_001516695.1), \u003cem\u003ePGZ78_RS07200\u003c/em\u003e (WP_000027057.1), \u003cem\u003edfrA1\u003c/em\u003e (WP_000777554.1), and \u003cem\u003esul1\u003c/em\u003e (WP_000259031.1), as well as homologs of resistance genes, including \u003cem\u003etetA\u003c/em\u003e (WP_000804064.1), and \u003cem\u003ePGZ78_RS00380\u003c/em\u003e (WP_032419057.1). Notably, one pathogen-associated gene, \u003cem\u003ePGZ78_RS16620\u003c/em\u003e (WP_000376623.1) was also identified (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). Similarly, MNH_G2C5F contained 39 GIs, comprising 25 predicted by the SIGI-HMM method and 14 by IslandPath-DIMOB, spanning 4,035\u0026ndash;190,576 bp, with ten GIs carrying VFs or AMR-related genes. This strain encoded multiple curated resistance genes such as \u003cem\u003eQ2T98_RS25690\u003c/em\u003e (WP_001516695.1), \u003cem\u003eQ2T98_RS25965\u003c/em\u003e (WP_000503573.1), \u003cem\u003edfrA17\u003c/em\u003e (WP_001389366.1), \u003cem\u003eQ2T98_RS26015\u003c/em\u003e (WP_000219391.1), \u003cem\u003emrxA\u003c/em\u003e (WP_000004159.1), \u003cem\u003eaac(3)-IId\u003c/em\u003e (WP_000557454.1), \u003cem\u003esul1\u003c/em\u003e (WP_000259031.1), and \u003cem\u003esul2\u003c/em\u003e (WP_001043260.1). It also harbored homologs of resistance genes, including \u003cem\u003ealaS\u003c/em\u003e (WP_004174700.1), \u003cem\u003efloR\u003c/em\u003e (WP_023300759.1), \u003cem\u003ekexD\u003c/em\u003e (WP_004200176.1), \u003cem\u003etetA\u003c/em\u003e (WP_000804064.1), \u003cem\u003eugd\u003c/em\u003e (WP_023328477.1), and \u003cem\u003eQ2T98_RS08145\u003c/em\u003e (WP_023341379.1) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eK. pneumoniae\u003c/b\u003e \u003cb\u003estrains utilized diverse metabolic pathways to facilitate adaptation and survival\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe systemic metabolic pathways of gene products in the MBBL2, MNH_G2C5, and MNH_G2C5F genomes were analyzed to better understand how these strains utilized nutrients, interacted with their environment, and influenced health and disease processes. A total of 3,524 genes (68.7%) from MBBL2, 2,973 genes (68.9%) from MNH_G2C5, and 3,514 genes (68.8%) from MNH_G2C5F were successfully annotated and mapped to KEGG pathways, spanning six major categories and forty-one subcategories (\u003cb\u003eFigure S4\u003c/b\u003e). Among the major categories, metabolism-related genes were the most abundant (MBBL2\u0026thinsp;=\u0026thinsp;1,712; MNH_G2C5\u0026thinsp;=\u0026thinsp;1,492; MNH_G2C5F\u0026thinsp;=\u0026thinsp;1,711), followed by those associated with environmental information processing, genetic information processing, cellular processes, human diseases, and organismal systems. Additionally, 58, 56, and 58 drug (antimicrobial) resistance genes were identified in MBBL2, MNH_G2C5, and MNH_G2C5F, respectively. All three genomes carried a complete biosynthesis of amino acids pathway that contributed to biogenic amine production. Seventeen complete modules related to production of biogenic amine identified in MNH_G2C5, while both MBBL2 and MNH_G2C5F genomes have 21 complete modules which correspond to serine biosynthesis, methionine biosynthesis, histidine biosynthesis and shikimate pathway respectively (\u003cb\u003eFigure S5\u003c/b\u003e, \u003cb\u003eFile S5\u003c/b\u003e). Further analysis revealed that the three genomes harbored multiple genes influencing cellular community, including 71 quorum sensing genes in MBBL2 and MNH_G2C5F and 63 in MNH_G2C5 (e.g., \u003cem\u003eluxS\u003c/em\u003e, \u003cem\u003eqseC\u003c/em\u003e, \u003cem\u003eqseB\u003c/em\u003e, \u003cem\u003elsrA\u003c/em\u003e, \u003cem\u003ehfq\u003c/em\u003e, etc.), as well as biofilm-associated genes homologous to those characterized in \u003cem\u003eVibrio cholerae\u003c/em\u003e (e.g., \u003cem\u003ecysE\u003c/em\u003e, \u003cem\u003ewecB\u003c/em\u003e, \u003cem\u003ecsrA\u003c/em\u003e, etc.), \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (e.g., \u003cem\u003egacS\u003c/em\u003e, \u003cem\u003ecrp\u003c/em\u003e, \u003cem\u003ebarA\u003c/em\u003e, etc.), and \u003cem\u003eEscherichia coli\u003c/em\u003e (e.g., \u003cem\u003eglgA\u003c/em\u003e, \u003cem\u003ebcsA\u003c/em\u003e, \u003cem\u003erpoS\u003c/em\u003e, etc.) (\u003cb\u003eFile S5\u003c/b\u003e). In addition, both MBBL2 and MNH_G2C5F genomes possessed 45 beta-lactam resistance genes while MNH_G2C5 contained 44 beta-lactam resistance genes. All three genomes also carried five vancomycin resistance genes and five platinum drug resistance genes. Moreover, MBBL2 and MNH_G2C5F harbored 58 cationic antimicrobial peptide (CAMP) resistance genes and seven antifolate resistance genes, compared with 57 and five, respectively, in MNH_G2C5. Moreover, all three genomes possessed 19 genes (e.g., \u003cem\u003edxr\u003c/em\u003e, \u003cem\u003eACAT\u003c/em\u003e, \u003cem\u003eatoB\u003c/em\u003e, \u003cem\u003eispA\u003c/em\u003e, \u003cem\u003euppS\u003c/em\u003e, \u003cem\u003eispE\u003c/em\u003e, \u003cem\u003eispD\u003c/em\u003e, \u003cem\u003edxs\u003c/em\u003e) associated with terpenoid backbone biosynthesis, along with 15 genes (e.g., \u003cem\u003eentA\u003c/em\u003e, \u003cem\u003eentB\u003c/em\u003e, \u003cem\u003edhbB\u003c/em\u003e, \u003cem\u003evibB\u003c/em\u003e, \u003cem\u003emxcF\u003c/em\u003e, \u003cem\u003eentC\u003c/em\u003e, \u003cem\u003eentD\u003c/em\u003e, \u003cem\u003epptT\u003c/em\u003e) related to the biosynthesis of siderophore group nonribosomal peptides.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSecondary metabolite gene clusters and human pathogenic potential in\u003c/b\u003e \u003cb\u003eK. pneumoniae\u003c/b\u003e \u003cb\u003estrains\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe genomes of MBBL2, MNH_G2C5, and MNH_G2C5F harbored multiple biosynthetic gene clusters (BGCs) linked to secondary metabolites (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). MBBL2 and MNH_G2C5 contained a redox-cofactor gene cluster, including \u003cem\u003epqqC\u003c/em\u003e, \u003cem\u003epqqD\u003c/em\u003e, and \u003cem\u003epqqE\u003c/em\u003e, involved in pyrroloquinoline quinone (PQQ) biosynthesis. Both genomes also encoded two azole-containing RiPPs (ribosomally synthesized and post-translationally modified peptides) encoded by \u003cem\u003epflA\u003c/em\u003e and \u003cem\u003eycaO\u003c/em\u003e (Figs.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA and \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eC). Moreover, MBBL2 and MNH_G2C5F genomes carried an NRP (non-ribosomal peptide)-metallophore gene cluster for enterobactin biosynthesis (\u003cem\u003eentF\u003c/em\u003e, \u003cem\u003eentC\u003c/em\u003e, \u003cem\u003eentA\u003c/em\u003e) and a terpene-precursor which is encoded by \u003cem\u003eispA\u003c/em\u003e gene (Figs.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA and \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eB). Importantly, all of three genomes possessed a RiPP-like protein dsbA involved in disulfide bond formation (Figs.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA-C). Additionally, BAGEL4 analysis identified \u003cem\u003erlmN\u003c/em\u003e (\u003cem\u003eBmbF\u003c/em\u003e) in \u003cem\u003eK. pneumoniae\u003c/em\u003e MNH_G2C5 (Protein ID: MDB1120801.1), a conserved bifunctional rRNA/tRNA methyltransferase experimentally validated at the protein level (PE\u0026thinsp;=\u0026thinsp;3). The protein showed 100% sequence identity with characterized methyltransferases across multiple \u003cem\u003eK. pneumoniae\u003c/em\u003e strains. Besides, MNH_G2C5 genome harbored \u003cem\u003eBmbF\u003c/em\u003e (dual-specificity RNA methyltransferase RlmN) protein (Protein Id\u0026thinsp;=\u0026thinsp;MDB1120801.1) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003eSimultaneously, the pathogenicity prediction analysis suggested that all three \u003cem\u003eK. pneumoniae\u003c/em\u003e genomes possess a high likelihood of being human pathogens, as evidenced by PathogenFinder scores of 0.901 for MBBL2 and MNH_G2C5F, and 0.911 for MNH_G2C5. These values corresponded to the identification of 322, 255, and 322 pathogenic gene families across these genomes, respectively.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEPS and capsule biosynthesis gene clusters in\u003c/b\u003e \u003cb\u003eK. pneumoniae\u003c/b\u003e \u003cb\u003estrains\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFurther analysis of EPS and capsule biosynthesis clusters in three \u003cem\u003eK. pneumoniae\u003c/em\u003e genomes revealed a largely conserved architecture with minor variations (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). All genomes harbored two EPS/capsule biosynthesis clusters, with the MBBL2 and MNH_G2C5F clusters showing relative similarity. Both MBBL2-C1 and MNH_G2C5F_C1 contained a canonical EPS/capsule cluster, including genes involved in sugar-nucleotide biosynthesis (\u003cem\u003eugd, gndA\u003c/em\u003e), glycosyltransferases and tailoring enzymes (\u003cem\u003eGT, GT2, GT4, wbaP\u003c/em\u003e), regulation and signaling (\u003cem\u003ewzc, wzb, wcaJ, galF\u003c/em\u003e), and export/translocation (wza, Wzi, EpsG) (\u003cb\u003eTable S5\u003c/b\u003e). Notably, MNH_G2C5F_C1 shared nearly all genes with MBBL2-C1, differing only by one or two hypothetical or accessory genes. Conversely, MBBL2-C2 and MNH_G2C5F_C2 contained a distinct EPS-like cluster comprising glycosyltransferases (\u003cem\u003ewecA, wecF, wecG, rffC, rffM\u003c/em\u003e), polymerization and chain-length control genes (\u003cem\u003ewzyE, wzzE\u003c/em\u003e), sugar-nucleotide biosynthesis genes (\u003cem\u003erffA, rffG, rfbA, wecB, wecC\u003c/em\u003e), and export-associated genes (\u003cem\u003ewzxE\u003c/em\u003e). These clusters were highly conserved between the genomes, suggesting functional equivalence in polysaccharide assembly. Additionally, MNH_G2C5_C1 carried genes for regulation and signaling (rho), glycosyltransferases (wecA, wecF, rffM), polymerization/chain-length control (\u003cem\u003ewzyE, wzzE\u003c/em\u003e), sugar-nucleotide biosynthesis (\u003cem\u003ewecB, wecC, rffG, rfbA, rffA\u003c/em\u003e), and export (\u003cem\u003ewzxE\u003c/em\u003e). MNH_G2C5_C2 featured a cluster including glycosyltransferases (\u003cem\u003eGT, GT2, GT4, GT9, kbl, rfaC, rfaF, waaZ, waaA\u003c/em\u003e), accessory enzymes (\u003cem\u003etdh\u003c/em\u003e), sugar-nucleotide biosynthesis (\u003cem\u003erfaD\u003c/em\u003e), and export (\u003cem\u003ewaaL\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e, \u003cb\u003eTable S5\u003c/b\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe emergence of \u003cem\u003eK. pneumoniae\u003c/em\u003e as a major pathogen in bovine mastitis [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] represents a significant challenge to both animal welfare and public health due to its potential for zoonotic transmission and MDR [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]. This study provides a comprehensive genomic characterization of three MDR \u003cem\u003eK. pneumoniae\u003c/em\u003e strains isolated from CM milk (MBBL2, MNH_G2C5) and feces (MNH_G2C5F) in the dairy farms of Bangladesh, revealing a complex interplay of AMR, virulence, and genomic plasticity. The high prevalence of \u003cem\u003eK. pneumoniae\u003c/em\u003e (22.5%), particularly in milk samples (27.14%), underscores its role as a primary mastitis pathogen. This is consistent with studies from China and the USA, which have reported an increasing incidence of \u003cem\u003eKlebsiella\u003c/em\u003e species in bovine CM, often linked to environmental contamination and poor udder hygiene [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Subsequent AST profiling revealed an alarming resistance scenario, with 86.67% of tested antibiotics ineffective and all 27 isolates classified as MDR. The high resistance to first-line antibiotics like ampicillin, tetracycline, and nalidixic acid mirrors trends observed in human and veterinary medicine worldwide, driven by the selective pressure of antimicrobial misuse [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. To unveil the genetic basis of this high MDR, three isolates (MBBL2, MNH_G2C5, MNH_G2C5F), resistant to 13 (out of 15) antibiotics, were subjected to WGS to characterize their resistome and virulence repertoire.\u003c/p\u003e\u003cp\u003eOne of the noteworthy findings was the co-circulation of two high-risk \u003cem\u003eK. pneumoniae\u003c/em\u003e clones, ST273 (MBBL2, MNH_G2C5F) and ST101 (MNH_G2C5), within the dairy herds of Bangladesh, underscoring their direct relevance to the One Health framework. While ST101 is a well-documented global MDR clone associated with hospital outbreaks in humans and increasingly reported in livestock [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e], ST273 is less commonly reported but has been linked to severe infections in both humans and animals in Asia [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e]. The phylogenetic proximity of these bovine-derived ST273 isolates to human clinical strains provides compelling evidence for recent cross-species transmission [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. Furthermore, the pangenome analysis revealed an open genome, characterized by a large accessory gene pool and a decaying core, a hallmark of \u003cem\u003eK. pneumoniae\u003c/em\u003e that facilitates niche adaptation [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The substantial number of strain-specific genes in MNH_G2C5 (ST101) and the nearly identical accessory genome of the ST273 isolates (MBBL2, MNH_G2C5F) underscore how clonal background shapes genomic plasticity. This open pangenome structure promotes the acquisition of MGEs, effectively turning the farm environment into a potential crucible for the evolution of new MDR and virulent variants through HGT [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The diverse resistome observed among the \u003cem\u003eK. pneumoniae\u003c/em\u003e strains through integrated phenotypic and genomic analyses reflects strong selective pressures driving genomic plasticity and adaptation. Such heterogeneity suggests frequent HGT and exposure to varied antimicrobial and environmental stressors [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Both MBBL2 and MNH_G2C5F genomes harbored a more extensive arsenal of AMR genes, conferring resistance to critically important beta-lactams and fluoroquinolones. This genetic repertoire is critical for successful MDR clones, and has been extensively documented in human clinical isolates [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e]. The presence of \u003cem\u003eoqxAB\u003c/em\u003e and \u003cem\u003efosA\u003c/em\u003e in all three genomes, conferring resistance to chloramphenicol and fosfomycin, is noteworthy as these are often considered last-resort treatments for MDR infections. A recent study from India similarly identified a high prevalence of \u003cem\u003eoqxAB\u003c/em\u003e in bovine \u003cem\u003eK. pneumoniae\u003c/em\u003e, suggesting a widespread and potentially overlooked resistance mechanism in livestock reservoirs [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]. Furthermore, the detection of metal and biocide resistance genes (\u003cem\u003eqacEdelta1\u003c/em\u003e, \u003cem\u003ears\u003c/em\u003e, \u003cem\u003emer\u003c/em\u003e) indicates adaptation to farm environments where disinfectants and heavy metals are commonly used, a trait increasingly recognized as co-selected with AMR in agricultural settings [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. Beyond their resistance traits, the pathogenic potential of these strains is notable, as all genomes were predicted with a high probability (\u0026gt;\u0026thinsp;0.90) of being human pathogens. The high number of VFGs, particularly those related to adherence and biofilm formation, is crucial for establishing infections in both the bovine udder and human tissues [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. The abundance of adherence genes in MNH_G2C5 and the effector delivery system genes in all strains suggest multiple strategies for host colonization and immune evasion. The presence of complete siderophore systems (\u003cem\u003ee.g.\u003c/em\u003e, enterobactin) is a key virulence factor for systemic infection, as recently demonstrated in hypervirulent \u003cem\u003eK. pneumoniae\u003c/em\u003e strains of livestock origin [\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe high genomic plasticity observed in the study strains underscores their remarkable ability to adapt and evolve in response to selective pressures. The identification of numerous AMR, drug resistance and virulence genes within predicted GIs strongly suggests their acquisition via HGT [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. A recent study on \u003cem\u003eK. pneumoniae\u003c/em\u003e from dairy farms similarly found that GI-carried genes were major contributors to the strain-specific adaptation and resistance profiles [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The metabolic versatility of the strains, evidenced by the extensive KEGG pathway annotations for amino acid biosynthesis, quorum sensing, and biofilm formation, further explains their ability to thrive in diverse niches, from the bovine gut to the udder [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e] and potentially the humans [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The distinct plasmid profiles further highlight the dynamic nature of MGEs; the presence of IncHI1B(pNDM-MAR) and IncFIB(K) plasmids in the ST273 isolates is particularly concerning, as these replicon types are frequently associated with the global dissemination of carbapenem resistance, even though no carbapenem resistance was phenotypically detected in this study [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Analysis of EPS and capsule biosynthesis clusters in the three \u003cem\u003eK. pneumoniae\u003c/em\u003e genomes revealed a largely conserved architecture with minor variations, emphasizing their key role in virulence and environmental adaptation [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e]. Core genes involved in capsule export and regulation (\u003cem\u003ee.g., wza, wzxE\u003c/em\u003e) are essential for assembling a protective capsule that shields the bacterium from phagocytosis, while the extensive repertoire of glycosyltransferases supports biofilm formation [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This is further corroborated by virulence factor analysis, which showed that all three isolates harbor numerous biofilm-associated genes. Collectively, the observed genomic plasticity within EPS clusters underscores the strains\u0026rsquo; potential for persistent infections through enhanced immune evasion and biofilm-mediated survival [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e, \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e]. The genomic insights from this study are limited by the small number of sequenced isolates and the absence of in-vitro or in-vivo validation of the predicted resistance and virulence determinants. Further investigations are necessary to confirm the pathogenic potential and zoonotic risk posed by these high-risk \u003cem\u003eK. pneumoniae\u003c/em\u003e clones.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis in-depth genomic investigation reveals that \u003cem\u003eK. pneumoniae\u003c/em\u003e strains from bovine CM-associated milk and feces are important pathogens harboring high-risk MDR clones (ST101 and ST273). The convergence of a broad resistome, a rich virulome, and significant genomic plasticity in these strains poses a significant threat not only for animal health and production but also a potential reservoir for human infections. These findings emphasize the role of dairy animals in the evolution and dissemination of MDR and hyper-virulent superbugs like \u003cem\u003eK. pneumoniae\u003c/em\u003e. This study underscores the urgent need for integrated One Health surveillance strategies that combine genomic epidemiology with robust antimicrobial stewardship in both veterinary and human medicine to mitigate the spread of these ever-challenging pathogens.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003cp\u003e The Animal Research Ethics Committee (AREC) of the Gazipur Agricultural University (Gazipur, Bangladesh) reviewed and approved the experimental procedures of this study (reference number FVMAS/AREC/2023/6679 [16 January 2023]). Written informed consent was obtained from each participating dairy farmer prior to the inclusion of their animals in this study, ensuring ethical compliance and voluntary participation.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eClinical trial number\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eConsent for publication\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eConflict of interest\u003c/h2\u003e\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis research was supported by a grant from the Bangladesh Bureau of Educational Information and Statistics (BANBEIS), Ministry of Education, Government of the People\u0026rsquo;s Republic of Bangladesh (Grant No. LS20221764, duration 2023\u0026ndash;2025).\u003c/p\u003e\u003ch2\u003eAuthors contributions\u003c/h2\u003e\u003cp\u003eM.N.H. conceived and designed the study. K.Y.A, M.A.A.G., M.M.R., N.S. and F.H. performed experiment, curated, analyzed and visualized data, interpreted results, and wrote original draft. M.N.H. critically reviewed and edited the manuscript. The final manuscript was read and approved by all authors.\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e\u003cp\u003eThe \u003cem\u003e16S rRNA\u003c/em\u003e gene sequences of \u003cem\u003eK. pneumoniae\u003c/em\u003e strains MBBL2, MNH_G2C5 and MNH_G2C5F have been deposited in NCBI GenBank under accession numbers PX447844, PX447845 and PX447846, respectively. The whole genome shotgun sequences for these strains are available in GenBank and the NCBI Sequence Read Archive (SRA) under BioProject accessions PRJNA1171635 for MBBL2, PRJNA923580 for MNH_G2C5, and PRJNA994715 for MNH_G2C5F. The genome versions reported in this study are JBINJS000000000.1, for MBBL2, JAQLOG000000000.1 for MNH_G2C5 and JAULSG000000000.1 for MNH_G2C5F. All datasets generated for this study are included in this article and the supplementary files.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHoque MN et al (2020) Insights into the resistome of bovine clinical mastitis microbiome, a key factor in disease complication. Front Microbiol 11:860\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHoque MN et al (2019) Metagenomic deep sequencing reveals association of microbiome signature with functional biases in bovine mastitis. Sci Rep 9(1):13536\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWani SA et al (2022) A brief analysis of economic losses due to mastitis in dairy cattle. Indian Vet J 90:27\u0026ndash;31\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHoque MN et al (2020) Microbiome dynamics and genomic determinants of bovine mastitis. 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Virulence 15(1):2439509\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Gazipur Agricultural University, Gazipur-1706, Bangladesh","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Bovine mastitis, K. pneumoniae, sequence type, pangenome, resistome, virulence","lastPublishedDoi":"10.21203/rs.3.rs-7912731/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7912731/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e, a major bovine clinical mastitis (CM) pathogen, carries multidrug resistance (MDR) and virulence factor genes (VFGs), posing serious animal and public health threats. This study screened 27 \u003cem\u003eK. pneumoniae\u003c/em\u003e isolates (19 from CM milk and 8 from feces) through culture, biochemical tests, and \u003cem\u003e16S rRNA\u003c/em\u003e-gene sequencing. An overall prevalence of \u003cem\u003eK. pneumoniae\u003c/em\u003e was 22.5% (27/120), with a higher rate in milk (27.14%) than feces (16.0%). Antibiogram profiling revealed that all isolates were multidrug-resistant, with high resistance to doxycycline, tetracycline, nalidixic acid, and ampicillin. Three highly resistant isolates (MBBL2, MNH_G2C5, MNH_G2C5F) underwent whole-genome sequencing for comprehensive genomic analysis. Sequence typing (ST), phylogenetic and pangenome analyses assigned MBBL2 and MNH_G2C5F to ST273 and MNH_G2C5 to ST101, clustering with global human- and animal-derived \u003cem\u003eK. pneumoniae\u003c/em\u003e strains, and carrying notable strain-specific accessory genes (MNH_G2C5:123; MBBL2/MNH_G2C5F:826). Functional annotation identified abundant genes for carbohydrate metabolism (~\u0026thinsp;10%), amino acid transport (~\u0026thinsp;9%), and transcription (~\u0026thinsp;9%). Resistome analysis identified 29\u0026ndash;41 resistance genes, covering 12 antibiotic classes, metals, biocides, and acid stress. Virulence profiling identified 44\u0026ndash;60 VFGs involved in adherence, biofilm formation, effector delivery, immune modulation, and metabolism. Genomic plasticity analysis revealed 27\u0026ndash;34 variable regions, multiple prophages, 46\u0026ndash;58 insertion sequences, and four plasmid replicons. Conserved exopolysaccharide/capsule clusters, secondary metabolites, and high pathogenicity scores (\u0026gt;\u0026thinsp;0.9) underscored both animal and human pathogenic potential. This study demonstrates that dairy cattle are a reservoir for high-risk MDR clones of \u003cem\u003eK. pneumoniae\u003c/em\u003e carrying an extensive resistome and virulome arsenal, highlighting the urgent need for strengthened surveillance and control measures.\u003c/p\u003e","manuscriptTitle":"Genomic Characterization of Multidrug-Resistant Klebsiella pneumoniae Strains from Bovine Mastitis Reveals Extensive Resistome and Virulome Arsenals","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-22 04:13:56","doi":"10.21203/rs.3.rs-7912731/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"355c18d6-c474-4935-bb16-4e5fe6fefc1f","owner":[],"postedDate":"October 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":56632207,"name":"Animal Science"},{"id":56632208,"name":"General Microbiology"},{"id":56632209,"name":"Bacteriology"},{"id":56632210,"name":"Epigenetics \u0026 Genomics"},{"id":56632211,"name":"Bioinformatics"}],"tags":[],"updatedAt":"2025-10-22T04:13:56+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-22 04:13:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7912731","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7912731","identity":"rs-7912731","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}