bioRxiv Science⌕ Search

Biology subjects

Vasudevan, K.

Publications and source records attributed to Vasudevan, K..

At least 19 recordsLinked to original sources

Population genomics of a biocontrol agent: Insights into post-introduction establishment in parthenium beetle

Biological control agents often experience demographic bottlenecks during introduction, which can reshape genetic diversity and inbreeding pattern influencing establishment and long-term ecological success in the introduced populations. The leaf-feeding beetle Calligrapha (Zygogramma) bicolorata, introduced in multiple countries across the globe to control the weed Parthenium hysterophorus, provides an opportunity to examine how introduction bottleneck and post-introduction breeding practices shape genomic variation and inbreeding patterns. We analyzed whole-genome variation in the introduced beetle population in India by sampling six regions encompassing its current distribution in the country. Using genome-wide variation data, we assessed population structure, genetic diversity, and inbreeding patterns across regions, and inferred historical changes in effective population size to reconstruct post-introduction demographic trajectories. The analyses reveal subtle genetic structure across regions, with overall genetic diversity relatively low compared to other invasive and biocontrol insects. Inbreeding patterns vary among populations, with some regions exhibiting higher cumulative runs of homozygosity than others. Notably, regions subjected to intensive propagation of beetle populations show elevated signature of inbreeding alongside reduced historical effective population size. These results underscore the dynamic genomic consequences of biocontrol introduction and subsequent breeding practices, providing insight into the evolutionary trajectories of introduced biocontrol agents.

evolutionary biology↗

Transcriptomics and mutational analysis to screen immunogenic neoantigen peptides and Patient stratification based on immune subtypes for TNBC

Triple-negative breast cancer (TNBC) is a highly aggressive and heterogeneous subtype with limited therapeutic options. In this study, we performed an integrative analysis of TNBC genomics data, including gene expression, somatic mutations, copy number alterations, survival outcomes, immune profiling, and clustering, to identify potential neoantigens, patient populations suitable for vaccination, and biomarkers for evaluating vaccine efficacy. This Integrated analysis identified POSTN and CAP1 as tumor-specific antigens. Incorporation of TNBC-specific mutations into the screened wild-type antigens led to the identification of three neoantigenic peptides with high potential for vaccine development. Immune subtyping stratified TNBC patients into four distinct subtypes, among which IS1 and IS3 were characterized by poor immune infiltration, lower mutation burden, and unfavorable prognosis, whereas IS2 and IS4 exhibited enhanced immune activity and better clinical outcomes. A vaccine incorporating the identified neoantigen peptides may potentially remodel the immune landscape of immune-cold subtypes (IS1 and IS3), converting them into immune-enriched phenotypes through vaccine-induced immune stimulation. Furthermore, weighted gene co-expression network analysis identified ten immune-related biomarkers from the blue and gray modules that were significantly associated with improved survival in IS2 and IS4. Functional enrichment and protein-protein interaction analyses revealed that hub genes primarily involved in immunoglobulin kappa chains and cytokine/TNF signaling pathways may serve as valuable immune biomarkers for prognostic assessment and monitoring vaccine efficacy.

cancer biology↗

Network-based integration of gene expression and DNA methylation identifies prognostic biomarkers for early-stage pancreatic cancer

Pancreatic ductal adenocarcinoma remains one of the most lethal malignancies, largely due to the absence of reliable early-stage biomarkers. Here, we present a network-based multi-omics framework that integrates gene expression and DNA methylation data through partial correlation analysis to uncover prognostic markers. Four distinct networks were constructed: gene expression co-expression, methylation-only, multiplex (inter-layer connections linking the same genes across omics layers), and monoplex (fused multi-omics). Weighted gene co-expression network analysis (WGCNA) was applied to each network to select non-redundant, topologically representative hub genes as features for machine learning classification. Models trained on cross-layer (multiplex) features achieved an ROC of 82%, compared with 50-60% using single-omics features alone. The most strongly associated genes with poor prognosis include TFCP2L1, DHX32, and NCK1.

cancer biology↗

Emergence of Dual-Risk Klebsiella pneumoniae: Global Hotspots of Convergence Between Resistance and Hypervirulence

BackgroundKlebsiella pneumoniae is a major pathogen causing both healthcare- and community-associated infections. Traditionally classified as classical (cKp) or hypervirulent (hvKp), recent reports suggest increasing overlap between antimicrobial resistance (AMR) and virulence, leading to "dual-risk" clones that are both invasive and difficult to treat. ObjectivesTo perform a large-scale genomic analysis of K. pneumoniae isolates and systematically characterize the convergence of AMR and hypervirulence, with a focus on global distribution, clonal structure, and accessory genome functions. MethodsWe analyzed 3,443 genomes curated from 25 international studies. Virulence scoring was standardized using a Kleborate-based framework, while AMR genes were identified with ResFinder. Multilocus sequence typing (MLST), plasmid replicon typing, and K/O antigen profiling were conducted. Convergence was defined as hvKp (virulence score [≥]3) carrying high-priority AMR determinants. Pan-genome-wide association (pan-GWAS) was performed with Roary and Scoary, followed by functional enrichment using ShinyGO. ResultsAmong hvKp isolates, 59.4% carried carbapenemases, ESBLs, or 16S rRNA methyltransferases, demonstrating widespread convergence. Convergent lineages were dominated by ST231 and ST23, with India and the Middle East identified as geographic hotspots. HvKp isolates carried a higher plasmid replicon burden and were enriched in KL1/KL2 and O1/O2 serotypes. Pan-GWAS revealed hvKp-associated accessory genes linked to envelope stress response, nucleotide metabolism, and membrane transport, highlighting adaptive traits beyond canonical virulence loci. ConclusionOur findings redefine the hvKp/cKp dichotomy as a continuum shaped by plasmids and selective pressures. The emergence of dual-risk clones has urgent implications for diagnostics, surveillance, and treatment strategies in regions with high AMR prevalence.

genomics↗

DeepEpitope: Leveraging Transformation-Based protein Embeddings for Accurate linear Cancer B-cell Epitope Identification

Conventional cancer treatments tend to have serious side effects, leading to the quest for safer and more specific treatment modalities. Immunotherapy with vaccines has appeared as a promising option, with B-cell epitopes being crucial for the generation of humoral immunity. But identification of the correct B-cell epitopes of cancer is a severe challenge since current tools are not pre-trained with cancer-generated datasets. To bridge this gap, we introduce DeepEpitope, a command-line tool based on deep learning designed exclusively for the prediction of linear B- cell epitopes from cancer antigens. We compiled a high-quality dataset from the Cancer Epitope Database and used Evolutionary Scale Modeling (ESM) embeddings to represent epitope and non-epitope sequences as vectors of 1280 dimensions. These embeddings were employed to train five machine learning models (Logistic Regression, Random Forest, XGBoost, LightGBM, and Naive Bayes) and three deep learning models (Multilayer Perceptron [MLP], Convolutional Neural Network, and Bidirectional LSTM). Of these, the MLP model performed best with an AUC of 0.85 and a benchmark AUC of 94%. In comparison with other tools like BepiPred (60%) and LBtope (54%), DeepEpitope demonstrated much higher predictive accuracy. It is a Linux- based command-line tool that can be accessed for free at: https://github.com/karthick1087/DeepEpitope.

cancer biology↗

Dynamic remodeling of centrioles and the microtubule cytoskeleton in the lifecycle of chytrid fungi

Cells reorganize in space and time to move and divide - complex behaviors driven by their internal cytoskeleton. While we have substantial knowledge of the molecular parts and rules of cytoskeletal assembly, we know less about how structures are remodeled, for example to interconvert centrioles from the ciliary base to the centrosome. To study this in an evolutionary context we use the chytrid fungus, Rhizoclosmatium globosum, a member of the zoosporic fungi which have centrioles and cilia, lost in other fungal lineages. Chytrids undergo reorganization of their microtubule cytoskeleton as they cycle from zoospore to multinucleated coenocyte. We use comparative bioinformatics, RNA sequencing, and expansion microscopy to map the microtubule cytoskeleton over the chytrid lifecycle. We find that when zoospores encyst, cilia are retracted into the cytoplasm and degraded, and centrioles detach but are protected from degradation. A shortened proximal centriole then forms the mitotic centrosome and ultimately elongates to form cilia at the end of the mitotic cycles, driven by a conserved transcriptional program. Thus, structural remodeling of the chytrid centriole is coupled temporally to ciliated stages rather than mitotic cycles, which may serve as a mechanism to tune microtubule organization to meet the needs of different lifecycle stages.

cell biology↗

Genome Analyses of A Worldwide Multisource Collection of Klebsiella variicola Reveal Adaptation Relevant for Human Infection

AO_SCPLOWBSTRACTC_SCPLOWKlebsiella variicola (K.var), part of the Klebsiella pneumoniae (K.pne) species complex, is an emerging human pathogen originally associated with plants. Phylogenomic analyses of a global dataset of isolates categorised as human, animal, plant, or environmental strains suggest that K.var are broadly disseminated regardless of hosts or habitats and exhibit genomic variability that is relevant for occupying and transmitting within and across multiple sources. Ancestral state analyses confirm that K.var are originally derived from non-human sources. Genome-wide association analyses of human versus non-human isolates of K.var indicate isolates from human origins are linked to the loss of cold-shock response genes such as lpxP and cspB. Importantly, human K.var isolates also showed enriched antimicrobial resistance gene content and diversity acquired through mobile genetic elements, horizontal gene transfer and mutations within the chromosomal loci which underscore the impact of antimicrobial exposure and proximity to antibiotic resistant K.pne in nosocomial environments. Capsular profiles of K.var suggest high levels of variability in gene composition and indicate that gene functionality for wcaJ in capsule formation differs between K.var and K.pne. Although capsular specialisation was not observed in a host/habitat or lineage-dependent manner, human isolates harbour, on average, a higher siderophore gene content in addition to mrkD mutations which impact on fimbriae and biofilm formation. There is limited evidence of any specific K.var lineages exhibiting convergence of both virulence and antimicrobial resistance genotypes which suggest that these attributes are evolving independently in clinical strains. Our work highlights that gene attrition and acquisition provide a basis for adaptation of K.var as human pathogens. The broad distribution and evolution of K.var highlight the need for improved diagnostic precision and surveillance under a One Health framework.

microbiology↗

VaxOptiML: Leveraging Machine Learning for Accurate Prediction of MHC-I & II Epitopes for Optimized Cancer Immunotherapy

In the realm of cancer immunotherapy, the ability to accurately predict epitopes is crucial for advancing vaccine development. Here, we introduce VaxOptiML (available at https://vaxoptiml.streamlit.app/), an integrated pipeline designed to enhance epitope prediction and prioritization. Utilizing a curated dataset of experimentally validated epitopes and sophisticated machine learning techniques, VaxOptiML features three distinct models that predict epitopes from target sequences, pair them with personalized HLA types, and prioritize them based on immunogenicity scores. Our rigorous process of data cleaning, feature extraction, and model building has resulted in a tool that demonstrates exceptional accuracy, sensitivity, specificity, and F1-score, surpassing existing prediction methods. The robustness and efficacy of VaxOptiML are further illustrated through comprehensive visual representations, underscoring its potential to significantly expedite epitope discovery and vaccine design in cancer immunotherapy, Additionally, we have deployed the trained ML model using Streamlit for public usage, enhancing accessibility and usability for researchers and clinician.

bioinformatics↗

Ventral hippocampus mediates inter-trial responding in signaled active avoidance

The hippocampus has a central role in regulating contextual processes in memory. We have shown that pharmacological inactivation of ventral hippocampus (VH) attenuates the context-dependence of signaled active avoidance (SAA) in rats. Here, we explore whether the VH mediates intertrial responses (ITRs), which are putative unreinforced avoidance responses that occur between trials. First, we examined whether VH inactivation would affect ITRs. Male rats underwent SAA training and subsequently received intra-VH infusions of saline or muscimol before retrieval tests in the training context. Rats that received muscimol performed significantly fewer ITRs, but equivalent avoidance responses, compared to controls. Next, we asked whether chemogenetic VH activation would increase ITR vigor. In male and female rats expressing excitatory (hM3Dq) DREADDs, systemic CNO administration produced a robust ITR increase that was not due to nonspecific locomotor effects. Then, we examined whether chemogenetic VH activation potentiated ITRs in an alternate (non-training) test context and found it did. Finally, to determine if context-US associations mediate ITRs, we exposed rats to the training context for three days after SAA training to extinguish the context. Rats submitted to context extinction did not show a reliable decrease in ITRs during a retrieval test, suggesting that context-US associations are not responsible for ITRs. Collectively, these results reveal an important role for the VH in context-dependent ITRs during SAA. Further work is required to explore the neural circuits and associative basis for these responses, which may be underlie pathological avoidance that occurs in humans after threat has passed.

neuroscience↗

Urea excreted by tropical frogs is explained by their body mass and the mass of insects consumed

Frog insect interactions are prominent and they result in services that are crucial in the ecosystem. The primary nitrogenous waste that frogs produce is urea. However, the role of biotic variables on urea excretion, has not been fully investigated. Frogs comprising of six Polypedates maculatus and seven Minervarya agricola were maintained in controlled condition after tagging them with passive integrated transponders. Thirteen experiments were performed to test whether, frog species or frogs body mass or insect body mass, or a combination of these explained the amount of urea excreted by the frogs. We found that body mass of the frogs and the amount of insect biomass consumed explained the amount of urea excreted in the two species. In the light of these findings, we discuss the role of frogs in converting insect biomass into urea in the ecosystem.

physiology↗

De novo genome assembly of the saw-scaled viper Echis carinatus, a medically important venomous snake in the Indian Subcontinent

Echis carinatus is a widely distributed venomous snake in the Indian subcontinent. It is one of the "Big Four" snake species responsible for mortality and severe health complications caused by envenomations. Given the significance of the species for human health, we assembled and annotated the whole genome of E. carinatus. Using long reads for assembly and short reads for correction, we achieved a highly contiguous 1.57Gb assembly, with a contig N50 of 17.1 Mb and scaffold N50 of 23.5 Mb. We could map 96.58% of our reads back to the assembled genome, and Benchmarking Universal Single-Copy Orthologs (BUSCO) score of 97.4%, indicates near completeness. 48.59% of the genome had repeat elements. The predominant types of repeats include retrotransposons (LINEs, SINEs and LTR elements), DNA transposons and satellite DNA (SSRs). Additionally, we conducted a gene prediction analysis, identifying a total of 26,711 protein-coding genes. These genes included alternatively spliced products, leading to the prediction of 31,106 proteins, 77.6% of which were successfully annotated using Blastp and InterProScan. Out of the total predicted gene set, we identified 119 toxin-coding genes, crucial for venom toxin production in the species. The acquisition of toxin sequence-based information resulted in a valuable dataset of genes that are involved in venom production in E. carinatus. This dataset advances our understanding of the biological processes underlying venom production and lays the foundation for the development of new antivenom formulations.

genomics↗

ompC/F mutations drive XDR phenotype and lineage defining super clones of E. coli: Sequential events and consequences

Multi-drug resistant Escherichia coli is an increasing public health problem. Though, PBP3 insertions with blaNDM, blaCMY and blaOXA-48 like is restricted to South-East Asia with few reports from USA. The study suggests ompC/F variants as a core factor to classify ESBL (E), non-ESBL (NE), and ESBL with PBP3 and carbapenemases (EPBP3) clones. EPBP3 results in treatment complication, as most of the time, E. coli with PBP3 insertions co-carries blaNDM (87.5%), blaCMY (96.3%) and blaOXA-48 like (88.8%) implicating it as a predisposing factor for carbapenemase gene acquirement. Cefiderocol and cefepime/zidebactam are the choice against EPBP3 E. coli. Evolutionary BEAST analysis revealed consecutive events of YRIN and YRIK insertions in PBP3 gene leading to a surge in MDR E. coli clones. Further, emergence of the super clones STs 410, 405, 167 and 617 featuring these phenotypes is a major threat for developing and developed countries, which needs close monitoring. ImportanceThe manuscript describes various E. coli resistant genotypes across the globe and their importance in the choice of antimicrobial for treatment. The study identified six clades based on ompC and ompF mutations with a strong correlation to PBP3 insertions co-carried with beta-lactamases including blaNDM. Though, the ompC and ompF mutations were reported to precede the acquisition of carbapenemases in E. coli, clade segregation based on AMR genes as observed in this study reveals the ompC and ompF genes as a potential biomarker for AMR clade identification in E. coli. Currently, cefiderocol and cefepime/zidebactam seems to be the only choice to cover the AMR mechanism mediated by PBP3 insertions. Further, emergence of the super clones STs 410, 405, 167 and 617 featuring these PBP3 phenotypes is a major threat for developing and developed countries, which needs close monitoring.

genomics↗

Genomic analysis unveils the role of genome degradation events and gene flux in the emergence and persistence of S. Paratyphi A lineages

Paratyphoid fever caused by S. Paratyphi A is endemic in parts of Asia and Sub-Saharan Africa. The proportion of enteric fever cases caused by S. Paratyphi A has substantially increased, yet only limited data is available on the population structure and genetic diversity of this serovar. We examined the phylogenetic distribution and evolutionary trajectory of S. Paratyphi A isolates collected as part of the Indian enteric fever surveillance study "Surveillance of Enteric Fever in India (SEFI)." In the study period (2017-2020), S. Paratyphi A comprised 17.6% (441/2503) of total enteric fever cases in India, with the isolates highly susceptible to all the major antibiotics used for treatment except fluoroquinolones. Phylogenetic analysis clustered the global S. Paratyphi A collection into seven lineages (A-G), and the present study isolates were distributed in lineages A, C and F. Our analysis documented that the genome degradation events and gene acquisitions or losses play a major role in the evolution of new S. Paratyphi A lineages/sub-lineages. A total of 10 pseudogene-forming mutations possibly associated with the emergence of lineages were identified. Pan-genome analysis identified the insertion of P2/PSP3 phage and acquisition of IncX1 plasmid during the selection in 2.3.2/2.3.3 and 1.2.2 genotypes, respectively. We also identified that the six characteristic missense mutations associated with the lipopolysaccharide (LPS) biosynthesis genes of S. Paratyphi A confer only a low structural impact and would therefore have minimal impact on vaccine effectiveness. Since S. Paratyphi A is human restricted, high levels of genetic drift are not expected unless these bacteria transmit to naive hosts. However, public-health investigation and intervention by means of genomic surveillance would be continually needed to avoid S. Paratyphi A serovar becoming a public health threat similar to the S. Typhi of today.

genomics↗

Genomic rearrangements of mobile genetic elements associated with carbapenem resistance of Acinetobacter baumannii

With the excessive genome plasticity, Acinetobacter baumannii has the capability to acquire and disseminate antimicrobial resistance genes that are often associated with mobile genetic elements (MGE). Analyzing the genetic environment of resistance genes often provides valuable information on the origin, emergence, evolution and spread of resistance. Thus, we characterized the genomic features of some clinical isolates of carbapenem-resistant A. baumannii to understand the role of diverse MGE and their genetic context that are responsible for the dissemination of carbapenem resistance genes. For this, a total of 17 clinical isolates of A. baumannii obtained from multiple hospitals in India between the years 2018 and 2019 were analysed. Antimicrobial resistance determinants, genetic context of resistance genes and molecular epidemiology were studied using whole genome sequencing. A high prevalence of blaOXA-23 was observed followed by the presence of dual carbapenemase, blaOXA-23 and blaNDM. Three novel Oxford sequence types were identified. Majority of the isolates belonged to dominant clone, IC2 followed by less prevalent clones such as IC7 and IC8. Complex diverse AbaR4 like and AbGRI-like islands belonging to IC2 lineage were identified. To the best of our knowledge, this is the first study that provides a comprehensive profiling of resistance islands along with the MGE, acquired antimicrobial resistance genes and the distribution of clonal lineages of carbapenem resistant A. baumannii from India.

microbiology↗

Identification of potential carboxylic acid-containing drug candidate to design novel competitive NDM inhibitors: An in-silico approach comprising combined virtual screening and molecular dynamics simulation

Metallo-{beta}-lactamases (MBLs) producing bacteria especially the ones with New Delhi metallo-beta-lactamase-1 (NDM-1) and its variants can potentially hydrolyse all the major {beta}-lactam antibiotics, ultimately escalating anti-microbial resistance world-wide. There is a dearth of approved inhibitors to combat NDM and other MBLs producing bacteria. Hence we focussed to find novel inhibitor(s) in-silico which can potentially suppress the activity of NDM/ MBLs. 2400 compounds were virtually screened to identify a promising carboxylic acid-containing compound (CID-53986787) analogous to NDM antagonist Captopril. Our lead compound can bind adjacent to the active site zinc ions (Zn1 and Zn2) in all highly resistant NDM variants. CID-53986787 possesses ~5-8% higher binding affinity than Captopril, exhibiting molecular interactions with crucial residues that can destabilize the hydrolytic activity of NDM. CID-53986787 was virtually evaluated to ascertain its safe pharmacological/ toxicity profile. Molecular dynamics simulation studies elucidated its stable interaction with the target protein (NDM-1).

bioinformatics↗

Colistin resistance in Acinetobacter baumannii is driven by multiple genomic traits: Evaluating the role of ISAba1-driven eptA overexpression among Indian isolates

Colistin resistance in Acinetobacter baumannii is mediated by multiple mechanisms. Recently, mutations within pmrAB two component system and overexpression of eptA due to upstream insertion of ISAba1 play a major role.To characterize colistin resistance mechanisms among the clinical isolates of A. baumannii in India. A total of 224 clinical isolates of A. baumannii collected from 2016 to 2019 were included in this study. Mutations within lipid A biosynthesis and pmrAB genes were characterized by Whole Genome Shotgun sequencing. Twenty eight complete genomes were further characterized for insertional inactivation of lpx genes and the association of ISAba1-eptA using hybrid assembly approach. Non-sysnonymous mutations like M12I in pmrA, A138T and A444V in pmrB and E117K in lpxD were identified. Four of the five colistin resistant A.baumannii isolates had insertion of ISAba1 upstream eptA. No mcr genes were identified.Overall, the present study highlights the diversity of colistin resistance mechanisms in A. baumannii. ISAba1-driven eptA overexpression could be responsible for colistin resistance among Indian isolates of colistin resistant A. baumannii.

microbiology↗

Evolutionary tracking of SARS-CoV-2 genetic variants highlights intricate balance of stabilizing and destabilizing mutations

The currently ongoing COVID-19 pandemic caused by SARS-CoV-2 has accounted for millions of infections and deaths across the globe. Genome sequences of SARS-CoV-2 are being published daily in public databases and the availability of this genome datasets has allowed unprecedented access into the mutational patterns of SARS-CoV-2 evolution. We made use of the same genomic information for conducting phylogenetic analysis and identifying lineage-specific mutations. The catalogued lineage defining mutations were analysed for their stabilizing or destabilizing impact on viral proteins. We recorded persistence of D614G, S477N, A222V V1176F variants and a global expansion of the PANGOLIN variant B.1. In addition, a retention of Q57H (B.1.X), R203K/G204R (B.1.1.X), T85I (B.1.2-B.1.3), G15S+T428I (C.X) and I120F (D.X) variations was observed. Overall, we recorded a striking balance between stabilizing and destabilizing mutations, therefore well-maintained protein structures. With selection pressures in the form of newly developed vaccines and therapeutics to mount soon in coming months, the task of mapping of viral mutations and recording of their impact on key viral proteins would be crucial to pre-emptively catch any escape mechanism that SARS-CoV-2 may evolve for. STUDY IMPORTANCEAs large numbers of the SARS CoV-2 genome sequences are shared in publicly accessible repositories, it enables scientists a detailed evolutionary analysis since its initial isolation in Wuhan, China. We investigated the evolutionarily associated mutational diversity overlaid on the major phylogenetic lineages circulating globally, using 513 representative genomes. We detailed phylogenetic persistence of key variants facilitating global expansion of the PANGOLIN variant B.1, including the recent, fast expanding, B.1.1.7 lineage. The stabilizing or destabilizing impact of the catalogued lineage defining mutations on viral proteins indicates their possible involvement in balancing the protein function and structure. A clear understanding of this mutational profile is of high clinical significance to catch any vaccine escape mechanism, as the same proteins make crucial components of vaccines recently approved and in development. In this direction, our study provides an imperative framework and baseline data upon which further analysis could be built as newer variants of SARS-CoV-2 continue to appear.

genomics↗

Mosaic antimicrobial resistance/virulence plasmid in hypervirulent ST2096 Klebsiella pneumoniae in India: The rise of a new superbug?

Hypervirulent K. pneumoniae (HvKp) is typically associated with ST23 clone; however, hvKp is also emerging from clones ST11, ST15 and ST147, which are also multi-drug resistant (MDR). Here, we aimed to characterise nine novel MDR hvKp isolates harbouring mosaic plasmids simultaneously carrying antimicrobial resistance (AMR) and virulence genes. Nine HvKp isolates obtained from hospitalised patients in southern India were characterized for antimicrobial susceptibility and hypervirulence phenotypes. All nine hvKp isolates were subjected to whole genome sequencing (WGS) using Ilumina HiSeq2500 and a subset of four were sequenced using Oxford Nanopore MinION. Among the nine isolates, seven were carbapenem-resistant, two of which carried blaNDM-5 on an IncFII plasmid and five carried blaOXA-232 on a ColKP3 plasmid. The virulence determinants were encoded in a mosaic plasmid ([~]320 Kbp) that formed as a result of its insertion in a IncFIB-IncHI1B plasmid co-integrate. The mosaic plasmid carried AMR genes (aadA2, armA, blaOXA-1, msrE, mphE, sul1 and dfrA14) in addition to rmpA2, iutA and iucABCD virulence genes. Interestingly the mosaic plasmid carried its own type IV-A3 CRISPR-cas system that is likely able to target the acquisition of IncF plasmid with the help of a traL spacer. The convergence of virulence and AMR is the biggest threat among invasive K. pneumoniae infections. However, increasing reports of the presence of mosaic plasmid carrying both AMR and virulence genes suggests MDR-hvKp isolates are no longer confined to selected clones and the containment of such isolates is very challenging. IMPORTANCEKlebsiella pneumoniae is an opportunistic pathogen that commonly associated with hospital-acquired infections in the urinary tract, respiratory tract, lung, wound sites. The organism has gained notoriety by acquiring additional genetic traits to become either hypervirulent (HV) phenotype or multidrug resistant (MDR) phenotype. Though the infections by both these phenotypes were very challenging to treat, the MDR K. pneumonia (MDR-Kp) were remained in the hospital settings while HV K. pneumonia (hvKp) strains were mostly originated from the community settings. In a recent turn of events, the evolution of MDR-Kp and hvKp has converged as both clones found to carry both MDR plasmids and virulence plasmid. These convergent strains are challenging to treat and is associated with higher mortality rate. As the recent hvKp isolates harbour mosaic plasmid encoding both AMR and virulence determinants there is a need to investigate the evolution of these pathogens. The significance of our research is in characterising the novel mosaic plasmid identified in MDR-hvKp isolates that belong sequence type (ST) 2096. Tracking the possible evolution pathway of MDR-hvKPs would greatly help in the proper surveillance and management of this superbugs. RepositoriesThe whole genome sequences of the present study isolates have been deposited in GenBank, NCBI, with accession numbers CP053765 - CP053770, CP053771 - CP053780, CP058798-CP058806, JAARNO010000001.1 - JAARNO010000005.1, JAAQSG000000000, JAARNJ000000000, JAARMH000000000 and JAAQTC000000000

genomics↗