Biology subjects

Cui, X.

Publications and source records attributed to Cui, X..

At least 19 recordsLinked to original sources

bioRxiv2026

TopoFlow: Evolutionarily Conditioned Flow Matching for Protein Conformational Ensemble Generation

Proteins function through dynamic conformational ensembles rather than a single static structure, yet accurately modeling these ensembles remains challenging. Here, we introduce TopoFlow, an evolutionarily conditioned flow-matching framework for protein conformational ensemble generation. TopoFlow uses evolutionary representations from multiple sequence alignments (MSAs) to encode global conformational heterogeneity. It combines this with structural variables from a variational autoencoder (VAE) to capture local flexibility. These complementary representations are then adaptively fused through a conditional modulation module to construct unified conditioning features that guide protein conformational ensemble generation. On the ATLAS molecular dynamics (MD) benchmark, TopoFlow improved the Jensen Shannon metrics for pairwise distances (JS-PwD), radius of gyration (JS-Rg), and time-lagged independent components (JS-TIC) by 10.73%, 5.78% and 7.75%, respectively, relative to BioEmu. Notably, this performance generalizes to experiment-based evaluation, where TopoFlow exhibits strong agreement with experimental observables, including chemical shifts (CS) and small-angle X-ray scattering (SAXS). Ablation analyses further indicated that the evolutionary representations and structural latent variables contributed complementary information to ensemble generation. Our results suggest that TopoFlow, through its integration of evolutionary and structural latent information, offers a promising strategy for generating structurally plausible and conformationally informative protein ensembles.

bioinformatics↗

bioRxiv2026

High-order enhancer hubs buffer allelic regulatory variation through kinetic compensation

Diploid genomes carry millions of heterozygous variants in cis-regulatory DNA, yet most genes produce similar RNA output from two parental alleles. How this balance is maintained is unclear. We developed Nanopore-HiChIP, a long-read method that maps high-order enhancer hubs on each haplotype. Over half of these enhancer hubs differ in chromatin architecture and transcription-factor occupancy between homologous chromosomes, but their target genes show substantially lower rates of allele-specific expression than genes lacking hub regulation. Single-cell kinetic modeling shows that burst frequency and burst size change in opposite directions, thereby preserving balanced transcriptional output. This hub-mediated kinetic buffering is enriched at haploinsufficient genes and coincides with smaller effects of expression quantitative trait loci. Enhancer hubs therefore absorb allelic regulatory variation through kinetic compensation, protecting dosage-sensitive transcription.

genomics↗

bioRxiv2026

Interrogation of noncoding schizophrenia risk variants using CRISPR-based functional genomics

Schizophrenia (SCZ) is a highly heritable complex disorder influenced by coding and noncoding genetic variation. Its genetic causes, particularly those involving noncoding variation, are largely unknown. High-throughput CRISPR screens enable dissection of disease-associated loci and identification of noncoding regulatory elements and variants that modulate gene expression. We screened SCZ GWAS loci linked to genes that are also associated in whole-exome sequencing studies to identify regulatory elements and variants impacting expression of disease-relevant genes. We used CRISPRi paired with HCR-FlowFISH to epigenetically silence 333 putative regulatory elements and measure the downstream effects on gene expression of causal SCZ genes, FAM120A, SV2A, and STAG1, in iPSCs and iPSC-derived neurons (iNeurons). We identified 78 regulatory elements that significantly alter expression of a SCZ gene, including noncoding enhancers/silencers as well as promoters of genes and lncRNAs. Pooled prime editing screens interrogated noncoding variant influence on gene expression for SCZ-associated variants and uncharacterized common variants from diverse population studies. We find that a common variant in the promoter of SV2A, rs112851681:A>G (MAF = 3.56%, 1000 Genomes) enhances transcriptional activity in iPSCs and iNeurons. These findings show distinct noncoding mechanisms that map within GWAS signals, and provide a path forward for interrogating noncoding regulatory elements and variants in disease loci.

genomics↗

bioRxiv2026

Cross-Kingdom Control: Yeast Prion Protein Modulates Host Physiology in Drosophila

Prions, once mainly studied for their pathogenic roles, are now gaining recognition as adaptive elements in microbial physiology. Over one-third of wild yeast isolates harbor prion proteins, yet their impact on host-microbe interactions remains poorly characterized. Given the ecological dominance of yeasts in the Drosophila mycobiome, we leveraged the Drosophila melanogaster-Saccharomyces cerevisiae system to investigate how the mycobiome-derived prion, [MRPL10+], modulates host physiology. We show that flies exposed to [MRPL10+] yeast exhibit significantly enhanced cold tolerance and increased locomotor activity. This effect persists with heat-killed yeast and diluted culture, suggesting a stable, potent bioactive factor. Using the genetically diverse Drosophila Global Diversity Lines (GDL), we identified natural variation in responsiveness to [MRPL10+] yeast. Genome-wide association and functional RNAi screening revealed a gut-brain signaling axis involving genes critical for digestion, intercellular communication, transcription regulation, and neural transmission. Notably, serotonin and octopamine pathways were essential for [MRPL10+]-induced changes in cold tolerance and locomotion, implicating neuromodulatory circuits in prion-mediated microbial signaling. Our findings establish a mechanistic link between a fungal prion and host metabolic and neural adaptation. This work provides the first genetic dissection of a prion-mediated host-microbe interaction, laying the groundwork for investigating beneficial prions in complex microbial communities and highlighting a new dimension of the mycobiomes influence on animal physiology.

evolutionary biology↗

bioRxiv2026

An open-access CT-based 3D anatomical dataset of extant sharks across all major lineages

0Sharks exhibit extraordinary morphological diversity across a wide range of ecological niches, yet large-scale, high-resolution digital datasets of their internal anatomy remain limited. Here we present an open-access 3D shark anatomical repository derived from published X-ray computed tomography (CT) data, featuring manually segmented and systematically annotated models of the chondrocranium, visceral arches, axial skeleton, musculature, and viscera in standard STL format. The dataset comprises 117 individuals, representing 72 species across 25 families and all nine extant shark orders, with 115 full-body reconstructions and two head-only models. This open-access dataset offers a comprehensive resource for comparative anatomy, biomechanical simulations, evolutionary developmental biology and biomimetics research of extant sharks.

evolutionary biology↗

bioRxiv2026

NLR from soybean Rsv1 locus confers broad-spectrum resistance to soybean mosaic virus G1-G7 strains by recognizing viral P3 protein

Nucleotide-binding leucine-rich repeat (NLR) immune receptor genes are of significant value in disease resistance breeding and the control of viral diseases. Soybean mosaic virus (SMV) poses a serious threat to soybean production and the Rsv1 locus in soybean cultivar Suweon 97 confers broad-spectrum resistance against SMV strains G1 to G7; however, this locus harbors no fewer than 18 NLR genes, and thus the broad-spectrum antiviral mechanisms underlying the Rsv1 locus remain poorly understood to date. Here, we established a rapid and highly efficient screening system for cloning NLR genes from soybean Rsv1 locus and identified a broad-spectrum antiviral NLR gene 13g184900 from this highly complicated locus. The NLR encoded by 13g184900 can recognize viral P3 protein from all SMV strains (G1-G7) and another potyvirus Bean common mosaic virus (BCMV). The coiled-coil (CC) domain of this NLR directly interacts with viral P3 protein. Additionally, we showed that this NLR originated from wild soybean accession in East China and has been introduced into several soybean cultivars during domestication. Collectively, we developed a high-throughput screening system for identifying NLR genes in soybean and our study provides new mechanistic perspective on how the Rsv1 locus mediates the broad-spectrum resistance to all SMV G1-G7 strains.

plant biology↗

bioRxiv2026

A unified smoothing framework for protein domain bigram model

MotivationBiomolecular sequences can be represented as strings over an alphabet, an analogy that has motivated many applications of computational linguistic techniques to biological problems. However, such methods must be adapted to the characteristic scale and organization of biomolecular data. Here, we consider the problem of bigram smoothing for multidomain protein architectures, where domain bigram frequency data is extremely sparse and differs from textual data in alphabet size, string length distribution, the relationship between bigram and unigram frequencies, tandem repeat lengths, and the distribution of domain adjacencies. Moreover, some domain combinations are unobserved because they are biologically incompatible, others because the data are incomplete. A smoothing method that distinguishes these two cases is required. ResultsWe propose a unified smoothing framework based on interpolation that can be tuned to accommodate different bigram data characteristics. Within this framework, we design specific model variants suited to protein domain bigram data: these assign low adjusted counts to pairs that are likely incompatible, while making appropriate adjustments for undersampled pairs. We demonstrate empirically that this approach distinguishes the two cases while preserving the characteristic signatures of multidomain data. Availability and implementationImplementations of smoothing methods, the scripts used to generate all results presented in this paper, and the curated lists of extracellular and DNA-binding domains are available at https://codeberg.org/xcui297/protein-domain-smoothing.

bioinformatics↗

bioRxiv2026

scMTG reconstructs single-cell temporal dynamics with Markov transition generators

Single-cell time-series data offer a unique opportunity to study how cell states emerge, evolve, and diversify over time. However, cells are destructively measured across time points and individual cells cannot be directly tracked, making it challenging to reconstruct cell-state transitions and uncover the dynamic regulatory programs. Existing methods are predominantly based on optimal transport and typically require predefined low-dimensional representations, which can limit scalability, flexibility, and mechanistic interpretability. Here we present scMTG, a single-cell Markov transition generative framework that jointly learns cell representations and temporal cell-state transitions from unpaired single-cell time-series data. In a series of experiments, scMTG demonstrates superior performance in interpolating held-out missing-time-point data and inferring cross-time-point transition matrices, compared with state-of-the-art methods. More importantly, the learned Markov transition generator provides an interpretable framework for identifying the molecular programs that drive cell-state changes, enabling characterization of cell fate decisions and construction of time-resolved regulatory networks. Together, scMTG provides a unified generative framework for reconstructing cellular dynamics and uncovering regulatory programs that shape development, differentiation, and disease progression. scMTG is available as open-source software at https://github.com/liuq-lab/scMTG.

bioinformatics↗

bioRxiv2026

TipQUANT: A robust algorithm for quantitative analysis of spatiotemporally dynamic activities in tip-growing cells

Cell polarity, essential for cell development and function, relies on dynamic subcellular distribution of structural and signaling molecules. Tip growth, an extreme form of polar growth, involves unidirectional expansion at the apical region of cells and requires precise spatiotemporal coordination to achieve periodic and directional growth. Understanding their spatiotemporal dynamics is critical for elucidating mechanisms and functions of cell polarity. However, manual quantification of such dynamics is extremely time-consuming, hindering advancements in the field. Current algorithms have limited power and flexibility in analyzing the distribution and dynamics of molecules and structures, particularly for tip-growing cells with oscillatory and dynamic behavior. To address this challenge, we present TipQuant, an automated analysis tool that robustly detects tips and analyzes spatiotemporal dynamics of fluorescently labeled molecules/structures on plasma membranes and in cytoplasm at apices of tip-growing cells, enabling quantitative understanding of signaling and structural components in these systems.

cell biology↗

bioRxiv2026

WTR: A Toolkit for Functional Anterograde Transsynaptic Circuit Mapping

The brain coordinates animal physiology and behavior via neuronal circuits. To understand and simulate brain functions, it is essential to delineate the synaptic connectivity between neurons. Transsynaptic tracers serve as powerful tools for such purposes. In response to the demand for anterograde tracers for circuit mapping and functional interrogation, we developed WTR, a fusion protein of mammalian codon-optimized WGA, TEV-protease cleavage sequence, and Recombinase. WTR expressed via AAV vectors in cell-type-specific starter neurons reaches their postsynaptic neurons and releases Cre/Flpo upon exposure to TEV-protease expressed in downstream neurons. Accompanied by Cre/Flpo-dependent expression of EGFP, GCaMP7s, or ChR2, the toolkit enables labeling, recording, or manipulation of downstream neurons. We utilized WTR to characterize downstream neurons of either glutamatergic or GABAergic neurons in the preoptic area of anterior hypothalamus for their differential actions in thermoregulation or stress responses, respectively. These results establish WTR as a versatile platform for functional anterograde circuit mapping.

neuroscience↗

bioRxiv2026

Genetically Engineered Biomimetic Nanozymes Reprogram Immune Niches to Intercept Colitis-Carcinoma Transition

Colitis-associated colorectal cancer (CAC) arises from chronic inflammatory niches characterized by persistent oxidative stress and dysregulated immune cell recruitment. Current anti-inflammatory therapies provide only transient symptom relief and fail to prevent malignant progression due to their inability to simultaneously mitigate oxidative injury and immune chemotaxis. Our analysis of clinical samples revealed markedly elevated C-X-C motif chemokine ligand 2 (CXCL2) in intestinal tissues from patients with inflammatory bowel disease (IBD) and CAC, implicating the CXCL2-CXCR2 axis in driving excessive neutrophil and macrophage infiltration and fostering tumorigenesis. Herein, we report a biomimetic nanozymes (PB@ECM) that reprogram inflammatory immune niches to intercept CAC progression. PB@ECM integrates a Prussian blue nanozyme core with genetically engineered macrophage membranes, enabling concurrent scavenging of reactive oxygen species through superoxide dismutase- and catalase-like activities and sequestration of CXCL2 via membrane-displayed CXCR2 receptors. In murine models of colitis and CAC, PB@ECM significantly alleviated intestinal inflammation, suppressed neutrophil and macrophage infiltration, and effectively inhibited colitis-carcinoma transition. By disrupting the pathological crosstalk between oxidative stress and immune chemotaxis, this work establishes a biomimetic nanozyme strategy for preventing inflammation-driven carcinogenesis.

bioengineering↗

bioRxiv2026

HitAnno: Atlas-level cell type annotation based on scATAC-seq data via a hierarchical language model

The single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) has emerged as a core technology for dissecting cellular epigenomic heterogeneity and gene regulatory programs. With the emergence of atlas-level scATAC-seq datasets, cell type annotation increasingly faces challenges arising from unprecedented data scale and increased cell-type diversity, which together place stringent demands on model reliability and robustness. Here, we introduce HitAnno, a hierarchical language model capable of accurate and scalable cell type annotation in atlas-level scATAC-seq data. Leveraging selected cell-type-specific peaks to construct "cell sentences", HitAnno employs a two-level attention mechanism that captures accessibility profiles hierarchically. Extensive evaluations show that HitAnno robustly annotates both major and rare cell types across multiple settings, including intra-dataset, cross-donor and inter-dataset annotation. The hierarchical attention mechanisms of the model reveal co-accessibility patterns among peaks and dependencies across higher-order peak sets, ensuring an interpretable annotation process. Training on a 31-cell-type human atlas, HitAnno can directly annotate new query datasets without retraining and is accessible through an online interface. Our model identifies heterogeneous subgroups within mixed labeled cells from unseen datasets, demonstrating its potential to assist researchers in refining existing cell atlases.

bioinformatics↗

bioRxiv2026

Spin-State Modulation by Atom-Cluster Synergy Steers H2O2 Conversion toward a Catalase-like Decomposition Pathway for Anti-Inflammatory Therapy

Nanozymes have emerged as promising enzyme mimics for anti-inflammatory therapy. However, their catalytic efficiency and substrate selectivity generally remain inferior to those of natural enzymes. Single-atom nanozymes (SAzymes), with isolated metal centers resembling enzymatic active sites, represent an important advance toward rational design of nanozyme, but achieving enzyme-like selectivity remains challenging. Herein, we reported a spin-state modulation strategy to prepare Fe-N-C nanozyme with coexisting single atoms and nanoclusters (FeSA+NC) via reductive-gas pyrolysis. Experimental analyses and density functional theory calculations revealed that Fe nanoclusters induced local symmetry breaking and charge redistribution around FeN4 sites, shifting the Fe centers toward a higher spin configuration and thereby modulating the free energy changes of the H2O2 conversion pathway. As a result, FeSA+NC showed dramatically enhanced catalase (CAT)-like activity (333.79 U mg-1) and suppressed peroxidase (POD)-like activity (38.49 U mg-1), achieving superior selectivity compared to Fe SAzymes (FeSA), which showed comparable CAT- and POD-like activities (62.39 and 60.39 U mg-1, respectively). Moreover, FeSA+NC achieved a higher superoxide dismutase (SOD)-like activity (929.27 U mg-1) than FeSA (249.68 U mg-1), enabling efficient SOD-CAT cascade. FeSA+NC effectively scavenged excessive intracellular reactive oxygen species, suppressed M1 macrophage polarization, and enhanced the therapeutic efficacy of intra-articular stem cell injection in a rat model of rheumatoid arthritis, a representative chronic inflammatory disease. This work highlights an atom-cluster synergy strategy for steering H2O2 conversion towards antioxidant pathway, offering a general design principle for safer, more controllable and more efficient nanozyme-based anti-inflammatory therapeutics.

bioengineering↗

bioRxiv2026

CellSwarm: LLM-Driven Cell Agents Recapitulate Tumor Microenvironment Dynamics and Sense Indirect Genetic Perturbations

Agent-based models of the tumor microenvironment (TME) traditionally rely on hand-coded rules that cannot generalize beyond their programmed logic. Here we present CELLSWARM, a framework that replaces rule-based cell decision-making with large language model (LLM)-driven autonomous agents. Each simulated cell maintains persistent state, 14 signal pathways, and a memory stream, with an LLM serving as its cognitive core. Using structured knowledge bases for cancer-specific context, CELLSWARM recapitulates TNBC microenvironment composition with fidelity comparable to hand-coded rules (Jensen-Shannon divergence 0.144 vs. 0.146; P=0.012 vs. random, Mann-Whitney U test). Beyond matching rule-based performance, LLM-driven agents demonstrate three capabilities absent from rule-based models: cross-cancer generalization by swapping knowledge base entries, treatment response prediction concordant with clinical data (anti-PD-1: 17.6% simulated vs. 21% clinical), and sensing of indirect genetic perturbations that propagate through intermediate signaling cascades (IFN-{gamma} KO: Agent +15.7% vs. Rules +0.3%; P=0.005). CELLSWARM demonstrates that LLM-driven cell agents can recapitulate and extend TME simulation beyond the reach of hand-coded rules.

systems biology↗

bioRxiv2026

Fully T2T pedigree assemblies reveal genetic stability and epigenetic plasticity of human centromeres across inheritance and cell-fate transitions

Centromeres are essential chromosome components yet remain poorly understood due to their highly repetitive sequence architecture. Using fully-phased telomere-to-telomere diploid assemblies from a three-generation pedigree integrated with long-read epigenomes from matched peripheral blood mononuclear cells, induced pluripotent stem cells, and neural progenitor cells, we generate allele-resolved single basepair resolution maps of centromere genetic and epigenetic dynamics across inheritance, reprogramming, and differentiation. We show that centromeric dip regions (CDRs), which define the functional core of centromeres, are positionally stable across generations and cell-fate transitions. In contrast, CDR epigenetic architecture is highly dynamic. Reprogramming markedly attenuates CDR hypomethylation, which is partially restored during differentiation in parallel with global hypomethylation of active alpha-satellite arrays and coordinated changes in nucleosome organization and protein occupancy. Centromeric remodeling is insulated from X-chromosome status, including Xa, Xi, and erosion. Finally, de novo mutations arising during reprogramming are enriched in centromeric regions but depleted within functional centromeric cores.

genomics↗

bioRxiv2026

The overall and sequence-specific degradation of soil extracellular 16S rRNA genes across China: rates and influential factors

While extracellular DNA persistence substantially influences soil microbiome investigations, its degradation kinetics remain poorly quantified. Here, we developed a primer-labeled DNA approach coupled with microcosm incubation to determine the overall and sequence-specific degradation rates of extracellular DNA amplicon fragments across China. We observed substantial variations in the overall degradation rates of extracellular 16S rRNA gene amplicon fragments among the study sites, with degradation rate constants ranging from 0.05 to 0.16 day-1. The overall degradation rate constants showed significant correlations with soil moisture content, prokaryotic abundance, prokaryotic community profiles, and mean annual precipitation (MAP). The significant influences of moisture content on the overall degradation rates were further verified by a moisture gradient microcosm experiment. The sequence-specific degradation rate constant profiles were additionally correlated with pH, nitrogen content, and mean annual temperature (MAT). Furthermore, propidium monoazide (PMA)-based exclusion of extracellular DNA signals significantly altered soil prokaryotic abundance, richness, and prokaryotic community profiles, and the pool sizes of sequence-specific extracellular 16S rRNA gene amplicon fragments were significantly correlated with their respective degradation rates. This study developed a methodology for determining the overall and sequence-specific degradation rates of extracellular DNA amplicon fragments, highlighting the profound influences of extracellular DNA on soil microbial research and informing the optimization of environmental DNA technologies. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=116 SRC="FIGDIR/small/699460v2_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@b1b3e2org.highwire.dtl.DTLVardef@98f334org.highwire.dtl.DTLVardef@1870650org.highwire.dtl.DTLVardef@1af7105_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗

bioRxiv2025

pGGTOX: a versatile plasmid platform for recombination-based genome editing across Enterobacteriaceae

Precise genome editing in Enterobacteriaceae is essential for studying gene function, pathogenesis, and antimicrobial resistance, yet many current systems face host-specific and efficiency limitations. We developed pGGTOX, a modular plasmid platform that enables efficient homologous recombination-mediated genome editing across diverse Enterobacteriaceae, including Escherichia coli, Klebsiella pneumoniae, Salmonella enterica, and Enterobacter intestinihominis. The system integrates a rhamnose-inducible toxin (MqsR) for stringent counterselection, a sfGFP reporter for visual tracking of recombination events, Golden Gate cloning for rapid assembly of homologous arms, an FRT-flanked resistance cassette for marker removal, and an oriT sequence for conjugative transfer. Together with the companion plasmid pCP20-oriT, pGGTOX supports precise, marker-free genomic modification. Using pGGTOX, we achieved targeted deletions of dapA in E. coli and mrkCD in carbapenem-resistant K. pneumoniae, both with 100% efficiency. The dapA mutant exhibited diaminopimelate auxotrophy, while mrkCD deletion markedly reduced biofilm formation, consistent with the loss of function associated with these genes. pGGTOX also enabled deletion of a 43.1-kb type IV secretion gene cluster (tra) from an IncN/FII plasmid in E. intestinihominis and insertion of a 10-kb CRISPR-Cas9 plasmid-curing module (pCasCure) into an S. enterica IncX1 plasmid. Deletion of the tra gene cluster resulted in a substantial reduction in plasmid conjugation efficiency. Conjugative transfer of the engineered IncX1-pCasCure plasmid into K. pneumoniae facilitated CRISPR-mediated curing of blaKPC, sensitizing carbapenem resistance to susceptibility. In summary, pGGTOX provides a versatile, efficient, and broadly applicable platform for genome engineering and CRISPR delivery in Enterobacteriaceae, expanding the toolkit for bacterial genetics and translational antimicrobial research. ImportancePrecise genetic manipulation in Enterobacteriaceae remains a major technical challenge, particularly for non-model or multidrug-resistant strains. We developed pGGTOX, a versatile and broadly applicable plasmid platform that enables efficient, marker-free genome editing through homologous recombination. By integrating stringent counterselection, visual screening, modular cloning, and conjugative transfer, pGGTOX simplifies construction and streamlines editing across multiple clinically relevant species. We demonstrate its utility in deleting chromosomal and plasmid-borne loci, inserting large genetic modules, and delivering CRISPR-Cas9 systems for targeted elimination of antibiotic resistance genes. This platform expands the molecular toolkit for functional genomics and provides a powerful new strategy for dissecting bacterial virulence, resistance, and plasmid biology.

microbiology↗

bioRxiv2025

Distinct and Shared Impacts of Virulence Plasmids on the Phenotype and Transcriptome in Convergent Carbapenem-Resistant and Hypervirulent Klebsiella pneumoniae

The global rise of convergent carbapenem-resistant and hypervirulent Klebsiella pneumoniae (CR-hvKp) represents a major clinical challenge, yet the role of virulence plasmids (pVirs) in shaping bacterial physiology and pathogenicity remains incompletely understood. Using a CRISPR-Cas9-based curing system, we precisely eliminated pVirs from two clinical CR-hvKp strains with distinct genetic backgrounds, ST23-KL1 (blaNDM-1) and ST11-KL64 (blaKPC-2). Loss of pVir conferred fitness advantages in vitro, reduced capsule production and hypermucoviscosity, and promoted biofilm formation, while markedly attenuating virulence in murine sepsis models. Despite this reduction, the pVir-cured ST23-KL1 strain retained higher virulence than the pVir-cured ST11-KL64 strain, underscoring the contribution of chromosomal background to pathogenic potential. Transcriptomic profiling revealed both shared and strain-specific transcriptional responses to pVir deletion, with broader perturbations observed in the ST11-KL64 strain. pVir removal had limited effects on antibiotic MICs. Complementation experiments further demonstrated differential regulatory roles of the rmpADC and rmpA2D2 operons in capsule expression and hypermucoviscosity across the two strains. Together, these findings establish pVirs as central determinants of CR-hvKp virulence and highlight complex host-plasmid interactions that influence bacterial adaptation and pathogenicity. IMPORTANCEThe emergence of carbapenem-resistant and hypervirulent Klebsiella pneumoniae (CR-hvKp) poses a critical threat to global health, yet the contribution of virulence plasmids (pVirs) to bacterial fitness and pathogenicity remains poorly defined. By employing a CRISPR-Cas9-based curing strategy, we dissected the role of pVirs in two genetically distinct CR-hvKp strains and uncovered their multifaceted impact on capsule production, hypermucoviscosity, biofilm formation, and virulence. Our findings reveal that pVir loss confers fitness advantages in vitro while attenuating virulence in vivo, with strain-specific transcriptional responses and differential regulation by rmp operons. These results underscore the complex interplay between plasmid-encoded and chromosomal determinants in shaping CR-hvKp pathogenicity and adaptation, offering mechanistic insights that may inform future therapeutic strategies targeting plasmid-mediated virulence.

microbiology↗