Cell Discovery

Japanese Encephalitis Virus (JEV) belongs to the Flavivirus family, and the RNA dependent RNA polymerase (RdRp) domain located at the C terminus of non structural protein 5 (NS5) regulates de novo viral genome synthesis. The conserved priming loop inserted in the thumb domain of RDRP initiates de novo genome synthesis. Interestingly, the reported replication process initiates with an interaction between NS5 (methyltransferase/RDRP) and NS3 (protease/helicase), and inhibiting this interaction directly correlates with the inhibition of viral replication. The function of the priming loop in the context of the NS5 NS3 interaction is not yet known. In this study, we studied the priming loop function in the NS5 NS3 interaction and viral replication. Using a structure based drug design approach, we screened the Maybridge compound library against the RdRp priming loop and identified 15 candidate compounds based on binding energy. Among them, DSHS00151 showed significant dose dependent inhibition of the NS5 NS3 interaction with an IC50 of 3.5 micromolar in the mammalian two hybrid assay, inhibited viral infectivity with an IC50 of 2.54 micromolar, and reduced viral RNA load with an IC50 of 2.9 micromolar, compared to CD10712. Molecular Dynamics (MD) simulations revealed that DSHS00151 exhibits stronger and more stable binding with the priming loop residues (790 to 812) compared to CD10712. The molecular mechanism suggested by the docking of the NS5 and NS3 proteins showed that the priming loop tends to rotate toward the NS3 protein to stabilize the complex, and compound binding restricts this loop rotation, thus compromising the stability of the NS5 and NS3 complex and affecting viral replication. Overall, our study validated the function of the NS5 priming loop as an allosteric site, and compounds binding to this allosteric site belong to the Non Nucleoside Reverse Transcriptase Inhibitors (NNRTI) class of inhibitors, which disrupt the NS5 and NS3 interaction and could be developed as novel anti JEV therapeutics.

Porcine deltacoronavirus (PDCoV) is a globally circulating coronavirus of swine that causes severe enteric disease and mortality in neonatal piglets. Its broad host range and zoonotic potential raises concerns about continued spillover into human populations. However, the host factors that govern PDCoV infection remain largely unexplored. Identifying host factors involved in virus infection may uncover novel therapeutic targets for antiviral drug development or targets for gene editing to create resistant pigs. Here, we conducted a genome-wide CRISPR knockout (GeCKO) screen to identify host factors contributing to PDCoV infection in swine testicular (ST) cells. Small guide RNAs (sgRNAs) targeting the ANPEP gene, expressing the main receptor porcine aminopeptidase N for PDCoV, were enriched in PDCoV-resistant cells, demonstrating the validity of the screen. Moreover, we identified transmembrane protein 30A (TMEM30A), an accessory {beta}-subunit of the P4-ATPase flippase complex, as a host dependency factor for PDCoV infection along with several potential PDCoV-induced cell death regulators, including DET1, IFNAR1, RFWD2, STAT1 and TP53. We further demonstrated that PDCoV attachment and internalization into cells were significantly impaired in TMEM30A knockout ST cells, suggesting that TMEM30A is important in the early stages of the PDCoV life cycle. Because TMEM30A also contributes to SARS-CoV-2 replication, future studies are warranted to investigate its mechanistic role in the context of coronavirus infection.

The resurgence of the Mpox virus (MPXV) highlights the urgent need for scalable, mutation-resistant countermeasures. Slow development timelines hinder traditional empirical vaccine discovery, while conventional vaccinology often yields high false-positive rates because it relies on static, linear sequence-based screening. These classical informatics filters consistently fail to predict physical structural stability or the dynamic presentation of immune cells under physiological conditions, creating a distinct translational gap between computational design and in vitro efficacy. To address these limitations, here we engineered an advanced, AI-augmented vaccine discovery pipeline targeting the most virulent components of the MPXV proteome. We systematically screened eight critical viral targets essential for replication, membrane morphogenesis, and host-cell entry to map highly conserved T-cell and B-cell epitopes. Moving beyond standard heuristic filtering, we implemented a high-fidelity deep learning validation layer: ESM-2 protein language models (pLMs) were deployed to calculate pseudo-perplexity scores across chimeric linker junctions (EAAAK, GPGPG) to guarantee structural naturalness, MHCflurry ensemble models successfully verified active intracellular antigen presentation, and structure-informed graph neural networks (GNNs) simulated the physical node-attention dynamics of the immune synapse. Finally, recurrent neural networks (RNNs)-driven mRNA kinetic modeling optimized translation initiation rates and minimum free energy profiles during in silico cloning. This multi-layered pipeline successfully yielded three structurally refined, multi-epitope vaccine constructs optimized for maximum global population coverage. ESM-2 structural validation confirmed exceptionally low perplexity scores at structural junctions, indicating that the engineered chimaeras have native-like stability and a minimized risk of proteolysis. GNN-based immune synapse modeling demonstrated highly stable binding kinetics and robust binding free energies between the target epitopes and human HLA alleles. Furthermore, RNN kinetic optimizations established that the cDNA sequences are optimized for high-yield expression in heterologous expression hosts without risk of ribosomal stalling or translational bottlenecks. This study establishes a deep learning-augmented framework that bridges the gap between theoretical sequence optimization and biopharmaceutical scalability. By validating the structural naturalness, real-world immunogenicity, and manufacturing kinetics of our vaccine chimeras, this framework presents a robust, proactive paradigm for rapid vaccine architecture against emerging orthopoxvirus threats.

Cilia are highly conserved organelles that use hundreds of unique proteins to drive extracellular motility and serve as signaling hubs for eukaryotic cells. The Ciliogenesis and Planar Polarity Effector (CPLANE) protein complex controls basal body docking during early ciliogenesis and recruits the intraflagellar transport (IFT) proteins to the base of growing cilia. Leveraging recent advantages in deep learning neural networks and high-performance computing, we predict the structure of JBTS17, the largest CPLANE subunit, and the tertiary structure of the complete CPLANE complex, revealing direct contacts between JBTS17 and three other CPLANE members. We then used this model for an in silico protein-protein interaction screen that identified several novel JBTS17 interactors. Experiments in Xenopus confirmed a functional link in vivo between Jbts17 and the Spinocerebellar ataxia-associated protein TTBK2. The data provide new insights into mechanisms of CPLANE function during ciliogenesis and demonstrate the power of modeling protein complexes for the discovery of physical and functional protein interactions in cell homeostasis and disease.

Dengue virus (DENV) causes dengue fever, a globally prevalent, epidemic-prone disease with no FDA-approved antivirals. Additionally, the available vaccine for DENV can increase the risk of severe dengue fever for those who have never had a DENV infection due to antibody-dependent enhancement. Thus, there is an urgent need to identify DENV antivirals. Drug repurposing, high-content screening, and machine learning were leveraged to efficiently identify antivirals likely to inhibit DENV replication. Using high-content screening in a DENV infection model, we characterized the morphological patterns of NS4B and envelope (E) protein expression over time and developed a viral pseudotime model that predicts infection progression to aid in phenotypic interpretation of drug effects. We then developed a single cell infection classifier for antiviral efficacy and performed high-throughput drug screening of 960 compounds. We identified four concentration-dependent inhibitors of DENV with nanomolar-to-submicromolar potencies: esomeprazole, GW4064, pralatrexate, and LY411575. With our pseudotime machine learning model trained on data from the time-series assay, we scored the concentration-dependent inhibitors to map their mechanism of action onto time points in the viral life cycle. Our most notable results show that LY411575, a gamma secretase inhibitor, exhibited an IC of 72 nM and reduced percent infection to near the level of the mock infection control. Pseudotime inferences generated mechanistic predictions that were supported by time-of-addition experiments, indicating that LY411575 arrests DENV infection before the development of late-stage infection associated morphologies, while retaining activity when added after inoculation.

Hepatitis B virus (HBV)-infected cells release hepatitis B surface antigen (HBsAg)-rich subviral particles (SVPs) in large excess over infectious virions. SVPs bind antibodies against HBsAg (anti-HBs), including neutralizing antibodies, but the physical products of antibody capture in human blood are uncharacterized. Here we used cryo-electron tomography (cryo-ET) to image HBsAg-enriched serum from a patient with severe acute Hepatitis B and observed three-dimensional assemblies of intact IgM-SVP immune complexes. These associations persisted at a lower particle density and were validated by a spatial-randomization null model. Subtomogram averaging and single-particle cryo-electron microscopy (cryo-EM) identified three serum IgM Fc-core assemblies, IgM-J-CD5L, IgM-J and IgM-J-SC, with cryo-EM maps reaching 2.8 angstrom resolution. Mapping these Fc core assemblies into tomograms revealed full-length IgM engaging individual SVPs through several Fab arms and bridging neighboring particles into immune complex networks containing multiple IgM molecules and SVPs. Thus, serum IgM uses multivalent Fab interactions to crosslink HBsAg-rich SVPs into supramolecular immune complexes. This observation extends the SVP decoy model from passive antibody sequestration to higher-order particle organization.

Emotional lability (EL) is a prevalent cross-diagnostic symptom with unclear etiology. Given the potential role of the gut-brain axis in linking gut microbiota to EL, we adopted a multi-step Mendelian randomization (MR) framework to investigate the causal effects of gut microbiota on EL and the mediating role of blood metabolites. Bidirectional two-sample MR was first implemented to determine the causal relationship and direction between gut microbiota and EL, followed by multivariable MR (MVMR) to assess the direct contributions of individual microbial taxa. We then applied a multistep MR approach to identify gut microbiota specifically associated with EL-related psychopathology. Finally, the mediation effects of blood metabolites were quantified via the coefficient of variation method, and pathway analysis was conducted to verify the biological plausibility of the enriched metabolic pathways. Bidirectional MR detected 16 gut microbiota species associated with EL risk. MVMR identified three causally associated bacteria: RUG013 sp001486445 exerted the strongest positive effect (odds ratio [OR] = 1.500, 95\% confidence interval [CI]: 1.029-2.187, P = 0.034), followed by CAG-485 sp002362485 (OR = 1.398, 95\% CI: 1.118-1.749, P = 0.003). Each standard deviation (SD) increment in CAG-485 sp002362485 was linked to a 39.8\% higher risk of EL. This bacterium was specific to EL and correlated with glycine/serine/threonine metabolites. Reverse MR analyses ruled out reverse causality .

Cellular diversity is required for the proper function of many tissues, including the retina, with its ~130 cell types.1-3 Previous lineage studies suggested that retinal progenitor cells (RPCs) generate cell diversity through biased cell divisions.4-9 However, the extent to which each progenitor cell contributes to diversity, and the overarching rules governing the lineages of the collection of progenitor cells, are unknown. While classic lineage tracing approaches including retroviral labeling4,6,10, dye injection11,12, and time-lapse microscopy13,14 were used to make the foundational insights regarding retinal lineages, they cannot be used to interrogate multigenerational lineages at scale. Here we describe the creation of an evolvable lineage tracing tool, "SCRIBBLE" for Sequential Combinatorial Recorder for Iterative Barcode-Based Lineage Evolution. SCRIBBLE uses prime editor to iteratively edit a barcode sequence while preserving the order of genesis of clonally related progeny. Through a series of rationally designed high-throughput screens and design optimizations, we identified novel sequences that support a high level of barcode editing and information content. Evaluation of SCRIBBLE in embryonic mouse retina recapitulated known lineages in retinal development, demonstrating that SCRIBBLE is capable of high-resolution lineage tracing in a complex tissue.

Pseudomonas species include important plant pathogens responsible for substantial agricultural losses. Although CRISPR-INTEGRATE has been applied for genome engineering in medically relevant Pseudomonas, its utility in plant-pathogenic Pseudomonas has not been established. Here, we demonstrate CRISPR-INTEGRATE, an RNA-guided Tn7-like transposition system that enables targeted chromosomal integration without double-strand breaks or host-dependent homologous recombination, across three plant-pathogenic Pseudomonas backgrounds. Targeted disruption of hrpJ, hrcC, and gacA was confirmed by PCR and Sanger sequencing and resulted in distinct phenotypes, including impaired type III secretion-associated virulence and hypersensitive response, altered colony morphology and biofilm formation, and reduced motility. We further coupled CRISPR-INTEGRATE with Cre-lox recombination to excise a ~40-kb prophage-associated region from the P. syringae pv. tomato DC3000 chromosome. Genomic characterization identified a 33.45-kb predicted prophage within this region, putative attL/attR sites sharing an identical 14-bp core sequence, an orthologous empty locus containing a candidate attB site, and conserved prophage-associated gene organization across P. syringae genomes. Deletion of the region altered bacterial growth and increased susceptibility to phage infection, with the strongest effect observed for phage Plaza, while having no detectable effect on the tested plant virulence phenotypes. Together, these findings establish CRISPR-INTEGRATE as a portable genome-engineering platform for plant-pathogenic Pseudomonas and demonstrate its utility for functional interrogation of individual genes and large accessory genomic elements.

Defective interfering particles (DIPs) represent promising antivirals against influenza A virus (IAV), yet strategies to further enhance their antiviral activity remain largely unexplored. Here, we engineered a next-generation OP7 DIP by truncating the viral interferon (IFN) antagonist non-structural protein 1 (NS1) to enhance IFN-mediated antiviral activity. A previously validated mathematical multiscale model predicted that loss of NS1 function would enhance antiviral activity, providing a mechanistic rationale for this design. We engineered OP7-trNS1 DIP, established a cell culture-based production process yielding infectious virus-free material, and evaluated its antiviral activity in human lung epithelial cells in vitro. OP7-trNS1 inhibited IAV replication by approx. two orders of magnitude more effectively than the parental OP7 DIP while inducing a stronger IFN response, consistent with the model predictions. Together, these findings demonstrate that reducing viral IFN antagonism is a viable strategy for rationally enhancing DIP antiviral activity and establish OP7-trNS1 as a promising candidate for further preclinical development.

Stem cell-derived (SC) islets hold promise as a transformative therapy for type 1 diabetes (T1D). To enhance graft uniformity, SC-islet organoids are often dissociated and reaggregated into standardized sizes. However, how endocrine cell composition varies with islet size in native human islets remains largely unknown. Defining this relationship is essential for establishing physiological benchmarks for islet engineering for transplantation. In this study, we examined the relationships among islet size, endocrine cell composition, and spatial distribution throughout whole pancreata from 10 age-matched, non-diabetic male subjects. Insulin-, glucagon-, and somatostatin-positive endocrine cells were identified as single-, double-, and triple-hormone populations ranging from non-islet single endocrine cells and small clusters (niSSCs) to large islets. Approximately 80% of the total endocrine area was contained in islets positive for all three hormones. Islet size strongly correlated with endocrine composition. Specifically, larger islets had increased alpha-cell fractions and reduced beta-cell fractions, while delta-cell fractions were consistent across sizes. Spatial analysis revealed that niSSCs, mono-, and tri-hormone islets frequently exhibit a clustered distribution. Additionally, tri-hormone islets were positioned near the core of the pancreas, whereas mono-somatostatin islets were often localized in the periphery. These findings were consistent across all three pancreatic regions (head, body and tail).

Metabolic disturbance is a key feature in acute kidney injury (AKI) and chronic kidney disease (CKD). The kidney highly depends on fatty acid metabolism; how renal cells rewire metabolism upon AKI and CKD transition remained unclear. Here, we combine spatial transcriptomics with biochemical analyses to characterize metabolic changes and intercellular interactions during AKI to CKD transition. Using aristolochic acid model of CKD, we spatio-temporally correlated changes in structure and function with metabolic profile during AKI to CKD transition. Surprisingly, keto-gluconeogenic metabolic axis was highly enriched in healthy kidney and paralleled injury phase transitions. Intercellular interaction analysis associated a subtype of macrophage with the drift to chronicity. Online scRNAseq datasets analysis confirmed altered keto-gluconeogenic metabolic pathways in ischemia-reperfusion injured mouse kidneys and AKI and CKD human kidney biopsies compared to healthy controls. This study identifies a metabolic axis transcriptionally mirroring renal homeostasis and injury responses, and tubulo-interstitial interactions that can be targeted to mitigate AKI to CKD transition.

Glycine transporter 1 (GlyT1) is a clinically investigated target whose conformational plasticity enables ligands to engage distinct extracellular and intracellular binding sites. However, methods to directly quantify intracellular binding remain limited and largely rely on radioligand-based approaches. Here, we report a NanoBRET-based binding assay to quantify intracellular GlyT1 target engagement in living cells using a fluorescent tracer derived from the GlyT1 inhibitor Cmpd1. With a structure-based approach followed by pharmacological characterization we identified a suitable meta-substituted exit vector for linker and fluorophore attachment while maintaining GlyT1 binding. A series of fluorescent probes was synthesized and evaluated, leading to the development of GlyT1-probe which displayed high-affinity binding and enabled robust NanoBRET measurements. Unlike the functional uptake assay, the NanoBRET assay distinguished intracellular from extracellular GlyT1 inhibitors and resolved structure-activity relationships at the intracellular binding site. This assay provides a quantitative approach to interrogate conformation-selective GlyT1 target engagement in living cells, facilitating the characterization of GlyT1 ligands targeting the intracellular site.

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a leading global health threat, especially due to multidrug-resistant strains. The first-line drug isoniazid (INH) and second-line drugs ethionamide (ETH) and prothionamide (PTH), are prodrugs that target the essential enoyl-ACP reductase InhA, a key enzyme involved in mycolic acid biosynthesis. Resistance to these drugs primarily arises from genetic mutations that inactivate the enzymatic function of their respective bioactivating enzymes. While the recent development of chemical boosters has shown promising results in restoring drug susceptibility in these mutants, genetic tools to dynamically modulate these pathways and fine-tune resistance could be extremely valuable to develop the next-generation of anti-InhA drugs. In this context, we leverage CRISPR interference (CRISPRi) to develop inducible and reversible genetic systems to fine-tune antibiotic susceptibility in Mycobacterium smegmatis (Msmeg) and Mtb. By using our CRISPRi-based approach we first generated an inducible inhA hypomorph, an essential target required for mycolic acid production and bacterial growth, therefore confirming that our method is fully functional. Then, we developed genetic tools to selectively target katG, ethA, and the transcriptional repressor ethR, in order to generate conditional hypomorphs with altered antibiotic susceptibility profiles. Antibiotic susceptibility assays confirmed that the conditional hypomorphs selectively displayed high-level resistance or hypervulnerability to INH or ETH upon CRISPRi induction. Altogether, this work establishes CRISPRi as a powerful genetic platform for selectively fine-tuning mycobacterial drug susceptibility, with potential applications in developing next-generation anti-TB therapies.

Cardiac G protein-gated inwardly rectifying potassium-K+ (GIRK) channels, formed by GIRK1/4 heterotetramers or GIRK4 homotetramers, are crucial regulators of heart rate, and their dysfunction is associated with atrial fibrillation. Despite their therapeutic potential as anti-arrhythmic targets, development of selective GIRK modulators has been limited by an incomplete understanding of their structures, gating mechanisms, and pharmacology. Here, we report high-resolution structures of the GIRK4 homotetramer and of GIRK1/4 heterotetramers, revealing that they form in unexpected 1:3 and 2:2 assembly stoichiometries that we corroborate using cell-based single molecule microscopy. Electrophysiological assays and molecular dynamics simulations further show that incorporation of one or two GIRK1 subunits into GIRK4-containing channels progressively opens the helix bundle crossing (HBC) gate and increases basal channel activity. Additional structures of GIRK1/4 complexes with ML297, a small-molecule ligand selective for GIRK1-containing channels, reveal distinct GIRK1-centered intersubunit binding environments. Remarkably, ML297 inhibits GIRK1/4 channels with a 1:3 stoichiometry but potentiates channels with a 2:2 stoichiometry, establishing a direct link between subunit composition, ligand-binding environment, and pharmacological efficacy. Together, these findings provide a structural and mechanistic framework for the rational design of ligands with enhanced selectivity among cardiac and neuronal GIRK channel heterotetramers.

Predicting molecular receptor status, including estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), directly from routine hematoxylin and eosin (H&E)-stained whole-slide images (WSIs) could reduce reliance on costly immunohistochemistry, but image-only models have no access to the transcriptomic programs that define these subtypes. Here we show that coupling a whole-slide vision transformer (GigaPath) with bulk RNA-sequencing profiles through a training-time-only contrastive objective improves receptor-status classification from WSIs alone, without requiring any RNA-seq data at inference. Rather than training a dedicated bulk-transcriptomics encoder, we purpose the gene-sentence encoding and pretrained text encoder from BioBERT1 and apply them to bulk RNA-seq profiles from The Cancer Genome Atlas breast cancer cohort (TCGA-BRCA). Under five-fold cross-validation, this RNA-guided pre-training consistently improved AUROC for ER, PR, and HER2 relative to a contrastive-pre-training-free baseline and reproducibly introduced receptor-relevant structure into the learned slide representation. However, evaluation on independent external cohorts revealed a striking, receptor-dependent divergence: gains for ER and PR, both governed by broad, multi-gene luminal transcriptional programs, generalized robustly, whereas the apparent AUROC improvement for HER2, driven by focal ERBB2 amplification rather than a coordinated transcriptional signature, masked a severe loss of classification sensitivity at the operating threshold. These findings establish training-time transcriptomic supervision as a practical route to enhancing histology-only molecular subtyping, while showing that gene-selection strategy, and not model architecture alone, determines which molecular alterations such supervision can teach a vision model to recognize.

A central unresolved problem in acute kidney injury (AKI) is how a transient epithelial insult is converted into persistent fibrotic repair that drives progression toward chronic kidney disease. Although tubular, immune and stromal responses are individually well recognized, the mechanistically continuous relay linking these three compartments has remained unresolved. Here we define a directional information-conversion pathway spanning injured tubular epithelial cells, macrophages and fibroblasts. Time-resolved single-cell profiling identified a TREM2/SPP1 macrophage state that emerged as post-ischemic repair became fibrotic. Tubular injury remodeled phosphatidylserine (PS) species, increased oxidized PS and PS externalization, and generated a membrane-lipid context for TREM2 sensing, supported by PS masking, defined liposomes and orthogonal binding assays. Structure-function analysis separated R47-dependent phospholipid recognition from K183-dependent DAP12 coupling, linking membrane damage to SYK activation and NF-kB/AP-1-driven Spp1 transcription. Macrophage-derived SPP1 then activated ITGAV/ITGB1-associated FAK-SMAD2/3 signaling, fibroblast contraction and matrix production. Crucially, repair-phase SPP1 neutralization and post-injury Cx3cr1-lineage Trem2 deletion attenuated fibrosis, with delayed Trem2 deletion protective in both ischemic and obstructive injury. Human single-cell, spatial, urinary and tissue analyses showed cross-species and cross-scale convergence. These findings resolve how transient tubular membrane damage is successively transformed across three cellular compartments into persistent, yet interruptible, fibrotic repair.

Transplantation is limited by how long organs survive outside the body. Existing preservation methods slow metabolism or sustain physiological support, but neither eliminates ischemia-reperfusion injury (IRI), which shortens storage and drives organ discard. Embryonic diapause and hibernation show that mammalian cells retain a latent capacity for reversible metabolic arrest. Screening the PI3K-mTOR axis, we identified a dual inhibitor that pauses embryonic stem cells reversibly at ambient oxygen and holds intact mouse embryos in arrest for 11 days. Combined with a mitochondria-targeted hydrogen sulfide donor, this yields TorPause: a two-component flush pairing metabolic pausing with mitochondrial protection, compatible with existing preservation protocols. In a rat liver transplantation model, TorPause reduced structural injury and improved recipient survival after severe warm ischemic storage, potentially expanding the usable donor pool.

Mammalian cochlear hair cells (HC) are crucial for hearing, and histone modifications may play an important role in HC maturation and functions. However, whether and how NSD2, a histone H3 lysine 36 (H3K36) dimethyltransferase, affects cochlear HC maturation remains unclear. Here, we established an HC-specific Nsd2 knockout mouse model and discovered that the loss of NSD2 results in severe structural defects in stereociliary bundles and profound hearing impairment. Integrated multi-omics profiling revealed that NSD2 deficiency leads to a decreased expression of H3K36me2, which in turn alters genome-wide chromatin accessibility and gene expression. Mechanistically, NSD2 deficiency triggers the aberrant upregulation of extracellular matrix (ECM) genes at the transcriptional level, causing excessive collagen accumulation and compromising tissue structure. Crucially, ECM intervention can mitigate NSD2-deficiency mediated hearing damage. Our study reveals an epigenetic mechanism by which NSD2 regulates cochlear HC maturation through inhibition of chromatin remodeling-induced ECM accumulation, and provides a potential new therapeutic direction for hearing impairment.

Drug targets and vaccines for bacterial diseases are challenging to develop. Computational subtractive genomics and reverse vaccinology offer a viable substitute for conventional drug and vaccine development approaches. In recent years, Pasteurella multocida, a Gram-negative pathogen responsible for severe infections in humans along with major diseases in livestock and poultry, has developed resistance to multiple drugs. As a result, there is an urgent demand for research into reliable, efficient, highly potent, and cost-effective strategies to combat the rise of Pasteurella multocida infections. To address this, the present study integrated an in silico subtractive genomics and reverse vaccinology workflow to pinpoint proteins with potential value as both drug and vaccine targets. From the complete Pasteurella multocida Pm70 proteome, we identified 446 proteins that had no similarities with human proteins, out of which 129 were found to be essential for the pathogens survival. These 129 proteins are therefore potential candidates for drug development. Further metabolic pathway analysis, virulence potential, subcellular localization, and structural analyses revealed two outer membrane proteins, namely, 47 kDa outer membrane protein and lipopolysaccharide-assembly protein LptD, as promising candidates for therapeutic development. Subsequent antigenicity analysis revealed both outer membrane proteins as potential vaccine targets, exhibiting highly favorable antigenicity scores. Candidate B- and T-cell epitopes were systematically mapped from these two targets based on antigenicity, immunogenicity, toxicity, and allergenicity potential and only high-confidence epitopes were assembled using adjuvants and class-specific linkers to construct the final multi-epitope vaccine (MEV). The designed MEV construct was demonstrated to be highly antigenic, non-toxic and non-allergenic to humans, while possessing favorable structural and physicochemical properties, and exhibited strong binding interactions with human toll-like receptors with minimal molecular deformability. Although further experimental validation is recommended to fully assess their efficacy, the present study establishes a solid foundation for the development of novel therapeutics and vaccine candidates against P. multocida, ultimately contributing to the reduction of its rising infections.