Biology subjects

Qi, X.

Publications and source records attributed to Qi, X..

At least 19 recordsLinked to original sources

bioRxiv2026

Keratin 17 Defines an Epithelial-Mesenchymal Transition-Associated Migratory Cell State in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is characterized by early invasion, metastasis, and therapeutic resistance that contribute substantially to its poor clinical outcome. Keratin 17 (K17) is a recognized marker of the aggressive basal-like subtype of PDAC and an independent predictor of adverse prognosis; however, the biological basis for this association remains incompletely understood. To define K17-associated cellular programs, we integrated single-cell RNA sequencing (scRNA-seq) data from 42 patients, Clinical Proteomic Tumor Analysis Consortium (CPTAC) proteomic data from 140 tumors, MACSima multiplex spatial imaging of 63 patients, dual-plex immunohistochemistry of 60 cases, and three-dimensional spheroid migration assays. Single-cell transcriptomic analysis demonstrated significant enrichment of epithelial-mesenchymal transition (EMT)-associated gene programs among K17-positive malignant epithelial cells. Consistent with this finding, K17-positive tumors in the CPTAC cohort exhibited enrichment of the Hallmark EMT pathway at the protein level. Among six candidate markers identified through transcriptomic analyses, laminin subunit gamma-2 (LAMC2) was the only candidate associated with K17 at every validation step. Tumors positive for both K17 and LAMC2 had significantly worse overall survival than double-negative tumors (adjusted hazard ratio = 2.53). Multiplex spatial imaging localized K17-positive cells predominantly to poorly differentiated tumor regions and demonstrated frequent single-cell co-expression with LAMC2. Whole-slide dual-plex immunohistochemistry further confirmed the association between K17 and LAMC2 and showed progressive enrichment of K17/LAMC2-positive tumor cells with increasing intratumoral histologic grade. Functionally, gain- and loss-of-function studies in three-dimensional PDAC spheroids demonstrated that K17 promotes migratory outgrowth, and differences in proliferation did not account for this effect. Collectively, these findings identify K17 as a marker of a poorly differentiated, EMT-associated migratory cell state in PDAC and provide functional evidence that K17 contributes to tumor-cell migration.

cancer biology↗

bioRxiv2026

N-Acetylglucosamine ameliorates knee osteoarthritis by enhancing UDP-GlcNAc conversion and chondrocyte DNA repair capacity

Background: Knee osteoarthritis (KOA) is a degenerative joint disease characterized by progressive cartilage degradation and synovial inflammation, while current therapies offer only symptomatic relief. This study aimed to determine whether N-acetylglucosamine (GlcNAc) is superior to glucosamine hydrochloride (GlcN{middle dot}HCl) in slowing the progression of KOA and to elucidate the underlying mechanisms involved. Methods: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was employed to assess serum concentrations of UDP-GlcNAc to conduct a comprehensive evaluation of the pharmacokinetics and pharmacodynamics associated with both GlcNAc and GlcN{middle dot}HCl. Using a destabilization of the medial meniscus (DMM) rat model, we performed micro-computed tomography and histopathological assessments to evaluate structural changes in the joint tissues. Additionally, we conducted bulk RNA sequencing, flow cytometry and ELISA to validate the efficacy of GlcNAc in anti-inflammatory immunoregulation and DNA repair in knee cartilage. Results: GlcNAc achieved higher peak serum concentrations and more efficient conversion to UDP-GlcNAc than GlcN{middle dot}HCl, with UDP-GlcNAc levels 4.57 times higher at 9 hours after administration. GlcNAc significantly attenuated KOA-like pathological changes, downregulated catabolic markers Mmp3 and Adamts4, decreased pain-related neural markers Pgp9.5 and Ngf, and alleviated pain sensitivity. RNA-seq identified 4,395 downregulated DEGs in DMM rats, of which GlcNAc upregulated 2,808 compared to only 391 by GlcN{middle dot}HCl. GlcNAc promoted DNA repair and adaptive immune cell differentiation pathways, and decreased serum IL-1{beta}, IL-6, and IL-17. Four candidate DNA repair genes, Hist1h2an, Poli, Ube2t, and Hells, were identified as significantly upregulated by GlcNAc, with GSEA confirming homologous recombination repair pathway enrichment. Conclusion: This study shows GlcNAc outperforms GlcN{middle dot}HCl in rat DMM knee osteoarthritis via multiple mechanisms, including 4.57-fold higher UDP-GlcNAc conversion, reduced cartilage degeneration, immune rebalancing, and DNA repair activation, supporting GlcNAc as a promising KOA candidate warranting further clinical study.

pharmacology and toxicology↗

bioRxiv2026

Cause-excluded Effect Evaluation: a framework for the faithful assessment of genetic perturbation target identification

Identifying which gene drives a desired cell-state transition is a foundational inverse problem in target discovery and cell-state engineering, yet far less developed than forward prediction. We show that prevailing benchmarks inflate performance through two artefacts: training leakage, where test-perturbation cells are seen during fitting, and evaluation leakage, where the perturbed gene's own expression change exposes the answer. Here, we introduce Cause-excluded Effect Evaluation (CEE), a framework that separates train and test perturbation targets, removes target-gene self-effects from expression profiles and scores candidates in downstream response space. With CEE, we find that simple structure-based methods consistently outperform complex deep learning models across 16 single-cell perturbation datasets, revealing that the recoverable signal is governed by low-rank and additive structure in perturbation responses rather than by model complexity. Our work disentangles evaluation artefacts from genuine predictive capacity and offers a design principle for developing perturbation target identification methods.

bioinformatics↗

bioRxiv2026

Angiotensin (1-7)-based Proteomimetic Polymers as Topicals for the Remediation and Repair of the Cornea following Injury

The cornea is the outermost layer of the eye, most vulnerable to injury including from chemical exposure, either environmental, industrial or chemical weapons. For example, exposure of the eye to sulfur mustard (SM) can cause mustard gas keratopathy, resulting in devastating consequences for vision. Available treatments for corneal mustard keratopathy are either ineffective, or if used for a prolonged time, have deleterious side effects. Here, we aimed to harness the anti-inflammatory and anti-angiogenic peptide angiotensin-(1-7), known as Ang-(1-7), that is derived from the renin-angiotensin system (RAS). We designed and developed a protein-like polymer (PLP) displaying a brush of norleucine modified Ang (1-7) peptides (NLE Ang (1-7) PLP), which is a more potent derivative of Ang-(1-7), for administration as an eye drop. In a mouse model of nitrogen mustard (NM)-induced corneal injury, topical treatment and intraperitoneal (i.p.) injection of NLE Ang (1-7) PLP persistently minimized: (i) corneal haze; (ii) edema; (iii), expression of pro-inflammatory and pro-angiogenic genes; and (iv) neovascularization and conjunctivalization as evidenced after a prolonged treatment and recovery period. Collectively, our observations have demonstrated the efficacy of this novel polymer proteomimetic based eye drop treatment in reducing chemical agent-induced corneal injury as well as indicating its potential application in other ocular surface diseases associated with inflammation and angiogenesis.

bioengineering↗

bioRxiv2026

A closed-loop language-model agent for target-specific multi-objective hit-to-lead optimization

Hit-to-lead optimization is a multi-objective molecular-design problem in which binding-related scores must be considered together with drug-likeness and synthetic accessibility. We developed a closed-loop language-model medicinal-chemistry agent that combines target and starting-hit context, PubMed retrieval, molecular-property tools, docking, and feedback from previously scored analogues. In a matched computational benchmark comprising six kinase targets, six methods, a 40-candidate budget, and six independent campaigns per method, the agent achieved the highest mean aggregate score under a pre-specified composite objective on four targets. Re-analysis of the same candidate sets with drug-likeness-gated docking and docking-drug-likeness hypervolume produced different target-level winners, showing that evaluation rules can change the comparative interpretation of an optimization campaign. Candidate distributions and component ablations indicated that the agent's advantage was associated primarily with retention of scored-candidate feedback and higher-QED regions rather than with docking alone. An EGFR case study illustrates a scaffold-preserving in-silico optimization trajectory from erlotinib. The study is a computational benchmark and evaluation framework; the prioritized molecules are hypotheses for subsequent experimental testing, not experimentally validated leads.

bioinformatics↗

bioRxiv2026

CellOS: Learning a World Model of Cellular State through Joint Embedding Prediction

Foundation models learned from single-cell transcriptomes are central to the prospect of AI virtual cell that can represent, query and predict cellular state. However, most current single-cell foundation models learn from a single view of gene expression and are optimized primarily through reconstruction or next-token prediction. As a result, they capture expression abundance but cannot explicitly reconcile complementary views of cellular state. Here we present CellOS, a multi-view foundation model that learns cellular representations from paired expression and perception views. CellOS integrates complementary views through a scalable three-stage training strategy that combines causal cell-sentence language modelling, function-preserving dense-to-mixture-of-experts expansion and latent-space alignment via an LLM-JEPA objective. Using this framework, we trained a 12-billion-parameter model on 390.5 million single-cell transcriptomes. Across diverse benchmarks spanning cell-state annotation, batch integration and perturbation-response prediction, CellOS consistently outperformed state-of-the-art single-cell foundation models. Together, these results suggest that predictive alignment between complementary cellular views provides a scalable path toward representation-centric cellular world models and transferable AI virtual cells.

bioinformatics↗

bioRxiv2026

Perturbation Curve models continuous transcriptional response trajectories and improves prediction of genetic modulations

Single-cell CRISPR screens, Perturb-seq, have revolutionized functional genomics by revealing biological causality. However, although perturbation assignments are typically represented as discrete labels, the cell-level effective strength of perturbations is often continuous and diverse. Current analytical frameworks struggle to decouple the variability in perturbation strength from the diversity of downstream responses. Here, we present Perturbation Curve (PertCurve), a nonlinear, curve-based computational framework that models the trajectories of transcriptomic responses by explicitly incorporating diverse perturbation magnitudes and strengths. By ordering cells by perturbation strength, we demonstrate that PertCurve accurately recapitulates the response magnitudes and reveals the distinct modularity and asynchrony patterns of downstream gene behaviors. These patterns are categorized into archetypes, including proportional, sensitive, and threshold responses. By applying this framework across CRISPRi/a modalities, we identify universal response patterns in viral infection, apoptosis, and proliferation genes, and reveal previously overlooked context-specific regulatory features in cell differentiation. Finally, incorporating PertCurve into perturbation prediction models and evaluation metrics enhances predictive performance, delivering actionable insights for refining established models.

bioinformatics↗

bioRxiv2026

Astrocytic D1 Dopamine-Signaling Regulates Synaptic Remodeling and Cocaine Seeking

D1-type receptor (D1R)-mediated dopaminergic signaling within the nucleus accumbens shell (NAcSh) is essential for forming adaptive circuit changes that embed persistent memories associated with drug seeking and craving. While D1R is expressed in both NAcSh neurons and astrocytes, the specific contribution of astrocytic D1R to drug-related circuit plasticity remains poorly understood. Here, we demonstrate in mouse NAcSh slices that D1R agonists increase astrocytic Ca2+ activity, an effect that is attenuated by astrocyte-specific D1R knockdown. Furthermore, selective knockdown of astrocytic D1R in the NAcSh prior to cocaine self-administration inhibits cocaine-induced generation of silent synapses, therefore hampering the associated remodeling of NAcSh circuits. Behaviorally, knockdown of NAcSh astrocytic D1R expedites the extinction of cocaine seeking and reduces cue-induced reinstatement. These results identify astrocytic D1R as a fundamental component of NAcSh dopamine signaling during cocaine experience that remodels synaptic connections and neural networks underlying drug seeking and relapse.

neuroscience↗

bioRxiv2026

HTRA1 deficiency in COL4A1 mutant hiPSC-derived astrocytes, a convergent mechanism of cerebral small vessel disease

Cerebral small vessel disease (cSVD) is a major contributor to stroke and cognitive decline, ultimately leading to vascular dementia (VaD). Genetic factors play a key role in disease susceptibility and progression, and variants in COL4A1 cause one of the most common forms of genetic cSVD. COL4A1 encodes the 1 chain of collagen type IV which is the major structural component of the basement membrane, a specialised extracellular matrix (ECM) structure, in the vasculature. In addition to this vascular basement membrane (vBM), in the central nervous system (CNS), the neurovascular unit (NVU) also has a unique parenchymal basement membrane (pBM) that is largely produced by astrocytes and forms a critical interface anchoring astrocyte end-feet to vascular cells. Together, these BMs play essential roles in regulating blood-brain barrier (BBB) function. However, the role of the pBM in cSVD has been relatively less investigated compared to the vBM. The lack of relevant human disease models that faithfully recapitulate the pBM, makes it difficult to dissect pBM-related cell-cell and cell-matrix interactions specific to cSVD, hindering the identification of effective therapeutic targets. In this study, we hypothesised that astrocyte-mediated ECM remodelling contributes to BBB dysfunction in COL4A1-associated cSVD. To investigate this, human induced pluripotent stem cells (iPSCs) derived from a patient carrying the COL4A1G755Rvariant and its isogenic control line were differentiated into astrocytes and brain microvascular endothelial cells (BMECs). Comparing to isogenic controls, the COL4A1G755Rastrocytes significantly reduced the expression of ECM-related genes and increased glutamate uptake. ECM preparations from COL4A1G755R astrocytes significantly damaged the tight junction (TJ) structure formed by control iPSC-BMECs and failed to rescue the TJ integrity in COL4A1G755R BMECs. The secretome from COL4A1G755Rastrocytes exacerbated the ECM defects in COL4A1G755R BMECs. Most importantly, COL4A1G755R astrocytes exhibited reduced expression of HTRA1, a serine protease that regulates both ECM turnover and homeostasis, and increased TGF-{beta} signalling. Functional rescue by recombinant human HTRA1 protein rescues TJ defects in COL4A1G755R BMECs, and normalized TGF-{beta} signalling and glutamate uptake in COL4A1G755R astrocytes. Together, these findings define a previously unrecognised astrocyte-driven pBM mechanism in COL4A1-associated cSVD and highlight HTRA1 in ECM remodelling as a therapeutic target for cSVD.

neuroscience↗

bioRxiv2026

Automated Multimodal Correlative Registration for Organelle-Specific Molecular Imaging

Mapping subcellular drug distribution is essential for understanding trafficking and off-target effects. NanoSIMS enables chemical imaging of labeled therapeutics, but signal interpretation requires ultrastructural correlation with electron microscopy, a manual and laborious process. We present an automated AI-driven pipeline for correlating chemical and ultrastructural images, enabling multiscale, organelle-precise imaging of molecules in cells and tissues. The method integrates bidirectional optical flow, confidence-guided affine transformation, and automated template matching for cross-scale EM alignment. Morphology-rich ion channels (e.g., 32S) estimate transformations that propagate to sparse therapeutic signals (e.g., 79Br, 15N), overcoming low signal-to-noise challenges. We validate this framework across diverse cell and tissue types, tracking oligonucleotide and antibody therapeutics in vitro and in vivo to reveal cell-type- and organelle-specific distribution patterns. This work establishes a generalizable platform for automated multimodal registration and organelle-resolved subcellular pharmacology.

bioinformatics↗

bioRxiv2026

A sequence-based proactive intelligence for influenza antigenic profiling improves vaccine strain selection

Seasonal influenza viruses accumulate antigenic changes, eroding population immunity and necessitating recurrent vaccine updates. Hemagglutination inhibition (HI) assays are the standard for measuring antigenic relationships between circulating and vaccine strains; however, their limited throughput constrains the scale and timeliness of surveillance. Here, we present fluProfiler, a foundation-model-based framework that learns a stable mapping from viral sequences to antigenic space and uses this representation to support influenza antigenic prediction, vaccine strain evaluation, and diversity-driven sampling. fluAgPredictor aligns hemagglutinin (HA) and neuraminidase (NA) sequence representations with HI-derived antigenicity, enabling accurate and consistent inference of pairwise antigenic distances across surveillance-aligned evaluation settings. Without prior annotation of antigenic sites, it identifies key residues in immunodominant epitopes and reveals the cooperative contributions of HA and NA to antigenic variation. Building on this antigenic-space representation, fluVacSelector provides antigenic coverage scores that are concordant with World Health Organization (WHO) vaccine recommendations while also flagging potential candidates that may offer broader coverage ahead of formal consultations. fluAgEnhancer further leverages the same representation to prioritize antigenically informative and diverse strains for experimental characterization, achieving comparable predictive accuracy with approximately 25% fewer HI measurements than random sampling. Together, these modules provide a high-throughput and interpretable complement to HI testing, converting routine genomic surveillance into a more proactive, data-driven support system for antigenic monitoring and vaccine strain selection.

bioinformatics↗

bioRxiv2026

Proteomic profiling reveals pleiotropic antimetabolite activity of triciribine in acute lymphoblastic leukemia

Acute lymphoblastic leukemia (ALL) exhibits marked genetic and metabolic heterogeneity that limits the efficacy of targeted therapies. Antimetabolite strategies remain central to ALL treatment, yet the mechanisms underlying differential drug sensitivity are incompletely defined. Here, we investigated the activity of the purine analog triciribine (TCN) across diverse ALL cellular models. We find that TCN exerts potent cytotoxic effects in multiple ALL cell lines, exceeding those observed with canonical Akt inhibitors in our datasets. Phosphoproteomic analyses indicate that, at early time points, TCN does not primarily suppress Akt signaling but instead induces transient pathway activation accompanied by inhibition of cyclin-dependent kinases in both sensitive and resistant cells. The monophosphorylated metabolite TCN-P represents the predominant intracellular species and requires adenosine kinase (ADK) for activity, with ADK protein levels positively correlating with TCN sensitivity in both cell lines and primary patient samples. Using Proteome Integral Solubility Alteration profiling, we identify candidate protein interactions of TCN-P distributed across multiple cellular pathways, including nucleotide metabolism, DNA replication, and protein synthesis. These interactions are accompanied by impaired purine biosynthesis, DNA damage, translational stress, and cell-cycle arrest, as supported by time-course quantitative proteomics and immunoblot analyses. Together, these findings characterize triciribine as an antileukemic agent with pleiotropic antimetabolite activity in ALL and highlight ADK-dependent metabolism as a key determinant of therapeutic sensitivity, suggesting that ADK levels may serve as a predictive biomarker to stratify patients for triciribine-based precision treatment strategies.

cancer biology↗

bioRxiv2026

Refinement of Nucleus Accumbens Neuronal Dynamics During Cocaine Self-Administration Training

Drug addiction is an acquired motivational-behavioral state that begins with drug taking, which is comprised of a series of phases, including initial acquisition, stabilization, habituation, and maintenance. In rodent models of cocaine self-administration, the forebrain region nucleus accumbens (NAc) has been critically implicated in the acquisition-maintenance process of drug taking and seeking behaviors. However, it remains unknown how NAc neurons shift their activity patterns in response to these phasic transitions during cocaine taking. To examine this, we used GCaMP6m-based in vivo Ca2+ imaging to monitor activities of principal medium spiny neurons (MSNs) in the NAc across eleven days of cocaine self-administration. Behaviorally, mice exhibited progressive stabilization of operant responding and locomotion across 11 days of cocaine self-administration. During the early training days, we detected a portion of NAc neurons--a potential neuronal ensemble--that exhibited increased activities temporally contingent to the lever-press for cocaine. The number of NAc neurons exhibiting contingent activity increased progressively over the first three training days and then decreased gradually during the later training days, exhibiting expansion-refinement dynamics that may correspond to the acquisition and subsequent stabilization/maintenance of cocaine self-administration. Using a neuron-tracking technique, we found that the lever-press-contingent NAc ensemble exhibited substantial compositional dynamics, with neurons dropping into and out across training days. These activity features of lever-press-contingent neurons may represent key circuit dynamics of the NAc that transition the acquisition toward the maintenance of cocaine-taking behavior.

neuroscience↗

bioRxiv2026

Z-RNA-ZBP1 axis drives Tau-mediated neurodegeneration

Although the causes of Tau aggregates vary, once Tau aggregates are formed, their neurotoxicity significantly contributes to neuronal death and cognitive decline in tauopathies, with Alzheimers disease (AD) being the most well-known example. Despite its central pathogenic role, however, effective therapeutic strategies targeting neurotoxicity of Tau remain poor. Here we demonstrate the pathogenic role of neuronal cell death in Tau-related neurodegeneration. Tau-expressing neurons undergo cell death through Z-DNA-binding protein 1 (ZBP1) activation triggered by endogenous Z-RNAs. These Z-RNAs are derived from reactivated transposable elements (TEs) that are typically silenced within heterochromatin. Tau aggregates show a strong affinity for H3K9me3-modified chromatin, effectively sequestering these epigenetic marks from Heterochromatin Protein 1 (HP1), thereby disrupting the condensation of constitutive heterochromatin. Clinically, an inverse correlation between ZBP1 expression levels in excitatory neurons and cognitive performance in AD patients was observed. Importantly, Zbp1 haploinsufficiency significantly ameliorated cognitive deficits in aged Tau-transgenic mice (24-month-old), highlighting the therapeutic potential of ZBP1 inhibition to strive against neurodegeneration in tauopathies.

neuroscience↗

bioRxiv2026

Sub-stoichiometric Degradation is Dispensable for Potent PROTACs: A Case Study for Irreversible Covalent BTK Degraders

Proteolysis-targeting chimeras (PROTACs) represent a transformative therapeutic modality, yet the viability of covalent PROTACs remains debated, as irreversible binding seemingly contradicts the catalytic mechanism central to their function. Here, we develop and characterize PSIRC3, a highly potent covalent PROTAC for Brutons tyrosine kinase (BTK) that addresses this ambiguity. PSIRC3 induces potent and selective BTK degradation with a sub-nanomolar DC50 of 0.75 nM and a Dmax greater than 85%, while its non-covalent counterpart is completely inactive. This degradation activity is strictly dependent on covalent bond formation with the Cys481 residue, as evidenced by a total loss of efficacy against the C481S BTK mutant. PSIRC3 acts with remarkable speed, achieving maximum BTK degradation within 30 minutes, a kinetic profile linked to rapid cell permeation and efficient ternary complex formation. In vivo, a single administration of PSIRC3 leads to substantial BTK degradation in both PBMCs (>80%) and splenocytes (>50%). Computational modeling, parameterized with experimental data, reveals that degradation efficacy is governed by a delicate balance between E3 ligase and target protein affinities. Specifically, excessively high E3 affinity is detrimental by inducing a hook effect, while higher target affinity is generally beneficial. Our findings provide strong evidence that covalent engagement can drive potent and selective protein degradation, challenging the prevailing notion that catalytic turnover is indispensable for PROTAC efficacy. This work establishes a new benchmark for covalent degraders and opens new avenues for targeting previously intractable proteins.

biochemistry↗

bioRxiv2026

ATLAS: Population-Level Disease Locus Discovery via Differential Attention in Genomic Language Models

Identifying disease-associated genetic variants remains a key challenge in genomics, especially in small cohorts or for rare and complex mutation types where genome-wide association studies (GWAS) often fall short. We introduce ATLAS, a population-level framework that leverages attention signals from pretrained genomic language models (gLMs) to detect disease-associated genes and loci directly from raw sequences--without requiring explicit variant calls or supervised training. ATLAS first performs gene-level differential attention analysis to prioritize candidate genes, followed by base-level analysis to localize disease-associated regions at single-haplotype resolution. We validate ATLAS on synthetic and {beta}-thalassemia datasets, demonstrating robust performance across diverse allele frequencies (down to 10%), cohort sizes (below 200 individuals per group), and genomic scales. Compared to GWAS, ATLAS achieves higher recall of known loci and captures haplotype-specific signals missed by traditional methods. Cross-model benchmarking further shows that precise localization depends on both model size and pretraining on diverse human genomes. In summary, ATLAS offers a scalable, sequence-native alternative to traditional statistical genetics.

genetics↗

bioRxiv2026

Functional characterization and molecular engineering of a O-methyltransferase involved in bis-benzylisoquinoline alkaloids biosynthesis from Nelumbo nucifera

Nelumbo nucifera (lotus), a traditional aquatic plant in Asia, is valued for its nutritional and therapeutic properties. Benzylisoquinoline alkaloids (BIAs) are its major bioactive components, with significant bioactivities and pharmacological values. O-methyltransferases (OMTs) play a crucial role in shaping the structural and functional diversity of BIAs. Herein, we characterized a specific OMT, designated Nn7OMT, which exhibits a novel catalytic function: methylating the C7 position of the bisbenzylisoquinoline (bisBIA) skeleton. Nn7OMT also displayed substrate promiscuity, catalyzing O-methylation at the C7 position of bisBIAs, C6/C7 positions of 1-benzylisoquinolines, C7 position of aporphines, and C9 position of protoberberines, with isoliensinine as its preferred substrate. The expression profile of Nn7OMT correlates with bisBIA accumulation in planta, supporting its involvement in bisBIA biosynthesis in N. nucifera. Protein engineering guided by molecular docking and molecular dynamics simulations identified key residues critical for Nn7OMT activity. Mutants M158A and V306A retained catalytic activity toward isoliensinine while showing nearly undetectable activity against 1-benzylisoquinoline alkaloids, thereby significantly improving Nn7OMTs substrate specificity. These findings advance our understanding of BIAs biosynthesis in lotus and provide valuable biocatalysts with enhanced specificity. SIGNIFICANCEIn this study, we report the innovative discovery and characterization of Nn7OMT, the first O-methyltransferase isolated from Nelumbo nucifera that harbors a novel catalytic activity toward the bisbenzylisoquinoline alkaloid (bisBIA) backbone. Nn7OMT displayed substrate promiscuity, catalyzing methylation at the C7 position of the bisbenzylisoquinoline skeleton (isoliensinine), C6/C7 positions of the 1-benzylisoquinoline skeleton (norcoclaurine, coclaurine, N-methylcoclaurine), C7 position of the aporphine skeleton (lirinidine), and C9 position of the protoberberine skeleton (scoulerine)--with isoliensinine as its most preferred substrate. Innovatively, the catalysis of isoliensinine by Nn7OMT was a novel function and the first O-methyltransferase identified to catalyze the bisbenzylisoquinoline backbone, which may be involved in the biosynthesis of neferine. Nn7OMTs expression profile correlated with bisBIA accumulation in planta, further supporting its role in bisBIA biosynthesis in N. nucifera. We further engineered Nn7OMT using molecular docking and MD simulation-guided strategies. Mutants M158A and V306A retained catalytic activity for isoliensinine while showing nearly undetectable activity against 1-benzylisoquinoline alkaloid substrates. This targeted engineering significantly improved the specificity of Nn7OMT, rendering it highly suitable for methylated isoliensinine biosynthesis by reducing by-product accumulation and simplifying purification processes. Our work deepens understanding of the unique BIA metabolic pathway in N. nucifera through the identification of the first bisBIA-catalyzing O-methyltransferase, and provides valuable biocatalysts with enhanced substrate specificity.

molecular biology↗

bioRxiv2026

The novel variant IBDV induces inflammatory responses via VP3-mediated pyroptosis by directly targeting Caspase-9

The novel variant infectious bursal disease virus (nVarIBDV), which has been widely prevalent since 2017, threatens the poultry industry by inducing severe bursal atrophy and intense inflammatory responses. Understanding the inflammatory mechanism underlying nVarIBDV infection is critical for preventing virus-induced damage. Pyroptosis, an inflammatory type of programmed cell death, may contribute to the inflammation and bursa of Fabricius damage induced by nVarIBDV. Here, we found that the nVarIBDV infection induced severe inflammatory responses both in vivo and in vitro, which were associated with pyroptosis. Further research revealed that the viral protein VP3 drove pyroptosis induced by nVarIBDV infection by indirectly activating the Caspase-3-GSDME pathway, leading to GSDME cleavage. Mechanistically, VP3 directly interacted with and activated Caspase-9, thereby initiating Caspase-9-Caspase-3-GSDME pathway. More importantly, the Serine 33 of VP3 was identified as the key amino acid for interacting with and activating Caspase-9. Mutation of this residue significantly weakened the ability of VP3 to interact with Caspase-9 and activate the Caspase-9-mediated pyroptosis pathway, altered the binding mode of the Caspase-9-VP3 protein complex, and ultimately reduced the ability of VP3 to induce pyroptosis. In conclusion, our results elucidated a novel mechanism by which nVarIBDV infection induced inflammatory responses whereby viral protein VP3 triggered pyroptosis by targeting the Caspase-9-Caspase-3-GSDME pathway. IMPORTANCEnVarIBDV is globally prevalent and poses a significant threat to the poultry industry by causing inflammation and damage to the bursa of Fabricius. This study revealed that nVarIBDV infection induced inflammatory responses and bursa of Fabricius damage, primarily mediated by the viral protein VP3 targeting Caspase-9 to induce pyroptosis. To our knowledge, this is the first report on the interaction between inflammatory responses induced by IBDV infection and pyroptosis. In addition, serine 33 was identified as the critical amino acid required for maintaining the stability of the interaction between VP3 and Caspase-9 and activation of the Caspase-9-Caspase-3-GSDME cascade pyroptosis pathway and further inflammatory responses. Collectively, our findings not only elucidate a novel mechanism by which nVarIBDV induces pyroptosis and further leads to inflammation but also suggest that the identification of this serine site may represent a potential therapeutic target to block nVarIBDV-induced inflammation and bursa of Fabricius damage.

microbiology↗