Biology subjects

Wan, J.

Publications and source records attributed to Wan, J..

At least 19 recordsLinked to original sources

bioRxiv2026

The constitutive androstane receptor protects against metabolic dysfunction-associated steatotic liver disease through sex specific interactions with the gut microbiota

Background: The gut-liver axis is involved in Metabolic dysfunction-Associated Steatotic Liver Disease (MASLD), but the host molecular actors involved in such dialogue have not yet been fully characterized. Objective: We investigated the sex-dependent role of the Constitutive Androstane Receptor (CAR) as a hepatic sensor of microbial signals in MASLD pathophysiology. Design: Male and female Car+/+ and Car-/- mice were fed a western diet (WD) for 4, 14 or 35 weeks. We performed plasma biochemistry, liver histology, bile acid and cholesterol quantification, untargeted multi-omics approach combining liver RNA-sequencing and 16S rRNA sequencing, together with co-housing, fecal microbiota transplantation and analysis of publicly available transcriptomics data in human cohorts. Results: Short-term WD revealed CAR-dependent protection against steatosis, together with perturbations in the transcriptional signatures of multiple transcription factors involved in hepatocyte identity in males. After 14 weeks, CAR deletion increased WD-induced liver damage, inflammation and fibrosis, and disrupted bile acid, cholesterol and gut microbiota homeostasis, in males only. Co-housing and fecal microbiota transplantations revealed that a Car+/+ gut microbiota protected against WD-induced liver damage, while a Car-/- microbiota was reshaped by a Car+/+ host. No CAR-dependent phenotype was observed in females. Finally, in human cohorts, hepatic CAR expression decreased in advanced clinical stages of MASLD. Conclusion: CAR is a sex-dependent protective nuclear receptor against MASLD progression, acting both as a transcriptional regulator of hepatocyte identity and as a mediator of the host-microbiota crosstalk.

physiology↗

bioRxiv2026

Temporal control of mitochondrial mutagenesis reveals the fate of mtDNA mutations with age

Mutations in the mitochondrial genome (mtDNA) play a critical role in the aging process and a wide variety of age-related diseases. However, it remains unclear when the mutations that drive physiological decline arise. To answer this question, we generated a new mouse model in which mitochondrial mutagenesis can be confined to a defined window of time. Surprisingly, we found that mutations that arise during the first two months of life are sufficient to drive a wide variety of age-related pathologies, and that the severity of this pathology is broadly regulated by distinct, tissue-specific selective pressures that control the fate of mtDNA mutations with age. Further, we found that selection against deleterious variants can be modulated by manipulation of mitochondrial fusion in vitro and in vivo. These observations raise the possibility that in some tissues, the pace of aging is pre-determined by events that occur early in life and that interventions targeting mitochondrial fusion may be able to slow down or reverse the expansion of these pathogenic variants. These results carry far-reaching implications for strategies aimed at preventing or delaying age-related decline.

genetics↗

bioRxiv2026

MetExPred: A Comprehensive Prediction Framework with Protein-Context-Aware Multi-view Learning for Drug Metabolism and Excretion

Within the ADMET continuum, metabolism and excretion (ME) form a critical bridge between drug exposure established by absorption and distribution and downstream efficacy and toxicity. However, no existing framework for drug ME prediction has simultaneously achieved broad coverage of endpoints and robust data recency and completeness. Here, we developed MetExPred, a multi-view prediction framework that comprises 17 classification endpoints and two regression endpoints, covering the overall drug ME process. The framework combines sequence-based and graph-based molecular representations, while optionally incorporating ESM-2 protein representations when experimentally annotated targets are available. A protein-aware masking strategy enables the same architecture to operate in both molecular-only and target-enhanced settings, and multi-view attention adaptively integrates the available representations. Across the classification tasks, MetExPred achieved mean AUROC, AUPRC and F1 scores of 0.844, 0.734 and 0.697, respectively. For clearance and half-life prediction, the model achieved RMSE values of 0.686 and 0.668. MetExPred showed the strongest average performance among the evaluated baselines, while ablation studies confirmed the complementary contributions of molecular sequence, graph and protein information. These results provide a unified and flexible modeling framework for systematic ME prediction of drug compounds, enabling early-stage virtual screening and pharmacokinetic assessment during lead optimization.

bioinformatics↗

bioRxiv2026

Inflammatory burning pain depends on a specific line of nociceptors

The development and persistence of burning pain and heat hyperalgesia following tissue injury and the subsequent inflammatory response, depend on the nuclear enzyme mitogen- and stress-activated kinase 1 (MSK1) expressed in a specific subset of transient receptor potential subfamily V member 1 (TRPV1)-expressing primary sensory neurons termed nociceptors, which are specialised for detecting harmful stimuli. Inflammation up-regulates and activates MSK1, and MSK1 governs TRPV1 expression in the MSK1 and TRPV1 co-expressing mouse and human nociceptors. Importantly, inhibition of inflammatory MSK1-mediated TRPV1 upregulation protects from heat hypersensitivity without affecting other relevant TRPV1 functions, such as the sensation of acute painful heat stimuli or the maintenance of the body core temperature. The newly discovered importance of the interaction between MSK1 and TRPV1 in a specific line of nociceptors provides mechanistic understanding of inflammatory pain and heat hyperalgesia pathogenesis.

neuroscience↗

bioRxiv2026

GWAS and multi-omics uncover the SLC6A3 locus for canine stranger-directed social anxiety and implicate NRIP3 in dopaminergic network regulation

The social anxiety disorder (SAD) is one of the most common mental health disorders, often developing in adolescence. It can severely impair educational achievement, career progression, and social functioning. Certain individuals within the Chinese Kunming dog (CKD) population display spontaneous, SAD-like behaviors towards strangers, offering a valuable model for genetic investigation. Using whole-genome sequencing data, we conducted a genome-wide association study on this SAD-like behavior in 100 CKDs, identifying several genes previously linked to human psychiatric disorders. Notably, SLC6A3 reached genome-wide significance, whereas CADPS2 exceeded only the suggestive threshold and is therefore considered a network-supported candidate locus. By integrating weighted gene co-expression network analysis with public RNA-seq data from the VTA of 38 mice (after quality control), we further showed that Slc6a3 and Cadps2 are part of a co-expression network module associated with the dopamine system. These findings suggest that this specific module may play a functional role in the stranger-directed anxiety-related behaviours in CKDs. Furthermore, we identified Nrip3 as a key candidate transcriptional coregulator in this specific module. Subsequent virus-mediated overexpression and behavioural experiments showed that Nrip3 regulates gene expression within this network and induces a spectrum of behavioural alterations in mice, including social avoidance, anhedonia, and increased locomotor activity. Collectively, this study highlights the involvement of dopamine system genes in canine social anxiety and suggests Nrip3 as an upstream regulator of Slc6a3 associated with anxiety. The identification of conserved anxiety-related signatures between humans and dogs further supports the dog as a valuable translational model for psychiatric research.

genetics↗

bioRxiv2026

NuGraph: Graph-Based Reasoning over 3D Primitives for Nucleus Segmentation Correction

Correcting segmentation errors in large-scale 3D nuclei reconstructions requires reasoning about which fragments belong to the same nucleus across densely packed regions. Existing correction methods rely on local pairwise fragment matching, which cannot resolve the global topology of nuclear clusters and fails to recover missing morphology. We propose NO_SCPLOWUC_SCPLOWGO_SCPLOWRAPHC_SCPLOW, a graph-based reasoning framework that operates over atomic 3D primitives obtained by decomposing erroneous masks. NO_SCPLOWUC_SCPLOWGO_SCPLOWRAPHC_SCPLOW encodes primitive geometry via a 3D point-cloud backbone and performs global relational reasoning through graph attention, capturing inter-primitive dependencies across entire clusters rather than isolated pairs. A primitive-proposal contrastive loss aligns local primitive features with nucleuslevel semantics, improving grouping accuracy in dense regions. The resulting proposals are then refined by a shaperefinement network that predicts signed distance fields to restore smooth morphology. To train without manual error annotations, we develop a self-supervised data engine that synthesizes realistic segmentation errors from clean nuclei labels. To benchmark correction at brain scale, we curate NucEMFix, the first brain-wide EM benchmark of nuclei error cases across FAFB and MICrONS (8,000+ annotated error nuclei). NO_SCPLOWUC_SCPLOWGO_SCPLOWRAPHC_SCPLOW attains 87.99% F1 on NucEMFix-F (FAFB) and 86.20% on NucEMFix-M (MICrONS), outperforming both re-segmentation baselines (e.g., +8.6% over nnU-Net) and pairwise correction methods, while reducing curation effort by over 100x relative to manual proofreading. Code and data are available at https://mingzhiwang618.github.io/NucEMFix.

neuroscience↗

bioRxiv2026

PARP1 catalytic domain mutations drive high-level resistance to saruparib while preserving DNA damage response vulnerabilities

Clinical poly (ADP)-ribose polymerase (PARP) inhibitors (PARPi) are limited by toxicities associated with inhibition of multiple PARP family proteins and acquired resistance. As PARP1-specific inhibitors, like saruparib (AZD5305), move toward standard-of-care status for BRCA and HR-deficient cancers replacing less specific PARPi, defining mechanisms of intrinsic and acquired resistance is essential for developing effective treatment strategies. Here, we established 5 saruparib-resistant (SR) cell lines from BRCA1-deficient MDA-MB-436 triple negative breast cancer (TNBC) cells using a selection strategy of high-level dosing consistent with clinical exposure, yielding models that are >1,000-fold resistant to saruparib. Whole genome sequencing identified PARP1 catalytic domain mutations in all SR cell lines, and in vitro reconstitution of these PARP1 mutants confirmed them as drivers of saruparib resistance, in contrast to HR restoration as observed in the case of less-selective PARPi. PARP1 mutations also induce altered saruparib-dependent PARP1 trapping and PARylation inhibition. While these mutations render cells highly resistant to saruparib, differential sensitivity to other PARPi was observed and SR cell lines retain, and in some cases, increase, sensitivity to alternative clinical PARPi and DNA damage response (DDR)-targeted therapeutics. Our findings demonstrate that high-intensity selection pressure favors target-site mutation over pathway restoration as a primary escape mechanism from PARP1-selective inhibition. This study provides a first-in-class characterization of saruparib resistance and maps a clear therapeutic path forward. By identifying these specific PARP1 mutations and their collateral DDR vulnerabilities, we provide the molecular framework necessary to monitor and treat patients who progress on next-generation PARP1-selective inhibitors.

cancer biology↗

bioRxiv2026

MilliMap: interactive closed-loop analysis for spatial omics

Spatial omics analysis requires iterative interplay between statistical computation and tissue-context interpretation, yet current workflows fragment these steps across disconnected environments. We present MilliMap, an interactive framework that unifies statistical analysis with spatial exploration. By closing the analysis-visualization loop, MilliMap empowers biologists to steer parameters, refine ROIs, and validate findings within a single environment. We demonstrate its utility by delineating complex neuroanatomy and identifying niche-restricted functional states in tumor microenvironments.

bioinformatics↗

bioRxiv2026

The chitin receptor-interacting protein LIK1 regulates extracellular ATP signaling via interaction with P2K1 in Arabidopsis thaliana

Previously, the chitin receptor-interacting protein kinase LIK1 (LysM receptor kinase 1/CERK1-interacting kinase) was shown to play an important role in regulating chitin signaling and plant defense. A limited proteolysis proteomics study revealed several LIK1-derived peptides that showed differential abundance between ATP-treated and mock-treated Arabidopsis samples, suggesting a possible involvement of LIK1 in extracellular ATP (eATP) signaling. To explore this possibility, LIK1 mutants were obtained and examined for their response to ATP. The results showed that mutations in LIK1 significantly reduced the expression of eATP-responsive genes. In addition, LIK1 was found to interact with the eATP receptor P2K1 and to be phosphorylated by it. The LIK1 protein was localized to the plasma membrane and its gene expression appeared to be ubiquitous. Collectively, these findings indicate that LIK1 not only contributes to chitin signaling but also participates in eATP signaling, highlighting its potential role as a shared component in multiple signaling pathways to regulate plant responses to diverse internal and external cues.

plant biology↗

bioRxiv2026

Systematic errors in enzymatic conversion limit cell-free DNA methylation specificity

Enzymatic methylation sequencing (EM-seq) converts unmethylated cytosines to uracils while preserving DNA integrity, making it attractive for liquid biopsies. Here we report a reproducible fragment-level over-conversion error in EM-seq, which is not observed in bisulfite-based conversion or in Oxford Nanopore sequencing. While bisulfite and nanopore errors occur at sporadic CpGs, EM-seq generates molecules that appear fully unmethylated, introducing a false-positive background signal that severely limits deconvolution specificity in cfDNA analysis.

genomics↗

bioRxiv2026

A Genetic Tool for Specific Tracking of Mature Neutrophils

Tracking mature neutrophils remains challenging due to the lack of reliable cell surface markers. Although CD101 is a promising candidate for mature neutrophils, its stability under pathological conditions is unclear. Using a CD101-tdTomato reporter mouse model, we confirmed that the reporting system does not alter CD101 expression, and tdTomato fluorescence is predominantly expressed in mature neutrophils across peripheral tissues. Further analysis revealed that CD101+ and tdTomato+ neutrophils display identical characteristics of mature neutrophil, including poly-segmented nuclei, cell size, and key functions under homeostasis. By comparing tdTomato fluorescence with CD101 protein levels, we demonstrate that reduced CD101 expression under pathological states was not attributed to shedding or degradation. Our finding enhances CD101 as a robust and reliable marker of neutrophil maturity, providing a foundation for future applications in spatial transcriptomics and lineage tracing studies to dissect neutrophil heterogeneity and function. Highlights of the studyO_LIIn CD101-tdTomato homozygous mice, tdTomato is predominantly expressed in neutrophils and labels nearly 100% of mature neutrophils, aligning with the phenotype of CD101+ mature neutrophils; C_LIO_LIThe CD101-tdTomato reporting system does not interrupt CD101 expression or neutrophil functions; C_LIO_LICD101 remains a stable and reliable cell surface marker for labeling mature neutrophils, even under pathological conditions. C_LI

immunology↗

bioRxiv2026

Single-Cell Raman Profiling Enables Rapid Precision Phage Therapy Against Multidrug-Resistant Hypervirulent Klebsiella pneumoniae

Multidrug-resistant hypervirulent Klebsiella pneumoniae (MDR-hvKP) poses a severe global health threat. Phage therapy is a promising alternative, but requires precise matching of phage to the bacterial strain. Here, we present a proof-of-concept method that integrates single-cell Raman spectroscopy with deep learning to enable rapid and precise selection of lytic phages against MDR-hvKP. By profiling Raman signatures of strains across multiple KL-types (capsule locus types), we trained three deep learning architectures for phage-host matching. Among them, the CNN_MLP-Transformer achieved the best performance (99.7%), slightly outperforming CNN_MLP (99.2%) and CNN_MLP-Attention (99.5%). Validation using 10 hvKP clinical isolates yielded an average phage selection accuracy of 78.3%. These findings demonstrate the feasibility and clinical potential of AI- augmented Raman spectroscopy as a rapid, label-free, precise strategy for guiding phage therapy against MDR-hvKP infections. TeaserAI-guided single-cell Raman profiling enables rapid precision phage selection against multidrug-resistant K. pneumoniae.

microbiology↗

bioRxiv2026

Microbial Antioxidants Reduce ROS In Human Skin Cells Under Oxidative Stress

Reactive oxygen species (ROS) play a dual role in cellular homeostasis, but excessive levels of ROS lead to oxidative stress, accelerating skin aging. Environmental stressors like UV radiation induce ROS overproduction, overwhelming endogenous antioxidant defenses and causing cellular damage. While the skin possesses an intrinsic antioxidant network that provides moderate protection, excessive oxidative stress can trigger inflammatory responses, thereby necessitating exogenous antioxidant intervention. Microbe-derived antioxidants (MA), produced via probiotic fermentation of sea buckthorn and chestnut rose, have shown promise in mitigating ROS-induced damage. In this study, we evaluated two MA formulations, MA1 and MA2, for their ability to scavenge free radicals and alleviate hydrogen peroxide (H2O2)-induced oxidative stress in human dermal fibroblasts (HDF) and dermal papilla cells (HDP). Both formulations displayed dose-dependent DPPH radical scavenging activity and enhanced cell viability at low concentrations. Under H2O2-induced oxidative stress, MA1 and MA2 effectively restored intracellular ROS to baseline levels, demonstrating significant cytoprotective effects. UHPLC-MS/MS profiling identified 12 compounds shared by both formulations, and Gene Ontology Biological Process enrichment analysis revealed that their associated target genes were significantly enriched in antioxidant-related pathways. Five compounds--adenosine, citric acid, 5-hydroxymethylfurfural, myricetin, and phenylalanine--emerged as key contributors to the observed antioxidative effects. Together, these findings highlight the potential of fermented microbial antioxidants to re-establish redox homeostasis in human skin cells and support their further development as therapeutic or cosmetic interventions targeting oxidative stress and skin aging. Given the heightened oxidative sensitivity of aged fibroblasts, MAs ability to alleviate ROS may offer novel therapeutic strategies against skin aging and related pathologies.

molecular biology↗

bioRxiv2026

KDM7B-mediated demethylation of RNF113A regulates small cell lung cancer sensitivity to alkylation damage

Chemoresistance remains a major obstacle to effective cancer treatment, often driven by enhanced DNA repair mechanisms that enable tumor cells to withstand genotoxic therapies. One such pathway involves the atypical DNA damage repair complex ALKBH3-ASCC, activated by the E3 ligase RNF113A in response to alkylation damage. We previously showed that SMYD3-dependent methylation of RNF113A stimulates this pathway, enhancing DNA repair and promoting resistance. Here, we identify KDM7B/PHF8 as the bona fide RNF113A demethylase, establishing one of the first functional examples of a dynamic, reversible non-histone methylation event regulating genome integrity. KDM7B antagonizes SMYD3 activity by maintaining low levels of methylated RNF113A, thereby limiting ASCC activation and sensitizing cancer cells to alkylating agents. To dissect this regulation in depth, we focused on small cell lung cancer (SCLC), a particularly aggressive malignancy characterized by limited therapeutic options and rapid acquisition of resistance. In SCLC, high KDM7B levels correlate with improved patient prognosis, whereas xenografts with reduced expression exhibit diminished responses to alkylating treatment. Moreover, CRISPR-based on/off modulation of KDM7B in genetically engineered SCLC mouse models demonstrates its central role in determining tumor response to chemotherapy. Our findings position the RNF113A-ASCC axis as a central modulator of chemoresistance, regulated through a post-translational methylation switch representing an innovative therapeutic vulnerability that could be exploited to enhance the efficacy of alkylating agents. Targeting this pathway may provide new opportunities to overcome chemoresistance, with KDM7B levels serving as a predictive biomarker to guide treatment in SCLC.

cell biology↗

bioRxiv2025

DeepDOX1: A Dual-Drive Framework Integrating Deep Learning and First-Principles Physics for Drug-Protein Affinity Prediction

In this work, we present DeepDOX1, a dual-drive drug-protein affinity (DPA) prediction tool features the tight integration of a concise AI architecture and a quantum mechanics based representation. The first-principle physics generated features incorporating the interactions between the drug and the protein pocket allows a relatively simple CNN model trained on a relatively small training set to exhibit exceptional generalization capabilities across extensive testing. Notably, DeepDOX1 outperforms popular AI models in the tests simulating real-world drug design scenario and a highly challenging test set featuring covalent ligands, halogenated ligands and metalloproteins. In addition, we designed a series of novel covalent inhibitors targeting the diabetes target hu-FBPase using DeepDOX1. Subsequent experimental validation including enzyme-level bioactivity assays and crystal structure determination confirmed the DeepDOX1s effectiveness in real-world drug design applications. It is conceivable that the combination of AI and first-principle QM might be one of the next breakthrough points of DPA prediction.

bioinformatics↗

bioRxiv2025

CDH3 as a Novel Therapeutic Target in Basal-like Double-Negative Prostate Cancer

PurposeBasal-like (also known as double-negative) prostate cancers are aggressive tumors that lack effective targeted therapies. We aimed to delineate the role of CDH3 (P-cadherin) in basal-like prostate cancer and evaluate CDH3-directed therapeutic strategies. MethodsWe integrated genetically engineered mouse models (GEMMs) of prostate cancer, bulk and single-cell transcriptomic analyses, and a suite of in vitro and in vivo experiments. CDH3 expression and associated signaling pathways were examined in Pten/Apc double-knockout mouse prostates and human datasets. Functional studies included antibody-drug conjugate (ADC) cytotoxicity assays and the development of chimeric antigen receptor (CAR) T cells targeting CDH3, tested in prostate cancer cell lines and xenograft models. ResultsPten/Apc double deletion in prostate GEMMs led to highly aggressive tumors with markedly elevated CDH3 expression and enrichment of non-canonical WNT signaling components. Transcriptomic analyses of patient-derived prostate tumors confirmed that CDH3 is significantly upregulated in basal-like prostate cancer subtypes relative to luminal subtypes. Single-cell RNA sequencing revealed CDH3 expression predominantly in basal epithelial cells. Mechanistically, we found that active YAP1 signaling and a WNT5A-ROR2 non-canonical WNT axis drive CDH3 expression. Targeting CDH3 with a CDH3-specific ADC induced potent, antigen-dependent killing of CDH3 prostate cancer cells in vitro and significantly suppressed tumor growth in in vivo metastatic prostate cancer models. Likewise, CDH3-targeted CAR T cells specifically recognized and lysed CDH3-expressing prostate tumor cells while sparing CDH3-negative cells, leading to tumor regression and improved survival in mouse models, especially when combined with PD-1 checkpoint blockade. ConclusionsCDH3 is a key marker and functional driver of basal-like prostate cancer. Therapeutic strategies leveraging CDH3, including ADCs and CAR T cells, demonstrate strong preclinical efficacy, supporting the development of CDH3-targeted treatments to overcome resistance in aggressive prostate cancer.

cancer biology↗

bioRxiv2025

The Lysis Cassette of Jumbophage phiKZ

Pseudomonas jumbophage phiKZ is prominent because of the proteinaceous nuclear structure that is formed during the infection cycle, conferring resistance of the replicating phage DNA to anti-phage resistance systems. Progress has been made in deciphering the molecular basis of nucleus formation and other unique aspects of phiKZ biology, but the understanding of how it causes host lysis remains minimal. Here we present bioinformatic, physiological and molecular evidence for a "lysis cassette", the expression of which is necessary and sufficient for the temporally regulated disruption of the host envelope. This cluster contains genes for the usual components of an MGL (multigene lysis) system, including the holin, endolysin, i-spanin and o-spanin. In addition, a fifth gene in the cluster, encoding a cytoplasmic protein, was found to accelerate the timing of holin-mediated lethality when expressed in trans. Evidence is provided that suggests this lysis regulator protein interacts with the cytoplasmic domain of the phiKZ class III holin. In support of this notion, alpha-fold analysis generated a high-confidence structure of a conserved holin-lysis regulator heterodimer complex. Infections at high multiplicity resulted in slower bulk culture lysis profiles than at low multiplicity, suggesting that phiKZ might have a lysis-inhibition system.

microbiology↗

bioRxiv2025

Plant-soil feedback persists beyond host death to shape density-dependent plant competition

Background and AimsPlant-soil feedback (PSF) shapes plant competition, yet classic PSF experiments often overlook the density dependence and temporal complexities of PSFs, especially after host death. We ask whether microbial effects vary after host death and mediate density dependence in seedling competition. MethodsWe combined forest inventory data from a subtropical forest with a density-gradient greenhouse experiment to evaluate seedling competition among two tree species with different mycorrhizal associations (ectomycorrhizal versus arbuscular mycorrhizal). In 2023, we collected soil inocula from living and dead trees (died between 2014 and 2019) with unsterilized and sterilized treatments. We applied invasion analysis to infer seedling competitive outcomes and used bootstrapping to evaluate uncertainty. ResultsSoil microbial communities shaped seedling competition, favoring the ectomycorrhizal species. Using soils collected from living versus dead hosts as live inocula, we found similar plant competitive outcomes, indicating that PSF persists for over 4-9 years following host death. In contrast, when using sterilized inoculum, we found shifts in competition after host death, suggesting underlying abiotic changes which might masked by microbial effects. Moreover, we found significant evidence that soil microbes can mediate nonlinear density dependence in seedling competition. ConclusionWe provide experimental evidence of persistent microbial legacies that benefit ectomycorrhizal tree species in a subtropical forest. Our study demonstrates how integrating field-based census data with density-gradient experiments and explicit uncertainty estimation can better capture the temporal dimensions, complexities of density dependence, and uncertainties of PSF.

ecology↗