Biology subjects

Zhou, X.

Publications and source records attributed to Zhou, X..

At least 163 records · Page 9Linked to original sources

bioRxiv2025

Human meibomian gland organoids to study epithelial homeostasis and dysfunction

Meibomian glands (MGs) are holocrine glands that secrete lipids to maintain the homeostasis of ocular surface, and their dysfunction leads to dry eye disease. Herein, we established long-term 3D organoid culture for murine and human MGs, which retained the cell lineages and lipid-producing ability. The organoids mimicked the drug treatment responses and generated functional MGs after orthotopic transplantation. Inspired by organoid cultures, we found FGF10 eye drops could rescue all-trans retinoic acid-induced MG dysfunction in mice. Besides, nicotinamide uniquely hampered the human MG organoid expansion by inhibiting FGF10 signaling. Single-cell atlas and lipidome not only aligned the delineated cell types and featured lipids between human MGs and organoids, but highlighting MAPK signaling inhibition enhanced acinar cell differentiation and functional maturation of MG organoids. In summary, this study established an organoid platform to explore epithelial homeostasis and dysfunction of MGs, facilitating drug development and regenerative medicine for dry eye disease.

cell biology↗

bioRxiv2025

Phytoene synthase modulates seed longevity via the action of β-carotene derived metabolites

Seed longevity, the seeds ability to stay viable over time, is an important trait in agriculture. Despite extensive research, seed longevity remains one of the fundamental topics in plant biology. Here, we discovered the novel role of carotenoid metabolites in prolonging seed lifespan. We found that phytoene synthase (PSY), the gene encoding a major rate-limiting enzyme in carotenoid biosynthesis, modulated seed storability in Arabidopsis under both natural and artificial aging conditions. Seeds from the PSY overexpression (OE) lines exhibited significantly enhanced lifespan with low levels of reactive oxygen species (ROS), a major factor affecting longevity, whereas those from the psy mutants had decreased viability with high ROS levels. While lutein and {beta}-carotene were detected in seeds, only {beta}-carotene and its derived apocarotenoids, i.e. {beta}-cyclocitral and {beta}-ionone, were found to improve seed lifespan. Notably, the carotenoid cleavage dioxygenase 1 and 4 (ccd1 ccd4) double mutant and PSY ccd1 ccd4 seeds showed significantly reduced seed longevity, indicating that {beta}-carotene cleavage is necessary for or it is apocarotenoids playing the role in preserving seed lifespan. Comparative proteomic analysis identified TIP2;2, an aquaporin protein, which showed differential abundances in seeds of PSY OE and psy mutant vs wild type. The mutant tip2;2 had reduced seed longevity, and its promoter was transactivated by apocarotenoids. Collectively, this study uncovers a novel role of apocarotenoids in protecting seed longevity and highlights the importance of seed carotenoid production in strengthening agriculture. One Sentence SummaryPhytoene synthase, the gene encoding a major rate-limiting enzyme in carotenoid biosynthesis, modulates seed longevity via {beta}-carotene derived apocarotenoids and an aquaporin protein TIP2;2 identified is a new player that responds to apocarotenoid signaling and influences seed longevity.

plant biology↗

bioRxiv2025

Regulating oxygen avaibility mitigates oxidative stresses-induced antibiotic resistance gene expression in E. coli under climate warming

Climate warming presents a critical challenge to global ecosystems, with rising temperatures inducing the emergence of antibiotic resistance genes (ARGs) in aquatic environments. Given the natural correlation between rising temperatures and declining oxygen levels in aquatic systems, we hypothesized that decoupling temperature and oxygen stress would reveal regulatory mechanisms mitigating ARG expression under future warming scenarios. Through transcriptomic analysis of Escherichia coli under temperature upshift (TU), dissolved oxygen upshift (DOU), and dissolved oxygen downshift (DOD), we identified 101 distinct regulons with 8 showing significant regulation (|log2FC| > 1.5). Key regulons (cusR, mhpR, pdhR) exhibited parallel regulation under TU and DOD but opposite patterns under DOU, revealing mechanistic links between temperature and oxygen stress through shared regulatory networks involving oxidative stress regulators (oxyR-metR) and aerobic respiration control (arcA-betI). Evolved strains from controlled temperature-oxygen fluctuations demonstrated sophisticated metabolic reprogramming, including enhanced carbohydrate metabolism, nucleotide biosynthesis, and putrescine degradation. These strains exhibited optimized energy metabolism through reduced downregulation of ATP synthase subunits and NADH dehydrogenase complex genes, preserving electron transport chain function under thermal stress. Simultaneously, they displayed strategic ROS management with reduced upregulation of peroxiredoxin (ahpF) and Cu/Zn-SOD (sodC), while reversing Fe-SOD (sodB) expression patterns. To validate these mechanisms, we conducted independent batch reactor experiments with two dissolved oxygen conditions (2-8 mg/L) using intermittent perturbation patterns. Non-targeted metaproteomic analysis revealed that lowered oxygen levels (2 vs. 8 mg/L) triggered comprehensive reconfiguration of antimicrobial resistance mechanisms, including downregulation of penicillin-binding proteins, alanine racemase, and cationic antimicrobial peptide resistance systems, while modulating two-component regulatory networks. Our findings reveal coordinated regulatory networks optimizing energy metabolism, ROS management, and antibiotic resistance, suggesting oxygen management strategies could mitigate climate warming effects on antibiotic resistance in aquatic environments.

microbiology↗

bioRxiv2025

Biomni: A General-Purpose Biomedical AI Agent

Biomedical research underpins progress in our understanding of human health and disease, drug discovery, and clinical care. However, with the growth of complex lab experiments, large datasets, many analytical tools, and expansive literature, biomedical research is increasingly constrained by repetitive and fragmented workflows that slow discovery and limit innovation, underscoring the need for a fundamentally new way to scale scientific expertise. Here, we introduce Biomni, a general-purpose biomedical AI agent designed to autonomously execute a wide spectrum of research tasks across diverse biomedical subfields. To systematically map the biomedical action space, Biomni first employs an action discovery agent to create the first unified agentic environment - mining essential tools, databases, and protocols from tens of thousands of publications across 25 biomedical domains. Built on this foundation, Biomni features a generalist agentic architecture that integrates large language model (LLM) reasoning with retrieval-augmented planning and code-based execution, enabling it to dynamically compose and carry out complex biomedical workflows - entirely without relying on predefined templates or rigid task flows. Systematic benchmarking demonstrates that Biomni achieves strong generalization across heterogeneous biomedical tasks - including causal gene prioritization, drug repurposing, rare disease diagnosis, micro-biome analysis, and molecular cloning - without any task-specific prompt tuning. Real-world case studies further showcase Biomnis ability to interpret complex, multi-modal biomedical datasets and autonomously generate experimentally testable protocols. Biomni envisions a future where virtual AI biologists operate alongside and augment human scientists to dramatically enhance research productivity, clinical insight, and healthcare. Biomni is ready to use at https://biomni.stanford.edu, and we invite scientists to explore its capabilities, stress-test its limits, and co-create the next era of biomedical discoveries.

bioinformatics↗

bioRxiv2025

Neurocomputational Mechanisms Linking Future Interaction Prospects to Reactive and Proactive Costly Punishment

Costly punishment within social bonds manifests as both reactive penalties for transgressions and proactive sanctions against fair behaviors, yet a unified neurocomputational framework remains elusive. Combining neuroimaging and computational modeling, this study examined how future interaction prospects--a key element of social bonds--modulate reactive and proactive punishment. Participants acted as second- or third-party punishers, responding to allocation offers from individuals with or without future interactions. Results showed that participants imposed harsher punishment on both fair and unfair offers from individuals they did not expect to interact with, aligning with lower self-reported social closeness. Heightened provocation sensitivity, reflected in dorsal anterior cingulate cortex activity, drove the increased reactive punishment toward wrongdoers without future interactions, whereas punishment of future-interacting transgressors was associated with enhanced dorsolateral and dorsomedial prefrontal cortex (dlPFC, dmPFC) activity. A stronger preference for relative advantage and reduced harm sensitivity, linked to dlPFC and temporoparietal junction activity, mediated greater proactive punishment towards non-future-interacting individuals. Moreover, proactive punishment and underlying neurocognitive processes followed a collective retaliation pattern, increasing after unfair (vs. fair) behavior from another non-future-interacting individual. These findings establish a unified neurocomputational framework for understanding how future interaction prospects regulate costly punishment, integrating reactive and proactive motives within social bonds.

neuroscience↗

bioRxiv2025

Machine learning identifies novel signatures of antifungal drug resistance in Saccharomycotina yeasts

Antifungal drug resistance is a major challenge in fungal infection management. Numerous genomic changes are known to contribute to acquired drug resistance in clinical isolates of specific pathogens, but whether they broadly explain natural resistance across entire lineages is unknown. We leveraged genomic, ecological, and phenotypic trait data from naturally sampled strains from nearly all known species in subphylum Saccharomycotina to examine the evolution of resistance to eight antifungal drugs. The phylogenetic distribution of drug resistance varied by drug; fluconazole resistance was widespread, while 5-fluorocytosine resistance was rare, except in Lipomycetales. A random forest algorithm trained on genomic data predicted drug-resistant yeasts with 54-75% accuracy. In general, frequency of drug resistance correlated with prediction accuracy, with fluconazole resistance being consistently predicted with the highest accuracy (74.9%). Fluconazole resistance accuracy was similar between models trained on genome-wide variation in the presence and number of InterPro protein annotations across Saccharomycotina (74.9% accuracy) and those trained on amino acid sequence alignment data of Erg11, a protein known to be involved in fluconazole resistance (74.3-74.9% accuracy). Interestingly, the top Erg11 residues for predicting fluconazole resistance across Saccharomycotina do not overlap with, are not spatially close to, and are less conserved than those previously linked to resistance in clinical isolates of Candida albicans. In silico deep mutational scanning of the C. albicans Erg11 protein revealed that amino acid variants implicated in clinical cases of resistance are almost universally destabilizing while variants in our most informative residues are energetically more neutral, explaining why the latter are much more common than the former in natural populations. Importantly, previous experimental analyses of C. albicans Erg11 have shown that amino acid variation in our most informative residues, despite having never been directly implicated in clinical cases, can directly contribute to resistance. Our results suggest that studies of natural resistance in yeast species never encountered in the clinic will yield a fuller understanding of antifungal drug resistance.

microbiology↗

bioRxiv2025

Adaptive Asymmetric Adjustment in Affective Evaluation and Reciprocity for Altruistic Behaviors from Exogenous Uncertainty to Certainty

In direct reciprocity, environmentally imposed exogenous uncertainty frequently decouples benefactors altruistic intentions from final outcomes. How do cooperative bonds remain resilient against this inevitable "noise"? Adopting a comprehensive levels-of-analysis framework across eight experiments, we integrate interpersonal paradigms, computational modeling, multivariate fMRI decoding, and third-party social evaluations to uncover a robust "asymmetric adjustment" in beneficiarys affective evaluation and reciprocity under exogenous uncertainty, systematically delineating its cognitive algorithmic rules, neural representations, and adaptive functions in sustaining human cooperation. Specifically, beneficiarys reciprocity amplifies for positive deviations from expectations while buffering against reciprocal reductions from unintended shortfalls. Modeling reveals this computational resilience is governed by an asymmetric intrinsic prosocial bias, extending beyond traditional frameworks of outcome/intention-based evaluation, prediction-error-based social learning, or loss aversion. Supported by theory-of-mind system, this "asymmetric adjustment" is perceived as morally superior to other calculations, thereby serving a critical adaptive function to sustain cooperation amidst the volatility of an uncertain world.

animal behavior and cognition↗

bioRxiv2025

Linking Oxygen-Induced Oxidative Stress to Resource Recovery by Enhancing the Production of Extracellular Polymeric Substances in Activated Sludge Microbial Communities

As the global transition toward circular wastewater treatment intensifies, extracellular polymeric substances (EPS) have emerged as valuable targets for resource recovery. Although most efforts have focused on aerobic granular sludge, conventional activated sludge systems, which account for most global wastewater treatment, remain underexploited for EPS recovery. Building on the established link between oxidative stress and EPS biosynthesis in pure strains, we propose that strategically manipulating oxygen exposure patterns to intensify oxidative stress in activated sludge microbial communities could enhance EPS production. To test this, we applied continuous oxygen perturbation under aerobic exposure to intensify oxidative stress. Compared to a stable oxygen condition simulating typical wastewater aeration, the perturbation considerably enhanced EPS yield to 74.4{square}mg/L/day, a 90.5% increase over the stable condition (39.0{square}mg/L/day). To validate the role of oxidative stress in EPS enhancement, intermittent anoxic phases were introduced into the perturbation pattern to relieve oxidative stress, causing the EPS-enhancing effect to disappear, with yield dropping to 9.8{square}mg/L/day. Mechanistically, intensified oxidative stress under aerobic continuous perturbation was primarily driven by elevated reducing substrates for non-respiratory flavoenzymes, exemplified by glutamate synthase, glutathione reductase, and dihydrolipoamide dehydrogenase, which are prone to generate H2O2 as an unintended metabolic byproduct. Among the multiple microbial groups contributing to H2O2 production, Methylophilaceae, Comamonadaceae, and Rhodobacteraceae were distinguished by simultaneously exhibiting upregulation of EPS biosynthesis proteins, suggesting that taxa within these families collectively mediated both H2O2 production and EPS enhancement. By modulating aeration, this study offers a chemical-free, controllable strategy for enhancing EPS production within conventional activated sludge systems. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/651171v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@1f52710org.highwire.dtl.DTLVardef@1d7b36corg.highwire.dtl.DTLVardef@4484b5org.highwire.dtl.DTLVardef@64979f_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

The landscape of structural variation in pediatric cancer

Structural variants (SVs) account for over 60% of the driver variants in pediatric cancer, and in many cases act as the cancer initiating event. To study SVs from a pan-cancer perspective, we analyzed 1,616 pediatric cancer genomes in 16 major cancer types of hematological malignancies (n = 908), brain tumors (n = 183), and solid tumors (n = 525) and compared their profiles to those of 2,203 adult cancers. The SV burden varied [~]100-fold across pediatric cancer types and demonstrated an 8-to 16-fold reduction compared to adult brain and solid tumors but was comparable in pediatric versus adult hematological malignancies. Recurrent SV hotspots occurred uniquely in pediatric acute lymphoblastic leukemias (ALLs) in proximity to RAG-mediated recombination signal sequences (RSS) and disrupted multiple immune-related loci as well as 69 genes, which often involved cryptic RSS sites. By contrast, such hotspots affected only immune-related loci but not driver genes in adult lymphoid cancers. Eight SV signatures extracted from the cohort had varying distributions across cancer types, with clustered translocations reflecting templated insertions in osteosarcoma, and medium-sized deletions (10 kb to 1 Mb) enriched in cancers with RAG-mediated deletions. Intra-patient evolutionary analysis in 13 patients with multiple spatiotemporally distinct samples revealed that RAG-mediated recombination in leukemia and complex rearrangements in solid tumors occurred both early in disease initiation and continuously during later diversification, contributing to clonal heterogeneity. Finally, we found that both driver genes and fragile sites were the two genomic regions most frequently disrupted by SVs. The unique and diverse SV landscapes that emerged from this comprehensive analysis expand the scope of RSS-mediated mutagenesis in pediatric ALL and will be a valuable resource for guiding future functional studies and the design of clinical genomic testing in pediatric cancer.

cancer biology↗

bioRxiv2025

Ancient co-option of LTR retrotransposons as yeast centromeres

The evolutionary origins of the genetic point centromere in the brewers yeast Saccharomyces cerevisiae, a member of the order Saccharomycetales, are still unknown. Competing hypotheses suggest that the point centromere tripartite genetic centromere DNA elements (CDEs) either evolved from ancestral epigenetic centromeres by descent with modification or were gained through horizontal transfer from selfish DNA plasmids.1,2 Here, we identified centromeres in the sister order Saccharomycodales and termed them "proto-point centromeres" due to sequence features that bridge the evolutionary gap between point centromeres and ancestral centromeres types. Comparative genomic analyses across multiple yeast orders showed an unexpected evolutionary link between point and proto-point centromeres to the long terminal repeats (LTRs) of Ty5 retrotransposons. Strikingly, one Saccharomycodales species, Saccharomycodes ludwigii, harbors compact Ty5-based centromeres, where its CDEII elements are divergent AT-rich Ty5 LTRs. These living fossil centromeres show how retrotransposon cis-regulation was likely co-opted for genetic centromere specification. These insights show that point centromeres are direct descendants of retrotransposons and have evolved by descent with modification. Ultimately, the many diverse centromere types across the yeast subphylum may share a common ancestry rooted in retrotransposon activity.

evolutionary biology↗

bioRxiv2025

ER fusogens maintain membrane reservoir to ensure brain function

How the morphological dynamics of the endoplasmic reticulum (ER) are linked to its functions is unclear. Atlastins (ATLs), a class of GTPases, mediate ER fusion, and human mutations in ATL1 cause hereditary spastic paraplegia (HSP). Here, we show that ATL2-knockout mice are embryonic lethal with compromised development, particularly of the cerebellum. ATL2 is highly expressed in neuroglia, though ATL1 is dominant in the brain. Lack of ATL2 disorganizes the positioning of Bergmann glia, which in turn interferes with granule cell migration. These cells have significant shrinkage in the intracellular membrane area, which is associated with decreased phosphatidylcholine and cholesterol synthesis. When tested in calyx-type synapses in ATL-deleted mice, a reduced membrane reservoir, represented by fewer presynaptic vesicles, leads to defective synaptic function and deafness. Collectively, these findings suggest that ER-shaping activity by ATL is essential for sustained lipid synthesis, and boosted lipid uptake is potentially beneficial for HSP patients.

neuroscience↗

bioRxiv2025

Increased Infectivity of Human Cytomegalovirus Strain TB40/E Conferred by Variants of the Envelope Glycoprotein UL128 and the Regulatory Protein IE2

Human cytomegalovirus (HCMV) infects various cell types in its human host, and this broad tropism plays a vital role in viral transmission, dissemination, and pathogenesis. HCMV strains differ in their ability to infect and replicate in different cell types, but the genetic determinants of cell tropism have only begun to be understood. A widely used HCMV strain, TB40/E, contains a mixture of genetically distinct virus variants. Only a few passages in ARPE-19 epithelial cells resulted in the selective enrichment of a substrain, termed TB40/EE, which infected epithelial cells more efficiently than the parental TB40/E and induced the formation of large multinucleated syncytia. Herein, we used sequence comparison and genetic engineering of a TB40/E-derived bacterial artificial chromosome clone, TB40-BAC4, to demonstrate that the high infectivity of TB40/EE and its ability to induce syncytia in epithelial cells depends on two single-nucleotide variants (SNVs) affecting the envelope glycoprotein UL128 and the major viral transactivator protein, IE2. While the intronic SNV in UL128 increased splicing of the UL128 transcript, it surprisingly decreased viral infectivity and replication in epithelial cells. The additional introduction of the IE2 SNV reversed this phenotype, increasing infectivity and syncytium formation. This SNV resulted in a D390H substitution and increased the levels of several early and late viral proteins, suggesting that it altered the ability of IE2 to activate viral genes. The same two SNVs increased the ability to infect THP-1-derived macrophages and JEG-3 trophoblast cells. These results demonstrate that HCMV cell tropism depends on both envelope glycoproteins and regulatory proteins. ImportanceDifferent genetic versions of human cytomegalovirus (HCMV) affect its ability to infect various human cell types. Here we focused on a commonly used strain, TB40/E, which contains a mix of virus variants. After growing it in epithelial cells, a specific variant called TB40/EE became dominant. This variant infected epithelial cells more effectively and caused the formation of large, fused cells (syncytia). In this study, we discovered that two small genetic changes were responsible for this behavior. One change affected a protein on the viral envelope (UL128) by altering how its RNA was processed. Surprisingly, this change reduced the viruss ability to spread, but a second change in a regulatory protein (IE2) reversed that effect. Together, these changes enhanced the viruss ability to infect not only epithelial cells but also macrophages and placental cells. This study highlights how small genetic tweaks can influence how HCMV targets different types of human cells.

microbiology↗

bioRxiv2025

Exploring Population Differences in the Human Gut Microbiome: from Microbial Abundance to Single Nucleotide Polymorphisms

The human gut microbiota exhibits significant diversity across populations, influenced by factors such as geography, diet, and lifestyle, particularly between the Han Chinese and non-Chinese populations. While previous studies have predominantly focused on the taxonomic abundance of the gut microbiome, the impact of single nucleotide polymorphisms (SNPs) in driving population-specific differences remains largely underexplored. In this study, we systematically investigated gut microbial differences between the Han Chinese and non-Chinese populations using the Human Gut Microbiome Reference Genome Catalog (HGMRGC). HGMRGC includes 271,480 non-redundant genomes from 5,785 prokaryotic species, which was generated by metagenomic sequencing data from 9,320 publicly available samples across 22 countries and 3,584 newly sequenced samples from Han Chinese individuals across 29 provinces and regions in China. We observed geography was the primary driver of microbial variation of abundance and SNPs. We identified 625 novel population-specific genome clusters from HGMRGC with functional differences in carbohydrate utilization and 126 species exhibiting distinct prevalence related to vitamin biosynthesis, antibiotic resistance, and carbohydrate metabolism. Beta diversity analysis highlighted significant inter-population differences in both microbial abundance and SNPs, while alpha diversity analysis revealed that non-Chinese populations exhibited higher diversity in microbial abundance, and Han Chinese populations displayed greater diversity in SNPs. These results provide valuable insights into population-specific microbial diversity, laying the groundwork for future research on its functional and health implications.

microbiology↗

bioRxiv2025

High-accuracy protein complex structure modeling based on sequence-derived structure complementarity

In living organisms, proteins perform key functions required for life activities by interacting to form complexes. Determining the protein complex structure is crucial for understanding and mastering biological functions. Although AlphaFold2 has made a revolutionary breakthrough in predicting protein monomeric structures, accurately capturing inter-chain interaction signals and modeling the structures of protein complexes remain a formidable challenge. In this work, we report DeepSCFold, a pipeline for improving protein complex structure modeling. DeepSCFold uses sequence-based deep learning models to predict protein-protein structural similarity and interaction probability, providing a foundation for identifying interaction partners and constructing deep paired multiple-sequence alignments (MSAs) for protein complex structure prediction. Benchmark results show that DeepSCFold significantly increases the accuracy of protein complex structure prediction compared with state-of-the-art methods. For multimer targets from CASP15, DeepSCFold achieves an improvement of 11.6% and 10.3% in TM-score compared to AlphaFold-Multimer and AlphaFold3, respectively. Furthermore, when applied to antibody-antigen complexes from the SAbDab database, DeepSCFold enhances the prediction success rate for antibody-antigen binding interfaces by 24.7% and 12.4% over AlphaFold-Multimer and AlphaFold3, respectively. These results demonstrate that DeepSCFold effectively captures intrinsic and conserved protein-protein interaction patterns through sequence-derived structure-aware information, rather than relying solely on sequence-level co-evolutionary signals.

bioinformatics↗

bioRxiv2025

T-World: A highly general computational model of a human ventricular myocyte

Cardiovascular disease is the leading cause of death, demanding new tools to improve mechanistic understanding and overcome limitations of stem cell and animal-based research. We introduce T-World, a highly general virtual model of human ventricular cardiomyocyte suitable for multiscale studies. T-World shows comprehensive agreement with human physiology, from electrical activation to contraction, and is the first to replicate all key cellular mechanisms driving life-threatening arrhythmias. Extensively validated on unseen data, it demonstrates strong predictivity across applications and scales. Using T-World we revealed a likely sex-specific arrhythmia risk in females related to restitution properties, identified arrhythmia drivers in type 2 diabetes, and describe unexpected pro-arrhythmic role of NaV1.8 in heart failure. T-World demonstrates strong performance in predicting drug-induced arrhythmia risk and opens new opportunities for predicting and explaining drug efficacy, demonstrated by unpicking effects of mexiletine in Long QT syndrome 2. T-World is available as open-source code and an online app.

cell biology↗

bioRxiv2025

Munc13-4 mediates tumor immune evasion by regulating the sorting and secretion of PD-L1 via exosomes

Tumor-derived extracellular vesicles primarily carry PD-L1 via exosomes, which interact with PD-1 receptors on T cells, impacting immune responses in the tumor microenvironment and beyond, leading to a more extensive immunosuppressive landscape. However, the mechanisms governing exosomal PD-L1 sorting and secretion remain elusive. In this study, we identified Munc13-4 as a crucial regulator of exosomal PD-L1 sorting and secretion. Deletion of Munc13-4 in breast tumors enhances T cell-mediated anti-tumor immunity, suppresses tumor growth, and improves the efficacy of immune checkpoint inhibitors. Our results illustrate how Munc13-4 collaborates with HRS, Rab27, and SNAREs to facilitate PD-L1 sorting and secretion via exosomes. The cryo-EM structure of the Munc13-4-Rab27a complex provide new insights into its role in exosome secretion. Importantly, we discovered that Munc13-4 has a novel role in sorting PD-L1 onto exosomes, which relies on the formation of a ternary complex with PD-L1 and HRS. In addition, IFN{gamma} stimulation modifies Munc13-4 and HRS, establishing a dynamic regulatory mechanism that enables tumor cells to adapt to immune pressure by modulating PD-L1 sorting. Using a specially designed peptide to disrupt the Munc13-4-PD-L1 interaction and impede PD-L1 sorting significantly enhances anti-tumor immunity and slows tumor growth in vivo. These results highlight the potential of targeting the Munc13-4-PD-L1 axis to suppress tumor immune evasion.

cell biology↗

bioRxiv2025

A Comprehensive Reference Catalog of Human Skin DNA Virome Reveals Novel Viral Diversity and Microenvironmental Influences

IntroductionHuman skin serves as a dynamic habitat for a diverse microbiome, including a complex array of viruses whose diversity and roles are not fully understood. ObjectivesThis study aims to enhance our understanding of this skin viral diversity through the construction of a detailed, non-redundant DNA viral reference catalog. MethodsA total of 2,760 skin metagenomes from six published skin studies were collected. A skin virome catalog was constructed using methods independent of reference databases. Viral characteristics were identified through cross-cohort meta-analysis and used to characterize viral features across different skin environments. ResultsWe identified 20,927 viral sequences, which clustered into 2,873 viral operational taxonomic units (vOTUs). Among these, 2,610 represent previously unrecorded viral sequences, uncovering a substantial breadth of viral diversity on human skin. The results also highlight significant differences in viral communities that are associated with varying skin microenvironments. The oily skin is enriched in Papillomaviridae; the dry skin area is enriched in Autographiviridae, Inoviridae and Mitoviridae; and the moist skin is enriched in Herelleviridae, indicating the adaptive nature of viruses. We also investigated the relationship between bacteriophages and bacteria on the skin surface. We found that skin bacteria such as Pseudomonas, Klebsiella, and Staphylococcus are infected by phages from the class Caudoviricetes. ConclusionThis comprehensive skin DNA viral catalog significantly advances our understanding of the viromes role within the skin ecosystem. The findings highlight the adaptive nature of viruses to different skin microenvironments and their interactions with resident bacteria. This catalog serves as a valuable resource for further epidemiological and therapeutic research, potentially leading to better management and treatment of skin conditions influenced by the skins virome.

microbiology↗

bioRxiv2025

cfMethDB: a comprehensive cfDNA methylation data resource for cancer biomarkers

Cancer is a major global health threat, and early detection of cancer is crucial for improving patient outcomes. DNA methylation in circulating cell-free DNA (cfDNA) has emerged as a promising biomarker for non-invasive cancer diagnosis. However, the integration and utilization of existing cfDNA methylation data have been limited, hindering comprehensive research efforts, especially in the discovery of cfDNA methylation biomarkers. To address this challenge, we introduce cfMethDB, a comprehensive database dedicated to cfDNA methylation in cancer that encompasses 4828 publicly available datasets. Through standardized analysis, we identified 1,048,770 differentially methylated cytosines (DMCs) as candidate biomarkers across seven cancer types. With cfMethDB, we not only identified known cfDNA methylation biomarkers, but also discovered several genes, such as ZIC4, that could be novel biomarkers. Moreover, cfMethDB offers a suite of user-friendly tools, including biomarker evaluation, pan-cancer search and end motif analysis. We hope that cfMethDB will serve as a valuable platform for the discovery of novel cancer cfDNA methylation biomarkers and will facilitate cancer research and clinical applications. cfMethDB is publicly available at: https://cfmethdb.hzau.edu.cn/home.

genomics↗