Biology subjects

Li, S.

Publications and source records attributed to Li, S..

At least 343 records · Page 19Linked to original sources

bioRxiv2025

Buffer Valency Engineering Enables High-concentration and Shelf-stable DNA Transfection Particles for Viral Vector Production

Cost-effective and scalable production is critical for advancing the clinical translation of adeno-associated virus (AAV)-mediated gene therapy. The widely used transient transfection method using plasmid DNA (pDNA)-loaded transfection particles for AAV production faces technical challenges due to instability of the particles and the concentration limits for particle preparation, hindering reproducibility and scalability. Here, we report a streamlined and scalable strategy to generate shelf-stable, highly concentrated pDNA/poly(ethylenimine) (PEI) transfection particles. By incorporating trivalent citrate ions in the dilution buffers, we kinetically modulate electrostatic complexation to achieve uniform nanoparticle assembly and prevent aggregation at high concentrations. This enables a tenfold increase in pDNA concentration in stabilized transfection particles from a typical range of 10-20 g/mL to 200 g/mL, while reducing the required dosing volume from 5-10% to 0.5% of the cell culture medium. The particle assembly process is robust to changes in mixing scale and timing and is compatible with standard workflows. We demonstrate equivalent AAV production efficiencies to standard methods and consistent performance in various production scales, which confirms the practical utility of this assembly method in developing robust, scalable, and cost-effective AAV manufacturing processes.

biochemistry↗

bioRxiv2025

NANOME: A Nextflow pipeline for haplotype-aware allele-specific consensus DNA methylation detection by nanopore long-read sequencing

Nanopore long-read sequencing has expanded the capacity of long-range, single-base, and single-molecule DNA-methylation (DNAme) detection and haplotype-aware allele-specific epigenetic phasing. Previously, we benchmarked and ranked the robustness of seven computational tools for DNAme detection using nanopore sequencing. The top performers were Megalodon, Nanopolish, DeepSignal and Guppy. However, these algorithms exhibit lower performance at regions with discordant non-singleton DNAme patterns compared to genome-wide regions. Furthermore, long-read sequencing analysis of mammalian genomes requires higher computational resources than next-generation sequencing. To address these issues, we developed a NANOpore Methylation (NANOME) a consensus DNAme predictive model using XGBoost, which integrates the output of Megalodon, Nanopolish, and Deepsignal for analyzing data obtained using Oxford Nanopore Technologies (ONT). NANOME enhanced DNAme detection precision (mean square error) at single-base resolution by 11% and improved accuracy (F1-score) at single-molecule resolution by 2.4% for human B-lymphocyte European cell lines (NA12878). The consensus model also detected [~]200,000 more CpGs than all three tools. Combing variant calling and long-read phasing, NANOME can detect haplotype-aware allele-specific DNAme in known imprinting controls in resolved and previously unresolved regions. We conducted haplotype-aware methylation detection on the T2T genome for dataset NA12878, revealing significant variations in differentially methylated region (DMR) density between gap and non-gap regions. Overall, NANOME represents a significant step forward in DNAme detection and long-range epigenetic phasing, offering a robust and accessible tool for researchers studying the epigenome.

bioinformatics↗

bioRxiv2025

Male-Biased Cyp17a2 Governs Antiviral Sexual Dimorphism in Fish via STING Stabilization and Viral Protein Degradation

Differences in immunity between males and females in living organisms are generally thought to be due to sex hormones and sex chromosomes, and it is often assumed that males have a weaker immune response. Here we report that in fish, males exhibit stronger antiviral immune responses, the male-biased gene cyp17a2 as a critical mediator of this enhanced response. First, we observed that male zebrafish exhibit enhanced antiviral resistance compared to females, and notably, zebrafish lack sex chromosomes. Through transcriptomic screening, we found that cyp17a2 was specifically highly expressed in male fish. Cyp17a2 knockout males were equivalent to wild-type males in terms of sex organs and androgen secretion, but the ability to upregulate IFN as well as antiviral resistance was greatly reduced. Then, Cyp17a2 is identified as a positive IFN regulator which located at endoplasmic reticulum, and specifically interacts with and enhances STING mediated antiviral responses. Mechanistically, Cyp17a2 stabiles STING expression by recruiting the E3 ubiquitin ligase bloodthirsty-related gene family member 32 (btr32), which facilitates K33-linked polyubiquitination. The capacity of IFN induction of Cyp17a2 was abolished when STING is knockdown. Meanwhile, Cyp17a2 also attenuates viral infection directly to strengthen the antiviral capacity as an antiviral protein, Cyp17a2 degrades the spring viremia of carp virus (SVCV) P protein by utilizing USP8 to reduce its K33-linked polyubiquitination. These findings reveal a sex-based regulatory mechanism in teleost antiviral immunity, broadening our understanding of sexual dimorphism in immune responses beyond the conventional roles of sex chromosomes and hormones.

immunology↗

bioRxiv2025

Competing Programs Shape Cortical Sensorimotor-Association Axis Development

The neocortex is organized along a dominant sensorimotor-to-association (S-A) axis, anchored by modality-specific primary sensorimotor areas at one end and transmodal association areas that form distributed networks supporting abstract cognition at the other. The developmental mechanisms shaping this axis remain elusive. Here, we present converging multispecies evidence supporting the Multinodal Induction-Exclusion in Network Development (MIND) model, in which S-A patterning is governed by competing processes of induction and exclusion, driven by opposing transcriptomically-defined identity programs emerging from different nodes. Key molecular and connectional features of association cortices arise through pericentral programs, originating around fronto-temporal poles and partially regulated by retinoic acid. They progress inward toward central territories of the naive neocortex along fronto-temporally polarized trajectories. Central programs are induced through interactions between topographically separated first-order sensorimotor thalamocortical inputs and the neocortex, promoting the formation of primary areas while excluding pericentral programs. Influenced by SATB2 and ZBTB18, these evolutionarily conserved programs compete for the same territory and create spatial compartmentalization of axon guidance, cell-cell adhesion, retinoic acid signaling, synaptogenesis, Wnt signaling, and autism risk genes. Notably, PLXNC1 and SEMA7A exhibit anti-correlated expression and repulsive functions in shaping cortico-cortical connectivity along the S-A axis. These processes of induction and exclusion establish an S-A equilibrium and topography in which primary sensorimotor areas emerge as focal islands within the broader ocean of distributed associative networks. The MIND model provides a unifying framework for understanding experimental, evolutionary, and clinical phenomena, revealing induction and exclusion as antagonistic complementary principles shaping the S-A axis and processing hierarchies.

neuroscience↗

bioRxiv2025

Dynamics and Regulation of mRNA Cap Recognition by Human eIF4F

Efficient eukaryotic messenger RNA translation requires dynamic collaboration between the three subunits of initiation factor 4F (eIF4F, eIF4E*G*A), which recognises and activates mRNA at its 5' cap structure for ribosome recruitment. Despite its high biological and pharmacological importance, the dynamics of full human eIF4F-mRNA engagement remain largely uncharacterised, hindering mechanistic understanding of translation initiation and its regulation. Here we observed human eIF4F activity with single-molecule fluorescence assays that directly visualise mRNA cap recognition by its eIF4E subunit. Unexpectedly, we find that inherently transient eIF4E-cap binding is repressed by full-length human eIF4G, predominantly through its C-terminus, representing an unanticipated role for eIF4G as a central rate-limiting factor in the eIF4F complex. This repression is relieved by nucleotide-bound eIF4A in the eIF4F heterotrimer, placing eIF4A as a crucial determinant of efficient cap recognition for translation. Molecular dynamics simulations reveal that electrostatic modulation of eIF4E-mRNA interaction allows eIF4G to control the cap-recognition frequency. Our findings also indicate that intrinsic eIF4F- mRNA dynamics are insufficient to support cap-tethered ribosomal scanning to locate translation start sites. They illuminate fundamental design-principle differences for the overall mechanism and division of labour among eIF4F subunits during mRNA recognition in humans and yeast.

biophysics↗

bioRxiv2025

Targeting PI3K Signaling for Broad Inhibition of β-Coronavirus Infection

The phosphatidylinositol 3-kinase (PI3K) signaling pathway plays a central role in regulating key cellular processes such as survival, metabolism, and immune responses. Aberrant activation of this pathway is associated with tumorigenesis, and several PI3K inhibitors have been developed as anticancer agents. Emerging evidence suggests that viruses, including {beta}-coronaviruses, have evolved mechanisms to exploit host PI3K signaling for their replication and immune evasion. In this study, we evaluated the antiviral efficacy of a panel of PI3K inhibitors against {beta}-coronaviruses, including mouse hepatitis virus (MHV), human OC43 (HuCoV-OC43) and four major SARS-CoV-2 variants using both cell line and organoid models. Our findings reveal that these compounds exhibit low micromolar potency in inhibiting viral replication. Notably, the inhibitor C20 (PWT33597) demonstrated broad-spectrum activity against multiple {beta}-coronaviruses, including SARS-CoV-2, MHV, and HuCoV-OC43, in conventional cell lines as well as in air-liquid interface (ALI)-cultured, differentiated primary human nasal and bronchial epithelial cells. Given that cytokine storm is a major contributor to SARS-CoV-2-related multiorgan failure and mortality, we further explored the impact of PI3K inhibition on host inflammatory responses. We found that MHV infection markedly increased cytokine expression in 17CL-1 fibroblasts and RAW264.7 macrophages. Interestingly, treatment with C20 further amplified cytokine production in this context, suggesting complex immunomodulatory effects that warrant further investigation. Together, our findings support the therapeutic potential of repurposing PI3K inhibitors as broad-spectrum antivirals. These compounds not only suppress viral replication but may also influence host immune responses, providing a promising avenue for intervention against current and emerging coronavirus threats.

microbiology↗

bioRxiv2025

Arabidopsis RabGDIs are essential for the asymmetric division of zygotes and embryonic patterning

An asymmetric division of zygotes sets up the apical-basal body axis and starts the life cycle of angiosperms. In addition to specific expression of transcription factors and polar distribution of auxin, vesicular trafficking-mediated endomembrane dynamics are critical for zygotic division and embryonic patterning. As key regulators of vesicular trafficking, whether Rab GTPases play a role in these processes is unclear. We report that Arabidopsis guanine nucleotide dissociation inhibitors for Rab (RabGDIs) are essential for the asymmetric division of zygotes and embryonic patterning likely through regulating the dynamic targeting of canonical Rab GTPases, especially Rab5. Arabidopsis RabGDIs specifically interact with canonical Rab GTPases. Functional loss of Arabidopsis RabGDI1 and RabGDI2 compromises the asymmetry of zygotic division, cell fate determination, and embryonic patterning. Polar distribution of vacuolar dynamics was disrupted in zygotes and 1-cell embryo of gdi1 gdi2, suggesting a key role of RabGDIs in vacuolar dynamics. Furthermore, genetic interference of canonical Rab5, a key regulator of vacuolar trafficking and biogenesis, in zygotes leads to similar defects, consistent with the disturbed localization of Rab5 in gdi1 gdi2 embryos. Results presented demonstrate the key role of RabGDIs through Rab GTPases in asymmetric division of zygotes and embryonic patterning.

plant biology↗

bioRxiv2025

Downregulation of LATS1/2 Drives Endothelial Senescence-Associated Stemness (SAS) and Atherothrombotic Lesion Formation

BackgroundAtherothrombosis, the main event leading to acute coronary syndrome (ACS), is strongly linked to disturbed blood flow (d-flow) regions. Although the involvement of the Hippo pathway and its kinases Large Tumor Suppressor Kinase 1and 2 (LATS 1 and 2) in mechanical stress responses is known, the mechanisms by which d-flow simultaneously induces senescence, proliferation, and atherothrombosis remain unclear. MethodsThe role of endothelial cells (EC)-specific LATS1/2 was examined using EC specific knock-out (EKO) mice in a partial left carotid ligation (PLCL) model. Plaque spatial multi-omics analysis was performed by integrating imaging mass cytometry, sequential immunofluorescence (COMET), and spatial metabolomics at the single-cell level in human and mouse atherosclerotic plaques. ResultsIn tamoxifen-inducible Lats1homo(-/-) /Lats2 homo(-/-) EC-specific knockout (EKO) mice, deletion of LATS1/2 induced by tamoxifen led to fatal outcomes, characterized by severe systemic edema and markedly increased vascular permeability. In contrast, Lats1het(+/-)/Lats2 homo(-/-)-EKO mice survived and developed atherothrombotic plaques exhibiting neovascularization even without further additional dietary or genetic intervention. Spatial proteomics analysis revealed that LATS1/2 depletion in ECs triggered a senescence-associated stemness (SAS) phenotype, primarily driven by CD38 upregulation. Complementary spatial metabolomics profiling demonstrated a significant increase in sulfite and taurine within LATS1/2-deficient plaques, indicating lowered sulfite oxidase (SUOX) activity. Mechanistically, CD38 upregulation was found to suppress SUOX expression, induce the reverse mode of mitochondrial complex V, and increase succinate dehydrogenase (SDH) activity along with ATP consumption. Paradoxically, despite ATP depletion, this metabolic disturbance enhanced glutamate metabolism and the tricarboxylic acid (TCA) cycle, sustaining EC proliferation under energetically stressed conditions. The combined effect of LATS1/2 deletion and CD38 activation established a unique EC phenotype defined by increased SAS, leading to proliferation, senescence, and eventual cell death. These pathological processes culminated in the formation of atherothrombotic plaques, which were attenuated by inhibition of CD38. Notably, a similar phenotype--marked by metabolically active ECs--was observed in human atherothrombotic plaques, suggesting translational relevance. ConclusionLoss of LATS1/2 in ECs induces SAS state that promotes excessive EC proliferation, senescent cell accumulation, and the development of structurally fragile, leaky neo vessels--hallmarks of atherothrombotic lesions. CD38-mediated SUOX deficiency further amplifies this pathological process by inducing mitochondrial dysfunction, depleting ATP, and triggering compensatory upregulation of glutamate and TCA cycle metabolism. These findings identify a novel LATS1/2-CD38-SUOX axis in ECs that orchestrates SAS-driven atherothrombosis. Targeting CD38 may represent a promising therapeutic strategy to mitigate vascular dysfunction and plaque instability in high-risk ACS patients. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=191 HEIGHT=200 SRC="FIGDIR/small/660635v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@149d313org.highwire.dtl.DTLVardef@1c0988borg.highwire.dtl.DTLVardef@15efec9org.highwire.dtl.DTLVardef@1a96e03_HPS_FORMAT_FIGEXP M_FIG C_FIG Under normal physiological conditions, LATS1/2 and Lamin A work together to suppress CD38 expression. Lamin A binds directly to the CD38 promoter to repress transcription, and LATS1/2 interact with Lamin A to reinforce this suppression. This collaboration helps maintain low CD38 activity and preserves cellular NAD levels. However, under disturbed flow (d-flow), both LATS1/2 and Lamin A are downregulated. The loss of this dual repression leads to increased CD38 NADase expression. Elevated CD38 accelerates NAD consumption, causing NAD depletion--a hallmark of cellular senescence. Reduced NAD disrupts key metabolic and stress-response pathways, contributing to the onset of the senescent state. At the same time, CD38 suppresses sulfite oxidase (SUOX), leading to sulfite accumulation and mitochondrial redox imbalance. This shift activates the reverse mode of mitochondrial Complex V, which decreases ATP production and increases mitochondrial ROS, intensifying metabolic and oxidative stress in endothelial cells (ECs). In response, ECs compensate by upregulating succinate dehydrogenase (SDH), enhancing TCA cycle activity and glutamate metabolism. This metabolic adaptation provides the biosynthetic building blocks needed for cell growth and proliferation. As a result, ECs adopt a paradoxical phenotype: they show classical features of stress-induced senescence (such as NAD depletion, oxidative stress, and cell cycle arrest signals), while simultaneously undergoing metabolic activation and proliferation, also mediated by YAP. This defines a non-canonical endothelial program known as senescence-associated stemness (SAS), characterized by the formation of abnormal, proliferative, yet fragile neovessels. These dysfunctional vessels contribute to atherothrombosis, setting this process apart from the more stable lesions typical of conventional atherosclerosis.

molecular biology↗

bioRxiv2025

OmicsSankey: Crossing Reduction of Sankey Diagram on Omics Data

In bioinformatics, Sankey diagrams have been widely used to elucidate complex biological insights by visualizing gene expression patterns, microbial community dynamics, and cellular interactions. However, computational scalability remains a challenge for large-scale biological networks. In this work, we present OmicsSankey, a novel formulation of the layout optimization problem for Sankey Diagrams that employs eigen decomposition as a closed-form solution, addressing graph disconnection through a teleportation mechanism that enhances connectivity and stabilizes eigenvector solutions. Experimental results on synthetic datasets with varying layers and nodes validate the efficacy of OmicsSankey compared to state-of-the-art layout-optimizers. Improving the Sankey layouts for Cell Layers, BioSankey, and Sequence Flow further validates OmicsSankey in enhancing the interpretability of biological insights.

bioinformatics↗

bioRxiv2025

Pattern and Precision: DNA-Based Mapping of Spatial Rules for T Cell Activation

The nanoscale spatial arrangement of T cell receptors (TCRs) ligands critically influences their activation potential in CD8+ T cells, yet a comprehensive understanding of the molecular landscape induced by engagement with native peptide-MHC class I (pMHC-I) remains incomplete. Using DNA origami as platform for multivalent engineering, we precisely organize pMHC-I molecules into defined spatial configurations to systematically investigate the roles of valency, inter-ligand spacing, geometric pattern, and molecular flexibility in regulating T cell function. We find that reducing inter-ligand spacing to [~]7.5 nm enhances T cell activation by up to eightfold compared to wider spacing ([~]22.5 nm), and that as few as six pMHC-I molecules are sufficient to elicit a robust response. Notably, the geometry of pMHC-I presentation emerges as a key determinant of signaling strength, with hexagonal arrangements proving most effective. In contrast, the introduction of flexible linkers into pMHC-I impairs TCR triggering. Together, these findings define spatial parameters that govern pMHC-I-TCR interactions at the T cell interface and provide design principles for engineering next-generation T cell-based immunotherapies.

bioengineering↗

bioRxiv2025

An Adaptive Visuomotor Transformation Reservoir Embedded in the Vertebrate Brain

Adaptive visuomotor transformation requires sensorimotor circuits to generate accurate, robust, and flexible outputs, but its underlying cellular mechanism remains poorly understood. Leveraging a zebrafish mesoscopic connectome, we built a biologically constrained spiking neural network of the optic tectum (OT), a conserved vertebrate center for visuomotor transformation, and drove the model with real retinal inputs. Integrating in silico and biological interrogations, we revealed that the OT functions as a biologically structured reservoir complemented by serotonergic systems to implement adaptive visuomotor transformation. Within the tectal reservoir, inhibitory interneurons with layer-matched axonal arborizations suppress task-unrelated pathways to ensure visuomotor accuracy, while excitatory interneurons with deep-layer terminating axons reinforce task-related pathways to enhance noise robustness. Furthermore, visually responsive OT-projecting serotonergic subsystems reweight competing pathways to confer visuomotor flexibility. Thus, our findings delineate how specific interneuron-type-embodied push-pull-like mechanisms coordinate with serotonergic neuromodulation to drive adaptive visuomotor transformation, offering a mechanistic framework for neural computational architectures.

neuroscience↗

bioRxiv2025

Highly accurate protein structure prediction-based virtual docking pipeline accelerating the identification of anti-schistosomal compounds

Schistosomiasis is a major neglected tropical disease that lacks an effective vaccine and faces increasing challenges from praziquantel resistance, underscoring the urgent need for novel therapeutics. Target-based drug discovery (TBDD) is a powerful strategy for drug development. In this study, we utilized AlphaFold to predict the structures of target proteins from Schistosoma mansoni and Schistosoma japonicum, followed by virtual molecular screening to identify potential inhibitors. Among 202 potential therapeutic targets, we identified 37 proteins with high-accuracy structural predictions suitable for molecular docking with 14,600 compounds. This screening yielded 268 candidate compounds, which were further evaluated in vitro for activity against both adult and juvenile S. mansoni and S. japonicum. Seven compounds exhibited strong anti-schistosomal activity, with HY-B2171A (Carubicin hydrochloride, CH) emerging as the most potent. CH was predicted to target the splicing factor U2AF65, and knockdown of its coding gene Smp_019690 resulted in a phenotype similar to CH treatment. RNA sequencing revealed that both CH treatment and Smp_019690 RNAi disrupted splicing events in the parasites. Further studies demonstrated that CH impairs parasite viability by inhibiting U2AF65 function in mRNA splicing regulation. By integrating RNAi-based target identification with structure-based virtual screening, alongside in vitro phenotypic and molecular analyses of compound-treated schistosomes, our study provides a comprehensive framework for anti-schistosomal drug discovery and identifies promising candidates for further preclinical development. Author SummarySchistosomiasis is a debilitating disease caused by parasitic worms and affects over 230 million people worldwide. For decades, control of the disease has relied on a single drug, praziquantel, which is less effective against juvenile parasites and increasingly threatened by the risk of drug resistance. To accelerate the discovery of new treatments, we integrated advanced computational tools with molecular validation. Using AlphaFold-predicted structures of 37 key schistosome proteins, we performed large-scale virtual screening to identify promising drug candidates. Over 200 compounds were prioritized for phenotypic screening on two major human-infective schistosome species, leading to the discovery of seven with potent anti-parasitic activity. Among them, Carubicin hydrochloride showed strong efficacy by targeting a critical splicing factor, U2AF65. Inhibiting this protein--either chemically or through gene silencing-- disrupted parasite movement, suppressed cell proliferation, and altered splicing events. Our work highlights the power of integrating AI-based protein modeling with phenotypic and mechanistic validation to accelerate drug discovery for neglected tropical diseases like schistosomiasis.

pathology↗

bioRxiv2025

Controlling Payload Heterogeneity in Lipid Nanoparticles for RNA-Based Therapeutics

Lipid nanoparticles (LNPs) are a leading platform for nucleic acid delivery, yet conventional assembly by mixing lipids with RNA yields particles with heterogeneous, bimodal payload distribution. Our transfection experiments demonstrate that heterogeneous siRNA distribution within LNPs significantly reduces gene knockdown efficiency. To systematically investigate the origin and extent of payload heterogeneity, we integrate coarse-grained molecular dynamics and kinetic Monte Carlo simulations with single-particle characterization via cylindrical illumination confocal spectroscopy and machine learning analysis. We find that the balance between RNA diffusion kinetics and lipid self-assembly dynamics is the dominant driver of payload heterogeneity. Leveraging this mechanistic insight, we show that (i) finely controlled turbulent mixing minimizes payload variance and increases the uniformity of RNA distribution without altering LNP size, and (ii) systematic adjustment of salt concentration and PEG-lipid content tunes RNA loading in a volume-dependent manner. Together, these results elucidate the self-assembly landscape of RNA-LNPs and provide actionable design principles for crafting more uniform, potent, and safer LNP-based nucleic acid therapies.

bioengineering↗

bioRxiv2025

ImmunoFusion: A Unified Platform for Investigating RNA-seq-Derived Gene Fusions in Cancer and Immunotherapy

BackgroundGene fusions play a critical role in cancer development by persistently activating kinases or inactivating tumor suppressor genes, leading to altered signal transduction and gene expression regulation. However, their impact on treatment responses remains poorly understood. Although existing cancer databases catalog numerous fusion events or immune checkpoint blockade (ICB) studies, no unified platform integrates gene fusion data across cancer types while linking them to the tumor microenvironment (TME) and patient outcomes. Such integration is essential for elucidating how fusions shape immune responses and for developing improved biomarkers for personalized cancer therapies. MethodsTo address this gap, we constructed the Fusion Immune Atlas (ImmunoFusion), a platform integrating data from TCGA, TARGET, CPTAC, and 29 ICB cohorts (including ICB treatments and other treatment modalities) across diverse cancer types. We identified fusion events from raw RNA-seq data using Arriba and STAR-Fusion, and standardized fusion calls by adapting MetaFusion to the GRCh38 reference genome. Additionally, we curated clinical data and estimated TME signatures and cell fractions using the Immuno-Oncology Biological Research (IOBR) approach. ImmunoFusion was developed using the high-quality Rhino framework for Shiny applications, built on R. ResultsImmunoFusion (https://shiny.zhoulab.ac.cn/ImmunoFusion) encompasses 21,014 clinical samples, serving as a comprehensive RNA-seq-derived gene fusion database and analytical tool. It offers functionalities to investigate fusion breakpoints, confidence scores, frequency patterns, and associations with clinical variables. The platform also enables TME evaluation and interactive exploration of fusions for analyzing tumor immunophenotypes in cancer and immunotherapy contexts. As an illustration, analysis of MTAP fusions in lung cancer cohorts revealed their association with a metabolically depleted, "cold" (immune-suppressive) tumor environment and poorer patient outcomes, pinpointing MTAP fusions as a novel biomarker for treatment selection. ConclusionsImmunoFusion represents a significant advancement, delivering a unified platform to explore the influence of gene fusions on cancer and immune responses. It offers particular value in understanding fusion-driven immunotherapy outcomes, paving the way for more effective therapeutic strategies.

bioinformatics↗

bioRxiv2025

OriGene: A Self-Evolving Virtual Disease Biologist Automating Therapeutic Target Discovery

Here, we present OriGene, a self-evolving multi-agent system that functions as a virtual disease biologist, systematically identifying original and mechanistically grounded therapeutic targets at scale. OriGenes architecture integrates over 600 specialized tools through a Model Context Protocol (MCP), enabling it to reason across diverse data modalities including genomics, protein networks, pharmacology, clinical records and literature evidence, to generate and prioritize target discovery hypotheses. We implemented a strategy combining a knowledge graph-based Tool RAG with an advanced agent selection mechanism to enable dynamic, context-aware tool deployment. Through a self-evolving framework, OriGene continuously integrates human and experimental feedback to iteratively refine its core thinking templates, tool composition, and analytical protocols, thereby enhancing both accuracy and adaptability over time. To comprehensively evaluate its performance, we established TRQA, an original benchmark comprising over 1,900 expert-level question-answer pairs spanning a wide range of diseases and target classes. OriGene consistently outperforms human experts, leading research agents, and state-of-the-art large language models in accuracy, recall, and robustness, particularly under conditions of data sparsity or noise. Critically, OriGene nominated previously underexplored therapeutic targets for liver (GPR160) and colorectal cancer (ARG2), which demonstrated significant anti-tumor activity in patient-derived organoid and tumor fragment models mirroring human clinical exposures. These findings demonstrate OriGenes potential as a scalable and adaptive platform for AI-driven discovery of mechanistically grounded therapeutic targets, offering a new paradigm to accelerate drug development.

bioinformatics↗

bioRxiv2025

Integrating Multimodal Data for a Comprehensive Knowledge Graph to Advance Infectious Disease Research

Infectious diseases remain a formidable threat to global public health, with their escalating morbidity and mortality rates compounded by recurrent epidemics and the alarming rise of antimicrobial resistance (AMR). These challenges have intensified the urgent demand for innovative therapeutic strategies that can accelerate drug development cycles and overcome traditional research bottlenecks. To address these critical needs, we present IDKG (Infectious Disease Knowledge Graph), a specialized large-scale biomedical knowledge network designed to bridge data fragmentation through multimodal data integration. The IDKG constructs comprehensive associations from 345 infectious diseases and 708 pathogens across heterogeneous biomedical sources systematically. The graph architecture comprises nearly 50,000 nodes (8 types, including Pathogen, Protein, etc.) and over 1.2 million edges (11 types, including treats, contains, etc.), establishing an interconnected framework that enables systematic interrogation of cross-disciplinary knowledge. The integrative approach effectively dismantles conventional data silos while preserving biological contextuality. We validated the IDKGs potential by applying graph neural network-based approaches for drug repurposing prediction in human metapneumovirus (hMPV) infection, a common acute respiratory infection for which effective specific antiviral drugs are currently absent. The successfully identification of established antiviral agents, such as ribavirin and emetine, by our M1 model demonstrated its predictive accuracy and biological relevance. IDKG unifies multimodal biomedical data into a network to accelerate drug discovery and bolster outbreak response. This establishes a data-driven, knowledge-based paradigm for infectious disease research. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=163 SRC="FIGDIR/small/657361v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@f5dc24org.highwire.dtl.DTLVardef@147d584org.highwire.dtl.DTLVardef@113083corg.highwire.dtl.DTLVardef@81d523_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

Contrastive Learning-Enhanced Drug Metabolite Prediction Drives the Discovery of an Orally Bioavailable RSK4 Inhibitor for Esophageal Cancer

Drug metabolism liabilities are a major bottleneck in drug development, necessitating accurate metabolite prediction tools. While AI-driven methods have advanced, challenges remain in achieving high-precision, robustness, broad reaction coverage and seamless integration into the drug development workflow. To address this, we first constructed the most comprehensive human-specific drug metabolism database to date, encompassing 11,665 human metabolic reactions and 2,497 high-quality rules. Leveraging this resource, we developed ConMeter (Contrastive learning and feature interaction based Metabolic Reaction prediction), a novel model integrating chemical feature interaction and contrastive learning. ConMeter demonstrates significant improvements, achieving [~]80% accuracy in identifying at least one metabolite within the top 5 predictions and showing an average 25% relative enhancement in ranking true positives compared to state-of-the-art methods. The comprehensive database also expands the range of predictable metabolic reactions. To demonstrate the utility of ConMeter, we integrated it into a metabolite prediction-guided drug design strategy aimed at addressing the low oral bioavailability of a metabolically vulnerable RSK4 lead compound -- a pervasive issue among known RSK inhibitors. This strategy successfully yielded R636, a novel RSK4 inhibitor exhibiting remarkably improved bioavailability (a 63-fold increase, reaching 63% absolute bioavailability) while maintaining its potent activity. Notably, R636 showed favorable safety profile and significant anti-tumor efficacy against esophageal squamous cell carcinoma (ESCC) in vitro and in two distinct patient-derived xenograft (PDX) mouse models. This work introduces ConMeter as a powerful and practical tool for high-accuracy metabolite prediction, demonstrating its potential to accelerate lead optimization, exemplified by the discovery of R636 as a promising orally bioavailable candidate for ESCC.

cancer biology↗

bioRxiv2025

Mechanical force-mediated cellular crosstalk maintains the integrity of the lung gas exchange niche

Respiratory motion imposes a constant mechanical strain that has important but poorly defined impact on tissue niches in the lung. We developed a reversible bronchial ligation model to induce and reverse unilateral blockade of lung mechanical motion in vivo and show that this leads to transcriptomic changes in multiple cell lineages that are not normalized upon reinitiation of respiratory motion. Perturbation of mechanosignaling specifically in alveolar epithelial type I (AT1) cells alters the transcriptomic state and fate of their niche neighbors, demonstrating that AT1 cells act as a node that propagates a mechanical cascade throughout the lung alveolus. Mechanically perturbed AT1 cells induce a distinct capillary endothelial cell state that persists after reactivation of respiratory motion, which is mediated by an integrin/TGF-{beta} network within the alveolus that is vulnerable to pharmacological intervention. Importantly, AT1 mechanosignaling and intercellular communication are altered in chronic human lung diseases, highlighting the critical role of an AT1-driven mechanosensing network in lung disease biology. Thus, mechanosensing cells propagate biophysical signals that regulate tissue function and program tissue responses in disease.

cell biology↗