Biology subjects

Liu, X.

Publications and source records attributed to Liu, X..

At least 163 records · Page 9Linked to original sources

bioRxiv2026

Monocytes shape the neuroprotective and immunomodulatory effects of mesenchymal stromal cell-derived extracellular vesicles

BACKGROUNDMesenchymal stromal cell-derived extracellular vesicles (MSC-EVs) exert neuroprotective effects in ischemic stroke largely through immunomodulatory mechanisms. Monocytes are first-line responders to MSC-EVs. Their contribution to MSC-EV-induced neuroprotection remains poorly understood. This study investigated the role of monocytes in shaping neuroprotective responses to MSC-EVs after ischemic stroke. METHODSMale C57BL/6J mice were exposed to transient middle cerebral artery occlusion (MCAO). Monocytes were depleted using pharmacological (clodronate liposomes), immunological (anti-CCR2), or genetic (Mrp8-Cre+/- Nr4a1fl/fl) approaches removing total, CCR2+, or Ly6Clow monocytes, respectively. In additional cohorts, neutrophils and T cells were simultaneously depleted by anti-Ly6G or anti-CD4/CD8 antibodies. Small EVs from clonally expanded immortalized MSCs were administered intravenously. Neurological deficits, ischemic injury, and immune responses were analyzed up to 72 hours post-MCAO. Complementary ex vivo studies were performed, in which MSC-EVs were administered to monocyte-depleted or non-depleted peripheral blood mononuclear cells (PBMCs) obtained from acute ischemic stroke patients. RESULTSIn ischemic mice with intact monocyte compartment, MSC-EVs reduced neurological deficits, infarct volume, neuronal injury, and brain leukocyte infiltrates. These protective effects were abolished in monocyte-depleted mice, particularly following CCR2+ monocyte depletion. Under these conditions, MSC-EV treatment exacerbated neurological deficits, ischemic injury, and leukocyte infiltration, accompanied by neutrophil and T cell expansion and overactivation. Depletion of neutrophils or T cells prevented the EV-induced worsening of stroke outcome in monocyte-deficient mice. Ly6Clow monocytes played a crucial role in orchestrating immune responses to MSC-EVs. Their depletion abolished EV-induced neuroprotection. In stroke patient PBMCs, MSC-EVs induced phenotypic reprogramming of monocytes, whereas they promoted CD4+ and CD8+ T cell activation in the absence of monocytes. CONCLUSIONSMonocytes shape the immunomodulatory actions of MSC-EVs. In their absence, MSC-EVs trigger neutrophil and T cell overactivation that worsens stroke outcome. These findings highlight the importance of monocyte- and T cell-related potency assays for the clinical translation of MSC-EV therapies.

neuroscience↗

bioRxiv2026

Metal Coordination Dynamics Governs Selective Epoxidation in Hyoscyamine 6β-Hydroxylase: Integrated Experimental and Computational Insights

Iron(II)- and 2-oxoglutarate-dependent (Fe(II)/2OG) enzymes catalyze a wide range of C-H bond activation and functionalization reactions and play essential roles in biosynthesis and metabolic regulation. Despite extensive mechanistic studies, the principles governing selectivity between canonical hydroxylation and alternative transformations remain incompletely understood. Here, we investigate the catalytic mechanism of hyoscyamine 6{beta}-hydroxylase (H6H), a Fe(II)/2OG-dependent oxygenase that sequentially catalyzes the 6{beta}-hydroxylation of hyoscyamine followed by 6,7-exo-epoxidation of 6{beta}-hydroxyhyoscyamine to generate scopolamine. Combined molecular dynamics and QM/MM calculations reveal that an inline Fe(IV)-oxo intermediate initiates hydrogen atom abstraction from the substrate C7 position. The resulting Fe(III)-OH species subsequently deprotonates the substrate hydroxyl group in a process coupled to substrate coordination to the iron center and an in-line-to-off-line rearrangement of the Fe(III)-OH moiety. This coordination dynamics machinery is further supported by the observed chlorination reactivity on the same substrate. Importantly, this coordination switch favors epoxide formation over hydroxyl rebound, thereby directing the reaction toward selective epoxidation. Further computational analysis of the L290F variant demonstrates that steric constraints imposed by L290 are essential for suppressing hydroxylation, revealing a bidirectional regulatory mechanism governing epoxidation/hydroxylation selectivity. Whereas iron coordination dynamics promote epoxidation reactivity, precise substrate positioning and protein-derived steric effects suppress the competing hydroxylation pathway. These findings are consistent with available experimental observations and establish metal coordination dynamics as a key determinant of selective C-H functionalization in Fe(II)/2OG enzymes.

biochemistry↗

bioRxiv2026

FAP-intrinsic Hedgehog signaling controls intramuscular adipogenesis, fibrosis, and myofiber regeneration

Fibro/adipogenic progenitors (FAPs) are multipotent stromal cells that support myofiber regeneration, but can also give rise to intramuscular adipose tissue (IMAT) and fibrotic scar tissue. While the Hedgehog pathway suppresses FAP adipogenesis and promotes myofiber repair through ligand Desert Hedgehog, the key cell type that senses this signal has remained unclear. Here, we demonstrate through FAP-specific deletion of the Hedgehog signal transducer Smoothened that FAPs are the primary Hedgehog-responding cells during muscle regeneration. Loss of Smoothened in FAPs increases IMAT, causes persistent fibrosis, reduces the Hedgehog-dependent effectors TIMP3 and GDF10, and impairs myofiber regeneration. FAPs lacking Smoothened also fail to support in vitro myoblast differentiation and fusion as efficiently as control FAPs, showing that Hedgehog signaling helps establish a pro-myogenic FAP state early after injury. Pharmacological Hedgehog activation via the Smoothened agonist SAG fails to rescue adipocyte accumulation or myofiber regeneration when FAPs lack Smoothened. Together, these findings provide direct genetic evidence that FAPs are the primary cellular mediators of Hedgehog signaling in muscle and establish FAP Hedgehog signaling competence as a key determinant of regenerative outcome and a target for restoring muscle repair in disease.

developmental biology↗

bioRxiv2026

A Human Vocal Fold Organ-On-Chip for Studying Platform-Dependent Mucosal Responses to Particulate Matter

BackgroundCoarse particulate matter (PM10) deposits at the vocal fold (VF) mucosa, yet upper airway responses remain poorly characterized. Existing in vitro VF models use monocultures that lack the stratified epithelium, lamina propria, and physiological perfusion. We developed a chip-based co-culture model of human VF mucosa and applied it to acute PM10 exposure. MethodsVocal fold organ-on-chip (VF-OOC) paired primary VF fibroblasts with either immortalized laryngeal epithelial cells (iLEC) or induced pluripotent stem cells (iPSC)-derived VF epithelial cells. Transwell and 2D chip cultures were controls. Epithelia matured at an air-liquid interface on fibroblast-embedded collagen over a perfused microchannel. PM10 urban dust (0 to 400 {micro}g/mL) was applied for 24 hours. Responses were assessed by histology, immunofluorescence, transmission electron microscopy, qPCR, and ELISA. ResultsVF-OOC produced a thicker stratified epithelium with upregulated barrier, mucin, and extracellular matrix genes versus transwell controls. Intercellular junctions and basement membrane matched adult human VF mucosa. PM10 remained at the epithelial surface across all doses. TranswelliLEC downregulated basal markers (TP63, KRT5, KRT14). VF-OOCiLEC upregulated MUC1 and HAS3, consistent with an adaptive mucosal response. VF-OOCiPSC additionally induced suprabasal, junctional, extracellular matrix, and cytokine genes largely absent in iLEC and transwell formats. ConclusionsVF-OOC reproduced key features of native human VF mucosa and captured distinct, platform-specific responses to PM10 that differed by epithelial cell source. By introducing new approach methodologies (NAMs) into laryngology, this platform extends respiratory toxicology to the upper airway beyond bronchial and alveolar compartments and allows mechanistic studies of exposure-linked diseases such as laryngitis.

cell biology↗

bioRxiv2026

Divergent Inclusion Body Structures and Stabilities Emerge from Native Monomer Properties

Protein aggregation is of broad importance in biotechnology and disease, yet the structural heterogeneity of cellular aggregates has confounded high-resolution structural analysis. Inclusion bodies (IBs) formed in Escherichia coli are an attractive, controllable system for unravelling the complexities of protein aggregation in a cellular context. Here, a multimodal analysis integrating residue-resolved quenched amide hydrogen-deuterium exchange (qHDX), proteolysis, FTIR, Congo red binding, and chemical denaturation is applied to IBs formed by proteins encompassing stable {beta}- and -globular folds, a partially structured protein fragment, and intrinsically disordered low complexity domains (LCDs). Remarkable conformational diversity is observed: IBs formed by well-folded proteins are extensively structured and include substantial local native-like features, whereas proteins with decreased access to stable native conformations form more heterogeneous and dynamic aggregates increasingly shaped by intrinsic sequence features. Strikingly, qHDX protection of TDP-43 LCD IBs strongly aligns with the core of cryo-EM structures of ex vivo pathological fibrils; however, peripheral regions that appear fully hydrogen-bonded in the cryo-EM structures exhibit little protection. The results reveal that individual protein IBs contain distinct mixtures of native-like, disordered, and amyloid-like conformers, informing the prediction and control of cellular aggregate structure and stability. Entry for the Table of Contents O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=192 SRC="FIGDIR/small/729379v2_ufig1.gif" ALT="Figure 1"> View larger version (56K): org.highwire.dtl.DTLVardef@1542626org.highwire.dtl.DTLVardef@194ad5forg.highwire.dtl.DTLVardef@26c13org.highwire.dtl.DTLVardef@1055573_HPS_FORMAT_FIGEXP M_FIG Inclusion body conformational heterogeneity. Left: aggregates retaining local native-like structure. Middle: assemblies populated by -helical intermediates coexisting with antiparallel -sheet oligomers. Right: initially disordered states undergo helix-helix interactions and progress towards -sheet-rich conformations, illustrating distinct routes of cellular aggregation. C_FIG

biochemistry↗

bioRxiv2026

Alignment-free phylogenetic inference via hyperbolic protein language models

Conventional phylogenetic methods rely on multiple sequence alignments which are computationally intensive and often fail for highly divergent lineages. Here, we introduce LucaPhylo, an alignment-free framework that infers evolutionary relationships directly from unaligned sequences. Through a cascaded learning strategy LucaPhylo integrates protein language models with hyperbolic geometry, a representation space naturally suited to hierarchical branching, to capture deep evolutionary constraints without explicit homology matching. Using highly divergent RNA virosphere as a test case, LucaPhylo places unaligned sequences into phylogenetic trees with an accuracy comparable to leading alignment-based tree construction tools, while retaining divergent sequences that conventional pipelines frequently discard. It further enables the integration of divergent viral lineages into phylogenetic trees, thereby expanding the evolutionary landscape of RNA viruses. Together, LucaPhylo establishes an AI-driven, alignment-free paradigm for phylogenetic inference and provides a robust computational foundation for resolving deep evolutionary relationships among RNA viruses and other biological systems.

evolutionary biology↗

bioRxiv2026

STID: A Standardized Spatial Transcriptomic Analysis Framework for Infectious Diseases

Spatial transcriptomic studies of infectious diseases still rely on fragmented data analysis processes. Here, we developed STID, a standardized framework for spatial transcriptomic analysis of infectious diseases that leverages the Seurat ecosystem and incorporates Python-based modules. STID provides an extensible infection-specific data structure and supports a full suite of analyses, such as pathogen background correction, infection-associated spot and niche identification, single-sample niche characterization, and multi-sample comparative and temporal analyses. Moreover, STID is broadly applicable to spatial transcriptomic data from infectious diseases caused by bacteria, viruses, and parasites, and enables systematic characterization of the structural features, cellular composition, molecular functions, and host-pathogen interactions within pathogen-infected and/or host-responsive niches. Overall, STID provides an accessible, reproducible, and extensible framework for analyzing infection-associated spatial transcriptomic data and for dissecting host-pathogen interactions in their native spatial microenvironments. MotivationSpatial transcriptomics technologies have emerged as powerful approaches for dissecting the structural and functional features of spatial microenvironments. However, the current general-purpose tools remain fundamentally inadequate for resolving the spatial heterogeneity of infectious disease samples, where the intricacies of host-pathogen interactions render spatial microenvironments both challenging to dissect and largely inaccessible. Tools tailored to infectious diseases are critically lacking, including those for reducing pathogen-derived background noise, identifying and isolating infection{square}associated spots or niches, dissecting host-pathogen interactions, and supporting systematic multi-sample analyses. We therefore developed STID, a unified framework that integrates standardized workflows and addresses the analytical bottlenecks in spatial transcriptomic analysis of infectious diseases. HighlightsO_LISTID standardizes spatial transcriptomic analysis in infectious diseases C_LIO_LISTID improves pathogen-infected spot detection by correcting pathogen background C_LIO_LISTID distinguishes pathogen-infected and host-responsive niches C_LIO_LISTID supports multi-sample comparative and temporal analyses of niches C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=194 SRC="FIGDIR/small/727492v1_ufig1.gif" ALT="Figure 1"> View larger version (75K): org.highwire.dtl.DTLVardef@167d351org.highwire.dtl.DTLVardef@1628848org.highwire.dtl.DTLVardef@1e157aforg.highwire.dtl.DTLVardef@143ca1b_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2026

Trait dissimilarity-based tree species loss affects tree diversity effects on herbivory

O_LIBiodiversity loss can alter interactions not only through changes in tree species richness, but also through the loss of particular functional strategies from ecological communities. Working in a subtropical forest diversity experiment we asked whether tree species richness effects on arthropod herbivory and leaf pathogen infestation depend on community functional diversity, and whether trait dissimilarity-based, non-random species loss alters these relationships compared to random loss. To address this, we combined already established planted scenarios with newly constructed extinction pathways. C_LIO_LIWe tested the responses of herbivory and leaf pathogen infestation (i) to tree species richness, functional diversity (Raos Q), community structure and resource strategies (i.e. ever-greenness) and community-weighted trait means as well as predation, and (ii) trait dissimilarity-based extinction pathway analyses that contrasted directed loss of functionally similar versus functionally distinct tree species. C_LIO_LIHerbivory increased with tree species richness and this increase was significantly stronger in communities with higher tree functional diversity. Under directed species loss scenarios, herbivory differed most strongly from random-loss expectations when similar tree species were lost first. By contrast, losing functionally distinct species first produced richness effects that were much closer to the random-loss scenarios. Trait-based species loss will therefore modify trophic interactions more strongly than random loss. For pathogen infestation tree richness effects depended on evergreenness and among planted extinction scenarios (three-way interaction), with only minor deviations of trait-based extinction path-ways from random-loss expectations. Pathogen infestation also tended to increase with community-weighted mean leaf nitrogen. Predation showed no clear relationship with tree species richness or functional diversity but was positively associated with herbivory. The strength of this association differed among extinction scenarios, providing no evidence for consistent top-down regulation. C_LI SynthesisThe ecological consequences of biodiversity loss for leaf damage depend on which functional strategies are lost, not only on how many tree species remain. By integrating ob-served tree diversity gradients with trait-based extinction pathways, this study shows that functional diversity and host redundancy help explain why herbivores and pathogens are shaped by the same changes in tree diversity through different functional constraints and im-prove predictions of interaction strength under non-random species loss.

ecology↗

bioRxiv2026

A Cross-tissue Temporal Multi-omics Atlas Reveals the Molecular Architecture of Pressure Injury

Pressure injury induces progressive necrosis of skin and deep muscle, yet how mechanical loading reshapes molecular programs across tissues and time remains poorly defined. To address this gap, we established a rat pressure-injury model and performed longitudinal integrated profiling of skin and deep muscle across four stages, combining transcriptomics, proteomics and untargeted metabolomics with histological assessment. This multi-layered atlas revealed a staged injury program dominated by early transcriptional activation of innate immunity and complement-coagulation crosstalk, accompanied by neutrophil-associated responses and engagement of upstream regulatory networks. As injury advanced, a second axis of remodeling emerged, characterized by sustained suppression of mitochondrial energy metabolism and oxidative phosphorylation, particularly in muscle, together with extracellular matrix and adhesion rewiring. In parallel, skin preferentially activated barrier-repair and protein-homeostasis programs, including keratinization and autophagy-linked processes, indicating tissue-specific adaptation to the same mechanical insult. Temporal clustering and pathway-network analysis further showed that immune activation and metabolic collapse are not independent events but are dynamically coupled across stages, with muscle exhibiting broader molecular reprogramming and a stronger shift toward irreversible structural failure. Together, these data define a cross-tissue, stage-resolved molecular framework for pressure injury progression and identify pathway-level windows that may inform tissue-targeted and stage-specific intervention strategies.

systems biology↗

bioRxiv2026

dbGIST: An LLM-Assisted Multi-Omics Resource for Target Exploration and Cross-Dataset Validation in Gastrointestinal Stromal Tumors

Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal neoplasms of the gastrointestinal tract, yet GIST-specific omics evidence remains scattered across small cohorts and is not represented as a dedicated disease project in major cancer genomics resources, limiting reproducible target exploration. Here, we present dbGIST (https://www.dbgist.com), a dedicated GIST-focused multi-omics resource built to make dispersed GIST evidence searchable, analyzable, and reusable. dbGIST harmonizes data from 37 centers and 1,991 samples, including pathologically verified in-house cohorts, across genomics, bulk transcriptomics, proteomics, phosphoproteomics, and single-cell transcriptomics, and couples these data with curated clinical annotations covering survival, mutation status, risk stratification, metastasis or recurrence, mitotic index, tumor site and size, and imatinib response. The platform supports cohort-level molecular-clinical association, survival, enrichment, immune-infiltration, drug-sensitivity, and single-cell analyses through interactive visualizations, downloadable source data, and public APIs for programmatic access to reusable analysis outputs and visualization-ready data. An optional LLM-assisted interface helps users navigate analyses and interpret outputs. Using MCM7 as a case study, dbGIST linked a resource-derived candidate to survival, risk features, metastatic or recurrent disease, imatinib-response phenotypes, proliferative cell states, and in vitro GIST-cell behavior. dbGIST therefore provides a traceable and interoperable resource for target exploration and precision oncology research in GIST.

cancer biology↗

bioRxiv2026

Genos-m: a foundation model for human-associated microbial genomes

Human-associated microbial genomes encode extensive strain-level diversity and niche-specific gene repertoires that are critical to host health. However, these complex sequence features remain difficult to capture using general-purpose DNA foundation models, highlighting the need for dedicated representation learning tailored to the human microbiome. Here, we introduce Genos-m, an open-source foundation model for human-associated microbial genome representation. Genos-m was pretrained on approximately 1.2 trillion nucleotide tokens from a curated microbial genome corpus, including human-associated prokaryotic isolates, high-quality metagenome-assembled genomes (MAGs) and bacteriophages, supplemented with GTDB species-level representative genomes to broaden prokaryotic taxonomic breadth. The model uses a sparsely activated Mixture-of-Experts (MoE) Transformer architecture, with 4.7 billion total parameters, approximately 330 million activated parameters per forward pass and a maximum context length of one million base pairs. We evaluated frozen Genos-m representations across short-sequence and gene-level tasks, biosynthetic gene cluster (BGC)-based regional sequence tasks, whole-genome strain phenotype prediction, and zero-shot transfer on prokaryote-related RNAfitness assays. Across these benchmarks, Genos-m consistently ranked among the leading comparison models, with the best performance in five of eight gene-fitness regression tasks and in BGC type classification. Using sparse autoencoders, we identified sparse features in Genos-m hidden activations that aligned with annotated ORFs, intergenic regions, and tRNA and rRNA loci. In downstream applications, Genos-m-derived genome-informed species representations in-corporated into a human microbiome self-supervised learning model improved colorectal cancer (CRC)-control classification over conventional species-abundance random forest models. Genos-m also generated stable sample-level embeddings from as few as 10,000 metagenomic reads, retaining gut microbial community structure that distinguished geographic origin and aligned with enterotypes defined from full-depth taxonomic profiles. Together, these results support Genos-m as a reusable representation model for microbial genomes and metagenomes, with conclusions bounded by the reported datasets, task definitions and evaluation protocols. Genos-m model weights, inference code, and usage documentation are publicly available on GitHub (https://github.com/BGI-HangzhouAI/Genos-m) and Hugging-Face (https://huggingface.co/BGI-HangzhouAI/Genos-m).

bioinformatics↗

bioRxiv2026

Decoding Immune Reconstitution Failure in People Living with HIV through Single-cell Genomics

Immune non-responders (INRs), a subset of people living with HIV (PLWH), fail to achieve full immune reconstitution and remain at increased risk of morbidity, mortality, and non-AIDS-related illnesses. As the mechanisms underlying this impaired immune recovery remain poorly understood, we performed single-cell multi-omics profiling on peripheral blood mononuclear cells from 43 INRs, 47 immune responders and 53 healthy donors. Our dataset comprises 2,744,009 transcriptomes and 1,226,658 chromatin-accessibility profiles across 58 identified immune cell types. INRs exhibited markedly elevated inflammatory signaling, increased apoptotic activity, and dysregulation of immune-activating ligand-receptor interactions. Additionally, we identified 2,996 interaction cis-eGenes and 5,938 cis-caPeaks, and validated key cell type-specific cis-xQTL effects associated with immune reconstitution failure. Furthermore, we identified 3,551 sc-eQTLs and 872 cell-state interaction eQTLs (ieQTLs) in CD4+ T cells. A genotype-specific upregulation of OAS3 in INRs, likely regulated by STAT1, was identified based on these results. We developed scPRISM (single cell Predictive Reconstitution Immune Status Model), a multi-modal framework that integrates scRNA-seq and scATAC-seq data to perform the dual tasks of differentiating disease states and predicting gene expression from chromatin accessibility, thereby deciphering the cell type-specific cis-regulatory basis of the disease. Our study delineates the transcriptional and epigenomic landscape of immune dysregulation in INRs and provides new genetic insights into HIV-associated immune reconstitution failure. These findings offer a foundation for developing biomarkers and precision therapies to restore immune function in PLWH.

genetics↗

bioRxiv2026

Cavity-nesting bees combine forest nesting habitats with surrounding floral resources in a subtropical forest diversity experiment

Wild bees face declines, and forests may serve as critical habitats for pollinators. However, how forest composition and the associated floral environment shape pollen provisioning and resource partitioning among cavity-nesting bees remains poorly understood. Here, we leveraged BEF-China, a large-scale subtropical forest biodiversity experiment with experimentally controlled plant (tree and shrub) communities, to investigate how forest composition and spatial context shape pollen provisioning, resource partitioning, and reproductive success of cavity-nesting bees. We used DNA metabarcoding to analyze floral composition of pollen provisioned by five cavity-nesting bee species, with samples collected from BEF-China across three years (2022- 2024). By comparing pollen taxonomic composition from whole-nest pooled samples and individual brood-cell samples with the experimentally planted species pool, we characterized dietary patterns and temporal dynamics of five bee species. Bees primarily relied on floral resources from the surrounding landscape, with planted trees providing essential but temporally restricted pollen supplements during specific phenological stages. Co-occurring bee species exhibited staggered nesting phenology and distinct dietary preferences for different plant families, with fine-scale resource differentiation even during periods of phenological overlap. Our results suggest that managed forests support cavity-nesting bees by providing critical woody floral resources during specific phenological gaps and offering stable nesting environments. To mitigate pollinator declines, forest management should prioritize maintaining diverse, phenologically complementary flowering vegetation within and surrounding forest stands. This ensures temporal continuity of pollen availability throughout the nesting season, which is particularly crucial for restoring pollinator services in simplified forest landscapes.

ecology↗

bioRxiv2026

Hierarchical Immune Suppressive Functions of Regulatory T Cells Built on Mechanical Force

Regulatory T (Treg) cells maintain immune tolerance via contact-dependent inhibition and soluble mediators. While canonical suppressive mechanisms are well characterized, their hierarchical spatiotemporal organization remains unclear. We previously showed Foxp3 represses ER Ca2+ channel RyR2, reducing cytoplasmic Ca2+ to inactivate m-Calpain (Calpain-2) and stabilize high-affinity LFA-1-mediated Treg-dendritic cell (DC) adhesion--an early step blocking DC antigen presentation. Using m-Calpain as a molecular switch, we generated mechanically deficient Tregs (TregFD) with constitutively active m-Calpain that abrogated high-force Treg-DC adhesion. TregFD retained a near-wild-type transcriptome (differential expression limited to adhesion pathways), yet failed to suppress autoimmunity or DC-driven T cell proliferation. Stable adhesion was required for localized TGF-{beta}/IL-10 delivery to DCs. Single-cell RNA sequencing of rescued Scurfy mouse lymphoid tissues revealed organ-specific division of labor: non-mechanical modules support homeostasis/tissue repair, while mechanical modules dominate epithelial barrier/antigen presentation suppression. Combined TregFD and RyR2-deficient Tconv transfer restored wild-type Treg activity, demonstrating module synergism. These findings establish a mechanical force-centered, two-tiered hierarchical model of Treg suppression, providing a framework for targeting Treg mechanics in autoimmunity and inflammation.

immunology↗

bioRxiv2026

Cortical vasodynamics exhibit multiscale propagation structure in the awake mouse

Spontaneous vasomotor rhythms and fluctuations are recognized contributors to functional MRI (fMRI) signals. Yet the spatial evolution of vasomotor contributions, which bear on the interpretation of fMRI signals in terms of functionally connected brain regions, remains unresolved. To clarify this issue, we analyze the 0.01 - 0.20 Hz space-frequency modes of 14T cerebral blood volume (CBV)-weighted fMRI across the awake mouse cortex. High-resolution CBV-fMRI identified single-vessel-aligned, frequency-specific modes of vasodynamic propagation, and ultra-fast CBV-fMRI enabled mapping of phase-gradients along tangential and radial axes. Tangential gradients extended maps of vasomotor traveling waves across the entire cortical mantle, with a median speed of 0.9 - 1.3 mm/s. Radial gradients revealed approximately three-fold slower changes in timing that support lamina-dependent regulation of perfusion. Region-specific differences in propagation speed and direction occur across cortical areas and between mice. These findings reframe vascular fluctuations as a feature of brain-wide physiology, as opposed to residual noise.

neuroscience↗

bioRxiv2026

A targetable opioid/cancer associated fibroblast axis drives extracellular matrix remodeling and tumor aggressiveness in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is an intractable disease with few effective treatment options. PDAC is characterized by a dense, fibro-inflammatory tumor microenvironment (TME) consisting mainly of cancer-associated fibroblasts (CAFs) and a CAF-generated collagen-rich extracellular matrix (ECM). As the ECM has profound impacts on tumor progression and therapy response, it is critical that we understand the mechanisms underlying ECM deposition and remodeling. In addition to a highly fibrotic and reactive TME, a hallmark of PDAC is pain. 93% of PDAC patients experience pain, and [~]70% are prescribed opioids for pain management during the course of their cancer treatment. Despite epidemiological evidence linking opioid use with diminished patient survival, how opioids impact tumor biology remains largely unknown. We now provide evidence that both endogenous and exogenous opioids drive ECM remodeling in the PDAC TME. We find that the commonly prescribed opioid morphine promotes the development of poorly differentiated tumors and increases collagen bundling and maturation in a mouse model of PDAC. Accordingly, RNA sequencing reveals that morphine induces significant upregulation of ECM genes and collagen modifying enzymes. We developed a morphine-induced gene signature which correlates significantly with the basal/mesenchymal subtypes of human PDAC and predicts worse overall survival in PDAC and other tumor types. Mechanistically, pharmacological inhibition and genetic knockdown of the mu opioid receptor (OPRM1) in CAFs attenuates expression of type 1a and type 3a collagens, and the myofibroblastic CAF marker alpha-SMA, demonstrating that opioid signaling is a direct regulator of CAF biology. Additionally, we provide the first evidence that CAFs produce endogenous opioids capable of activating OPRM1 and driving collagen expression. Finally, treatment with the FDA-approved peripherally restricted OPRM1 antagonist methylnaltrexone (MNTX) reduces desmoplasia, tumor weight, and ascites burden in a mouse model of PDAC. Therefore, we have identified a novel opioid-mediated signaling axis driving PDAC desmoplasia and reveal MNTX as a potential therapeutic to inhibit both exogenous and endogenous opioid-induced ECM remodeling and tumor aggressiveness.

cancer biology↗

bioRxiv2026

Force-Gated Thrombosis (FGT): A Non-Equilibrium Mechanical Theory of Shear-Induced Blood Clot Initiation

Arterial thrombosis is initiated when mechanical forces in flowing blood exceed the activation thresholds of platelets and von Willebrand factor (vWF). Despite extensive experimental characterization of shear-induced platelet aggregation, a unified theoretical framework that maps hemodynamic forcing onto clot nucleation is lacking. Here we present Force-Gated Thrombosis (FGT), a non-equilibrium mechanical theory that treats thrombus formation as a continuous phase transition driven by an effective mechanical forcing {Sigma} ={sigma} + |{nabla}{sigma}| + {beta}{varepsilon}, which combines local wall shear stress{sigma} , shear gradient |{nabla}{sigma}|, and extensional strain rate{varepsilon} . We introduce a dimensionless Thrombosis Number {Theta} = ({Sigma}/{Sigma}c)(P/P0)m(C/C0)n, which incorporates platelet concentration P and coagulation factor concentration C, and governs the transition between stable flow ({Theta} < 1) and active clot growth ({Theta} > 1). The thrombus density is represented by a scalar order parameter{varphi} whose dynamics follow a Ginzburg- Landau free energy functional. For a simplified stenosed artery we derive an analytic closed-form thrombosis onset criterion and a critical flow rate [Formula], where{delta} is stenosis severity. Linear stability analysis shows that perturbations grow at rate{omega} (k) = {Lambda}({Theta}) - D{varphi}k2, becoming unstable when {Theta} > 1. Near threshold the clot volume fraction scales as{varphi} [~] ({Theta} - 1)1/2, a mean-field critical exponent consistent with Ginzburg- Landau theory. Systematic comparison with fifteen published experimental and computational datasets spanning shear rates from 100 to 15,000 s-1 confirms that FGT correctly predicts the existence, location, and approximate severity of pathological thrombus formation across diverse vascular geometries. The theory provides a quantitative bridge between single-molecule mechanobiology and macroscale clinical thrombosis, and yields experimentally testable predictions distinguishing FGT from purely biochemical models.

biophysics↗

bioRxiv2026

TRMT6/61A-mediated m1A methylation facilitates human pre-tRNA maturation and prevents surveillance by XRN2

Transfer RNAs (tRNAs) are dynamically regulated by RNA modifications. The conserved TRMT6/61A catalyzes m1A (N1-methyladenosine) deposition at position 58. While TRMT6/61A dysregulation is linked to human diseases, its downstream processing consequences and molecular surveillance mechanisms remain unclear. Here we demonstrate that TRMT6/61A installs m1 A on precursor tRNAs prior to processing. Utilizing a dTAG rapid depletion system, we show that acute loss of TRMT6/61A swiftly reprograms the human tRNAome. Although elongator tRNA fluctuations are buffered by isodecoder redundancy, hypomethylated tRNAiMet is selectively and rapidly degraded by the exoribonuclease XRN2, reducing global protein synthesis and activating ATF4 expression. Furthermore, m1A58 is a prerequisite for tRNA end processing; its absence leads to the aberrant accumulation of unprocessed pre-tRNAs and disrupted tRNA-derived fragment (tRF) populations. Mechanistically, TRMT6/61A facilitates in vitro RNase Z cleavage, likely by promoting proper pre-tRNA folding. Lastly, XRN2 inhibition rescues tRNAiMet levels and reverses growth defects, identifying the XRN2-mediated surveillance of tRNAiMet as a primary driver of the cellular pathology. Collectively, our results uncover a pivotal role for TRMT6/61A-dependent m1A in human tRNA maturation and define the molecular checkpoints essential for translational homeostasis.

genetics↗