Biology subjects

Gao, B.

Publications and source records attributed to Gao, B..

At least 19 recordsLinked to original sources

bioRxiv2026

Autonomic and neurotrophic signaling in alcohol-associated liver disease

Alcohol-associated liver disease (ALD) is a leading cause of liver-related morbidity and mortality, yet its pathogenesis remains incompletely understood. While neural regulation is critical for hepatic homeostasis, how autonomic and neurotrophic signaling is regulated in the liver during ALD progression remains largely unexplored. Here, we performed an integrative analysis of bulk and single-cell transcriptomic datasets of human livers across the spectrum of ALD. We identified stage-dependent remodeling and coordinated expression patterns of autonomic and neurotrophic genes. Autonomic signaling exhibited a consistent decline, with reduced expression of sympathetic (DBH, TH) and the parasympathetic (ChAT) markers. In contrast, pan-neuronal and neuroplasticity-associated genes (UCHL1, TUBB3, STMN2) were upregulated, indicating active neural remodeling. In parallel, factors such as MANF, GDNF, and NRG2, with the receptor NTRK1, were upregulated and positively correlated with clinical indicators of disease severity, inflammation and fibrosis. In contrast, trophic factors including NTF3 and CDNF, and receptors such as GFRA1 and GFRA3, were downregulated and inversely associated with these parameters. Single-cell analyses revealed that neurotrophic factors are predominantly expressed by hepatic stellate cells, supporting their role as resident neuroglia-like cells in the liver. In another independent cohort, we observed a coordinated downregulation of NTF3 and sympathetic nerve markers in alcohol-associated hepatitis (AH), suggesting impaired NTF3-mediated neurotrophic support may contribute to sympathetic dysfunction in AH. Collectively, these findings uncover previously unrecognized neuro-regulatory dimensions in ALD and suggest that dysregulated autonomic and neurotrophic signaling may contribute to disease progression. Conflict of interestThe authors have declared that no conflict of interest exists.

bioinformatics↗

bioRxiv2026

ProteoScopeR: A Shiny Workflow for Method Comparison and Reproducible Quantitative Proteomics Analysis

Quantitative proteomics requires decisions about normalization, missing-data handling, and statistical modeling that can change the reported results. ProteoScopeR is an R package and Shiny application that connects these decisions in a traceable workflow and complements downstream exploration in xOmicsShiny. Side-by-side comparisons expose changes in distributions, feature retention, effect estimates, and selected protein sets. An optional external artificial-intelligence assistant reviews exported evidence and proposes settings for researcher approval; statistical calculations remain in R. A group-only case study used DIA-NN-derived aqueous humor data from 69 samples and 3,667 imported protein groups. Six normalization methods and seven missing-data strategies were screened, and the approved cyclic-loess analysis compared five differential workflows. For nAMD versus pmCNV, limma and proDA selected 54 and 37 protein groups, respectively, with 31 shared selections at adjusted P < 0.05 and absolute log2 fold change [≥] 0.5. Input routing, scientist decisions, locked settings, and an execution receipt preserve the analysis record. These comparisons describe sensitivity to analytical choices rather than identify a universally superior method.

bioinformatics↗

bioRxiv2026

Cell-Lens: Advancing LLM Reasoning at Single-Cell Resolution

Recent work applies large language models (LLMs) to single-cell data, but the cell usually reaches the model as a short ranked list of genes. This list drops much of what defines a cell, so the model reasons from a partial view. Yet the information is not lost in the measurement, only in the text. Here, we introduce Cell-Lens, a training-free structured representation of the measured cell. It writes the cell as typed blocks, from paired measurements to marker-supported programs. On CellVerse, SOAR, CellPuzzles, and SC-Arena, across five model families, Cell-Lens improves performance by up to 27.1 points. It also narrows the model gap and reduces API-reported reasoning-token usage. The largest gains occur when a defining RNA marker falls out of the ranked list. In these cases, the paired protein data still capture the corresponding signal. Shuffling the added blocks removes the gain. The gain persists after selected label-associated proteins are removed. These controls link the improvement to cell-matched biological content. We also build and release CellSpectrum, a broader benchmark spanning eight sources and seven tasks with paired modalities. The gains hold there across tasks, tissues, and modalities. These results show that a better cell representation can improve single-cell reasoning without retraining the model. Code and CellSpectrum are publicly available at https://github.com/LiZaiyuan0619/Cell-Lens.

bioinformatics↗

bioRxiv2026

TRAPPC8 Is an Endogenous Brake on UFMylation That Suppresses Tauopathy

UFMylation, a ubiquitin-like protein modification, drives tau spread through the brain, but what keeps this process in check has remained unclear. We show that TRAPPC8 acts as a natural brake on UFMylation, binding directly to the E1 enzyme UBA5 to dampen pathway activity. In Alzheimer's disease brain tissue, TRAPPC8 is reduced while UFMylation is elevated, suggesting this brake fails as disease progresses. Sustaining UFMylation in human iPSC-derived neurons increased tau aggregation and spread while disrupting lysosomal function and lipid balance. Restoring TRAPPC8-UBA5 binding reversed these defects through the lysosomal protein CLN8, which restored lysosomal function and reduced tau pathology. Notably, expressing just the UBA5-binding region of TRAPPC8 was enough to suppress tau pathology in vivo, marking it as a promising therapeutic target.

neuroscience↗

bioRxiv2026

Lineage Memory and Convergent Adaptation Dictate the Single-Cell and Spatial Architecture of Brain Malignancies

How diverse cancer lineages navigate the draconian central nervous system environment--whether constrained by ancestral ontogeny or driven by convergent adaptation--remains a fundamental biological paradox. To decode this, we integrated extensive in-house and public resources to construct the largest single-cell atlas of primary and secondary brain malignancies (>550,000 cells). We demonstrate that malignant cells balance strict lineage imprinting with shared brain-adaptive programs, powerfully converging upon a dominant pan-cancer mesenchymal (MES)-like state alongside a SYT1+ pioneer subpopulation exploiting neuronal mimicry. Concurrently, the microenvironment undergoes lineage-constrained divergence. The myeloid landscape shifts from a resident-dominated architecture in gliomas to extensive blood-borne infiltration in metastases. Lymphoid responses parallel this, crowning laryngocarcinoma as an ultra-hot subtype and revealing that massive T cell influx in highly infiltrated niches is paradoxically driven into terminal exhaustion, contrasting with severe immune exclusion in cold tumors. Furthermore, stromal-vascular adaptation couples pro-angiogenic tip-endothelial activation with a dynamic opposition between structural extracellular matrix (ECM) deposition and focal proteolytic degradation. Anchored by the pan-cancer MES adaptation, we leveraged subcellular spatial transcriptomics to redefine the microenvironment around four MES-like architectural niches, mapping an evolutionary trajectory from perivascular entry to immunosuppressive stromal remodeling. Finally, projecting these architectures onto independent clinical cohort establishes the MES-S2 proliferative niche as the primary driver of severe clinical deterioration across both transcriptomic and proteomic dimensions.

Cancer Biology↗

bioRxiv2026

CytoGem-XAI:A Hypergraph Neural Network Framework for Genome-Scale Metabolic Modeling and Interpretable Analysis

Genome-scale metabolic models are essential for understanding cellular metabolism, yet existing deep learning approaches remain black boxes, and traditional flux balance analysis (FBA) cannot provide sample-specific predictions. To our knowledge, CytoGem-XAI is the first framework to combine hypergraph neural network representation with interpretable, FBA-parallel analysis and sample-specific metabolic characterization. Built upon hypergraph representations where reactions are encoded as hyperedges connecting their participating metabolites, CytoGem-XAI introduces three analysis modules: perturbation-based carbon source importance ranking, hard intervention reaction bottleneck identification, and pathway-level topological attribution. Beyond prediction, CytoGem-XAI uniquely enables condition-dependent carbon source essentiality and reaction bottlenecks that vary with genetic background--capabilities absent from both traditional FBA and existing deep learning methods. Trained on 17,400 E. coli growth conditions using 10-fold cross-validation, our framework achieves R2 = 0.862, substantially outperforming AMN (R2 = 0.81, +6.4%), FBA (R2 = 0.62, +39%), and gradient boosting baselines (R2 = 0.71, +21%). Biological validation confirms that CytoGem-XAI identifies known essential carbon sources (e.g., alanine, malate) and rate-limiting enzymes (e.g., TCA cycle), while also revealing N-acetylmuramate--a peptidoglycan precursor--as a previously underappreciated essential nutrient.

bioinformatics↗

bioRxiv2026

GalaxyVS: Exploring 100-Billion Compounds in Seconds

We present GalaxyVS, a hardware-software co-designed virtual screening framework built to explore the 100-billion commercially accessible chemical space in seconds, deployed at the National Supercomputing Center in Tianjin. Built upon the dense vector retrieval paradigm of DrugCLIP, GalaxyVS bypasses the structural dependencies and computational overhead of classical docking to enable rapid screening against experimentally determined as well as geometrically feasible pockets on AlphaFold-predicted structures. To scale this paradigm to the 100-billion level, the system must overcome the significant computational burden of offline representation encoding, critical memory and I/O bottlenecks during online retrieval, and the risks of diversity collapse and precision loss within final screening results. Utilizing the heterogeneous supercomputing infrastructure, GalaxyVS accelerates the offline encoding through deep operator adaptations and resolves online retrieval bottlenecks via disk-native vector indexing coupled with in-memory staging to ensure both broad accessibility and high throughput. Concurrently, a two-stage refinement protocol effectively mitigates diversity collapse and ensures high-fidelity affinity ranking. Consequently, GalaxyVS achieves a daily scoring throughput of 1.5 x 1016 target-ligand pairs, representing a six-orders-of-magnitude leap over previous supercomputing records. Driven by this throughput, we screened nearly 100,000 protein structures across six species against the 100-billion compound library in just 16 hours. The resulting comprehensive cross-species interaction landscape, GalaxyDB, will be openly released at https://galaxyvs.drugclip.com.

bioinformatics↗

bioRxiv2026

Microglial sTREM2 limits dyskinesia and acts on TrkB to support circuit plasticity

Microglia continuously survey the brain and shape neuronal activity, but their contribution to experience-dependent synaptic plasticity is unclear. Levodopa-induced dyskinesia (LID) is a disabling complication of late-stage Parkinsons disease (PD) that is linked to maladaptive striatal remodeling and is often assumed to reflect detrimental neuroinflammation. Here we identify a dyskinesia-associated microglial gene program in the striatum of PD patients and show that microglia instead act as a protective brake on LID. In a mouse model, microglial depletion exacerbated dyskinesia, whereas microglial repopulation mitigated it. Delivery of AAV expressing soluble TREM2 (sTREM2) similarly reduced LID without impairing the therapeutic benefit of levodopa. Single-nucleus transcriptomics revealed that microglial loss drives extensive remodeling of both direct and indirect spiny projection neurons (SPNs), while repopulation or sTREM2 reverses a large fraction of LID-associated transcriptional changes. Mechanistically, sTREM2 directly engages TrkB and potentiates BDNF-dependent TrkB-ERK signaling, consistent with positive allosteric modulation. Functionally, sTREM2 enhances BDNF-TrkB-dependent hippocampal synaptic plasticity and acutely rebalances striatal dendritic excitability in a compartment- and cell type-specific manner. These findings reveal an unexpected neuroimmune pathway in which microglia restrain maladaptive plasticity via sTREM2-TrkB signaling, with therapeutic implications.

neuroscience↗

bioRxiv2026

Loss of inwardly rectifying potassium channel Kir4.2 drives Parkinson's disease-like motor, cognitive and neuropathological features in mice

A critical barrier to therapeutic development in Parkinsons disease (PD) is the lack of endogenous genetic models that spontaneously recapitulate the diseases progressive, anatomically selective nigrostriatal pathology. Genetic studies have linked KCNJ15, encoding the inwardly rectifying potassium channel Kir4.2, to familial PD via a loss-of-function dominant-negative variant; however, its mechanistic role in neurodegeneration remains unexplored. Here, we demonstrate that Kcnj15-/- mice spontaneously develop a progressive PD-like phenotype, exhibiting a "coordination-first" motor syndrome, anxiety-like behavioural changes and spatial memory impairments. Crucially, neuropathology reveals selective degeneration of substantia nigra pars compacta neurons, sparing the ventral tegmental area, with marked microglial hyperactivation and phosphorylated -synuclein accumulation, faithfully recapitulating the topography of human PD. Striatal transcriptomics further reveals upregulation of oligodendrocyte- and myelin-associated genes, implicating compensatory glial remodeling. These findings identify Kir4.2 as a critical homeostatic regulator of nigrostriatal integrity and establish the Kcnj15-/- mouse as a new physiologically accurate and translatable model for PD research.

neuroscience↗

bioRxiv2026

Metformin Stabilizes the Abdominal Aorta in Aneurysm by Restoring VSMC Mitochondrial Homeostasis via the AMPK-SIRT1-PGC-1α Axis

BACKGROUNDAbdominal aortic aneurysm (AAA) is a life-threatening condition with >80% mortality upon rupture and no effective pharmacotherapy available. Despite epidemiological evidence linking metformin use to reduced AAA progression, its mechanism remains elusive. Notably, peroxisome proliferator-activated receptor {gamma} coactivator 1 (PGC-1, encoded by Ppargc1a) is downregulated in human AAA, yet its functional role in metformins protection is unknown. METHODSWe employed porcine pancreatic elastase (PPE)-induced murine AAA, VSMC-specific Ppargc1a knockout (Ppargc1aVSMC-KO), primary VSMC senescence models, and pharmacological inhibition (Compound C for AMPK; Ex-527 for SIRT1) to define the AMPK-SIRT1-PGC-1 axis. RESULTSMetformin significantly inhibited AAA expansion, suppressed VSMC senescence (p53/p21{downarrow}, SA-{beta}-gal{downarrow}), and preserved contractile phenotype (SMTN{uparrow}, IL-6/TNF-{downarrow}). Crucially, all benefits were abrogated in Ppargc1aVSMC-KO mice, which exhibited accelerated aneurysm growth, mitochondrial fragmentation, ATP depletion, and ROS accumulation. Mechanistically, metformin activated AMPK/SIRT1 to upregulate PGC-1; AMPK or SIRT1 inhibition blocked this cascade and reversed protection. CONCLUSIONMetformin restrains AAA by restoring VSMC mitochondrial homeostasis via the AMPK/SIRT1[->]PGC-1 axis, positioning PGC-1 as a non-redundant, cell-autonomous guardian against vascular degeneration. These findings provide a mechanistic foundation for repurposing metformin and developing PGC-1-targeted therapies in AAA.

cell biology↗

bioRxiv2026

Rapid and Quantitative Phage Susceptibility Test by Ramanome

Antimicrobial resistance poses an escalating global threat, renewing interest in bacteriophage therapy as a precision alternative to antibiotics. However, clinical translation remains hindered by the lack of rapid and quantitative phage susceptibility testing (PST) platforms capable of evaluating host range, infection potency, and effective multiplicity of infection (MOI). Here we present RPST, a ramanome-based phenotypic platform that captures infection-induced remodeling of bacterial macromolecular composition to unify these diagnostic requirements within a single workflow. RPST integrates four Raman biomarkers into a Composite Infection Index (CII), enabling rapid and lysis-independent discrimination between susceptible and resistant bacterial populations within [~]1 hour, with 96.0% categorical concordance (24/25) to plaque assays. As a continuous population-level metric, CII quantifies the proportion of infected cells, allowing quantitative ranking of phage potency against shared hosts. By resolving CII trajectories across the MOI and time, RPST further determines the minimal effective MOI, which is the lowest phage-to-bacterium ratio sustaining self-propagating infection, thereby defining the lower boundary for therapeutic feasibility. Together, these capabilities transform PST from static compatibility assays into a dynamic and quantitative framework that bridges in vitro infectivity assessment and infection dynamics relevant to phage therapy. Impact StatementBased on the rapid emergence of antimicrobial resistance, this study introduces RPST, a novel ramanome-based phage susceptibility testing platform. RPST detects phage-induced biochemical remodeling in bacteria within [~]1 hour, achieving 96.0% concordance with gold-standard plaque assays. By integrating four Raman biomarkers into a Composite Infection Index, it not only distinguishes susceptible from resistant strains but also quantifies phage potency and determines the minimal effective multiplicity of infection required for self-sustaining infection. This transformative approach moves beyond binary diagnostics to offer a dynamic, quantitative framework for precision phage therapy, significantly accelerating therapeutic decision-making and enhancing our ability to combat resistant infections.

microbiology↗

bioRxiv2026

Beyond Lipschitz: Ranking Binding Affinity in Hyperbolic Space

Despite the importance of protein-ligand affinity ranking in drug discovery, existing deep learning models struggle to distinguish hard inactives that are structurally similar to active compounds but biologically inactive. We theoretically show this failure stems from the Lipschitz continuity constraint in Euclidean space, which makes neural networks locally insensitive to subtle yet critical structural perturbations. To overcome this, we propose AlphaRank, which demonstrates that scoring affinity as the negative hyperbolic geodesic distance allows subtle tangential variations to bypass Lipschitz constraints, intuitively corresponding to pivotal binding mode factors such as conformational fit. Meanwhile, AlphaRank employs joint optimization to simultaneously ranking affinity scores among actives in a proximity-aware manner and separate actives from decoy inactives through a geometric cone constraint. Experiments demonstrate that AlphaRank outperforms state-of-the-art models like Boltz-2 in both affinity ranking and active-inactive discrimination, while providing a interpretable representation space.

bioinformatics↗

bioRxiv2026

Follistatin improves vascular function by inhibiting oxidative stress and inducing browning of perivascular adipose tissue in essential hypertension

BackgroundEssential hypertension, characterized by vascular dysfunction, remains a leading modifiable cause of death globally. Perivascular adipose tissue (PVAT), which normally reduces vasoconstriction, becomes less anticontractile in hypertension due at least in part to increased reactive oxygen species (ROS). Brown PVAT has emerged as a protective regulator of vascular tone. Follistatin, an activin antagonist, induces browning of peripheral adipose tissue depots via AMPK. We recently reported improved blood pressure, vascular function and reduced vascular ROS by follistatin in the spontaneously hypertensive rat (SHR) model of essential hypertension. Here, we investigate whether follistatin reduces ROS and induces browning in SHR PVAT to restore PVAT function. MethodsSHR were treated with vehicle, follistatin or hydralazine for 8 weeks. Mesenteric white and thoracic brown PVAT from SHR and normotensive Wistar-Kyoto were utilized, with wire myography used to assess vascular function. Nitric oxide (NO) and nitrite were measured in PVAT using DAF-2 FM fluorescence or Griess reagent, respectively. PVAT ROS and browning markers were assessed biochemically and via immunohistochemistry. PVAT was treated ex vivo for 3 days to assess mechanisms of browning. Unbiased proteomic analysis of PVAT was performed using liquid chromatography-mass spectrometry. ResultsSHR PVAT dysfunction, manifest as a pro-contractile effect, was inhibited by follistatin through reducing ROS, enhancing NO bioavailability and inducing browning. Activin neutralization and AMPK phosphorylation mediated the beneficial effect of follistatin on SHR PVAT. Hydralazine-induced blood pressure reduction did not replicate follistatin effects, suggesting vascular benefits of follistatin are mediated by direct PVAT modulation. Proteomic analysis showed that follistatin shifts PVAT proteome towards normal state, upregulating processes associated with adipose tissue browning. ConclusionFollistatin restores PVAT-mediated vascular relaxation via ROS reduction, activin neutralization and AMPK-dependent browning, positioning the potential for PVAT as a therapeutic target for vascular dysfunction in essential hypertension.

physiology↗

bioRxiv2025

A Comprehensive Treatment-Induced Resistance Atlas of Glioblastoma Reveals a Fibrotic Niche Shielding the Tumor from Immunotherapy

Therapeutic resistance in IDH-wildtype glioblastoma (GBM) is driven by an intricate interplay between cellular plasticity and protective microenvironmental niches. By constructing the GRIT-Atlas--a massive transcriptomic compendium encompassing nearly one million high-quality single cells across 17 cohorts--and cross-analyzing it with 48 independent Visium spatial transcriptomics sections, we discover a recurrent "Spatial Resistance Triad" comprising mesenchymal-like (MES-like) malignant cells, myeloid-derived suppressor cells (MDSCs), and collagen-secreting cancer-associated fibroblasts (CAFs). This large-scale spatial integration reveals that the triad physically fortifies microvascular proliferation (MVP) and pseudopalisading necrosis (PAN) niches. To substantiate these findings at true single-cell resolution, we deploy high-plex spatial molecular imaging (CosMx SMI) to map over 400,000 single cells across a clinical validation cohort. This high-resolution architecture firmly validates the triads geography and, critically, provides structural gradient evidence unmasking a spatiotemporal continuum wherein PAN emerges as a direct functional consequence of MVP advancement and subsequent vascular collapse. Mechanistically, stromal CAF-derived COL6A1 engages CD44 receptors on MES-like cells to accelerate a potent neural stemness cascade within these protective domains. Utilizing a blood-brain barrier (BBB)-penetrant multi-library compound screen, we identify Lacidipine as a multi-modal stromal disruptor that successfully silences CAF activation and halts matrix secretion. Incorporating Lacidipine into the standard chemo-immunotherapy backbone (TMZ + anti-CSF1R) completely dismantles the protective desmoplastic matrix niche, forcing a profound collapse of intracranial tumor burden and dramatically extending overall survival in orthotopic models. Collectively, our study leverages unprecedented single-cell and spatial scale to provide a definitive blueprint of GBM therapeutic evasion, establishing matrix-targeted intervention as a mandatory prerequisite for successful glioblastoma eradication.

cancer biology↗

bioRxiv2025

Chronic alcohol exposure drives inflammaging and transposon derepression in hematopoietic stem and progenitor cells

Chronic alcohol use can cause pancytopenia and diminished immune responses against pathogens. However, its underlying molecular mechanisms remain unclear. Furthermore, whether chronic alcohol consumption directly induces inflammation in human hematopoietic stem progenitor cells (HSPCs) or whether it affects aging hematopoiesis differently is unknown. To examine how chronic alcohol use influences HSPCs, we performed single-cell RNA-seq in murine and human HSPCs and single-cell ATAC-seq in aged murine HSPCs following alcohol exposure. In the native murine bone marrow, chronic alcohol exposure primed HSPCs to differentiate into myeloid cells and to exhibit heightened inflammation, DNA damage, and epigenetic reactivation of transposable elements (TEs) in an age-dependent manner. Alcohol-exposed aged long-term hematopoietic stem cells (LT-HSCs) displayed increased chromatin accessibility at TE-containing loci correlated with aberrant TE transcription. This transposon derepression was associated with the accumulation of dsRNAs in aged bone marrow cells, and activation of innate immune pathways, perpetuating HSC inflammaging. Furthermore, we identified two epigenetically distinct LT-HSC clusters, LT-HSC1 and LT-HSC2, with the LT-HSC2 cluster expanding in response to chronic alcohol consumption, resembling activated HSCs. In xenotransplanted human HSPCs, chronic alcohol feeding resulted in a significant myeloid bias, heightened inflammation, upregulation of double-stranded RNA (dsRNA) sensors, activation of type I interferon responses, and increased expression of endogenous retroviruses. Despite these molecular alterations, we did not observe a decrease in long-term repopulation capacity in either human or murine HSCs. This suggests that HSC function may recover following alcohol cessation. However, previous chronic alcohol exposures imprint murine HSPCs to exhibit long-term myeloid bias and reduced cell cycle entry upon bacterial LPS challenge. Our data illuminate potential interactions between alcohol and aging that can reinforce inflammaging and epigenetic dysregulation in HSPCs. KeypointsO_LIAging perpetuates alcohol-induced myeloid bias, inflammation, DNA damage, and TE upregulation in murine HSPCs C_LIO_LIPrior chronic alcohol consumption does not affect long-term repopulation but causes persistent myeloid bias and inefficient stress responses after LPS challenge C_LIO_LIChronic alcohol consumption alters chromatin accessibility in TE-overlapping regions C_LIO_LIChronic alcohol consumption promotes myeloid bias, inflammation, and upregulation of endogenous retroviruses in xenotransplanted human HSPCs. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=129 SRC="FIGDIR/small/696246v2_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@e0357aorg.highwire.dtl.DTLVardef@1d702fdorg.highwire.dtl.DTLVardef@10553ddorg.highwire.dtl.DTLVardef@c4e62e_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2025

Human trunk embryoids with patterned anterior-posterior and dorsal-ventral body axes: utility for understanding human development and disease

Human embryoid models enable mechanistic studies of development and disease. We generated trunk embryoids from human pluripotent stem cells that recapitulate posterior trunk formation at Carnegie stage (CS) 8-10, with patterned anterior-posterior (A-P) and dorsal-ventral (D-V) axes. These self-organizing structures comprise a ventral notochord, dorsal neural tube, floor plate and bilateral somites. Genetic and chemical perturbations of SHH signaling confirmed the notochords central role in D-V patterning. Moreover, VANGL1/2 loss-of-function mutations recapitulated mouse phenotypes, including axial truncation and somite segmentation failure. This model enables detailed study of key developmental events that underlie posterior trunk formation and provides a promising platform for human disease modeling.

developmental biology↗

bioRxiv2025

A SARS-CoV-2 entry inhibitor trimerizes to lock the spike protein in a closed conformation

The SARS-CoV-2 spike protein binds its receptor ACE2 to initiate target-cell infection. To engage ACE2, at least one of the three receptor-binding domains (RBDs) of the spike must adopt the up orientation. Here we describe S22, a potent, bioavailable, and non-toxic inhibitor of BA.2 and all subsequent Omicron variants. Cryo-EM analyses showed that S22 assembled as a trimer in a previously uncharacterized pocket of the spike apex, stabilizing all three RBDs in the down orientation, thereby preventing ACE2 association. Binding studies, especially those using mixed S22-sensitive and -resistant spikes, imply a cooperative assembly of three S22 molecules with three RBDs, resulting in an unusually slow S22 off-rate. Consistent with its slow dissociation and favorable pharmacokinetics, S22 suppressed viral replication 100-fold in the lungs of XBB.1.5-infected mice. Thus, S22 potently inhibits Omicron entry through a distinct mechanism whereby a small compound assembles cooperatively as a trimer to stabilize spike in an inactive conformation.

microbiology↗

bioRxiv2025

Siglec-F Protects Against Elastase-induced Lung Inflammation and Emphysema in Mice

Respiratory surfaces are exposed daily to billions of inhaled particles that could cause injury to alveolar tissues where gas exchange occurs. Accordingly, robust defense is essential but must involve minimal physiologic disruption. Airspace macrophages (AMs) protect lung surfaces while also maintaining tissue integrity through non-inflammatory homeostatic responses in health. However, in chronic obstructive pulmonary disease (COPD), AMs contribute to emphysematous alveolar destruction through mechanisms that are poorly understood. We hypothesized that damaging effects of AMs in emphysema result from loss of mechanisms that normally restrain homeostatic AMs. We found that Siglec-F, a common marker of AMs, exerts suppressive effects on tissue resident AMs (RAMs), thereby supporting alveolar integrity in mouse lungs during health and in a model of elastase-induced alveolar destruction. Siglec-F-deficient mice exhibited decreased alveolar numbers at baseline, and they had worsened alveolar damage after elastase challenge that was unexpectedly RAM-mediated. Transcriptomic profiling revealed dysregulation of key pathways involved in tissue remodeling and repair, including extracellular matrix degradation, TGF-{beta} signaling, and phagocytosis. These findings uncover previously unrecognized roles for RAMs and Siglec-F in preserving alveolar integrity. Our findings implicate RAMs and Siglecs as potential therapeutic targets for preserving alveolar integrity in health and for limiting alveolar damage in COPD.

immunology↗