Biology subjects

Deng, Y.

Publications and source records attributed to Deng, Y..

At least 19 recordsLinked to original sources

bioRxiv2026

Live Spatial Transcriptomics Enables Longitudinal Tissue Mapping

Spatial transcriptomics has become an important technology in biomedical research by preserving the spatial context of gene expression in tissues and enabling the study of cellular states and interactions in situ. However, most existing methods provide only static snapshots of individual tissue specimens, requiring inference of the molecular dynamics underlying development, disease progression, and therapeutic response from different specimens rather than direct tracking in the same living tissue. Here, we introduce Live Spatial Transcriptomics (Live-ST), a technology that enables longitudinal, transcriptome-wide profiling of living tissue. Live-ST combines electroporation-based intracellular sampling and spatial barcoding to enable repeated, spatially resolved mRNA measurements in intact living tissue through next-generation sequencing. We demonstrate its capabilities by (i) benchmarking spatial mRNA capture in patterned two-dimensional cell systems, (ii) spatially profiling transcriptomes in intact, patient-derived living melanoma tissues while preserving tissue viability, and (iii) longitudinally tracking drug-response dynamics within the tumor microenvironment. Together, Live-ST enables repeated, non-destructive measurements of spatial gene expression, providing a new framework for studying dynamic tissue biology in native physiological and pathological contexts.

bioengineering↗

bioRxiv2026

MicroDLP: Microscope-Enabled Resolution-Switchable 3D Microprinting

Complex three-dimensional (3D) microarchitectures are increasingly important for microfluidics, microrobotics, organ-on-chip systems, biomedical devices, and architected materials. However, fabricating complex 3D microstructures with micrometre-scale precision remains a major manufacturing challenge. Integrating these fine features with larger supporting structures presents an additional challenge, requiring fabrication across multiple length scales within a single architecture. Although microscale 3D printing enables intricate geometries, the trade-off between resolution and build volume limits multiscale fabrication, while existing approaches often require complex optics and precise registration. Here, we introduce MicroDLP, a microscope-enabled digital light processing platform for versatile, resolution-switchable 3D microprinting. By integrating a projection module into a conventional inverted microscope, MicroDLP exploits its revolving objective turret to switch between 4x, 10x, and 20x objectives, providing projected pixel sizes from 1.89 to 0.378 um. We characterize photopolymerization, voxel geometry, and lateral feature resolution across magnifications to establish suitable microscale printing conditions. MicroDLP enables the fabrication of diverse and complex 3D microarchitectures, including freestanding trusses with 170 um struts, microvascular structures with 10 um features, interlocking gears, suspended microbridges, and microneedles with 3-5 um tips. Importantly, switching from 10x to 20x during fabrication produces monolithic 3D structures combining larger supporting foundations with fine micropillar arrays, without manual optical realignment. The shared optical pathway also enables coaxial in situ monitoring of photopolymerization. Together, these results establish MicroDLP as a versatile platform for microscale additive manufacturing, combining complex 3D microfabrication with resolution switching within a single monolithic structure.

bioengineering↗

bioRxiv2026

Receptor-like kinase RLK15 binds a fungal RNase effector to enhance autophosphorylation and activate host defense

Fungal pathogens secrete diverse effectors to suppress host immunity, yet the plant receptors that perceive these virulence factors often remain elusive. Here, we identify Ss1624, a secreted RNase from the sugarcane smut pathogen Sporisorium scitamineum, and show that it is recognized by the plasma-membrane-localized CrRLK1L-family receptor kinase RLK15. This recognition triggers canonical immune outputs, including reactive oxygen species burst, callose deposition, defense gene activation, and induces hypersensitive cell death. Mechanistically, Ss1624 physically interacts with the receptor-like kinase RLK15, which is required for Ss1624-triggered cell death. Functional assays indicate that this interaction enhances RLK15 autophosphorylation in a kinase activity-dependent manner, suggesting that Ss1624 can act as an elicitor. Transcript profiling further reveals coordinated expression patterns of Ss1624 and RLK15 during infection, and perturbation of Ss1624 expression alters RLK15 transcript levels and pathogenic outcomes. Extending these findings to rice, the ortholog OsRLK15 contributes positively to resistance to bacterial and fungal diseases without yield penalty in rice. Our results support a model in which a secreted RNase effector is directly sensed by a receptor kinase to initiate broad-spectrum immune responses, providing insights into host-pathogen interactions and identifying RLK15 as a candidate for crop improvement.

microbiology↗

bioRxiv2026

Charting sex divergence in the human brain across the lifespan

Biological sex fundamentally shapes human brain organization, but sex-specific normative neuroanatomical trajectories across the lifespan remain largely uncharted. Here, we constructed independent, sex-specific lifespan brain charts using structural neuroimaging data from 59,915 healthy individuals (29,760 males and 30,155 females) ranging in age from 266 postconception days to 100 years. By examining 296 structural phenotypes across global, cortical, and subcortical measures, these models revealed widespread sex differences in maturational timing, with males reaching peak milestones later than females. These trajectories demonstrate that sex differences evolve dynamically, with phenotype-specific windows of emergence and maximal separation. Compared with conventional sex-pooled references, sex-specific models achieved superior predictive accuracy and reduced misestimation of individual deviations in healthy populations. Across five neuropsychiatric conditions, sex-specific models improved the detection of extreme deviations and revealed both shared and sex-dependent patterns of disorder-related neuroanatomical abnormalities. These sex-specific charts establish tailored normative references for assessing brain development, ageing, and disease.

neuroscience↗

bioRxiv2026

Role of Uridine Phosphorylase 1 (UPP1) in Pancreatic β-Cell Physiology and Its Dysregulation in Obesity and Type 2 Diabetes

Aims/hypothesis Fasting plasma uridine concentrations are elevated in obese mice and in individuals with type 2 diabetes (T2D), suggesting that uridine may function as a metabolic signal that adjusts insulin secretion to changes in metabolic demand. Here, we tested this hypothesis by determining whether uridine potentiates glucose-stimulated insulin secretion (GSIS) in mouse and human islets and by identifying uridine phosphorylase 1 (UPP1), the principal enzyme responsible for systemic uridine catabolism, as a key mediator of this effect. Methods Whole-body Upp1 knockout (KO) and {beta}-cell-specific Upp1 knockout (KO{beta}) mice were used to determine the requirement for UPP1 in uridine-potentiated glucose-stimulated insulin secretion (GSIS) and glucose-stimulated MAPK activation. Leptin-deficient and diet-induced obese mouse models were used to assess the impact of obesity on uridine responsiveness. UPP1 protein abundance and subcellular localization were examined in islets from obese mice and human donors spanning a range of glycemic control. Integrated single-nucleus RNA sequencing and ATAC sequencing were performed on wild-type and Upp1 KO mouse islets to characterize {beta}-cell molecular remodeling associated with UPP1 deficiency and altered responses to uridine. Results Uridine potentiated GSIS in islets from chow-fed and high-fat diet-fed mice, but not in leptin-deficient obese mice. Uridine also potentiated GSIS in human islets, although this effect progressively declined with worsening glycemic control. In mouse islets, uridine potentiation was accompanied by transient activation of the MAPK pathway. Both uridine-potentiated GSIS and uridine-enhanced glucose-stimulated MAPK activation were abolished in islets from Upp1 KO and KO{beta} mice. The requirement for a transient MAPK signaling was further supported by pharmacological inhibition of MEK and constitutive activation of MEK1. Leptin-deficient islets exhibited impaired glucose-induced MAPK activation together with increased UPP1 protein expression. In human islets, UPP1 protein abundance positively correlated with donor HbA1c and displayed heterogeneous subcellular localization. Integrated single-nucleus multiomic analysis identified UPP1 as an important regulator of {beta}-cell identity, function, and transcriptional responses to uridine. Conclusions These findings establish UPP1 as a key regulator linking pyrimidine metabolism to {beta}-cell function and identify impaired uridine responsiveness as a potential contributor to and/or consequence of {beta}-cell dysfunction during the progression of T2D.

molecular biology↗

bioRxiv2026

The m6A methyltransferase complex protein VIRMA engages hepatitis C virus RNA through a WTAP-independent mechanism

Cellular proteins in the m6A methyltransferase protein complex (m6A-MTC) work together to modify both cellular and viral RNAs with N6-methyladenosine (m6A), an RNA modification that regulates viral infection. We previously showed that hepatitis C virus (HCV), a cytoplasmic positive-sense RNA virus, has an m6A-modified RNA genome. We also found that m6A deposition on HCV RNA requires WTAP, which promotes association of the METTL3-METTL14 catalytic heterodimer to the viral RNA. However, the factors that directly recognize HCV RNA and recruit the m6A-MTC to the viral genome are unknown. Here, we identify the cellular m6A-MTC component VIRMA as an HCV RNA-targeting factor required for METTL3 association with the viral genome. We show that endogenous VIRMA can associate with both HCV and cellular RNAs independently of WTAP. Further, we define distinct domains of VIRMA involved in WTAP interaction and RNA binding and show that the regions of VIRMA involved in WTAP-interaction are required for cellular but not HCV RNA association. Together, these results establish that VIRMA uses distinct molecular determinants to engage viral and cellular RNAs and define VIRMA as a substrate-recognition factor required for m6A-MTC association with HCV RNA.

molecular biology↗

bioRxiv2026

A tissue-resolved endothelial surface proteome atlas informs organ-selective vascular targeting

BACKGROUND Endothelial cells (ECs) exhibit organ-specific functional diversity that shapes vascular homeostasis, disease susceptibility, and therapeutic accessibility. Although single-cell transcriptomic studies have defined endothelial heterogeneity at the RNA level, the in vivo cell-surface protein landscape that directly mediates vascular signaling and drug targeting remains incompletely characterized. Here, we mapped organ-specific endothelial surface proteomes atlas in vivo to define tissue-enriched vascular protein candidates relevant to organ-selective therapeutic design. METHODS We generated Cdh5-CreERT; Cre-iPEEL mice, referred to here as CHRP mice, in which membrane-tethered horseradish peroxidase is induced selectively in ECs after tamoxifen treatment, and compared CHRP labeling with non-selective NHS-Biotin vascular labeling. Following in vivo biotin-phenol perfusion, endothelial surface proteins were enriched by streptavidin affinity purification and analyzed by mass spectrometry across six organs. Proteomic profiles were used to resolve tissue- and subtype-associated endothelial surface signatures, compare protein and transcript detection patterns, and nominate tissue-selective endothelial membrane candidates, which were annotated using ChEMBL compound-target information. RESULTS Compared with non-selective NHS-Biotin labeling, CHRP improved endothelial specificity and produced clearer separation of tissue-resolved endothelial surface proteomes across brain, white adipose tissue, small intestine, kidney, lung, and skeletal muscle. CHRP proteomics revealed pronounced organ-specific heterogeneity and resolved canonical arterial, venous, and capillary programs, as well as specialized endothelial signatures including blood-brain barrier and glomerular endothelial features. Comparison with single-cell endothelial references revealed systematic differences between transcriptomic and proteomic detection of endothelial membrane proteins. Further analysis identified tissue-selective endothelial membrane candidates, and ChEMBL annotation linked a subset of these candidates to existing compound-target records, supporting the candidate atlas as a resource for future tissue-selective vascular targeting studies. CONCLUSIONS CHRP-based in vivo proximity labeling enables systematic, protein-level mapping of organ-specific endothelial surface proteomes. Together with transcriptomic comparison and compound-target annotation, this study provides a tissue-resolved endothelial surfaceome resource for vascular biology and future organ-selective therapeutic target evaluation.

cell biology↗

bioRxiv2026

Coalescent-Based Time-Stratified Statistics Reveal Population Structure Dynamics using the Ancestral Recombination Graph

Many questions in population genetics require reconstructing evolutionary history through time, such as inferring how population structure has changed throughout the past. Yet, many existing approaches have only an implicit temporal component, using quantities such as allele frequency or haplotype length as rough proxies for age. Recent advances in the inference of Ancestral Recombination Graphs (ARGs) have made it possible to estimate the entire sequence of local genealogies along the genome. These genealogies explicitly encode how samples are related to each other at different time points in the past, enabling the inference of how population structure has changed over time. To this end, recent work has used ARGs to define time-stratified versions of widely-used population genetics summary statistics in an attempt to capture the population structure present within a particular time window. Here, we show that naive approaches result in statistics that cannot be interpreted solely in terms of the population structure present within the time window they are targeting. To address this problem, we introduce a framework of coalescent-based time-stratified statistics, which use coalescence probabilities to partition classical summary statistics into interval-specific contributions. Using coalescent simulations, we demonstrate that these statistics accurately isolate population structure at different temporal depths and avoid spurious signals. Our results highlight the necessity of integrating coalescent theory into ARG-based temporal analyses and provide a principled and practical foundation for studying the dynamics of population structure through time.

evolutionary biology↗

bioRxiv2026

Continuous and discrete brain dynamics to study behavioral adaptation during cognitive motor dual-tasking in younger and older adults

Dual-task paradigms are widely used to detect age-related cognitive and motor decline. Conventional evaluations typically average performance across an entire dual-task condition and compare it with a single-task baseline, implicitly treating performance as stable throughout testing. We challenged this assumption by examining block-wise behavioral adaptation and its dynamic functional-connectivity correlates. Forty older adults (50-80 years) and 20 younger adults (20-40 years) performed a cognitive Go/NoGo task, a motor pedaling task, and a combined cognitive-motor dual task during functional magnetic resonance imaging (fMRI) using a custom-built MRI-compatible pedaling device. Motor reaction-time (RT) variability was assessed across eight dual-task blocks, and dual-task benefit was defined as the relative reduction in variability from the first to the final block. Dynamic functional connectivity was characterized using two complementary approaches: dynamic independent component analysis (dyn-ICA), capturing continuously varying circuit properties, and a hidden Markov model (HMM), identifying recurring discrete network states. Across participants, motor RT variability was highest in the first dual-task block, progressively decreased to its lowest level at Block 6, and remained comparatively stable thereafter. Both age groups achieved behavioral stabilization but followed distinct trajectories. Older adults progressed from pronounced initial variability toward their single-motor reference while continuing to perform the dual task, whereas younger adults began closer to this reference and maintained comparatively stable performance. Greater dual-task benefit was associated with higher mean strength of a broadly distributed dyn-ICA circuit encompassing attentional, control, sensorimotor, visual, cerebellar, and default-mode systems (Circuit 4), as well as greater temporal variability of a functionally distinct circuit (Circuit 2).HMM analyses similarly linked greater benefit to more frequent visits to State 6 and greater occupancy of State 9, configurations involving coordinated sensorimotor, salience, dorsal-attention, and frontoparietal systems. Across both approaches, network features preferentially expressed by older adults were associated with greater relative benefit, whereas younger-enriched features accompanied smaller changes from a more stable initial level.These findings demonstrate that dual-task performance evolves substantially within a single session and that behavioral stabilization is related to both continuous circuit properties and discrete network-state visitation. Healthy older and younger adults may therefore achieve successful cognitive-motor adaptation through distinct regimes of dynamic whole-brain organization.

neuroscience↗

bioRxiv2026

Ficd loss rescues motor impairments and reverses oligodendrocyte maturation deficits in a mouse model of spinocerebellar ataxia type 3

Spinocerebellar ataxia type 3 (SCA3) is an inherited, fatal neurodegenerative disease caused by a pathological CAG repeat expansion in the ATXN3 gene, resulting in the selective degeneration of vulnerable neuronal populations. Recent work has identified impairments in oligodendrocyte maturation as a novel and robust feature of SCA3 pathogenesis. Oligodendrocytes synthesize myelin structural components through the endoplasmic reticulum (ER), rendering this organelle essential for white matter integrity. Despite this, the role of ER function in SCA3 remains unclear. In this study, we show that loss of FICD-mediated AMPylation, a post-translational modification regulating the ER-resident HSP70 chaperone, BiP, rescues motor impairments in a transgenic SCA3 mouse model. Ficd-/- SCA3 mice exhibit significantly reduced levels of nuclear ATXN3 in vulnerable brain regions, while Ficd+/+ littermates show an increased burden of AMPylated BiP in the spinal cord, identifying aberrant AMPylation as a novel contributor of SCA3 pathology. Using unbiased proteomics, we demonstrate that Ficd deletion mitigates the pathological decrease in myelin structural proteins and oligodendrocyte maturation factors, restoring levels of mature, myelinating oligodendrocytes. In parallel, we show that Ficd activates SREBP2-dependent cholesterol biosynthesis to support myelination. Taken as a whole, these findings posit ER homeostasis as a critical driver of oligodendrocyte pathology and identify FICD as a novel target for alleviating non-neuronal toxicity in SCA3.

molecular biology↗

bioRxiv2026

A benchmarking framework for single-cell genome-scale metabolic model construction

Single-cell genome-scale metabolic models (scGEMs) enable characterization of metabolic heterogeneity underlying cellular states and phenotypes. However, methodological choices during scGEM construction can substantially alter model structure and predictions, challenging the reliability and comparability of resulting analyses. Here, we established a systematic benchmark to assess three key construction factors: data preprocessing method, model extraction method (MEM) and gene expression threshold. We evaluated 26 strategies representing different combinations of these factors across nine scRNA-seq datasets in three dimensions: accuracy, sensitivity to expression perturbation and computational feasibility. We found that MEM had the greatest influence on most accuracy metrics, data preprocessing strongly influenced the discrimination of cellular identities, and expression threshold balanced model completeness and cellular specificity. These findings indicate that strategy performance varies across evaluation criteria. Our benchmark provides practical guidance for strategy selection and an empirical basis for standardized evaluation and future scGEM method development.

systems biology↗

bioRxiv2026

Integrative spatial profiling of 3D genome organization and gene expression in tissue

The interplay between 3D genome architecture and transcriptional activity is fundamental to gene regulation. However, existing methodologies cannot simultaneously measure these modalities within intact tissues, limiting our understanding of how genome organization coordinates transcriptional programs across diverse cell types and spatial microenvironments. Here, we introduce Spatial Hi-C-RNA, a spatial multi-omics technology that enables the genome-wide co-mapping of chromatin conformation and transcriptome directly from the same tissue section at near- single-cell resolution. Applied to the mouse embryo and adult brains, Spatial Hi-C-RNA generated high-resolution tissue maps revealing that chromatin organization and gene expression jointly define spatially coherent domains aligned with histological structures. While concordant features were observed across modalities, distinct domain patterns also emerged, indicating that chromatin structure and transcription each contribute complementary layers of spatial regulation. We further demonstrated the robustness and biological insight of Spatial Hi-C-RNA in human melanoma, where both modalities delineated tumor boundaries and microenvironmental niches. Notably, chromatin maps revealed fine-scale tumor subdomains undetectable by transcriptomic profiling alone, highlighting the added resolution provided by spatial chromatin architecture. Integrated analysis revealed that multiscale 3D genome features, from A/B compartments and topologically associating domains to chromatin loops, are closely coupled with domain- and cell-type-specific transcriptional programs. In addition, Spatial Hi-C-RNA resolves spatiotemporal dynamics underlying embryonic lineage specification and tumor progression. Together, these capabilities extend the spatial omics landscape beyond transcriptome and epigenome profiling to the level of chromatin organization, establishing an integrative framework for understanding tissue biology across development and disease.

genomics↗

bioRxiv2026

Large-scale functional coupling and computational modelling reveal frontotemporal hotspots in distributed network connectivity during working memory recognition, encoding, and retrieval

Working memory depends on coordinated activity across distributed brain networks, but how these interactions support recognition, encoding, and retrieval remains unclear. Here, we analyzed intracranial local field potentials from 1,652 sites in 36 epilepsy patients performing a naturalistic card-matching task. Phase-amplitude and phase-phase coupling revealed widespread condition-dependent interactions, with frontal and temporal regions emerging as recurrent network hubs. Event-related analyses showed reproducible within-trial coupling dynamics across participants. Directed phase transfer entropy further identified frequency-specific information flow, including frontal regions acting as a theta-band source and an alpha-band sink. Finally, a time-delay-embedded hidden Markov model identified task-locked latent states with condition-dependent occupancy trajectories and distinct coherence profiles. Together, these results suggest that working memory is implemented through dynamic, directionally organized large-scale networks, in which frontotemporal hubs coordinate flexible transitions among distributed neural states rather than operating in isolation.

neuroscience↗

bioRxiv2026

Structural Connectivity Between the Locus Coeruleus and Nucleus Basalis of Meynert Relates to Dual-Task Performance

The noradrenergic locus coeruleus (LC) and the cholinergic nucleus basalis of Meynert (nBM) are key hubs of ascending neuromodulatory systems that shape large-scale brain dynamics. However, the behavioral relevance of the structural and functional connectivity between these nuclei remains poorly understood. Here, we investigated whether LC-nBM structural or functional connectivity is related to cognitive-motor dual-task performance in healthy younger and older adults. Fifty-four participants (36 older, 18 younger) underwent diffusion MRI, resting-state fMRI, and behavioral assessment using an MRI-compatible cognitive-motor dual-task paradigm. LC-nBM structural connectivity was estimated using tractography, whereas resting-state functional connectivity was quantified as Fisher z-transformed correlations between LC and nBM time series. LC-nBM structural connectivity was better explained by a quadratic rather than a linear or cubic age model, indicating non-linear age-related variation, whereas functional connectivity showed no significant age-related association. Higher LC-nBM structural connectivity was associated with greater cognitive dual-task cost, but not with motor dual-task cost or single- or dual-task reaction times. This association was not moderated by age group and was not statistically explained by attentional and executive performance as measured by the Test of Attentional Performance. These findings suggest that LC-nBM structural connectivity is selectively associated with cognitive-motor interference, potentially reflecting a neuromodulatory pathway that constrains the balance between task-specific stabilization and flexible cross-domain coordination during a cognitive-motor dual-tasking.

neuroscience↗

bioRxiv2026

scSAID: A Comprehensive Cross-Species Single-Cell Skin Atlas Reveals Species-Specific Responses to Psoriasis

Single-cell RNA sequencing has rapidly expanded the scale of skin transcriptomic data, yet these datasets remain fragmented across studies spanning different species, diseases and experimental manipulations. An up-to-date, comprehensive, and queryable single-cell cross-species repository for skin is still lacking. Here, we present scSAID (skin-scsaid.com), a single-cell database with an interactive web portal offering a broad suite of in-depth analyses for human and mouse skin. It integrates more than 1.2 million high-quality cells collected from 252 samples, establishing a unified reference for cell-type annotation, cross-species comparison and pathological studies. Using psoriasis as a case study, we demonstrate how scSAID can be used to evaluate how faithfully mouse models reproduce human pathology. Systematic comparison with the imiquimod-induced mouse model revealed numerous species-specific molecular signatures of psoriasis, including human-specific NFKB1 activation and STAT1 involvement, indicating that the current mouse model captures only limited aspects of the disease. We further introduce psoSpotter, a disease-biomarker-selection algorithm that, coupled with in silico perturbation using scSAID data, uncovers PPIA as a novel psoriasis drug target, illustrating the potential of scSAID for identifying therapeutic approaches. Overall, scSAID delivers a large-scale, cross-species skin single-cell resource and analysis platform, opening new opportunities for the discovery of disease-relevant targets in skin diseases.

bioinformatics↗

bioRxiv2026

PCIF1 loss licenses antitumour immunity via cholesterol biosynthesis

Cholesterol biosynthesis is classically viewed as a tumour supportive metabolic programme, yet cholesterol-associated metabolic states can paradoxically coincide with improved responses to immune checkpoint blockade (ICB)1, highlighting an unresolved context-dependent relationship between cholesterol homeostasis and antitumour immunity. Here we identify PCIF1, a cap-specific RNA methyltransferase2, as a tumour-intrinsic brake on the inflammatory potential of cholesterol biosynthesis. PCIF1 depletion had limited effects on tumour cell proliferation in vitro, but suppressed tumour growth in immunocompetent, not immunodeficient, hosts and sensitized immune-refractory syngeneic tumours to ICB. Immune profiling by single-cell RNA sequencing, flow cytometry and multiplex immunofluorescence revealed increased CD8+ T cell infiltration in PCIF1-deficient tumours, and CD8+ T cell depletion restored tumour growth. Mechanistically, PCIF1 loss selectively enhanced translational engagement of SCAP, activated SREBP2-dependent cholesterol biosynthesis and promoted intracellular cholesterol accumulation. Unexpectedly, activation of this cholesterol programme induced a tumour cell inflammatory cytokine state enriched for T cell-recruiting chemokines, including CXCL10. Pharmacological perturbation of the SCAP-cholesterol axis attenuated this inflammatory programme, placing cholesterol sensing upstream of PCIF1 loss-induced tumour cell inflammatory activation. In ICB-treated patient cohorts, high PCIF1 expression in pre- and on-treatment samples was associated with poor clinical response, and across tumour types, PCIF1 expression inversely correlated with cytolytic immune signatures. These findings reveal PCIF1-mediated SCAP translational control as a tumour cell checkpoint that constrains the antitumour inflammatory activity of a canonical growth-associated cholesterol programme and shapes checkpoint therapy responsiveness.

cancer biology↗

bioRxiv2026

Spatial Glyco-Codes Define Human Liver Pathology and Progression

Glycosylation is a fundamental process regulating cellular function, tissue organization, and disease progression. However, comprehensive glycan profiling at single-cell spatial resolution remains largely inaccessible, particularly in clinical archival tissues. Here we develop spatial-GPT, a multimodal platform for simultaneous profiling of glycans, proteins, and/or transcripts in archival formalin-fixed paraffin-embedded (FFPE) tissues. Using a panel of 30 DNA-encoded lectins recognizing major mammalian glycan motifs and structural classes, sequencing-based spatial-GPT (DBiT-GPT) mapped the spatial glycome, proteome, and transcriptome across 16 human liver specimens encompassing steatosis, fibrosis, cirrhosis, and hepatocellular carcinoma (HCC), leading to identification of spatial glyco-codes - combinatorial glycan states associated with distinct cellular identities, tissue features, and pathological processes. Unexpectedly, glyco-codes alone were sufficient to resolve major cell types, disease states, and HCC subtypes, revealing a previously unappreciated level of biological information encoded within the tissue glycome. Spatial glycomics uncovered tumor-like glyco-codes in premalignant regions, suggesting that glycan reprogramming may precede overt malignant transformation. Using imaging-based single-cell spatial glycan-protein profiling (CODEX-GP), we track glyco-codes across the whole-tissue architecture of 3 representative HCC samples. We further examined the glyco-codes across more than 300 patient specimens and quantified cell-type- and disease-specific glyco-codes as well as glycan-defined immune-evasion, T-cell-exhaustion, and steato-fibrotic niches. Together, these findings establish spatial glyco-codes as a previously unrecognized layer of tissue organization that encodes cellular identity, tissue function, and disease progression. The ability of glyco-codes to distinguish major liver pathologies across independent patient cohorts further highlights their potential as a new class of molecular histopathology biomarkers.

pathology↗

bioRxiv2026

Cellfm-datasets: A Unified Data Infrastructure for Single-Cell and Spatial Transcriptomics Foundation Model Pretraining

Large-scale cell foundation models are increasingly limited not only by model architecture, but also by the data infrastructure required to repeatedly sample sparse transcriptomic profiles from out-of-core cohorts. AnnData/H5AD has become a standard exchange format for single-cell and spatial omics analysis, yet its HDF5-backed layout is not designed for high-frequency random mini-batch loading under multi-worker and distributed pretraining. We present Cellfm-datasets, a data infrastructure artifact that converts H5AD cohorts into a self-describing compressed sparse row (CSR) memmap layout and exposes the resulting corpus through Hugging Face Dataset and IterableDataset interfaces. The artifact stores a shared gene vocabulary, per-sample metadata, optional spatial coordinates, observation metadata, manifests, and checksums, and reconstructs sparse cell or group records at runtime without dense expansion. A unified sampling abstraction supports random-cell groups, manifest-defined biological regions, and coordinate-based spatial blocks, with deterministic sharding across distributed ranks and data-loader workers. Spatial demonstrations on P14 mouse brain transcriptomics sections illustrate region- and block-level sampling over real anatomical structures. In controlled benchmarks on a public heterogeneous ModelScope scRNA-seq subset, Cellfm-datasets reached 60,571 {+/-} 1,734 samples/s in single-core random loading, scaled to approximately 160,000 samples/s with eight workers, and maintained near-constant process-private memory while reading up to one million cells. By moving sparse single-cell and spatial corpora from model-specific loader code into reusable, validated, and framework-native dataset artifacts, this design may reduce the engineering burden of reproducible cell foundation model pretraining and make repeated training runs, model comparisons, and mixed-modality data reuse easier to standardize. Code availabilityhttps://github.com/PangJiangShuan/cellfm-datasets

bioinformatics↗