Biology subjects

Dai, J.

Publications and source records attributed to Dai, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Sensitive untargeted metabolomics via 3-nitrophenylhydrazine derivatization maps gut microbiota-related metabolites across multiple mouse biological compartments

The gut microbiome communicates with distal organs via small molecules, yet systematic tracking of gut microbiota-related metabolites across host compartments remains limited. Although 3-nitrophenylhydrazine (3-NPH) derivatization improves sensitivity for carboxyl-, carbonyl- and phosphate-containing metabolites, the resulting derivatives cannot be identified against conventional spectral libraries. Here, we developed a 3-NPH derivatization-based untargeted metabolomics approach coupled with a purpose-built theoretical spectral library and identified 301 gut microbiota-related metabolites across five compartments of young and adult mice of both sexes. Cross-compartment comparisons revealed compartment-specific compositions and fewer sex-associated differences in serum, liver and brain than in the gut. Spearman correlation analysis along the gut-brain and gut-liver axes identified coordinated metabolite pairs, including glycolysis intermediates and stereochemically diverse fatty-acid derivatives, supporting transmission of gut microbiota-related metabolites to circulation and distal organs. Our approach overcomes the long-standing identification bottleneck of derivatization-based untargeted metabolomics, providing a transferable platform for compartment-resolved mapping of gut microbiota-related metabolites and highlighting the gut-brain and gut-liver axes as routes for microbiota-host metabolite exchange.

systems biology↗

bioRxiv2026

CHAIR an antigen-resolved antibody-reactome resource for healthy adult immune aging

Antigen-recognition histories accumulate across adult life, but existing human aging resources largely emphasize host-state measurements rather than antigen-resolved humoral memory. We present CHAIR, the Chinese Healthy Aging Immune Resource, which integrates self-antigen, human virome and toxin/virulence-factor PhIP-seq with routine clinical measurements and T/B/NK phenotyping in clinically screened adults aged 20-94 years. The resource framework includes 1,008 unique PhIP-seq samples, 995 clinical records, 977 T/B/NK records and 853 participants with all three layers. Across modeled spaces comprising 23,584 self-antigen targets, 210 virome targets and 1,258 virulence-factor source targets, most measured antibody-reactivity architecture was consistent with broad preservation within domains, whereas age- and sex-associated signals were concentrated in focal targets and modules. Together, CHAIR provides a traceable, antigen-resolved reference framework based on clinically screened adults for investigating focal humoral remodeling across healthy adult aging.

immunology↗

bioRxiv2026

GluD1 Modulates GluN2B-containing NMDAR Function and Plasticity at Subicular Synapses

Dysregulation of the delta-type glutamate receptor GluD1 and N-methyl-D-aspartate receptors (NMDARs) is implicated in neuropsychiatric disorders including schizophrenia and intellectual disability, and GluD1 modulates NMDAR response in hippocampal neurons. However, the precise mechanisms by which GluD1 influences specific NMDAR subtypes remain undefined, representing a critical gap given the reliance of synaptic plasticity and cognition on NMDAR composition. GluN2A- and GluN2B-containing NMDARs are essential for synaptic long-term potentiation (LTP) and contextual learning and memory. Here, we used CRISPR/Cas9 to generate GluD1 knockout (KO) in cultured hippocampal neurons and observed a selective decrease in GluN2B-containing NMDAR responses. In acute hippocampal slices, GluD1 KO similarly reduced GluN2B-containing NMDAR currents at ventral CA1[->]subiculum synapses and impaired LTP at these synapses. In vivo, region-specific GluD1 deficiency in the ventral subiculum disrupted long-term contextual memory, indicating a critical role for GluD1 in cognitive processes. These findings demonstrate that GluD1 is indispensable for preserving GluN2B-containing NMDAR function, synaptic plasticity, and memory, providing molecular insight into how GluD1 regulates NMDAR subtypes implicated in synaptic dysfunction in neuropsychiatric disorders. Understanding this mechanism will guide the development of therapeutic strategies that selectively target GluD1-dependent modulation of NMDAR subtypes in brain disease.

neuroscience↗

bioRxiv2026

Hurricane-induced structural disturbance amplifies forest vulnerability to subsequent heatwaves

Sequential hurricane-heatwave events threaten forest resilience via understudied legacy effects. Using Bayesian Structural Time Series, piecewise Structural Equation Modeling, and a 21-event global synthesis, we quantify how structural degradation non-linearly amplifies productivity loss during subsequent heatwaves. Our Hurricane Michael (2018) case study reveals significant negative GPP legacy effects during the 2019 heatwave. Intact, tall and diverse canopies buffer microclimates and moderate thermal sensitivity. Hurricane-induced structural simplification removes this protection, exposing temperature-sensitive shaded leaves to extreme stress. We identified a context-dependent hydraulic trade-off: structural complexity provides shading but exacerbates forest sensitivity to water deficits during peak heat, the vulnerability of which reverses during the recovery phase. Globally, these legacy effects are triggered by heatwave intensity and modulated by soil type, with loamy-soil forests most vulnerable. These findings highlight the critical role of forest structure in forest responses to compound disturbances. Neglecting structural legacies in Earth System Models likely underestimates risks to global carbon sinks.

ecology↗

bioRxiv2026

CD133+ progenitor cells promote pulmonary hypertension through CXCR4 signaling

BackgroundPulmonary hypertension (PH) is characterized by pulmonary vascular remodeling and smooth muscle cell accumulation, but the progenitor-like cells that contribute to this process remain incompletely defined. MethodsWe combined analyses of human pulmonary arterial hypertension lungs and experimental PH models with bulk and single-cell RNA sequencing, lineage tracing, inducible ablation of CD133+ cells, and conditional deletion of Cxcr4 in CD133+ cells. ResultsCD133 expression was markedly increased in human and experimental PH lungs. Transcriptomic analyses identified inflammatory, metabolic, chemokine-associated, and smooth muscle cell-like programs in CD133+ cells from PH lungs. Lineage tracing showed that CD133+ cells contributed to endothelial and smooth muscle cell compartments during experimental PH. Genetic ablation of CD133+ cells attenuated hypoxia-induced PH and pulmonary vascular remodeling, whereas Cxcr4 deletion in CD133+ cells reduced PH severity. ConclusionsCD133+ progenitor cells are functional contributors to pulmonary vascular remodeling, and CXCR4 signaling mediates their pathogenic activity. Targeting pathogenic CD133+ cell states or CXCL12/CXCR4 signaling may provide a strategy to limit vascular remodeling in PH.

pathology↗

bioRxiv2026

Distillation enables scalable high-fidelity virtual screening across ultra-large chemical libraries

Accurate virtual screening of ultra-large chemical libraries remains challenging. Existing approaches rely on lower-fidelity scoring functions or sampling-based strategies that can limit predictive accuracy and bias the exploration of chemical space. Here, we present FastBindRank, a distillation-based framework that transfers the predictive power of the structure-based model Boltz-2 into an efficient sequence-based surrogate. Trained on [~]1% of the 122-million-compound PubChem library, FastBindRank enables high-fidelity screening at scale. Applied to histone deacetylase 11 (HDAC11), FastBindRank substantially enriched high-confidence binders relative to the background chemical space. The lightweight model captured structural patterns associated with predicted binding, revealing structural determinants of binding. Under a comparable computational budget, FastBindRank achieved a 74-fold increase in hit rate and over a 30-fold increase in discovery yield over direct subset-based screening. Experimental validation confirmed the activity of two novel compounds. These results establish distillation as a practical strategy for scalable, high-fidelity virtual screening of ultra-large chemical libraries.

bioinformatics↗

bioRxiv2026

Ciliary integrity defines a central canal repair checkpoint linking microtubule stabilization to spinal cord regeneration

Microtubule-stabilizing agents consistently improve functional recovery after spinal cord injury (SCI), yet the structural mechanism underlying their shared therapeutic effects remains unclear. Here, we find that chemically distinct stabilizers converge on preservation of ciliary integrity within central canal-associated cells, including ependymal cells and cerebrospinal fluid-contacting neurons. Using complementary SCI models, including complete transection and crush injury, we observe that maintenance of ciliary architecture is associated with reduced glial scarring, improved tissue continuity, and enhanced locomotor recovery. Single-cell transcriptomic analysis further identifies these cell populations as prominent responders to microtubule stabilization, with ciliogenesis-related programs selectively preserved. Importantly, pharmacological disruption of cilia-associated signaling attenuates recovery, whereas promoting ciliogenesis partially recapitulates therapeutic effects, identifying ciliary integrity as a critical cilia-associated structural dependency that contributes to microtubule-stabilizer-mediated spinal cord repair. Together, these findings identify a cilia-dependent central canal regenerative niche as a candidate structural checkpoint linking microtubule stabilization to functional recovery after SCI and identify ciliogenesis as a therapeutically actionable target for SCI. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=151 SRC="FIGDIR/small/733052v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@320578org.highwire.dtl.DTLVardef@5240dorg.highwire.dtl.DTLVardef@181f251org.highwire.dtl.DTLVardef@4bacd1_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2026

NF1 deficiency induces metabolic reprogramming and epithelial-mesenchymal transition in glioblastoma

BackgroundMetabolic reprogramming is a common occurrence in tumor cells, where enhanced glycolysis promotes cell growth, invasion and migration. NF1 is tumor suppressor gene that downregulates the encoded neurofibromin protein. However, the effects of NF1 on energy metabolism and epithelial-mesenchymal transition (EMT) in glioblastoma multiforme (GBM), as well as the underlying molecular mechanisms, remain unclear. MethodsCRISPR/Cas9 gene editing technology was employed to construct GBM cell lines with NF1 gene mutations. Metabolomics was utilized to examine the impact of NF1 on metabolic remodeling in GBM. The Seahorse XF24 extracellular flux analyzer was used to detect the effect of NF1 knockdown on glycolysis and mitochondrial oxidative phosphorylation in GBM cells. Wound healing assay and Transwell chamber assay were utilized to detect the effect of NF1 on GBM cell invasion. Orthotopic tumor model in nude mice was established to explore the role of NF1 in vivo. In addition, Co-IP, western blotting, and immunofluorescence were used to explore the changes of key enzymes in glycolysis and mitochondrial oxidative phosphorylation and the relationship between NF1 and MFN1. ResultsThe expression of NF1 is decreased in glioma tissues and is significantly correlated with patient prognosis. NF1 knockdown may promote the invasion, migration, and EMT of GBM cells. At the same time, the activation of the AKT/mTOR signaling pathway promotes aerobic glycolysis in GBM cells, promotes mitochondrial division through targeted regulation of MFN1, and inhibits mitochondrial oxidative phosphorylation. NF1 deficiency promotes EMT in GBM cells by enhancing aerobic glycolysis and mitochondrial division. ConclusionNF1 deficiency promotes GBM glycolysis by activating the AKT/mTOR signaling pathway and inhibits the mitochondrial oxidative phosphorylation by regulating MFN1; NF1 deletion promotes GBM EMT by remodeling the pattern of energy metabolism.

Cancer Biology↗

bioRxiv2026

Is level-1 blob reconstruction under the network multispecies coalescent easy?

Hybridization is an important evolutionary process, commonly modeled by the network multispecies coalescent. Reconstructing evolutionary histories under this model is notoriously costly, even for level-1 networks where hybridization events are isolated from each other. The widely used methods that combine speed with statistical guarantees rely on quartet concordance factors computed for all subsets of four species, resulting in an O(n^4k) bottleneck that severely limits scalability to large numbers of species (n) and genes (k). Among quartet-based methods, NANUQ+ is notable because it decomposes the problem into two steps: first reconstructing a tree of blobs, which compresses each non-treelike part of the network, called a blob, into a single vertex, and second reconstructing the internal structure of each level-1 blob, specifically its circular order and hybrid vertex. Here, we investigate whether level-1 blob reconstruction is difficult once the tree of blobs is known. We present a fast and statistically consistent algorithm, called NetCS, based on two simple primitives: majority voting and merge sort, circumventing the bottleneck of computing all quartet concordance factors. In simulations, NetCS achieved comparable accuracy to NANUQ+ and was dramatically faster, enabling analyses of 200 taxa and 1000 genes in only a few minutes. Both methods attained near-perfect accuracy when given the true tree of blobs; however, their performance degraded in end-to-end pipelines due to errors in tree of blobs reconstruction. Strikingly, even methods that reconstruct level-1 networks directly struggled to accurately predict hybrid ancestry. Our results suggest that reconstructing level-1 blobs is unexpectedly easy once the tree of blobs is known, and that a major challenge for phylogenetic network inference lies in accurate tree of blobs reconstruction.

bioinformatics↗

bioRxiv2026

Integrating Histology with Spatial Molecular Programs Using a Multimodal Foundation Model

Histopathological assessment remains central to cancer diagnosis and stratification, yet its mechanistic interpretation remains limited without molecular context. To address this, we developed SQUALL, a multimodal foundation model integrating histology with spatial molecular programs. For pretraining, we assembled histMol, a large-scale corpus of 1.76 billion paired histology-spatial transcriptomics spots/bins across 33 tissues and 12 platforms from 3,446 tissue sections. Following pretraining, SQUALL enables transcriptome-wide virtual biomarker profiling, prognostically relevant spatial niches discovery, and integrative disease progression modeling. Leveraging its multimodal embeddings, SQUALL identifies niches associated with tertiary lymphoid structure (TLS) maturation and ovarian cancer relapse, reconstructs molecular trajectories of breast cancer invasion across 325,112 spots, and uncovers underlying transcriptional programs. Applied to whole-slide images from 898 patients, SQUALL outperforms existing pathology foundation models in outcome prediction while enabling interpretable risk stratification. Together, these results establish spatially aligned multimodal pretraining as a new paradigm for extending molecular insights into pathology images.

bioinformatics↗

bioRxiv2026

The discovery of missing taxane C13α-O-deacetylases re-delineates the biosynthetic pathway of paclitaxel

The prevalence of naturally occurring C13-acetoxy taxanes, together with the presence of a native C13-acetyltransferase in yew trees, suggests that the natural biosynthetic pathway for paclitaxel may involve a cryptic C13-O-deacetylation step. However, whether a putative taxane C13-O-deacetylase (T13dA) acts in the pathway of paclitaxel biosynthesis remains elusive. Herein, we functionally characterized two novel taxane C13-O-deacetylases (T13dA1 and T13dA2) from Taxus x media cell cultures, providing experimental evidence for the molecular and biochemical plausibility of C13-O-deacetylation in paclitaxel biosynthesis in Taxus species. Furthermore, T7dA1, a novel taxane C7{beta}-O-deacetylase with higher activity than the reported T7dA was discovered and characterized here. Notably, we reconstituted a new 19-gene pathway enabled by the integration of a C13-O-acetylation-deacetylation module for the de novo biosynthesis of baccatin III in Nicotiana benthamiana leaves, reaching a yield of 71{square} g{square} g-1 DW, much higher than that obtained from the 17{square} gene pathway lacking this module. These findings not only demonstrate the functional importance of the C13-O-acetylation-deacetylation module as a branch within the paclitaxel biosynthetic network, but also expand the multi-branched taxane metabolic network in Taxus and provide novel enzymatic tools and engineering strategies to facilitate heterologous pathway reconstitution and efficient paclitaxel production.

biochemistry↗

bioRxiv2026

Single-Cell Transcriptomic Signatures Enable Stratified Combination Therapy for Platinum-Resistant Ovarian Cancer

In high-grade serous carcinoma (HGSC), extensive intra-tumoral heterogeneity hinders complete eradication and remains a major obstacle to developing combination therapies capable of eliminating subpopulations resistant to standard-of-care treatment. Using single-cell RNA sequencing of 72 samples from 54 HGSC patients spanning treatment-naive, post-neoadjuvant chemotherapy and relapse stages, we established a carboplatin-anchored framework that identifies transcriptional signatures of intrinsic (pre-existing) and adaptive (therapy-induced) resistance in individual tumors and prioritizes mechanistically matched drugs to potentiate carboplatin efficacy. Candidate compounds were ranked by integrating orthogonal resources--viability (GDSC, PRISM) and perturbational transcriptomics (L1000, Perturb-seq)--to reduce context bias. Among 64 candidates, three carboplatin adjuvants enhanced long-term efficacy in patient-derived organoids (PDOs), and pevonedistat further significantly reduced tumor burden in orthotopic xenografts. This tiered validation pipeline--from short-term and long-term PDOs and in vivo orthoptic xenografts--establishes a translational framework linking single cell resistance programs to actionable, tumor-specific, carboplatin-anchored combinations for HGSC.

cancer biology↗

bioRxiv2026

Towards Cross-Sample Alignment for Multi-Modal Representation Learning in Spatial Transcriptomics

AO_SCPLOWBSTRACTC_SCPLOWThe growing number of spatial transcriptomics (ST) datasets enables comprehensive multi-modal characterization of cell types across diverse biological and clinical contexts. However, integration across patient cohorts remains challenging, as local microenvironment, patient-specific variability, and technical batch effects can dominate signals. Here, we hypothesize that combining specialized transcriptomics correction methods with deep representation learning can jointly align morphology, transcriptomics, and spatial information across multiple tissue samples. This approach benefits from recent transcriptomics and pathology foundation models, projecting cells into a shared embedding space where they cluster by cell type rather than dataset-specific conditions. Applying this framework to 18 skin melanoma, 12 human brain, and 4 lung cancer datasets, we demonstrate that it outperforms conventional batch-correction approaches by 58%, 38%, and 2-fold, respectively. Together, this framework enables efficient integration of multi-modal ST data across modalities and samples, facilitating the systematic discovery of conserved cellular programs and spatial niches while remaining robust to cohort-specific batch effects. Code availabilityhttps://github.com/ratschlab/aestetik

bioinformatics↗

bioRxiv2026

A Dual-Phase Strategy to Integrate the VITEK MS RUO Database into Routine Clinical Practice: From Validation of Analytical Performance to Implementation of an Automated Workflow

BackgroundMatrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is pivotal in clinical microbiology. The VITEK MS Research Use Only (RUO) database offers broader species coverage, yet its clinical adoption is hindered by insufficient performance validation against the approved in vitro diagnostic (IVD) database and inefficient manual operational workflows. ObjectiveThis two-phase study first aimed to develop and evaluate an automated integrated workflow to enhance laboratory efficiency and diagnostic capability. MethodsThe RUO databases two-tier identification architecture was utilized and in-house automated relay software was developed to parse IVD results and fully automate RUO reanalysis. Phase 1 (Mar 2021-Jun 2022) involved parallel manual testing of 2,432 isolates with both databases to analyze concordance and supplementary performance. Phase 2 (Jul-Nov 2022) prospectively incorporated 3,954 isolates to implement and assess the "IVD screening - automated RUO reanalysis" workflow. ResultsPhase 1 demonstrated high RUO-IVD concordance (95.7% species/genus agreement). The RUO database correctly identified 98.9% of isolates and provided valid supplementary identification for 84.4% (108/128) of IVD-failed cases, with Tier 2 contributing 28.9%. Phase 2 revealed that the integrated workflow increased the overall identification rate from 95.5% to 98.7%, with Tier 2 contributing an additional 14.5%. The automated software reduced reanalysis turnaround time by > 75%, saving consumables and labor. ConclusionThe VITEK MS RUO database is a reliable and complementary tool to the IVD database. Integration with automated software creates an efficient, compliant clinical workflow, providing a practical model to enhance pathogen identification for infectious disease management. IMPORTANCEThe present study bridges the validation-to-application gap for the VITEK MS RUO database. We confirm its high concordance (95.7%) and complementary value to the IVD database, quantify the impact of manual workflow inefficiency and introduce an automated software solution. The strategy highlights the key role of Reference Spectra (Tier 2) in expanding coverage and simultaneously improves diagnostic efficacy ([~]99% ID rate), operational efficiency (> 75% time saved) and cost-effectiveness, offering a practical model to accelerate pathogen reporting and to guide therapy.

microbiology↗

bioRxiv2026

eScreen: a deep learning framework for functionally decoding the regulatory genome at single-nucleotide resolution

The human genome is densely populated with cis-regulatory elements (CREs), yet deciphering their functional regulatory syntax and combinational logic remains a fundamental challenge. Here, we integrate 379 genome-scale CRISPR screen experiments, encompassing 21 million perturbations across 23 cell types, to construct a compendium of 41,239 high-confidence functional CREs from 530,527 candidates. Leveraging this resource, we develop eScreen, a deep learning model built on the StripedHyena2 architecture to functionally decode the regulatory genome at single-nucleotide resolution. eScreen achieves three primary functions: (1) predicts genome-wide cell-type-specific CRE functional activity with high accuracy, outperforming existing models; (2) provides mechanistic interpretation of regulatory syntax at single-nucleotide resolution; (3) dissects the functional organization of enhancer clusters through in silico perturbation analysis. We perform multiple independent CRISPR knockout, CRISPR interference (CRISPRi), and base editing screens to validate these functions of eScreen both at scale and on individual cases. Furthermore, we provide an interactive web server (https://escreen.huanglabxmu.com/) for the community to access the integrated CRISPR screen resources and eScreen functions. Collectively, our work establishes a highly precise and convenient tool to decode the causal effects of the regulatory genome.

genomics↗

bioRxiv2026

A single-cell transcriptomic atlas of the periventricular proliferative zone in the late gestation fetal brain in the pigtail macaque

BackgroundThe fetal brain undergoes rapid changes in late gestation, when waves of neurogenesis and gliogenesis shape cortical circuitry. The periventricular proliferative region and adjacent white matter are enriched in neuroprogenitor cells, newborn neurons, and interneurons, which is challenging to study in the late gestation human fetal brain. The nonhuman primate (NHP) provides a powerful translational model to overcome this limitation, given its close similarity to human neurodevelopmental trajectories. The study objective was to construct a single-cell RNA-Seq (scRNA-Seq) atlas of the late-gestation fetal brain of the pigtail macaque (Macaca nemestrina), focused on the periventricular proliferative zone. MethodsA sample of the lateral ventricular wall, subventricular zone, and overlying white/gray matter was dissociated into single cells and processed through the 10X Genomics pipeline, followed by SoupX removal of ambient RNA, and Seurats pipeline to aggregate, cluster and annotate single-cell populations. Monocle3 was used to determine pseudotime and map lineage progression. ResultsThis analysis captured diverse populations of neuroprogenitors, newborn neurons, developing lineages of excitatory and inhibitory neurons, oligodendrocyte and astrocyte lineages, and resident immune and endothelial cells. ConclusionsSingle-cell populations from the third-trimester nonhuman primate fetal brain are highly similar to those in the human fetus. This late-gestation single-cell atlas of the periventricular proliferative zone provides a unique reference for progenitor, neuronal, glial, vascular, and immune cell states during a critical window of primate neurodevelopment, enabling mechanistic interrogation of how inflammatory, infectious, or hypoxic insults disrupt vulnerable neurogenic niches.

genomics↗

bioRxiv2025

Organization of mouse prefrontal cortex subnetwork revealed by spatial single-cell multi-omic analysis of SPIDER-Seq

Deciphering the connectome, anatomy, transcriptome and spatial-omics integrated multi-modal brain atlas and the underlying organization principles remains a great challenge. We developed a Single-cell Projectome-transcriptome In situ Deciphering Sequencing (SPIDER-Seq) technique by combining viral barcoding tracing with single-cell sequencing and spatial-omics. This empowers us to delineate a integrated single-cell spatial molecular, cellular, anatomic and projectomic atlas of mouse prefrontal cortex (PFC). The projectomic and transcriptomic cell clusters display distinct modular organization principles, but are coordinately configured in the PFC. The projection neurons gradiently occupied different territories in the PFC aligning with their wiring patterns. Importantly, they show higher co-projection probability to the downstream nuclei with reciprocal circuit connections. Moreover, we integrated projectomic atlas with their distinct spectrum of neurotransmitter/neuropeptide and the receptors-related gene profiles and depicted PFC neural signal transmission network. By which, we uncovered potential mechanisms underlying the complexity and specificity of neural transmission. Finally, leveraging machine learning, we predicted neuron projections with high accuracy by combining gene profiles and spatial information. As a proof of concept, we used this model to predict projections of fear recall engram neurons. This study facilitates our understanding of brain multi-modal network and neural computation.

neuroscience↗

bioRxiv2025

Super-CUT&Tag: A Sensitive, Spatially Resolved Approach for Epigenomic Profiling in Tissue Sections

Spatial profiling of protein-DNA interactions is essential for understanding gene regulatory processes, but current methods suffer from low sensitivity, limited resolution, and complex workflows. Here we introduce Super-CUT&Tag (Solid-phase interface embedded with an Ultra-dense DNA barcode array to Profile Epigenomic landscapes for spatially Resolved CUT&Tag), a robust spatial epigenomic method that directly transfers in situ protein-DNA interactions from tissue sections onto a pre-fabricated spatially barcoded array. Incorporating 3D polyamidoamine (PAMAM) dendrimers markedly improves chromatin capture efficiency, achieving several-fold higher sensitivity compared to current spatial CUT&Tag approaches. Using Super-CUT&Tag, we profile H3K27ac spatial landscape and uncover previously hidden active-chromatin heterogeneity across mouse embryonic tissues and stages. Integration with spatial transcriptomics further reveals spatiotemporal enhancer regulation dynamics of Neurod2 during corticogenesis. By overcoming key bottlenecks in sensitivity, resolution and usability, Super-CUT&Tag establishes a powerful platform for spatial epigenomic profiling in complex tissues.

genetics↗