Biology subjects

Jin, W.

Publications and source records attributed to Jin, W..

At least 19 recordsLinked to original sources

bioRxiv2026

Optimized dosing of spatially heterogeneous radiopharmaceutical therapy reprograms poorly immunogenic tumors to enhance response to immune checkpoint blockade

Immune checkpoint inhibitors (ICIs) are ineffective in patients with poorly immunogenic tumors due to exclusion or exhaustion of effector T cells in the tumor microenvironment (TME) and/or inadequate priming of tumor-specific T cells. Preclinical and clinical studies suggest that radiopharmaceutical therapy (RPT) may overcome such challenges, but an optimal approach to RPT dosing has not been clarified in combination with ICIs. Conventional RPT dosimetry emphasizes mean absorbed radiation doses in tumors and normal tissues, neglecting the spatial distribution of this dose in the TME. We hypothesize that RPT dose heterogeneity in tumors may be leveraged to initiate spatially restricted immuno-radiobiological effects in TME that potentiate antitumor immunity when injecting an activity that delivers high dose (V10%>20 Gy) while also preserving low dose regions (V90%<2.5 Gy) in the TME and not inducing systemic lymphopenia. In studies using lutetium-177 RPT in combination with ICIs, administered activities that met these dosimetric optimization metrics occurred at different mean tumor doses for different RPT agents and different models, yet each achieved therapeutic efficacy in poorly immunogenic murine tumors. Spatial transcriptomics at day 7 after RPT revealed heterogeneous distribution of tumor cell markers with distinct dose-response profiles and localization of dendritic cell (DC) migratory markers in regions of moderate/high dose response marker expression. Combination therapy sustained conventional type 1 DC (cDC1) activation in tumor draining lymph nodes and promoted systemic expansion of antigen-specific CD8 T cells, while serial biopsies revealed effector T cell recruitment and inflammatory cytokine expression in the TME. Optimized intratumoral dose heterogeneity may enable and predict response to ICIs when combined with RPT in tumors not responding adequately to ICIs alone.

cancer biology↗

bioRxiv2026

Base Editing as a Therapeutic Strategy for Autosomal Dominant Tubulointerstitial Kidney Disease caused by Pathogenic UMOD Variants

Autosomal dominant tubulointerstitial kidney disease caused by pathogenic UMOD variants (ADTKD-UMOD) is an untreatable monogenic kidney disease in which misfolded uromodulin is retained in the endoplasmic reticulum and exerts a toxic gain-of-function effect. Here we systematically evaluate the full spectrum of base editing strategies targeting the UMOD locus. Base editors corrected a representative missense patient variant, p.Cys170Tyr, with A-to-G conversion efficiencies of up to 83.4%, restoring uromodulin trafficking to the plasmamembrane in cell lines and in human 3D kidney tubuloids. Mutation-agnostic inactivation wasachieved by four routes: premature stop codon introduction, splice-site disruption, allele-specific stop codon introduction and promoter attenuation. Maximum on-target efficienciesranged from 44.1% to 71.9%, providing a strategy set applicable across the UMOD allelicspectrum. Endogenous UMOD expression is rarely recapitulated in human cell models,leaving strategies that act on the endogenous gene difficult to assess in patient cells. Wetherefore established CRISPR activation (CRISPRa) of the endogenous UMOD promoterand confirmed its ability to upregulate UMOD expression in human urine-derived cells. Thisapproach further enabled quantification of endogenous UMOD transcript reduction followingbase editing in HEK293 cells. These results establish base editing as a versatile approachfor ADTKD-UMOD and provide a primary human system for testing interventions targetingendogenous UMOD expression, from nucleic acid-based silencing to small molecules.

genetics↗

bioRxiv2026

Neural Representations of Visual Anagrams in Macaque Inferotemporal Cortex

Visual recognition requires stable representations of object identity despite large changes in the retinal image. Yet this stability must be selective: some transformations change not only how an image looks, but also what object it appears to depict. Visual anagrams highlight this challenge: a single image can resemble two different objects at different orientations, such as an elephant and a rabbit. Here, we asked how macaque inferotemporal (IT) cortex represents such transformations. We recorded large neuronal populations while presenting visual anagrams and unambiguous exemplars of their two interpretations across rotations. Neurons preferring one exemplar tended to prefer anagram orientations supporting the corresponding interpretation. At each of the two interpretation-relevant canonical angles, population responses more closely resembled those to the matching exemplar than those to the nonmatching exemplar. This matching advantage persisted when both exemplars were presented at the alternative canonical angle. Decoders trained exclusively on exemplars across rotations also tracked the shifts in anagram representations. Visual models showed anagram-exemplar alignment as well, with stronger alignment in models with greater relative shape preference. These findings suggest that transformation tolerance in IT is sensitive to what an image appears to depict, while relative shape preference is associated with similar representational organization in visual models.

neuroscience↗

bioRxiv2026

Pan-cancer remodeling of reactive oxygen species homeostasis: distinct roles of the ROS-generation and antioxidant arms in immune context and outcome

Reactive oxygen species (ROS) are double-edged in cancer: tumor cells sustain high ROS generation while up-regulating antioxidant defense, so that the net balance between the two arms, rather than absolute ROS abundance, is the biologically meaningful quantity. Whether that balance defines a conserved tumor state across cancer types has been unclear. Here an experimentally measured ROS phenotype, obtained from a three-channel gold-nanocluster array, was generalized to public transcriptomes through a 107-gene ROS program scored in a large cell-line panel and in pan-cancer tumor and adjacent-normal tissue. The optical readout was reproducible and fully discriminative between cell lines, establishing the fingerprint as a quantitative starting point. In tumors, the generation and antioxidant arms were coordinately up-regulated relative to normal tissue, yet the two arms dissociated in their biology. The composite balance score tracked reduced immune infiltration consistently across cohorts, but arm-level decomposition showed that it was carried by low generation-arm activity in immune-cold tumors and followed arithmetically from how the balance score is defined; the association does not implicate antioxidant defense in immune infiltration. The clinical association pointed the other way: adverse outcome was attributable to the antioxidant arm, whereas generation was null. In cohort-held-out validation, tumors were separated from adjacent normal tissue, with redox programs outperforming generic phenotypic programs, indicating that the same program transfers across tumor types. Tumor remodeling of ROS homeostasis is therefore widespread, but its two arms carry distinct meanings: the balance score, driven by its generation term, reports immune context, whereas the antioxidant arm reports clinical risk.

cancer biology↗

bioRxiv2026

Genomic splice-donor disruption rescues systemic disease in progeria

RNA splicing determines which protein isoforms a gene produces, and aberrant splice-site activation can cause severe disease. In Hutchinson-Gilford progeria syndrome, a synonymous LMNA mutation strengthens a cryptic 5' splice donor site to produce progerin, a toxic lamin A isoform driving premature cardiovascular death. Within this cryptic donor, the activating mutation lies near the canonical GT dinucleotide required for splice-site recognition. A single guide can therefore preferentially pair with the mutant sequence while positioning Cas9 cleavage at this dinucleotide. Here we show that CRISPR/Cas9-mediated disruption of this splice site suppresses progerin without requiring precise correction of the activating mutation and prolongs lifespan in progeroid mice. In patient-derived fibroblasts and induced pluripotent stem cell-derived mesenchymal stem cells, this intervention reduced progerin by 92.7-96.8% while retaining lamin A and lamin C expression. A single neonatal injection of AAV9 carrying the corresponding mouse guide increased median survival from 115 to 279 days in Cas9-expressing LmnaG609G/G609G mice. Treatment attenuated aortic, skeletal and multiorgan pathology. Treated homozygous pairs produced 52 offspring across seven litters. These findings establish pathogenic splice signals as genomic targets for sustained suppression of toxic isoforms while retaining canonical gene outputs.

cell biology↗

bioRxiv2026

Cross-Species Comparison of Topologically Associating Domains (TADs) in Cereals Reveals Their Role in Genome Stability During Evolution

Topologically associating domains (TADs) are essential structural and functional modules of the genome that play a crucial role in regulating gene expression. In this study, we systematically investigated the conservation and evolution of TADs in five closely related crops, including maize, sorghum, coix, foxtail millet and broomcorn millet. Our results show that 74% of TAD boundaries are conserved between two inbred maize lines, B73 and Mo17, and that approximately 50% or more of TAD boundaries are conserved across different crop species. TAD number remains relatively stable in the face of changes in genome size. However, the length of TADs varies depending on genome size. Furthermore, we found that large-scale transposable element expansion leads to TAD expansion, while chromosomal inversions lead to TAD fusion and the formation of new TAD boundaries. Frequent chromatin interactions between subgenome chromosomes occur after whole-genome duplication. Moreover, we also found that crossovers are enriched at TAD boundaries in maize, indicating the importance of TADs as a fundamental unit during species evolution. Overall, our study provides insights into the conservation and evolution of TADs in crop genomes and their roles in genome organization and function.

plant biology↗

bioRxiv2026

D-Mannose treats obesity by increasing adipose Treg cells and suppressing gut Firmicutes

Early-life microbiota represent an indispensable factor for the proper development and function of host metabolism and the immune system. We have demonstrated that neonatal exposure to antibiotics for the first 3 weeks (NeoATB) leads to obesity in adulthood, characterized by gut microbiota dysbiosis and dysregulated immune responses. Here, we demonstrate that feeding D-mannose suppresses NeoATB-induced obesity, accompanied by improved glucose tolerance and decreased insulin resistance. Mechanistically, D-mannose feeding decreased hypoxia and increased oxygenation and recovery of metabolic activity of adipocytes. D-mannose restored CD4+Foxp3+ST2+ Tregs, leading to a reduction of Th1 pro-inflammatory cells in the adipose tissue of NeoATB mice. Significantly, we revealed that D-mannose treatment reversed the dysregulated ratios of phylum Firmicutes to phylum Bacteroidetes in obese NeoATB mice, which was surprisingly attributed to D-mannose-mediated suppression of the growth of Firmicutes rather than an increase in the growth of Bacteroidetes. These findings should have therapeutic implications for the treatment of obesity in human patients.

immunology↗

bioRxiv2026

Elucidating enzyme-substrate specificity through co-folding foundation model

Enzymatic catalysis relies on precise structural and chemical complementarity, yet systematically mapping enzyme-substrate interactions remains a critical bottleneck. While structure-aware methods have advanced functional annotation, their reliance on predefined binding pockets and rigid-body docking fails to capture the ligand-induced conformational changes essential for catalytic turnover. Here we introduce Boltz2ESI, an end-to-end framework that predicts enzyme-substrate interactions by leveraging structural knowledge learned by a biomolecular foundation model. Through native co-folding, the framework inherently captures active-site plasticity without requiring predefined pocket annotations. Integrating these learned biophysical priors with global evolutionary context and geometric molecular descriptors, Boltz2ESI consistently outperforms state-of-the-art sequence-based and rigid-docking approaches. Extensive validation demonstrates that the framework accurately discriminates tight sub-family specificities, enabling effective candidate prioritization for biosynthetic pathway elucidation, as demonstrated on the withanolide pathway. Ultimately, this structure-dynamic approach establishes an actionable foundation for accelerating rational biocatalyst discovery and large-scale pathway de-orphaning.

bioinformatics↗

bioRxiv2026

Destabilization of intratumor Tregs by CTLA-4 engagement confers anti-CTLA-4-driven immunotherapy

Immune checkpoint inhibitors (ICI) that are antibodies against CTLA-4 have achieved therapeutic effects on multiple types of cancers 1-4, but the mechanisms underlying the therapy remain incompletely understood. In contrast to the initial theory that the antibody blockades CTLA-4 on T cells is of central importance, it has recently been demonstrated that selective reduction of CD4+Foxp3+ regulatory T cells (Tregs) in the tumor microenvironment by the antibody plays a key role in the anti-tumor effects5-8, although this phenomenon remains under debate in human patients9-12. We show here that anti-CTLA-4 antibody engages CTLA-4 in Tregs specifically in the tumor tissues to reduce their stability and survival and weaken their suppressive function through upregulating TGF-{beta} signaling. This leads to the antibody-mediated - upregulation of CD4+ and CD8+ effector T cell anti-tumor immunity and consequently cancer immunotherapy. Specifically, anti-CTLA-4 antibody directly stimulates CTLA-4 in intratumor Tregs to enhance their TGF-{beta} receptor I (T{beta}RI)-mediated TGF-{beta} signaling13. This results in reduction of IL-2 receptor CD25 expression and downregulation of lactate metabolism in intratumor Tregs to reduce their stability and survival 14-16, and also compromises their suppressive function by inhibiting Foxp3 expression. This activity requires high levels of CTLA-4 expression in the intratumor Tregs and the presence of antibody Fc receptors in the tumor tissues. Strikingly, deletion of T{beta}RI specifically in Tregs completely prevents the reduction of intratumor Tregs and abrogates the anti-CTLA-4-mediated cancer immunotherapy. In contrast to intratumor Tregs, anti-CTLA-4 antibody treatment blocks CTLA-4 in the intratumor CD4+ Foxp3- and CD8+ T effector cells and in the peripheral Tregs to decrease their T{beta}RI expression and increase their expansion due to their relatively low levels of CTLA-4 in the same tumor bearing mice. Significantly, the engagement of CTLA-4 by anti-human CTLA-4 antibody (ipilimumab) also upregulates TGFBR1 but decreases Il2RA expression and lactate metabolism in human Tregs in vitro and in humanized mice in vivo, leading to suppression of tumor progression. We have provided additional mechanism underlying anti-CTLA-4-mediated anti-tumor effects through destabilizing intratumor Tregs by CTLA-4 engagement-mediated TGF-{beta} signaling. This could lay a theoretical foundation for designing optimal immunotherapy based on anti-CTLA-4 antibody in cancer patients.

immunology↗

bioRxiv2026

Intratumoral dose heterogeneity promotes adaptive anti-tumor immunity and predicts clinical response to radiopharmaceutical therapy

Radiopharmaceutical therapies (RPT) deliver non-uniform radiation dose in tumors and the impact of this on response is poorly understood. Dose heterogeneity could engender treatment resistance in low dose regions, yet we hypothesize that a broader array of dose-dependent immuno-radiobiological mechanisms in tumor microenvironments (TME) and preservation of immune function in low-dose regions could promote adaptive anti-tumor immunity and response. In murine models, non-uniform lutetium-177 delivering <2.5 Gy to >20 Gy in a TME induced broader immunomodulatory effects and T cell-dependent survival improvement compared to more uniform distributions. Preserving low-dose regions promoted dendritic cell activation and TME infiltration of clonally expanded CD8+ T cells. In three independent cohorts of patients with prostate cancer, heterogeneous tumor dose distribution strongly correlated with improved clinical outcomes. These findings defy expected radiobiological dose-response and define a novel mechanism of action for RPT, supporting clinical investigation of dose distribution for optimizing patient selection and personalized dosing.

cancer biology↗

bioRxiv2026

PertDiffBench: Benchmarking Diffusion Models for Single-Cell Perturbation Response Prediction

Diffusion models are increasingly used to predict transcriptional responses to perturbations, but whether they improve on simpler generative and representation-based baselines remains unclear. Existing evaluations often do not separate the effects of model architecture, input representation, biological context and metric choice, making it difficult to determine where diffusion-based methods are useful. Here we introduce PertDiffBench, a standardized benchmark for diffusion-based transcriptomic perturbation prediction across single-cell and bulk RNA-seq datasets. PertDiffBench evaluates diffusion-based models across three complementary evaluation settings: standard prediction in known single-cell contexts and bulk perturbation conditions, generalization to unseen cell types, species, drugs and intermediate time points, and stress tests of feature dimensionality, input representation, noise type and gene ordering. Across these settings, diffusion models did not show a consistent advantage. scGen remained a strong baseline in common prediction tasks, whereas scDiffusion was the most competitive diffusion-based method in several generalization settings. Temporal imputation showed a different pattern, with a simple DDPM operating directly in expression space outperforming more specialized models. Stress tests showed that performance was model dependent and sensitive to feature dimensionality, encoder choice, noise type and gene ordering. Pretrained encoders did not consistently improve performance, with the classical scVI representation slightly exceeding STATE in seen-condition and unseen-cell-type settings. These results indicate that diffusion-model performance in perturbation response prediction depends strongly on task design and representation choice. PertDiffBench provides a practical framework for evaluating these models under biologically varied and stress-tested conditions.

bioinformatics↗

bioRxiv2026

Organoid-based colorectal tumor microenvironment model for immuno-oncology research

The development of cancer immunotherapies is hindered by the lack of human-relevant models that accurately translate to patient outcomes. We combine patient-derived colorectal tumor organoids (PDOs) and cancer-associated fibroblasts (CAFs) into floating extracellular matrix drops to form miniature colorectal tumors. These SHaking Organoid CO-cultures (SHOCOs) reproducibly capture key features of the tumor microenvironment (TME), including physiologically relevant ECM, hypoxic regions, and a diversified stromal compartment that captures primary CAF states. Compared with traditional PDO-based co-culture models, SHOCOs maintain immune cells in numbers, states and functional interactions that more closely reflect the physiological tumor microenvironment. The modularity of the system allowed controlled simulation of diverse patient tumor archetypes, and defining how TME components shape therapy response. Immune-rich SHOCOs treated with T-cell bispecific antibodies exhibited robust anti-tumor responses that were stronger and more rapid than their PDO-based counterparts. Stroma-rich tumors, on the other hand, diminished therapy responses by physically hindering both immune cell recruitment and limiting antibody penetration. Thus, SHOCOs enable the construction of modular tumor microenvironments, providing a versatile platform to dissect immune and stromal tumor biology and to catalyze the discovery of novel therapeutic approaches.

cancer biology↗

bioRxiv2026

Protein structure-informed deep learning enables species-specific codon optimization

Codon usage bias is highly species-specific, posing a major challenge for heterologous protein expression. Existing deep learning approaches to codon optimization rely primarily on DNA or protein sequence information and largely neglect constraints imposed by protein structure and folding. Here, we present Protein structure-Informed Species-specific Codon Optimization (PISCO), a Geometric Vector Perceptron (GVP)-based model that integrates protein sequence, three-dimensional protein structure, and host codon usage statistics to generate optimal, host-specific codon sequences. Compared with protein-structure-agnostic models, PISCO improves codon recovery by 6% and substantially increases similarity to natural coding sequences, reducing divergence by at least 42% in Codon Similarity Index (CSI), 50% in Codon Frequency Distribution (CFD), and 14% in Dynamic Time Warping (DTW) metrics. Ablation analyses demonstrate that incorporating protein folding kinetics and host-specific information is critical to these gains. Moreover, by leveraging host codon usage statistics, PISCO generalizes to optimize codon sequences for species absent from the training data. An autoregressive variant of PISCO further enhances concordance with natural codon usage patterns, at the cost of a modest reduction in codon recovery rate. Wet-lab validation confirms that PISCO-optimized sequences significantly enhance protein solubility and functional expression. Together, these results establish protein structure as a key determinant of species-specific codon optimization and provide a transferable framework for structure-aware gene design.

molecular biology↗

bioRxiv2026

A hypothalamo-septo-hippocampal circuit for REM sleep-dependent consolidation of social memory

REM sleep constitutes a critical window for memory consolidation, yet the brain circuits orchestrating this process remain incompletely defined. Here, we identify a lateral supramammillary nucleus (SuM)-medial septum (MS) projection as a REM sleep-specialized pathway essential for hippocampal memory consolidation. Fiber photometry and optrode recordings revealed that lateral SuM-MS projecting neurons were selectively active during REM sleep. REM-specific optogenetic silencing of this projection impaired consolidation of both social and contextual fear memories. Crucially, silencing of its downstream target, the MS-CA2 pathway, during REM sleep selectively disrupted social memory while sparing contextual fear memory. This functional dissection establishes a hypothalamo-septo-hippocampal circuit (lateral SuM-MS-CA2) dedicated to social memory processing, in parallel to the recently-described direct SuM-CA2 pathway. These results also position the SuM as a REM sleep-hub that routes information via parallel septal pathways to consolidate distinct memory modalities.

neuroscience↗

bioRxiv2025

FlashAffinity: Bridging the Accuracy-Speed Gap in Protein-Ligand Binding Affinity Prediction

Accurate prediction of protein-ligand interactions is central to computational drug discovery. Recent foundation models such as Boltz-2 have achieved remarkable accuracy in binding affinity prediction, yet their prohibitive computational cost remains a major barrier to large-scale virtual screening. Here we introduce FlashBind, a lightweight structure-based model that achieves a 50x speedup over Boltz-2 at inference time by replacing expensive structure prediction with a fast docking model and substituting costly PairFormer modules with a streamlined EGNN architecture. FlashBind attains early enrichment competitive with Boltz-2 on standard virtual screening benchmarks and demonstrates strong generalization to enzyme-substrate specificity prediction. To evaluate real-world applicability, we apply FlashBind to target-based antibiotic screening against the essential bacterial proteins in E. coli and show that FlashBind substantially outperforms Boltz-2 and other virtual screening baselines. Notably, several top-ranked candidates exhibit potent inhibition of DnaG and effective bacterial growth inhibition against E. coli in wet-lab validation. Together, these results demonstrate that FlashBind bridges the gap between accuracy and efficiency, enabling ultra-fast and accurate screening of massive chemical libraries for drug discovery.

molecular biology↗

bioRxiv2025

BayesCNet: Bayesian inference for cell type-specific regulatory networks leveraging cell type hierarchy in single-cell data

Understanding gene regulatory networks (GRNs) is essential for deciphering biological processes and disease mechanisms. Single-cell multiome technologies now enable joint profiling of chromatin accessibility and gene expression, offering an powerful means to infer cell type-specific GRNs. However, existing methods analyze each cell type independently or aggregate data into pseudo-bulk profiles, limiting their ability to resolve rare populations and capture cellular heterogeneity. We introduce BayesCNet, a Bayesian hierarchical model that jointly infers enhancer-gene linkages across all cell types while leveraging their hierarchical relationships for information sharing. Through extensive simulations, BayesCNet consistently outperforms state-of-the-art methods, with the largest improvements in rare cell types. When applied to real datasets, BayesCNet identifies enhancer-gene linkages with higher accuracy validated by promoter-capture Hi-C data, and reconstructs cell type-specific GRNs that highlight key regulators, demonstrating its power to resolve gene regulatory programs across diverse cell types.

bioinformatics↗

bioRxiv2025

Reference-Informed Spatial Domain Detection Using Weak Supervision for Spatial Transcriptomics

One of the key objectives in spatial transcriptomics (ST) studies is to map the complex organization and functions of tissues. We introduce GraphScrDom, a reference-informed and weakly supervised contrastive learning model that uniquely integrates expert-provided manual annotations (i.e., scribbles) on spatial grids or histology images with cell type-specific gene expression profiles derived from reference single-cell RNA-seq data to perform tissue segmentation. With only limited scribble annotations, GraphScrDom consistently outperforms existing methods across various ST platforms and at both bulk and single-cell resolutions, as evaluated by six widely used metrics, demonstrating strong generalizability and robustness. Additionally, we have developed an integrative software toolkit that includes an interactive annotation interface and a model training module for spatial domain detection, providing a unified and user-friendly framework to facilitate spatial domain analysis.

bioinformatics↗

bioRxiv2025

Therapeutic Salmonella induces long-term protective trained immunity in NK cells against cancer metastasis

Trained immunity, a form of innate immune memory initially recognized in pathogen defense, has recently been reported to aid in combating cancer. Although trained immunity has been well-characterized in myeloid lineage cells, its presence in innate lymphoid cells, particularly natural killer (NK) cells, remains largely unexplored. Here, we report that a single dose of Salmonella YB1, an attenuated candidate anticancer vaccine strain, provides long-lasting protection against cancer metastasis in mice by inducing trained natural killer (NK) cells. Functional assays coupled with multiomics analysis revealed that Salmonella-trained NK (stNK) cells establish an enduring reprogrammed epigenome characterized by enhanced pro-survival signaling and immune effector functions, resulting in more potent IFN-{gamma} release and cytotoxicity upon secondary stimulation. We further revealed that IL-12 and IL-18 are essential but insufficient for this NK cell training effect. Crucially, stNK cells far outperform the common immune checkpoint therapies, including PD-1 and TIGIT blockade, in suppressing metastasis, underscoring the unique immunological mechanisms in combating metastasis. These findings uncover a novel long-term anti-metastatic function of trained immunity in NK cells, highlighting its potential as an effective antitumor strategy.

immunology↗