Biology subjects

Li, D.

Publications and source records attributed to Li, D..

At least 73 records · Page 4Linked to original sources

bioRxiv2026

Rapid imaging of lysyl oxidase activity and fibrogenesis with a turn-on fluorophore

Fibrogenesis is essential to wound healing, but aberrant fibrogenesis is a driver of many chronic diseases and cancers. Lysyl oxidases (LOX) play a pivotal role in fibrogenesis by catalyzing the oxidation of lysine residues to reactive aldehydes (allysine) in collagens and elastin, resulting in the crosslinking and excessive deposition of these extracellular matrix components. Currently, rapid and robust histological assays to visualize the spatial distribution of LOX activity are lacking, hindering the precise validation of anti-fibrotic therapies. Here, we present a histological fluorescent staining method to visualize fibrogenesis (active fibrosis) and LOX activity in tissue sections utilizing a bioorthogonal tag and a click reaction with a turn-on fluorophore. Notably, requiring only two commercial reagents, this protocol can be completed in under two hours and is compatible with other imaging modalities, including second-harmonic generation and immunofluorescence staining. We validated this method across various healthy and fibrotic mouse and human tissue specimens.

bioengineering↗

bioRxiv2026

Reduction in Hepatic Phosphatidylcholine Biosynthesis Promotes MASH Through Copper Deficiency

Metabolic dysfunction-associated steatohepatitis (MASH) is a progressive liver disease for which the mechanisms linking lipid dysregulation to fibrosis remain poorly defined. Hepatic phosphatidylcholine (PC) content is reduced in MASH, but how this alteration drives disease progression is unclear. Here, we identify a role for copper (Cu) homeostasis as a downstream effector of impaired PC biosynthesis. Using single-nucleus RNA sequencing in complementary genetic and dietary mouse models, we found that reduced hepatic PC is associated with marked depletion of hepatic Cu and a concomitant increase in circulating Cu, indicating disrupted Cu distribution. Mechanistically, PC depletion impaired plasma membrane localization of the high-affinity Cu transporter CTR1 (SLC31A1) in hepatocytes, limiting Cu uptake. In human hepatic stellate cells, Cu promoted fibrogenic activation, whereas suppression of Cu import or pharmacologic inhibition of MAPK signaling attenuated fibronectin deposition. In vivo, liver-directed Cu supplementation restored hepatic Cu levels and reduced steatosis but failed to improve fibrosis. In contrast, pharmacologic Cu chelation with bathocuproinedisulfonic acid (BCS) reduced fibrosis without affecting inflammation. Together, these findings identify Cu redistribution as a consequence of impaired PC biosynthesis and implicate Cu-dependent signaling in stellate cell activation, fibrogenesis and MASH pathogenesis. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=141 SRC="FIGDIR/small/723926v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@1c2bd52org.highwire.dtl.DTLVardef@1b8295org.highwire.dtl.DTLVardef@1a129dorg.highwire.dtl.DTLVardef@1bc2b87_HPS_FORMAT_FIGEXP M_FIG C_FIG

physiology↗

bioRxiv2026

Allogeneic CRISPR-Engineered CAR-T Cells Drive Potent Antitumor Activity in Solid Tumors

Chimeric antigen receptor (CAR) T-cell therapy has shown limited efficacy in solid tumors, in part due to variability in autologous T cells derived from heavily pretreated patients with advanced disease. To address these constraints, we developed an off-the-shelf allogeneic CAR-T platform using CRISPR-Cas9-mediated genome editing in T cells from healthy donors to enable targeted CAR insertion at the TRAC locus with concurrent disruption of B2M. Using adeno-associated virus (AAV) delivery, we designed CAR-T cells targeting glypican-2 (GPC2) and glypican-3 (GPC3), emerging antigens expressed in pediatric and adult solid tumors. Genome-edited allogeneic CAR-T cells exhibited potent, antigen-specific cytotoxicity across multiple tumor models. GPC2-directed allogeneic CAR-T cells demonstrated enhanced or comparable activity relative to conventional lentiviral CAR-T cells in neuroblastoma models and mediated tumor regression with prolonged survival in preclinical models. Notably, repeated dosing augmented antitumor efficacy without evidence of toxicity, supporting multi-dose regimens for solid tumors. Similarly, GPC3-targeted allogeneic CAR-T cells based on a single-domain antibody showed robust activity against hepatocellular carcinoma cells in vitro and in vivo. These findings establish a scalable, genome-engineered allogeneic CAR-T strategy with strong therapeutic potential and support the clinical development of off-the-shelf cell therapies for pediatric and adult solid tumors.

immunology↗

bioRxiv2026

ExMODE: A Multi-Omics Repository for Extremophile Adaptation and Bioprospecting

Extreme environments, though hostile to most life forms, host specialized extremophile communities that have redefined biological cognition and emerged as vital biotechnological resources, with their unique adaptive traits and bioactive molecules driving advances in multiple scientific and industrial fields. However, research on extremophiles is hindered by limitations in culture-based methods, fragmented multi-omics data with non-uniform annotation standards across repositories, the lack of cross-extreme comparative research in existing resources, and the singularity of data dimensionality that neglects key structural information, all of which restrict the functional interpretation of extremophile microbes and the exploitation of their bioprospecting potential. To tackle these challenges, we developed ExMODE (https://db.genomics.cn/exmode/), a comprehensive multi-omics database platform dedicated to extremophiles. It centrally integrates multi-omics data from diverse extreme habitats with a standardized annotation framework, resolving data fragmentation and enabling systematic cross-environment comparative analyses to elucidate extremophile adaptive mechanisms. Moreover, ExMODE aggregates multi-dimensional datasets including genes, genomes, secondary metabolite sequences and protein structures, overcoming the constraints of single-dimensional data and significantly improving the efficiency of biotechnological resource discovery from extreme microorganisms.

microbiology↗

bioRxiv2026

Identification of AAV Capsids with Enhanced Intravitreal Transduction and Favorable Safety Profile in Non-Human Primates

We report the discovery of novel adeno-associated virus (AAV) capsid variants engineered for superior intravitreal (IVT) gene delivery to the primate retina. Utilizing the REACH platform, we constructed a diverse AAV variant library and employed a multi-stage screening strategy involving in vitro selection on human retinal pigment cells followed by direct in vivo screening in non-human primates (NHPs). Following IVT administration in NHPS of a barcoded variant pool, next-generation sequencing analysis of retinal tissues identified lead candidates (e.g., E52, E54, and E57) that achieved transduction levels in the neural retina and RPE 5-10 fold higher than the benchmark R100. Concurrently, these high-potency variants exhibited an exceptional ocular confinement profile, with minimal to undetectable vector genome distribution in systemic organs. This combination of markedly enhanced retinal transduction and stringent local tropism establishes these engineered capsids as promising next-generation vectors for the treatment of inherited and acquired retinal diseases via a minimally invasive IVT route.

bioengineering↗

bioRxiv2026

Dissecting inter-focal heterogeneity and convergent immunosuppressive ecosystems in multifocal hepatocellular carcinoma through single-cell and spatial multi-omics

Background Multifocal hepatocellular carcinoma (HCC) comprises spatially separated tumor foci with distinct evolutionary trajectories, posing a major therapeutic challenge. Whether divergent lesions retain shared immune-evasion mechanisms beyond lesion-specific heterogeneity and offer cross-focal therapeutic opportunities remains unknown. Objective To resolve malignant and microenvironmental heterogeneity across tumor foci and identify conserved immunosuppressive programs underlying multifocal HCC progression. Design Matched tumour foci and peritumoural tissues from patients with multifocal HCC underwent integrated single-cell and spatial multi-omics profiling, including scFAST-seq (n=15), scATAC-seq (n=12), and Stereo-seq (n=14). In-house RNA-seq (n=13), public scRNA-seq (HRA001748) and RNA-seq datasets (TCGA-LIHC, OEP000321) were used for validation. Multiplex immunohistochemistry (n=96) and functional assays validated key findings. Results Multifocal HCC exhibited extensive inter-focal heterogeneity in malignant genomic, transcriptional, epigenetic, and evolutionary states, accompanied by diverse immune and stromal landscapes. Despite this divergence, spatially separated tumor foci converged on shared malignant states marked by elevated TMED2 expression and conserved immunosuppressive ecosystems characterized by regulatory T-cell (Treg) and SPP1+/SPRED1+ macrophage enrichment, impaired cytotoxic CD8+ T-cell immunity, and recurrent stromal-vascular remodeling. Mechanistically, malignant hepatocytes engaged SPP1+/SPRED1+ macrophages through C3/C5 complement signaling across divergent tumor foci, while macrophages and Tregs contributed to CD8+ T-cell dysfunction through CD274-PDCD1, CD80/CD86-CTLA4/CD28, and MHC-I-CD8 interactions. A tumor-intrinsic TMED2-ADAR1-dependent A-to-I RNA editing program promoted C3/C5 complement expression and secretion, linking malignant heterogeneity to conserved tumor-immune signaling. Conclusions Despite divergent malignant evolution, multifocal HCC converges on shared immunosuppressive ecosystems. The TMED2-ADAR1-C3/C5 complement axis represents a conserved tumor-immune vulnerability that may enable therapeutic strategies targeting common immune-evasion mechanisms across heterogeneous tumor foci.

cancer biology↗

bioRxiv2026

OneGenomeRice (OGR): A Genomic Foundation Model for Rice

The transition of genomics to a predictive intelligence discipline is driven by the advent of genomic foundation models. While substantial progress has been observed in all-life and human-centric models, plant species, particularly for the staple crops, remains hindered by a lack of models. Here we introduce OneGenome-Rice (OGR), a rice (Oryza sativa) genomic foundation model pre-trained on a genomic dataset comprising 422 high-quality genomes of cultivated and wild rice. OGR is engineered upon a Mixture of Experts (MoE) transformer architecture with 1.25-billion parameters and supports an ultra-long context window of up to 1 million base (Mb) pairs at single-nucleotide resolution. A comprehensive benchmark demonstrated that OGR significantly outperforms existing state-of-the-art multi-plant or all-life genome models in 11 categories (e.g. motif identification, sweep detection, etc). We further demonstrated the utility of OGR in several downstream applications, such as indica-japonica subspecies introgression analysis, identification of agronomy trait-associated functional loci and prediction of gene expression from DNA sequences. These results establish OGR as a promising foundational computational infrastructure for rice functional genomics and precision breeding. The OGR and its fine-tuned models, including pretrained weights, training code and the rice genomic benchmark suit, have been fully opened.

genomics↗

bioRxiv2026

RNABag: A Generalizable Transcriptome Foundation Model for Precision Oncology across Biopsy Modalities

Transcriptomic data is highly sensitive to cancer state and progression, making transcriptome-based foundation models a great promise for diverse clinical ontological inference. However, analyses of transcriptome are conventionally hindered by technical batch effects and limited generalization across platforms. Here, we introduce RNABag, a foundation model designed to generalize well to external datasets. In particular, the model only focuses on highly variable genes to reduce noise; and extensive data augmentation was utilized to pretrain RNABag to learn robust representations, invariant to batch variations. We demonstrate that RNABag achieves superior performance in pan-cancer tissue-of-origin classification and cancer detection in internal validation sets, as well as in zero-shot generalization to external cohorts and in-house clinical samples. Furthermore, RNABag, after specialized finetuning, exhibits strong capabilities in a wide range of clinical applications. The model effectively stratifies patient survival and predicts relapse risks, highlighting key molecular pathways driving tumor progression. Crucially, we extend RNABags utility to liquid biopsies, achieving high diagnostic accuracy in plasma cfRNA and tumor-educated platelets (TEPs), thereby supporting its application in non-invasive cancer monitoring. Interpretability analysis revealed pivotal role of tumor immune escape in the cancer induced plasma cfRNA signals. In summary, our study indicates that cancer states and progression may be monitored in details and precision via comprehensive modeling of transcriptome across biopsy modalities.

bioinformatics↗

bioRxiv2026

A TRANSLATIONAL LC-MS/MS FRAMEWORK FOR LIPID BIOMARKER IDENTIFICATION AND QUANTIFICATION IN HUMAN PLASMA

Lipid metabolism is increasingly recognized as a hallmark of cancer, yet translating lipidomic discoveries into clinically actionable biomarkers remains constrained by analytical variability and limited standardized validation frameworks. This challenge is further compounded by a chicken-or-egg problem, where expensive standards and labelled internal standards are required to identify and quantitate target lipids, but the diagnostic importance of these targets is uncertain until they can be reliably measured. Previous work had indicated the potential of 48 lipid biomarker species for the prediction of breast cancer from plasma samples using high resolution liquid chromatography mass spectrometry. This study aimed to identify each of these 48 species and develop a quantitative method to determine the absolute concentrations of these lipids in plasma to provide the basis for the development of a clinical assay for use in breast cancer detection. In doing so, we present a pragmatic workflow that bridges lipid discovery with lipid identification and robust quantitative analysis. A curated library of 48 lipid species was established using authentic standards to verify plasma lipids through retention-time matching and high-resolution spectral comparison. In plasma, 41 lipids were confidently identified based on co-elution with standards and diagnostic fragment ions. Method qualification, including assessment of accuracy, precision, recovery, and linearity, was performed across all 48 lipids in parallel with identification, and 46 lipids ultimately met all predefined qualification criteria. Notably, practical constraints, including time, cost, and availability of authentic standards, necessitated performing identification and targeted method development in parallel, highlighting challenges inherent to translating lipidomics into commercial or clinical assays. This workflow provides a reproducible framework for harmonizing lipid identification and quantification, enabling the reliable integration of lipidomic data into biomarker discovery and clinical applications.

biochemistry↗

bioRxiv2026

cryoAgent: An agentic workflow for robust and adaptive end-to-end cryo-EM image processing

Cryo-electron microscopy (cryo-EM) is the mainstream method for structure determination, yet current automated workflows remain rigid and require expert intervention for failure recovery, heterogeneity analysis, and optimization. We present cryoAgent, an agentic workflow for autonomous cryo-EM image processing with adaptive tool use to address these challenges. cryoAgent improves reconstruction quality across diverse datasets, identifies a previously unreported structural state, and outperforms state-of-the-art automated workflows, advancing scalable and discovery-oriented structural biology.

biophysics↗

bioRxiv2026

Dynamic dissociation of the IFT complex drives ciliary dysfunction during C. elegans ageing

Intraflagellar transport (IFT) is essential for cilia, and its dysfunction drives ciliopathies and systemic ageing. However, the in vivo dynamics of individual components in the IFT complexes remain obscured, leaving the mechanisms of age-dependent IFT failure largely unknown. Here, we report a dual-color super-resolution imaging strategy to dissect the structural integrity and kinetics of IFT trains in the sensory cilia of young and aged Caenorhabditis elegans. We show that IFT complexes are not static entities. Instead, distinct components undergo dynamic dissociation within IFT trains. This intra-complex dissociation causes a remarkable reduction in IFT velocity and is significantly exacerbated in the cilia of aged worms. Mechanistically, we identify the conserved TRiC/CCT chaperonin complex and daf-19/RFX, the master transcription factor driving IFT genes, as critical regulators of IFT stability. We demonstrate that their age-dependent downregulation drives the progressive IFT component dissociation. Our findings re-frame the IFT complex as a highly dynamic assembly, uncover a new dimension of IFT regulation, and identify the progressive uncoupling of IFT components as a key driver of ciliary dysfunction during ageing.

cell biology↗

bioRxiv2026

Benchmarking scRNA-seq Copy Number Inference: A Comprehensive Evaluation and Practitioner Guide

Accurately inferring copy number variation (CNV) from scRNA-seq data is critical for identifying malignant cells, reconstructing tumor subclonal architecture, and uncovering the genomic drivers that dictate cancer cell biology. However, the performance of existing tools varies significantly, and current benchmarks lack the breadth of datasets and methods necessary to provide definitive guidance. We present a comprehensive benchmark of 12 CNV inference methods across 28 real datasets (>100,000 cells) and diverse synthetic datasets. By evaluating methods based on malignant cell classification accuracy, CNV inference accuracy, scalability, and robustness, we establish a definitive practitioners guideline: allele-aware methods like Numbat excel when high-quality allelic inference can be achieved, whereas expression-centric tools such as Clonalscope, CopyKAT, inferCNV, and SCEVAN remain reliable when raw sequencing data are unavailable. Our study provides both a practical decision-making framework for researchers and a public repository of standardized CNV profiles to catalyze further methodological innovation.

cancer biology↗

bioRxiv2026

Time-resolved hemodynamic responses to sentence-level speech perception, production, and self-monitoring

Functional magnetic resonance imaging (fMRI) has been widely utilized to explore the neural mechanisms underlying speech processing. However, the intertwining of perception and production that exists in real-world scenarios remains underexplored due to challenges such as gradient noise and head motion artifacts from speaking. Previous research has often employed sparse-sampling designs, pausing image acquisition intermittently to present auditory stimuli or record overt speech. While this approach mitigates some challenges, it cannot capture continuous brain activity during speech processing and does not separate the mixed hemodynamic responses to external and self-generated speech occurring in succession. We overcame these limitations and continuously scanned thirty-one participants as they listened to and recited English sentences. Through independent component analysis (ICA), we decomposed each functional scan into spatially independent components (ICs), identifying task-related ICs in the superior temporal cortex, inferior frontal gyrus, and orofacial sensorimotor cortex. These ICs demonstrated time-resolved hemodynamic responses corresponding to distinct stages of speech perception, planning, and production. A linear subtraction between the IC time courses from the listening-reciting (perception-to-production) and listening (perception-only) tasks further revealed a secondary hemodynamic response to self-generated speech in the superior temporal cortex. Furthermore, we established precise temporal relationships between overt speech output and the peak, rise, and fall of hemodynamic responses for each independent component. Together, we present a methodological framework that can inform future fMRI studies on naturalistic tasks involving the perception of external auditory stimuli and monitoring of self-generated sounds.

neuroscience↗

bioRxiv2026

Curvature-mediated prewetting organize mitochondrial nucleoid

The emergence of spatiotemporal order in diffusive cellular environments requires physical mechanisms to overcome the entropic drive toward disorder. While the organizing role of chemical signaling is well characterized, how complex membrane curvature regulate soluble molecular organization remains a fundamental open question. Here, we establish membrane curvature as a thermodynamic control parameter for the condensation of soluble proteins through prewetting. Using the mitochondrial transcription factor TFAM, we demonstrate that intrinsic membrane curvature locally drives a prewetting transitiona surface-mediated phase separation distinct from bulk condensation. By combining in vitro reconstitution, live-cell super-resolution imaging, cryo-electron tomography, and thermodynamic theory, we show that negatively high-curvature regions lower the nucleation energy barrier of Tfam, driving localized protein condensation at physiological concentrations. These results reveal that membrane curvature does not merely scaffold cellular machinery but manipulates the local free energy landscape, establishing a geometric principle for the spatial control of biological processes.

biophysics↗

bioRxiv2026

Novel Engineered AAV Variants Demonstrate Superior Blood-Brain Barrier Penetration and Safety in Non-Human Primates

Systemic delivery of adeno-associated virus (AAV) for gene therapy of central nervous system (CNS) disorders is limited by inefficient blood-brain barrier (BBB) penetration and dose-limiting toxicity in peripheral organs, notably the liver and dorsal root ganglia (DRG)1-5. Here, we report the development of novel AAV variants via a proprietary capsid engineering platform (REACH). In non-human primates (NHPs), intravenous administration of lead variants resulted in transgene expression levels in the brain that were 600-2000 fold higher than AAV9 at the RNA level, concomitant with a 10-50 fold reduction in liver tropism and minimal off-target exposure in the heart and DRG. These engineered capsids achieve unprecedented, pan-CNS transduction with a markedly improved safety profile, representing a transformative platform for treating a broad spectrum of neurological diseases.

neuroscience↗

bioRxiv2026

Local interaction networks reconstructed from global biodiversity data improve pollinator restoration decision making

Global pollinator declines threaten the health of ecosystems and food systems, underscoring the urgency of conservation actions such as habitat restoration. However, data gaps on plant use among pollinators continue to limit reliable design of restoration plant mixes. To address this, we present NECTAR (Network-Enhanced Conservation Tool for Analysis and Recommendation), a new modular framework that integrates multiple data modalities - including species distributions, phenological metrics, and phylogenetic data - to infer flower visitation and host plant interactions from spatial, temporal, and phylogenetic overlap, generating spatially explicit plant-insect interaction networks that guide planting recommendations for pollinator habitat restoration. We demonstrate the utility of NECTAR by generating a large plant-insect metaweb across California, comprising 2,473,729 spatially explicit interactions that included 3,792 pollinator species and 4,363 native plant species. NECTAR achieved high interaction recall across withheld interactions and independent datasets, substantially outperforming null models and matching or exceeding values reported in comparable studies. NECTAR's data-driven plant mix recommendations are predicted to support up to 2.4 times more pollinator species compared to existing resources and random selection of plants. This optimization facilitates the inclusion of multiple goals and constraints, and provides complementary decision-making information to existing resources. NECTAR offers a scalable, evidence-based framework for translating increasingly available global biodiversity data into locally actionable restoration guidance, with broad potential to improve pollinator habitat restoration worldwide.

ecology↗

bioRxiv2026

Mitochondrial ATP production promotes T cell differentiation and function by regulating chromatin accessibility

Immune elimination of chronic infection or cancer requires cytotoxic CD8+ T cells that adopt and maintain an effector phenotype. Cytotoxic T cell function is a bioenergetically demanding process and T cells subjected to chronic antigen exposure have compromised effector function despite high rates of glycolysis. Here we report the ability of the short-chain -hydroxy acid, D--hydroxybutyrate, to act as a signaling molecule that increases mitochondrial ATP production and drives the conversion of proliferating T cells into cytotoxic effector cells. DAHB signaling switches ATP production from glycolysis to oxidative phosphorylation supported by fatty acid oxidation, even in glucose-replete media. This conversion suppresses both AMPK phosphorylation and the integrated stress response (ISR) in activated T cells while significantly elevating the level of the phosphagen, phosphocreatine (PCr). Both the PCr bioenergetic reserve and oxidative phosphorylation were required for T cell effector differentiation. DAHB-induction of CD8-effector gene transcription was coupled to bioenergetics by enhanced ATP-dependent remodeling of chromatin accessibility at effector gene loci. DAHB enhanced CD8+ T cell antitumor activity both in vitro and in vivo, and DAHB treatment of transferred T cells led to persistent in vivo antitumor effects. Together, these findings link cellular bioenergetics to the regulation of chromatin accessibility and gene expression required to support effector function.

immunology↗

bioRxiv2026

Clonal Hematopoiesis Instructs Maladaptive Tissue Repair to Promote Fibrosis

Tissue repair is increasingly recognized as a systemic process influenced by age-associated changes beyond the injured organ itself. Clonal hematopoiesis of indeterminate potential (CHIP), a common consequence of somatic evolution in hematopoietic stem cells, has been linked to inflammatory disorders, yet whether it directly regulates tissue remodeling remains unclear. Here, we integrate population genomics, preclinical models, and human lung analyses to examine the role of CHIP in fibrotic lung disease. In large cohorts, idiopathic pulmonary fibrosis (IPF) was associated with a distinct CHIP mutational spectrum enriched for non-DNMT3A variants and for larger mutant clones. In mouse models, hematopoietic mutations exacerbated bleomycin-induced fibrosis and reprogrammed macrophages toward inflammatory, profibrotic states, including expansion of a distinct, injury-responsive SPP1+ population conserved in human disease. CHIP-associated macrophages were sufficient to directly promote fibroblast activation and alter epithelial differentiation, linking hematopoietic genotype to parenchymal remodeling. Consistently, a CHIP-derived macrophage transcriptional signature predicted adverse outcomes in independent IPF cohorts. Notably, immune and epithelial alterations were detectable even in the absence of overt injury, indicating that CHIP establishes a primed tissue environment permissive for maladaptive repair. Together, these findings identify clonal hematopoiesis as a systemic regulator of tissue repair and demonstrate that somatic evolution in blood can actively instruct organ remodeling through immune-parenchymal interactions. This framework supports the possibility that disease-associated selective pressures may shape clonal architecture with functional consequences for organ health.

immunology↗