Biology subjects

Pan, L.

Publications and source records attributed to Pan, L..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Endothelin 2-Mediated Neuroinflammation Drives Hypertension-Associated Retinal Dysfunction

Systemic hypertension is a significant risk factor for glaucoma, a leading cause of irreversible blindness, yet the mechanistic basis connecting the two conditions remains elusive. Here, we demonstrate that hypertensive rats develop accelerated retinal degeneration characterized by retinal thinning, functional impairment, reduced perfusion, and progressive neuroinflammation. Critically, these changes occur despite persistently lower intraocular pressure (IOP), indicating an IOP-independent mechanism of pathology. Transcriptomic and biochemical analyses identified a robust activation of the retinal endothelin system, with endothelin-2 (EDN2) being the earliest and most significantly upregulated component. AAV-delivered retinal Edn2 knockdown completely restored retinal function, ameliorated neuroinflammation, and enhanced retinal blood flow in hypertensive rats. Pharmacological blockade of endothelin receptor type A (EDNRA), but not type B, replicated these protective effects without altering IOP. Our findings establish EDN2 as a central, IOP-independent driver of hypertension-associated retinal neurodegeneration and identify the endothelin-EDNRA axis as a potential therapeutic target to prevent vision loss in hypertensive patients.

neuroscience↗

bioRxiv2026

VAETracer: Mutation-Guided Lineage Reconstruction and Generational State Inference from scRNA-seq

Somatic mutations accumulate with cell division and are key to understanding tumor evolution. While single-cell RNA sequencing (scRNA-seq) can effectively capture somatic mutations in the 3' untranslated region (3' UTR), enabling its use for lineage tracing, these data are inherently noisy and exhibit high false-positive rates. To address this limitation, we propose VAETracer, a deep learning framework that is able to reconstruct cellular lineages by extracting cellular generation index (CGI) from mutation profiles of 3' UTR in scRNA-seq data, thus enabling the inference of developmental trajectories without relying on noisy mutation signals (https://github.com/Kaiyu-W/VAETracer). There are two core components for VAETracer: (1) scMut module, which infers the CGI directly from sparse and noisy mutation matrices using our cumulative mutation model (CMM), effectively bypassing error-prone phylogenetic tree topologies caused by mutation noise, and (2) MutTracer module, which predicts ancestral and future latent cellular states or gene expressions at the single-cell level by integrating CGI information with measured transcriptomes. Validation on simulated and real tumor datasets shows that this method can accurately reconstruct clonal relationships, quantify tumor progression, and effectively infer unmeasured cellular states using only the measured scRNA-seq data. This work provides a new computational tool for extracting lineage information and revealing tumor evolution directly from widely available RNA-seq data.

bioinformatics↗

bioRxiv2025

Residual blinking-driven channel alignment for multicolor single-molecule localization microscopy

Given the nanometer-scale resolution of single-molecule localization microscopy (SMLM), sequential multicolor SMLM is inherently challenged by inter-channel misalignment arising from unpredictable sample drift during channel switching. Traditional fiducial-based strategies are limited by added complexity in sample preparation. Here, we report a residual blinking-driven method for channel alignment in multicolor SMLM, termed ReBling alignment. By exploiting residual blinking events under dual-wavelength excitation, our method extracts shared localizations as intrinsic registration anchors and performs accurate cross-correlation-based alignment. We validated ReBling alignment across biological systems featuring distinct spatial patterns, including continuous patterned structures (mitochondria-microtubule co-imaging, dual-labeled microtubules), and discrete point-cluster assemblies (dual-color nuclear pore complex components), demonstrating its broad applicability and reliability. These results establish ReBling alignment as a practical, versatile, fiducial-free solution for accurate channel registration in sequential multicolor SMLM, enabling more precise and reliable characterization of complex cellular architecture and molecular interactions.

cell biology↗

bioRxiv2025

QuNex Recipes: Executable, Human-Readable Workflows for Reproducible Neuroimaging Research

Preprocessing and analysis of neuroimaging data are technically demanding, often requiring a combination of multiple software tools, modality-specific pipelines, and extensive parameter tuning to match dataset characteristics. These complexities make it difficult to document workflows in sufficient detail to ensure complete transparency and reproducibility. To address these challenges, we introduce QuNex recipes, a framework for defining and executing complete neuroimaging workflows - encompassing data onboarding, preprocessing, and analysis - in a transparent, machine- and human-readable format. Recipes are implemented as an integrated feature of the Quantitative Neuroimaging Environment & Toolbox (QuNex), a containerized, open-source platform for end-to-end multimodal and multi-species neuroimaging processing. The recipes framework enables seamless integration of QuNex commands with custom scripts and external tools, capturing every processing step and parameter setting. A fully reproducible study can thus be shared and replicated by providing only (a) the QuNex version used, (b) the recipe file, and (c) the data. This approach standardizes workflow specification, enhances transparency, and enables one-command replication of complex neuroimaging analyses. By providing a standardized way to describe and share workflows, recipes facilitate open exchange of best practices and reproducible methods within the neuroimaging community.

neuroscience↗

bioRxiv2025

A whole-body cell type atlas mapped into an electron microscopy volume of an annelid worm

Differential gene expression establishes the distinct physiology and morphology of cell types in an animal body. Single-cell sequencing and volume EM represent milestones toward the characterization of cell types, yet are difficult to combine for a comprehensive view on the cellular genotype-phenotype link. Here, we map a whole-body single-cell transcriptome into the PlatyBrowser, a multimodal cellular atlas for the marine annelid Platynereis dumerilii, and establish this combination uniquely for an entire animal. We learn that, in the 6-days-old worm, the majority of genes are tightly co-regulated to jointly implement one of eight major cellular morphotypes representing epidermis, gut, vasculature, myofibres, glia, motile cilia, glands, or neurons. Focusing on neurons, we uncover 14 families that by transcription factor identity, axonal projection, or sensory-secretory apparatus resemble conserved neuron types found in vertebrates, insects, or nematodes. We hypothesize that these existed in urbilaterian ancestors and represent the ancient core of nervous system centralization.

evolutionary biology↗

bioRxiv2025

TMEM100 attenuates NF-κB activation via disrupting the PRDX1-GNAI2 complex to alleviate acute lung injury

Acute lung injury (ALI) is a severe and diffuse inflammatory disorder of interstitial lung. Emerging evidence suggests that TMEM100 is closely associated with lung development and function. However, its role in ALI remains unclear. In this study, we observed a significant downregulation of TMEM100 expression in both mouse lung tissues with ALI and lipopolysaccharide (LPS)-induced pulmonary vascular endothelial cells (PVECs). Overexpression of TMEM100 markedly attenuates LPS-induced lung injury and inflammation, while also restoring the imbalance between proliferation and apoptosis in PVECs. Mechanistically, TMEM100 interacts with both PRDX1 and GNAI2, disrupting the PRDX1-GNAI2 complex and thereby inhibiting LPS-induced NF-{kappa}B activation, which contributes to its anti-inflammatory effects. These findings highlight the protective role of TMEM100 in endotoxin-induced ALI and provide a theoretical basis for understanding its biological functions and potential applications in ALI gene therapy.

immunology↗

bioRxiv2025

Universal super-resolution for subcellular fluorescence imaging

Super-resolution fluorescence microscopy has emerged as an essential instrument for investigating subcellular structures and monitoring intracellular physiology. Despite rapid advances driven by deep learning, most existing approaches are modality specific and exhibit limited generalizability, restricting their practical applicability. Here we introduce universal super-resolution (UniSR), a framework that operates across microscopes and subcellular structures without optical modifications or prior sample knowledge. UniSR is initially pre-trained on simulated image pairs to establish mappings from low-to high-resolution features and subsequently fine-tuned with only one experimental image pair, reducing data demand and acquisition time. Across wide-field and point-scanning modalities, UniSR enhances resolution to match structured illumination, single-molecule localization, or stimulated emission depletion microscopy. Applied to diverse biological samples, it reveals nanoscale structures, dynamic processes, and organelle interactions with high spatiotemporal fidelity. UniSR provides a practical and broadly generalizable tool for super-resolution imaging in live-cell research.

bioinformatics↗

bioRxiv2025

Genetic inhibition of IL-12β suppresses systolic overload-induced cardiac inflammation and heart failure development

Inflammation promotes heart failure (HF) development, and inhibition of IL-12{beta} simultaneously attenuates interleukin-12 (IL-12) and interleukin-23 (IL-23), two important proinflammatory cytokines. In this study, we used IL-12{beta} knockout (KO) mice to test the hypothesis that genetic inhibition of IL-12{beta} would attenuate transverse aortic constriction (TAC)-induced cardiac inflammation, hypertrophy, and dysfunction, as well as the consequent lung remodeling. IL-12{beta} KO in male and female mice significantly attenuated TAC-induced cardiac dysfunction as evidenced by improved left ventricular (LV) ejection fraction and fractional shortening. IL-12{beta} KO also significantly ameliorated the TAC-induced increase of LV weight, left atrial weight, lung weight, right ventricular (RV) weight, and their ratios to body weight or tibial length in male and female mice. In addition, IL-12{beta} KO significantly attenuated TAC-induced LV leukocyte infiltration, cardiomyocyte hypertrophy, fibrosis, and the consequent lung inflammation and remodeling. Moreover, IL-12{beta} KO reduced TAC-induced alterations of LV gene profile associated with inflammation and fibrosis, as shown by bulk LV RNA sequencing. Furthermore, we found that IL-12{beta} KO significantly attenuated TAC-induced LV accumulation of multiple immune cell subsets, activation of CD4+ and CD8+ T cells, and the percentage of central memory CD4+ and CD8+ T cells in the cardiac drainage lymph nodes. Finally, IL-12{beta} KO mice showed significantly reduced IFN{gamma}+CD8+ and CXCR3+CD8+ T cells in the drainage lymph nodes as compared with WT after TAC. These findings collectively demonstrate that IL-12{beta} plays a critical role in systolic overload-induced LV inflammation, remodeling, and dysfunction, likely through cardiac immune cell infiltration.

physiology↗

bioRxiv2025

Lead (Pb) exposure alters neural cell fate in the developing human brain

The heavy metal lead (Pb) is a developmental neurotoxicant associated with cognitive and behavioral deficits, but the cellular mechanisms underlying these impairments remain unclear. Here we show that prenatal Pb exposure biases human radial glia fate, prolonging neurogenesis and suppressing astrogenesis. We used hiPSC-derived cortical organoids, primary human fetal tissue, and in vivo xenografts to demonstrate that Pb exposure alters radial glial differentiation. Pb-exposed organoids contain a higher proportion of neurons and fewer astrocytes. We validated this differentiation bias in primary radial glia from human cortices (GW16-20), observing Pb-associated reductions in astrocyte commitment via genetic lineage tracing. This correlated with increased H3K27me3, a repressive histone modification deposited by the histone methyltransferase complex PRC2, suggesting epigenetic reprogramming as a mechanistic link between Pb and neural cell fate commitment. Our findings indicate that prenatal Pb exposure impacts lineage commitment in the developing brain, which may contribute to cognitive and behavioral impairment.

neuroscience↗

bioRxiv2025

Functional integrity of the SEL1L-HRD1 complex is critical for ERAD and organismal viability

The SEL1L-HRD1 complex represents the most evolutionarily conserved branch of endoplasmic reticulum-associated degradation (ERAD), with SEL1L acting as a key cofactor for the E3 ubiquitin ligase HRD1. While the physiological relevance of this complex has been increasingly recognized, whether SEL1L is strictly required for HRD1 function in mammals has remained unclear. Here, using complementary in vivo and in vitro approaches, we define the architecture and physiological significance of the mammalian SEL1L-HRD1 ERAD complex. Our data demonstrate that direct binding between SEL1L and HRD1 is essential for ERAD function and neonatal survival in mice. In three knock-in mouse models harboring targeted mutations at the SEL1L-HRD1 interface, we show that the L709P variant - unlike the benign P699T mutation - results in complete neonatal lethality within 30 hours of birth, a phenotype more severe than that of the partially lethal S658P variant. Mechanistically, the L709P mutation abolishes SEL1L-HRD1 interaction, disrupting substrate engagement and impairing recruitment of the E2 enzyme UBE2J1, leading to the accumulation and aggregation of misfolded proteins in the ER. Notably, these defects can be partially rescued by HRD1 overexpression, echoing findings from yeast. Together, our results provide definitive evidence that the SEL1L-HRD1 interaction is essential for ERAD activity and neonatal viability in mammals, resolving a long-standing question in ERAD biology and identifying a new therapeutic strategy for modulating ERAD activity in humans. SIGNIFICANCE STATEMENTThe endoplasmic reticulum-associated degradation (ERAD) pathway is essential for maintaining cellular proteostasis and organismal health, yet its molecular regulation in mammals remains incompletely defined. The SEL1L-HRD1 complex constitutes the central axis of this conserved pathway, but whether SEL1L is required for HRD1 function in vivo has remained unresolved. Here, using genetic mouse models and biochemical analyses, we demonstrate that the physical interaction between SEL1L and HRD1 is essential for ERAD activity and neonatal viability. These findings resolve a long-standing question in ERAD biology, provide new insights into the structural and functional organization of the mammalian ERAD machinery, and highlight the SEL1L-HRD1 interface as a potential therapeutic target for modulating ERAD activity in diseases.

cell biology↗

bioRxiv2025

Integrating 12 Spatial and Single Cell Technologies to Characterise Tumour Neighbourhoods and Cellular Interactions in three Skin Cancer Types

Cutaneous squamous cell carcinoma (cSCC), basal cell carcinoma (BCC), and melanoma - the three major skin cancers - collectively comprise over 70% of all cancer cases. Despite their prevalence, much understanding of cellular interactions in the skin cancer microenvironment is needed, both in the outer skin layer where the cancer originates and at the deeper junctional and dermal layers into which it progresses. To address this gap, we integrated 12 complementary spatial and single-cell technologies to generate orthogonally-validated cell signatures, spatial maps, and interactomes for cSCC, BCC, and melanoma. Through comprehensive comparisons and integrating these spatial methods, we provided practical benchmarking guidelines for experimental design and analysis. By identifying keratinocyte cancer cells and melanomas, we found distinct signatures of these cells compared to non-cancer keratinocytes and melanocytes. Spatial integration of transcriptomics, proteomics and glycomics uncovered cancer niches enriched for cancer initiating cells (melanocytes or keratinocytes) and fibroblast and T-cell (MKFT) clusters, with altered tyrosine and pyrimidine metabolism. Ligand-receptor analysis across >700 cell-type combinations and >1.5 million interactions highlighted key roles for CD44, integrins, and collagens, with CD44-FGF2 emerging as a potential therapeutic target. Consistently, melanoma showed strong MFT interactions, validated by Opal Polaris, RNAScope, Proximal Ligation Assay and two additional single-cell spatial platforms (making a total of 14 technologies). For population-scale generalisation, genetic associations from >500,000 individuals were mapped onto spatial skin tissues, identifying SNPs enriched in domains containing melanocytes and T cells and their ligand-receptor pairs, shedding light on functional mechanisms linking genetic heritability to cells within cancer tissue. We built an interactive multiomics resource for exploring spatially-resolved molecular signatures and cellular crosstalk in skin cancer, available at https://skincanceratlas.com.

cancer biology↗

bioRxiv2025

The Spatial Atlas of Human Anatomy (SAHA): A Multimodal Subcellular-Resolution Reference Across Human Organs

The Spatial Atlas of Human Anatomy (SAHA) represents the first multimodal, subcellular- resolution reference of healthy adult human tissues across multiple organ systems. Integrating spatial transcriptomics, proteomics, and histological features across over 15 million cells from more than 100 donors, SAHA maps conserved and organ-specific cellular niches in gastrointestinal and immune tissues. High-resolution profiling using CosMx SMI, 10x Xenium, RNAscope, GeoMx DSP, and single-nucleus RNA-seq reveals spatially organized cell states, rare adaptive immune populations, and tissue-specific cell-cell interactions and ligand-receptor pairs. Comparative analyses with colorectal cancer and inflammatory bowel disease demonstrate the power of SAHA to detect disease-associated spatial disruptions, including crypt dedifferentiation, perineural invasion, and therapy-resistant immune remodeling. All data are openly accessible through a FAIR-compliant interactive portal to support exploration, benchmarking, and machine learning model training. Through SAHA, we provide a foundational framework for spatial diagnostics and next-generation precision medicine grounded in a comprehensive human tissue atlas, enabling the development of context-aware models that simulate tissue behavior, decode complex pathologies, and accelerate therapeutic innovation at unprecedented scale.

systems biology↗

bioRxiv2025

Developmental landscape of shark telencephalon sheds light on the evolution of telencephalic cell types and the ancient origin of Cajal-Retzius cells

The emergence of predation and associated complex behaviors in jawed vertebrates (gnathostomes) were major driving forces in brain evolution. To gain insight into the neuronal complexity of the last common gnathostome ancestor, we studied the development of the shark telencephalon by combining single-cell and spatial transcriptomics. Our findings suggest an ancient origin of pallial neurogenesis, including basal progenitors, which were previously only identified in tetrapods. We find evidence for migrating gabaergic neurons populating the dorsal pallium, where we observe incipient layering. Finally, we provide evidence for the existence of Cajal-Retzius cells in the developing shark telencephalon, with a conserved molecular profile and tissue localization relative to mammals. Our analyses revealed that major features of the vertebrate pallium arose much earlier than previously thought, in the gnathostome lineage.

developmental biology↗

bioRxiv2025

SM3DD with Segmented PCA: A Comprehensive Method for Interpreting 3D Spatial Transcriptomics

We developed Standardised Minimum 3D Distance (SM3DD), an entirely cell segmentation/annotation-free approach to the analysis of spatial RNA datasets, using it to compare lung tissue from 16 clinically normal individuals to those of 18 SARS-CoV-2 patients who died from acute respiratory distress syndrome. RNA spatial coordinates were determined using the CosMx Spatial Molecular Imager (Bruker Spatial Biology, US). For each individual transcript location, we calculated the three-dimensional distances to the nearest transcript of each transcript type, standardising the distances to each transcript type. Mean SM3DDs were compared between normal and SARS-CoV-2 patients. Notably, hierarchical clustering of the directional log10(P) values organized genes by functionality, making it easier to interpret biological contexts and for FKBP11, where a decrease in distance to MZT2A was the most significant difference, suggesting a role in interferon signaling. Using a segmented principal components analysis of the entire SM3DD dataset, we identified multiple pathways, including SARS-CoV-2 infection, even though the assay did not include any SARS-CoV-2 transcripts.

bioinformatics↗

bioRxiv2025

SEL1L-HRD1 ER-Associated Degradation Facilitates Prohormone Convertase 2 Maturation and Glucagon Production in Islet α Cells

Proteolytic cleavage of proglucagon by prohormone convertase 2 (PC2) is required for islet cells to generate glucagon. However, the regulatory mechanisms underlying this process remain largely unclear. Here, we report that SEL1L-HRD1 endoplasmic reticulum (ER)-associated degradation (ERAD), a highly conserved protein quality control system responsible for clearing misfolded proteins from the ER, plays a key role in glucagon production by regulating turnover of the nascent proform of the PC2 enzyme (proPC2). Using a mouse model with SEL1L deletion in proglucagon-expressing cells, we observed a progressive decline in stimulated glucagon secretion and a reduction in pancreatic glucagon content. Mechanistically, we found that endogenous proPC2 is a substrate of SEL1L-HRD1 ERAD, and that degradation of misfolded proPC2 ensures the maturation of activation-competent proPC2 protein. These findings identify ERAD as a novel regulator of PC2 biology and an essential mechanism for maintaining cell function.

cell biology↗

bioRxiv2025

AGP-Net: A Universal Network for Gene Expression Prediction of Spatial Transcriptomics

In the era of high-throughput biology, molecular phenotypes have proven effective in predicting disease states and future trajectories. Transcriptomics, in particular, has enabled the dissection of complex diseases with heterogeneous genetic and environmental aetiology, both aiding diagnosis and augmenting treatment. As improving technology has led to measurements of gene expression at increasing granularity, it has become progressively feasible to resolve disease traits that present locally or with spatial heterogeneity. Principal among these are cancers in which tumour gene expression, while itself heterogenous, exhibits a distinct signature from that of the surrounding tissue. Identifying this signature through molecular phenotyping facilitates specific cancer diagnosis and treatment. Here, we introduce AGP-Net, a multi-modal foundation framework capable of predicting gene expression from histopathology images. Rather than produce an aggregated estimate of expression for each gene, AGP-Net disaggregates images into spots and attempts to resolve the variation in gene expression across them, thereby providing coarse spatial transcriptomic predictions across the tumour slice and surrounding region. The challenge in doing so is due to data sparsity relative to the dimensionality of the problem: the number of genes and their contextual heterogeneity within and between tissue and cancer types makes it difficult to train a model on the limited data available. The innovation of AGP-Net lies in borrowing strength across similar genes as defined by their textual language descriptions. Our AGP-Net supports datasets with varying gene coverage and facilitates the prediction of gene expression for previously unseen genes based on their textual descriptions. Trained on millions of spots from diverse dataset sources, AGP-Net establishes state-of-the-art performance in zero-shot spatial gene expression prediction, demonstrating its adaptability to generalize across novel scenarios.

pathology↗

bioRxiv2025

A Novel Glia-immune humanized mouse model for investigation of HIV CNS infection and neuroinflammation.

Dysregulation in neuroimmune interactions drives pathology in diverse neurological disorders. However, human cell-based in vivo models are limited for clinically relevant mechanistic studies and drug testing. To address this, we developed a novel humanized mouse model integrating all four major types of human glia - astrocytes, oligodendrocyte precursor cells (OPCs), oligodendrocytes, and microglia - in the brain, alongside donor-matched human immune system in peripheral blood and lymphoid tissues. We applied this model to study HIV-associated neurocognitive disorders, which can persist in tissue reservoirs including in the brain despite viral suppression by antiretroviral therapy. These glia-immune humanized mice supported robust HIV-1 replication in the peripheral blood, lymphoid tissues, and the brain, and recapitulated the synapse loss observed in patients. Furthermore, HIV-infected mice exhibited heightened inflammation in both peripheral and brain tissues. Notably, OPCs and oligodendrocytes in HIV-infected brains adopted an immune activated phenotype, upregulating interferon-stimulated genes, highlighting understudied roles of oligodendroglia in HIV infection. RNA-sequencing of human glia identified the upregulation of inflammasome-associated genes and the downregulation of genes involved in transcriptional, epigenetic, and metabolic regulation. Overall, this model provides a powerful in vivo platform to investigate human neuroimmune interactions relevant to diverse neurological disorders, offering critical insights into HIV CNS infection, pathology, and potential therapeutic strategies targeting CNS reservoirs and neuroinflammatory pathways.

immunology↗

bioRxiv2025

LCORL and STC2 variants increase body size and growth rate in cattle and other animals

Using ancestral recombination graphs, we investigated recent selection signatures in European beef cattle breeds, pinpointing sweep-driving variants in the LCORL and STC2 loci with notable effects on body size and growth rate. The ACT-to-A frameshift mutation in LCORL occurs mainly in central-European cattle, and stimulates growth. Remarkably, convergent truncating mutations were also found in commercial breeds of sheep, goats, pigs, horses, dogs, rabbits, and chickens. In the STC2 gene, we identified a missense mutation (A60P) located within the conserved region across vertebrates. We validated the two natural mutations in gene-edited mouse models, where both variants in homozygous carriers increase the average weight by 11%. Our findings provide insights into a seemingly recurring gene target of body size enhancing truncating mutations across domesticated species, and offer valuable targets for gene editing-based breeding in animals.

genetics↗