Biology subjects

Li, R.

Publications and source records attributed to Li, R..

At least 73 records · Page 4Linked to original sources

bioRxiv2026

Cardiomyocytes Undergo a Mesenchymal-Like Fate Transition in Myocardial Fibrosis

BACKGROUNDMyocardial fibrosis, a pathological hallmark of adverse cardiac remodeling and heart failure, has been conventionally attributed to the activation of resident fibroblasts. Although recent studies suggest contributions from non-fibroblast lineages, direct in vivo genetic evidence that cardiomyocytes can undergo a mesenchymal-like fate transition during myocardial fibrosis remains absent. This study aims to investigate whether such a transition occurs and to elucidate the underlying regulatory mechanisms. METHODSHuman myocardial infarction (MI) tissues were analyzed by immunohistochemistry and integrated with public single-nucleus RNA sequencing (snRNA-seq) data to detect mesenchymal-like signatures in cardiomyocytes. Genetic lineage-tracing was performed in MI mice, and in cardiomyocyte-specific Hgs (hepatocyte growth factor-regulated tyrosine kinase substrate) gene knockout mice, to map the fate of cardiomyocyte-derived cells. Mechanistic insights were obtained through proteomic and snRNA-seq analysis of Hgs knockout hearts and validated through gain- and loss-of-function experiments targeting Aldh1a2 (aldehyde dehydrogenase 1 family member A2). RESULTSIn human MI samples, a subset of cardiomyocytes showed reduced expression of cardiomyocyte markers concurrent with acquisition of mesenchymal-associated markers. Genetic lineage tracing demonstrated that adult cardiomyocytes can adopt a mesenchymal-like cell fate during post-MI remodeling. We identify HGS as a factor constraining this transition. Hgs knockout in adult cardiomyocytes upregulated Aldh1a2, triggered the mesenchymal-like fate transition, and gave rise to cells expressing markers of activated fibroblasts or osteoblasts, accompanied by pronounced myocardial fibrosis and calcification. Forced Aldh1a2 overexpression in cardiomyocytes drove the mesenchymal-like fate transition in vitro and in vivo, whereas Aldh1a2 deletion in cardiomyocytes mitigated MI-induced myocardial fibrosis. CONCLUSIONSThis study provides in vivo genetic evidence that adult cardiomyocytes possess the capacity to undergo a mesenchymal-like fate transition under pathological conditions. Our data suggest that HGS and ALDH1A2 serve as regulators of the transition, offering a new basis for understanding cellular and molecular mechanisms of myocardial fibrosis. Novelty and SignificanceO_ST_ABSWhat Is Known?C_ST_ABSO_LIMyocardial fibrosis is primarily driven by resident fibroblast activation, with additional contributions from cardiac CD34+ cells, pericytes, and macrophages. C_LIO_LIAdult cardiomyocytes exhibit phenotypic plasticity and transdifferentiate into epicardial-like or pacemaker cells under specific conditions. C_LI What New Information Does This Article Contribute?O_LIA subset of cardiomyocytes adopts a mesenchymal-like cell fate during myocardial fibrosis, marked by downregulation of cardiomyocyte identity markers and loss of aligned cell-cell contacts. C_LIO_LIThese cells acquire mesenchymal morphology and markers, ECM components, migratory gene signatures, and proliferative capacity. C_LIO_LIHGS and ALDH1A2 act as regulators of this mesenchymal-like fate transition. C_LI Myocardial fibrosis drives heart failure progression, yet the cellular sources of pathological fibroblasts remain incompletely defined. Here, we demonstrate that a subset of cardiomyocytes adopts a mesenchymal-like cell fate during myocardial fibrosis by using an integrated approach combining human MI samples, murine genetic lineage tracing, and snRNA-seq. Mechanistically, we identify HGS and ALDH1A2 as regulators of this transition. Cardiomyocyte-specific Hgs deletion upregulates Aldh1a2, triggering the mesenchymal-like fate transition. Furthermore, Aldh1a2 overexpression drives this transition, while its deletion attenuates MI-induced fibrosis. These findings reveal a previously unrecognized plasticity of adult cardiomyocytes and identify potential therapeutic targets for fibrotic heart disease.

genetics↗

bioRxiv2026

DyMoTree decodes early cell state transitions and drivers from single-cell transcriptomes using a tree-structured neural network

Inferring early cell fate from single-cell RNA-sequencing data is essential for identifying cellular origins and fate plasticity in development and disease. However, existing methods often fail to exploit tree-structured lineage trajectories, limiting the accuracy and interpretability of fate mapping. Here we present DyMoTree, a computational framework that models cell fate decisions as nonlinear mappings between progenitor and terminal cell states under explicit lineage constraints. By integrating lineage graphs with a tree-structured neural architecture, DyMoTree learns lineage-resolved cell-state transition maps from single-cell transcriptomes, enabling robust inference of early fate bias and identification of fate-specific progenitor substates and driver genes. Across simulations, lineage-tracing experiments, and in vivo systems, DyMoTree outperformed existing methods in resolving early fate biases. Applications to mouse embryogenesis, lung adenocarcinoma progression, and CAR-T immunotherapy revealed regulatory programs underlying developmental and disease-associated transitions. DyMoTree provides a general framework for modeling lineage-resolved cell-state dynamics underlying development and disease progression. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=156 SRC="FIGDIR/small/731114v2_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@11e715dorg.highwire.dtl.DTLVardef@1a4c695org.highwire.dtl.DTLVardef@e98805org.highwire.dtl.DTLVardef@1e14054_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2026

Transient suppression of the ECM1 gatekeeper is essential for HGF/c-MET-driven liver regeneration

Hepatocyte growth factor (HGF) is a multifunctional cytokine stored in the extracellular matrix as an inactive precursor and is essential for tissue repair. How HGF activity is dynamically regulated during regeneration remains unclear. Here, we identify extracellular matrix protein 1 (ECM1) as a physiological inhibitor of active HGF during liver regeneration. Following 70% partial hepatectomy, active HGF rapidly increases in parallel with a sharp decline in ECM1, and preventing this downregulation delays liver mass recovery. Mechanistically, ECM1 directly binds the active HGF -subunit through a mechanism dependent on residue R392, thereby suppressing c-MET-ERK-MYC signaling and hepatocyte proliferation. Loss of ECM1 permits activation of this pathway, whereas MYC overexpression rescues ECM1-mediated growth inhibition. In patients, proliferative hepatocytes localize to ECM1-negative regions. Supported by transcriptomic analyses and computational modeling, these findings identify ECM1 as an extracellular gatekeeper whose transient downregulation enables HGF-driven tissue repair. HighlightsO_LIECM1 is temporally downregulated during liver regeneration, while forced ECM1 expression delays liver mass recovery after 70% PHx by suppressing hepatocyte proliferation. C_LIO_LIRapid and transient ECM1 downregulation permits HGF-c-Met-ERK-MYC signaling to drive hepatocyte cell-cycle entry and expansion. C_LIO_LIECM1 directly binds the active HGF -subunit with residue R392 playing a critical role, revealing a novel extracellular mechanism for growth factor inhibition. C_LIO_LILoss of ECM1 marks proliferative hepatocytes in human liver repair, identifying ECM1 as a tunable regulator of regenerative capacity. C_LI

cell biology↗

bioRxiv2026

Transgenic human dipeptidyl peptidase-4 Syrian hamsters support MERS coronavirus infection and contact transmission

Middle East respiratory syndrome coronavirus (MERS-CoV) is a global health concern due to a high fatality rate associated with human infections and no approved vaccines or therapeutics. While Syrian hamsters are a value animal model for coronavirus research, including SARS-CoV-2, MERS-CoV does not infect wild-type hamsters. Here, we generated transgenic Syrian hamsters expressing human dipeptidyl peptidase-4 (hDPP4), the cellular receptor for MERS-CoV., MERS-CoV replicated efficiently in the respiratory tract tissues of hDPP4 hamsters, causing lethal disease. Treatment with the 3CLpro inhibitor nirmatrelvir significantly reduced viral titers in the lower respiratory tract of infected hDPP4 hamsters. While airborne transmission was not observed, direct contact transmission was observed in all contact hDPP4 hamsters cohoused with infected cage mates. Immunization with purified MERS receptor-binding domain protein reduced virus replication and disease severity but did not prevent direct contact transmission. Collectively, our findings demonstrate that hDPP4 transgenic Syrian hamsters are useful for studying MERS-CoV pathogenesis, transmission, and countermeasure efficacy.

microbiology↗

bioRxiv2026

First evaluation of a human DPP4 transgenic hamster model for MERS-CoV pathogenesis and transmission

MERS-CoV poses a constant pandemic risk, as its viral lineages continue evolving, and zoonotic spillover events could lead to random viral polymorphisms that might lead to human adapted variants. Currently, no small animal model reliably recapitulates both disease progression and transmission dynamics, which are critical aspects for counter-viral measures like vaccine development. Although the Syrian hamster is an optimal animal model for SARS-CoV-2 infection and transmission, it is naturally resistant to MERS-CoV infection. Dipeptidyl peptidase-4 (DPP4) is the functional receptor for MERS-CoV infection, and is highly expressed in human kidney, intestine, liver, and lung tissues. Here, we evaluated the suitability of a human DPP4 (hDPP4) transgenic Syrian hamster model for MERS-CoV research. We used two different MERS-CoV strains (EMC/2012 and D10540/2023) for intranasal inoculation of hamsters. Both strains replicated efficiently, led to comparable severe clinical outcomes, and had similar viral transmission efficiencies. MERS-CoV RNA and nucleoprotein antigen were mainly detected in the brain and the respiratory tract. In summary, we validated a novel hDPP4-transgenic hamster as a suitable model for MERS-CoV infection enabling vaccine and transmission research.

microbiology↗

bioRxiv2026

Nucleolar Dynamics During Oogenesis

Ribosome biogenesis is a conserved and highly regulated process that starts in the nucleolus, a membrane-less multi-phase organelle. Although the architecture of the nucleolus is known to change due to perturbations, how nucleolar organization is modulated during physiological processes to meet changing translational demands remains unclear. Here, we use zebrafish oogenesis as a developmental context requiring a rapid expansion of translational capacity to investigate the regulation of nucleolar architecture. We show nucleoli undergo coordinated changes in number, size, subnuclear localization, and layering throughout oogenesis. We further demonstrate that nucleoli form around extrachromosomal DNA circles that contain the rDNA locus. Notably, mouse oocytes undergo similar developmental changes in nucleolar layering and phase organization, indicating that remodeling of nucleolar condensates is a conserved feature of oogenesis. These findings reveal previously unexplored regulation of nucleolar architecture as developmental adaptations to changing biosynthetic needs.

developmental biology↗

bioRxiv2026

Somatic mutations reveal the ontogeny of human microglia

Microglia are the resident hematopoietic cells of the central nervous system1. In mice, microglia seed the brain during embryogenesis and can be maintained throughout life with minimal input from adult hematopoiesis2-4. The origins of human microglia are less clear, but recent evidence suggests that marrow-derived cells may be able to supplement the human microglial pool in certain individuals5,6. Here, to investigate the ontogeny of human microglia, we develop a method that uses the collection of accumulated somatic mutations which uniquely labels each clone of cells to track the infiltration of marrow-derived cells into the human brain. Applying this method to 20 aged individuals, we find evidence of an influx of marrow-derived cells into the brain in all examined individuals. Single cell analysis, including single cell lineage tracing using mitochondrial DNA variants, demonstrates that these infiltrating cells are nearly identical to microglia and can comprise a large fraction of the microglial pool. Analysis of large-scale sequencing cohorts demonstrates a protective association between most types of clonal hematopoiesis and Alzheimers disease. In sum, this work uncovers a widespread influx of myeloid cells into the healthy human brain which serves to reinforce the pool of human microglia and becomes common with aging.

immunology↗

bioRxiv2026

A data-driven redefinition of global biodiversity hotspots

The 36 global biodiversity hotspots harbor a disproportionate share of the worlds endemic species, making their conservation critical for planetary health. Traditionally hotspots were defined as ecoregions with [≥]1,500 endemic vascular plant species and >70% natural habitat loss; this relied heavily on expert judgment, with subjective assessments of endemism and habitat loss applied. Challenges in defining endemism, quantifying habitat loss, and the global unevenness in available vascular plant data have hindered hotspot identification over the past decades. Here, we built a global dataset of 150,487 rare vascular plants, identified from 88.1% of the worlds known vascular species, and recognize hotspots based on their richness using three complementary conservation targets and algorithms. We then quantified natural habitat loss and habitat fragmentation using high-resolution remote sensing data and assessed the diversity and distribution of terrestrial vertebrates within these newly identified hotspots. Our data-driven method recovered all the 36 established global biodiversity hotspots, revised 17, and identified 11 new hotspots spanning diverse ecosystems across six continents. These 47 hotspots cover 26.63% of global land area, yet contain 83.8% of rare vascular plants, 92.4% of mammals, 96.1% of birds, 87.8% of reptiles, and 95.0% of amphibians. Collectively, they encompass >89% of terrestrial vertebrates classified as IUCN threatened species. Only 10 hotspots have undergone [≥]70% habitat loss, and the lack of a consistent relationship with habitat fragmentation suggests that this criterion is not globally applicable. Effectively protecting [~]27% of Earths land could theoretically safeguard >89.8% of threatened terrestrial species and >67% of threatened terrestrial species hotspot area, assuming effective protection of the identified biodiversity hotspots. Targeted conservation efforts within these global biodiversity hotspots can meet the established biodiversity targets of the Kunming-Montreal Global Biodiversity Framework as well as post-2030 biodiversity targets. Most importantly, our framework enables conservation scientists to iteratively identify and update global biodiversity hotspots in step with growing global biodiversity data.

ecology↗

bioRxiv2026

Tumor cell specific total mRNA expression informed neural networks predicts cancer progression

Inferring tumor molecular phenotypes from high-dimensional multi-omic data is a fundamental challenge in computational biology. Current methods for estimating tumor cell-specific total mRNA expression (TmS) require matched DNA and RNA sequencing data and rely on computationally intensive deconvolution pipelines. We present TmSNet, a deep learning framework that predicts TmS using mRNA, DNA methylation, miRNA, and immune cell proportions as input features. TmSNet integrates structured feature selection (gradient boosting, LASSO, elastic net) with specialized neural architectures to predict continuous TmS. Across 12 TCGA cancer types, TmSNet achieved cross-validated performance up to concordance correlation coefficient (CCC) = 0.93 and correlation R{superscript 2} = 0.88 and generalized to external cohorts with correlations of 0.54 (SCAN-B) and 0.43 (FUSCC). Predicted TmS values effectively stratify patients by risk and preserve known transcriptional profiles across tumor subtypes. These results demonstrate that TmSNet can infer biologically meaningful phenotypes from multi-omic data and provide a scalable framework for modeling tumor transcriptional activity in heterogeneous cohorts.

bioinformatics↗

bioRxiv2026

A unified framework for causal gene regulatory network inference grounded in orthogonal molecular evidence

Gene regulatory networks (GRNs) govern gene expression, cellular differentiation, and stable transcriptional states. Yet inferring GRNs that integrate molecular regulatory mechanisms and reproduce transcriptional states as stable outcomes remains a central challenge. Here we present SETIA, a framework that infers GRNs whose explicit dynamical models reproduce transcriptional profiles as one or more stable states across conditions. Applied to RNA-seq data from wild-type and transcription factor knockout strains in Saccharomyces cerevisiae, SETIA infers GRNs that accurately reproduce held-out transcriptional states in cross-validation experiments. Incorporating TF-promoter binding and protein-protein interaction priors, SETIA yields GRNs ranging from mechanistically grounded architectures to flexible models that capture indirect regulatory influences. SETIA reveals that gene expression organizes into discrete stable states that represent distinct transcriptional programs, all emerging as stable attractors of a single underlying GRN whose dynamics are predominantly explained by TF-DNA binding and protein-protein interactions from orthogonal molecular evidence. HighlightsO_LISETIA infers causal gene regulatory networks whose dynamics reproduce and generalize to held-out transcriptional profiles as stable attractors C_LIO_LIGenes occupy multiple discrete, reproducible expression states C_LIO_LIA ChIP-exo-derived protein-protein/DNA interaction network provides structural priors that ground the GRN in molecular mechanisms C_LIO_LIMolecular structural priors improve mechanistic interpretability while maintaining dynamical performance C_LIO_LISETIA generalizes across bulk and single-cell data and scales to a semi-genome-scale regulatory network C_LI

systems biology↗

bioRxiv2026

Exploring the ageing and survival costs of investment in anti-predation responses in a wild insect?

Escape behaviour directly influences survival, yet individuals often vary substantially in escape performance. Laboratory studies have documented trade-offs between anti-predator responses and life-history traits, but it remains unclear whether such trade-offs occur under natural predation risk. We studied a natural population of the field cricket Gryllus campestris. Mortality risk and behavioural performance are known to change with age in this species. We aimed to determine whether individuals expressing a higher escape response pay a cost in terms of a faster increase in mortality risk with age or a shorter lifespan. We quantified escape speed in response to a vibrational predation cue. We found no clear evidence for a trade-off between escape performance and lifespan or age-specific mortality risk. The relationship between escape speed and the among-individual effect of age differed between sexes: older males showed faster escape speeds compared with younger males, whereas younger females were faster than older females. This pattern is consistent with sex-specific selective disappearance. Individual baseline mortality risk varied with sex and escape speed, but age-dependent mortality did not. It suggests that such trade-offs in the wild may be context- or condition-dependent rather than reflecting a universal life-history trade-off.

animal behavior and cognition↗

bioRxiv2026

Insulin receptor substrate 2 (IRS2) confers resistance to PI3K pathway inhibition in PIK3CA mutant breast cancer

Activating mutations in PI3K are one of the most frequent mutations in breast cancer and are associated with worse patient outcomes in many breast cancer subtypes. Despite intense interest, cancer treatments that target the PI3K pathway have been only modestly effective due to intrinsic and acquired resistance mechanisms which reactivate PI3K signaling. Here, we characterize a feedback mechanism by which PI3K pathway inhibitors increase insulin receptor substrate 2 (IRS2) abundance and demonstrate the role of IRS2 in promoting resistance to these drugs. In PIK3CA mutant breast tumors and cell lines, there is a significant reduction in IRS2 mRNA and protein abundance which is reversed by PI3K pathway inhibition and mediated by the transcription factor FOXO3. PIK3CA mutations do not alter IRS1 expression. IRS2 confers resistance to PI3K pathway inhibition by sustaining PI3K signaling in PIK3CA mutant, but not wild-type breast cancer cells. Increased IRS2 abundance also correlates with PI3K pathway inhibitor resistance across PI3K mutant cancer cell lines from a variety of tissues. The clinical relevance of these findings is highlighted by the frequency of PI3K mutations in cancer and the identification of a new target to address the challenges associated with prior efforts to block the reactivation of PI3K signaling during PI3K inhibition.

cancer biology↗

bioRxiv2026

SNAC-DB: An ML-Ready Database for Antibody and NANOBODY(R) VHH-Antigen Complexes with Expanded Structural Diversity and Real-World Benchmarking

Predicting antibody and NANOBODY(R) VHH-antigen complexes remains a critical challenge for state-of-the-art structure prediction models, limiting their impact in therapeutic discovery pipelines. We introduce SNAC-DB, an ML-ready database and curation pipeline enriched with structural biology expertise, designed to accelerate model accuracy and generalization by providing 31-37% expanded structural diversity over existing resources like SAbDab through comprehensive re-curation that extracts maximum value from available experimental structures. SNAC-DB expands coverage by capturing often-overlooked complexes and accurately identifying complete multi-chain epitopes through improved biological-assembly-based logic. Built for ML practitioners, SNAC-DB provides standardized formats with multi-threshold structure-based clustering to enable principled sample weighting during training. Using a rigorous benchmark of public PDB entries deposited post-May 2024 plus confidential therapeutic structures, we evaluate seven leading models (Protenix-v1, OpenFold-3p2, RosettaFold-3, Boltz-2, Boltz-1x, Chai-1, and AlphaFold2.3-multimer) with evaluation methodology tailored to antibody/NAN-OBODY(R) VHH-antigen complexes to ensure correct handling of multi-chain epitopes, revealing systematic performance gaps: success rates rarely exceed 25%, confidence-based ranking fails to identify best predictions even when accurate structures exist in ensembles, and all models consistently struggle with therapeutically relevant NANOBODY(R) VHHs. Systematic evaluation of sampling strategies demonstrates that while generating 1000 samples per target substantially increases the likelihood of producing accurate structures (oracle selection improves from 11.9% to 50.5%), confidence-based ranking remains nearly flat (between 10.9% and 14.9%), revealing that improved ranking mechanisms represent a more tractable path to performance gains. Finally, fine-tuning GeoDock on SNAC-DB yields higher success rates than training on SAbDab (11.0% vs. 7.1% for antibodies; 7.0% vs. 4.0% for NANOBODY(R) VHHs), suggesting that SNAC-DBs expanded structural diversity translates to improved model generalization. Significance StatementComputational antibody/NANOBODY(R) VHH design shows promise but remains unreliable for therapeutic development. SNAC-DB provides 31-37% expanded structural diversity through comprehensive data curation, immediately accelerating model development. Benchmarking seven leading AI models reveals accuracy rarely exceeds 25% on therapeutic targets, with confidence-based ranking failing to identify correct structures even when they exist in model outputs. Training on SNAC-DB increases prediction accuracy, validating that high-quality, diverse training data is critical for advancing computational methods toward clinical impact.

bioinformatics↗

bioRxiv2026

Comparative benchmarking of single-cell transcriptomes and immune repertoires across technologies

Immune receptor profiling enables tracking of individual T or B cell clones across time and tissues, providing insight into immune responses, cancer, and autoimmunity. When combined with single-cell transcriptomics, it links clonotype identity to cellular function, revealing the diversity and dynamics of immune cell populations. This study presents a head-to-head benchmarking comparison of two single-cell immune profiling technologies: droplet-based microfluidics from 10x Genomics (10x) and combinatorial barcoding from Parse Biosciences (Parse). Using matched human samples from PBMCs, the analysis evaluates performance across transcriptomic and T cell immune receptor features to assess data quality, reproducibility, and chain-specific recovery. The findings provide a framework for interpreting single-cell immune profiling platforms and emphasize the importance of accounting for technology-specific biases in bioinformatic analyses.

bioinformatics↗

bioRxiv2026

Tetrahydrocurcumin Suppresses Bladder Carcinogenesis via Reprogramming O-GlcNAcylation-Phosphorylation Crosstalk

Bladder cancer exhibits high recurrence rates and limited therapeutic options in advanced stages. Although post-translational modifications (PTMs) are critical regulators of tumor biology, their systems-level remodeling during bladder carcinogenesis remains insufficiently defined. Using a BBN-induced murine bladder cancer model combined with tumor-derived organoids and bladder cancer cell lines, we observed a consistent global elevation of protein O-GlcNAcylation across tumor-associated contexts. Site-resolved quantitative proteomics revealed that this increase reflected selective redistribution rather than uniform accumulation, with differential O-GlcNAc sites nearly evenly divided between up-and down-regulated events. Integrated analyses demonstrated preferential enrichment of up-regulated O-GlcNAcylation within cytoskeleton-adhesion modules and Notch-related domains, whereas down-regulated events were more closely associated with structural maintenance and homeostatic programs. Approximately half of differentially O-GlcNAcylated proteins exhibited concurrent phosphorylation changes, indicating coordinated multi-layer PTM remodeling. Pharmacological inhibition of O-GlcNAc transferase suppressed bladder cancer cell proliferation and organoid growth, supporting a functional association between elevated O-GlcNAcylation and tumor growth. Tetrahydrocurcumin (THC) reduced global O-GlcNAcylation and induced directional remodeling of BBN-associated O-GlcNAc patterns. Cross-comparative analyses identified subsets of sites exhibiting opposite regulation trends following THC intervention. Collectively, these findings define a spatially and functionally organized PTM remodeling landscape in bladder cancer and suggest that THC exerts anti-tumor effects in part through coordinated reprogramming of O-GlcNAcylation and phosphorylation networks.

cancer biology↗

bioRxiv2026

Discovery of Selective Nrf2 Activators from Natural Products: AComputational Screening Approach to Minimize Off-Target Effects on PXR and CYP2D6

Nuclear factor erythroid 2-related factor 2 (Nrf2) is a central regulator of cellular antioxidant responses and a highly promising therapeutic target for a range of oxidative stress-related diseases. However, the clinical translation of Nrf2 activators has been hampered by significant off-target effects--notably unintended activation of the pregnane X receptor (PXR) and inhibition of cytochrome P450 2D6 (CYP2D6)--which can lead to dangerous drug-drug interactions and metabolic complications. To overcome this critical barrier, we conducted the first large-scale computational screening of 628,898 natural products from the COCONUT database, integrating molecular docking with a rigorous three-tier selectivity strategy designed to prioritize compounds that strongly bind KEAP1 (the primary Nrf2 repressor) while minimizing interactions with PXR and CYP2D6. Our innovative approach identified 10 ultraselective candidates that demonstrate potent KEAP1 affinity, negligible PXR engagement, and only moderate CYP2D6 binding--achieving up to 12.29-fold selectivity for Nrf2 pathway activation. These top hits are structurally novel, enriched in lipid-like and nucleoside-inspired scaffolds, and exhibit promising drug-like properties. By providing both a curated set of chemically diverse, selectivity-optimized leads and a publicly accessible screening dataset, this work establishes a new foundation for the rational development of safer, more precise Nrf2-targeted therapies, bridging a crucial gap between target potential and clinical viability. By prioritizing compounds with minimal off-target effects on PXR and CYP2D6, our approach offers a scalable template for reducing drug development failures and advancing safer therapeutics for oxidative stress-related diseases. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=124 SRC="FIGDIR/small/718057v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@13c6c79org.highwire.dtl.DTLVardef@1f5a078org.highwire.dtl.DTLVardef@fa4f4borg.highwire.dtl.DTLVardef@16bc881_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO C_FIG

bioinformatics↗

bioRxiv2026

Sharp cell type boundaries emerge from coordinated morphogen signaling

Classic models of the French flag problem depict sharp cell-type boundaries emerging from threshold responses to morphogen gradients. How discrete cell-type boundaries arise from morphogen signals that vary continuously across developing tissues is not completely understood. We use hair follicle dermal condensate formation to study a sharp developmental transition in which proliferative progenitors undergo cell-cycle exit concurrent with molecular differentiation. Using genetic and genomic approaches, we show that Wnt and Hedgehog signaling interact to coordinate the timing of these two processes. We identify a division of labor between the pathways: Wnt signaling promotes cell-cycle exit by regulating chromatin binding of the Hedgehog mediator GLI3, while Hedgehog signaling induces differentiation genes in a Wnt-dependent manner and simultaneously elevates Wnt activity. When Wnt and Hedgehog activities are temporally aligned, differentiation and cell-cycle exit occur within the same developmental window, restricting both the duration and abundance of intermediate states and producing a sharp cell-type boundary. When these signals are misaligned, intermediate states persist and expand, producing fuzzy boundaries. These findings reveal a mechanism in which interacting morphogen signals regulate the duration and abundance of intermediate states during a developmental transition, thereby controlling how continuous cell-state progression is translated into discrete tissue patterning.

developmental biology↗

bioRxiv2026

Systemic and tumor intrinsic expansion of FCRL5 expressing B cells associates with poor response to Bacillus Calmette-Guerin immunotherapy in patients with non-muscle invasive bladder cancer

The majority of patients treated with Bacillus Calmette-Guerin (BCG) immunotherapy, for non-muscle invasive bladder cancer (NMIBC), experience early recurrence due to pre-existing mucosal immune dysfunction. Since B cell are mucosal immune sentinels, we characterized the systemic and local B cell responses in 45 patients with NMIBC. Expansion of circulating atypical B cells (ABCs) following repeated BCG instillation, expanded IgG autoantibody repertoire, progressive IgG reactivity against BCG antigens, and higher tumor IgG deposition, were features of patients who recurred early. Integrated spatial immunophenotyping and single cell spatial transcriptomic analysis of corresponding tumors revealed increased ABCs within tertiary lymphoid structures, and co-localization with PD-1 B cells, regulatory T cells, and CD163 macrophages. Independent validation in two patient cohorts (total n = 409), revealed a significant association between high expression of the ABC specific, FCRL5, and poor outcomes. Our study identifies ABCs as key mediators of poor response to BCG in patients with high-risk NMIBC.

cancer biology↗