Biology subjects

Huang, W.

Publications and source records attributed to Huang, W..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Molecular Editing in Protein Degradation: From a Dual NSD2/GSPT1 Degrader to an NSD2-Selective PROTAC and a GSPT1-Selective Molecular Glue

Both NSD2 and GSPT1 represent compelling targets for anti-cancer drug discovery. Herein, we carried out single-atom modification of LLC0424, an NSD2 degrader with GSPT1 neosubstrate engagement, to yield two structurally analogous molecules with divergent modes of action: 424-ND, an NSD2-selective degrader, and 424-GD, a GSPT1-selective degrader. 424-ND drove selective NSD2 degradation and suppressed androgen receptor (AR) signaling in prostate cancer cells. 424-GD induced selective degradation of GSPT1 and upregulated the integrated stress response markers ATF4 and ATF3. Biolayer interferometry revealed distinct ternary complex cooperativity profiles in the presence of NSD2 or GSPT1, which directly correlate with the observed biased degradation activity. Molecular dynamics and metadynamics simulations showed that the compounds adopt distinct low-energy conformational ensembles with different spatial orientations, likely underlying their divergent cooperativity and selectivity. These findings demonstrate that minimal structural alteration permits precision control over degrader target selectivity, while furnishing selective chemical probes for NSD2 and GSPT1.

cancer biology↗

bioRxiv2026

A physics-informed hybrid deep learning model for spatiotemporal rice disease prediction using multi-source data

Accurate, reliable, large-scale disease predictions are essential to ensure rice production. Existing disease prediction models often face a trade-off between interpretability and predictive capability, necessitating the integration of mechanistic knowledge and data-driven learning within a modelling framework. Accordingly, we propose a physics-informed hybrid gated recurrent unit (PI-HGRU) model for spatiotemporal dynamic prediction of rice sheath blight disease, caused by a fungus. Our model embeds differential equations describing disease transmission dynamics into a hybrid gated recurrent unit (HGRU) framework as mechanistic constraints, thereby enabling collaborative modelling between epidemiological processes and data-driven learning. We conducted model training and evaluation using a long-term, multi-source dataset spanning 17 years (2000-2016) and covering 16 major rice-producing provinces in southern China. These rich data include spatiotemporally aligned field disease observations, remote sensing data, meteorological data, and soil property data. In addition, to address the challenges of irregular sampling intervals and inconsistent sequence lengths in disease survey data, we adopted a sliding time-window-based prediction framework. We further conducted a time-window sensitivity analysis to determine appropriate configurations of the input time window and lag time, enabling the model to represent the cumulative and delayed effects of environmental factors. Our PI-HGRU framework substantially outperforms the purely data-driven HGRU baseline model, improving the squared Pearson correlation coefficient (r2) by 22.8% while reducing the root mean square error (RMSE) and mean absolute error (MAE) by 10.2% and 18.0%, respectively. Furthermore, analysis of the models intermediate variables showed that the transmission rate {beta}(t) exhibited interpretable relationships with environmental conditions within the input time window, providing a process-related link between environmental drivers and modeled disease transmission dynamics. Overall, our work demonstrates that integrating epidemiological mechanisms into deep learning models in a physics-informed manner can improve predictive accuracy and stability while enhancing model interpretability, highlighting its potential for large-scale disease forecasting and precision disease management.

bioinformatics↗

bioRxiv2026

Time-Resolved Single-Cell Atlas Reveals Early Endothelial Activation and Stage-Dependent Immune-Stromal Communication in HFpEF

BackgroundHeart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome associated with metabolic stress, hypertension, systemic inflammation, and microvascular dysfunction. Early cell-type-specific events and intercellular communication programs that accompany disease onset and progression remain poorly defined. MethodsWe performed a longitudinal study of HFpEF progression in high-fat diet (HFD)+L-NAME mice at control/baseline (0 weeks, 0w/Ctrl), early (1w), intermediate (4w), and established (8w) stages. Metabolic, hemodynamic, exercise, echocardiographic, and single-cardiomyocyte function were assessed. Cardiac non-cardiomyocytes (non-CMs) were profiled by single-cell RNA sequencing (scRNA-seq), with bulk RNA-seq for tissue-level comparison. Endothelial remodeling was assessed in an L-NAME-independent HFD plus mild transverse aortic constriction model (HFD+mTAC) and a published human HFpEF single-nucleus RNA-seq cohort. An endothelial-macrophage adhesion assay tested whether HFpEF-mimic stress promotes endothelial activation and macrophage adhesion. ResultsIn the HFD+L-NAME model, metabolic dysfunction, hypertension, reduced exercise tolerance, abnormal diastolic filling with preserved ejection fraction, and altered cardiomyocyte calcium handling were detected by 1w and persisted through 8w. Bulk RNA-seq showed progressive remodeling, with limited change between 8w and 12w, guiding scRNA-seq timepoint selection. scRNA-seq of 94,848 cardiac non-CMs identified nine major populations with stage-dependent remodeling. Endothelial cells (ECs) were recovered in high proportion and showed an early, pronounced transcriptional response, with inflammatory, adhesion, interferon-response, migratory, and vascular-remodeling programs emerging by 1w. Related EC activation signatures were observed in HFD+mTAC and human HFpEF data. Functionally, HFpEF-mimic stress increased adhesion and chemokine expression in human ECs and enhanced macrophage adhesion. Fibroblast matrix remodeling occurred at later stages, while macrophages progressively shifted toward inflammatory states. CellChat suggested stage-dependent communication remodeling from early endothelial-immune interactions toward later macrophage-fibroblast crosstalk. ConclusionTime-resolved scRNA-seq reveals coordinated, stage-dependent remodeling of the cardiac microvascular and interstitial microenvironment during HFpEF progression. Early endothelial activation emerges before later fibroblast matrix remodeling and inflammatory macrophage remodeling, identifying candidate cell states and signaling pathways for future mechanistic investigation. Clinical PerspectiveO_ST_ABSWhat Is New?C_ST_ABSO_LIThis study provides a time-resolved single-cell atlas of the cardiac non-cardiomyocyte compartment across baseline, early, intermediate, and established stages of HFpEF progression, rather than a single late-stage snapshot. C_LIO_LIEndothelial cells exhibit early inflammatory, adhesion, interferon-response, and vascular-remodeling programs within the first week of disease, preceding the later predominance of fibroblast matrix remodeling and inflammatory macrophage remodeling. C_LIO_LIThis endothelial activation signature is supported across two mechanistically distinct HFpEF mouse models and aligns with endothelial inflammatory and vascular-remodeling programs in human HFpEF myocardium, supporting its translational relevance. C_LI What Are the Clinical Implications?O_LIEarly endothelial activation may represent a targetable stage of HFpEF pathogenesis that arises before more established structural and fibrotic remodeling. C_LIO_LITherapeutic strategies aimed at limiting endothelial inflammatory activation or endothelial-immune interactions may help attenuate downstream vascular, immune, and stromal remodeling in HFpEF. C_LIO_LIThese findings provide a preclinical foundation for future longitudinal human studies testing whether early endothelial activation can serve as a biomarker, therapeutic target, or disease-staging feature in HFpEF. C_LI

cell biology↗

bioRxiv2026

BCL11B targeting in tumor CD8+ T cells amplifies anti-tumor response by blocking exhaustion while promoting stemness and cytotoxicity

Tumor infiltrating CD8+ T cells (TILs) progress to a state of terminal exhaustion (Ttex) which have impaired functionality and are nonrenewable. However their precursors (Tpex) are renewable and can generate efficient effector cells. We started from the observation that melanoma patients undergoing therapy with checkpoint inhibitors show increased survival when their T cells have low BCL11B mRNA. In line with this, ablation of Bcl11b in CD8+ TILs conferred a superior anti-tumor response in murine melanoma and ovarian cancer models. Bcl11b KO TILs failed to progress to the Ttex state and retained elevated stemness. Bcl11b exerted its role by repressing expression of essential transcription factors (TF) controlling stemness, and conversely by promoting expression of exhaustion-associated TFs and inhibitory receptor genes, through complex epigenetic control. In addition, Bcl11b KO CD8+ T cells showed increased Ag-specific cytolytic activity and elevated Gzmb and Prf1 proteins, but no increase in their mRNAs, however presented higher expression of genes with role in translation. Furthermore, CRISPR-CAS9-mediated deletion of BCL11B in human TILs from a patient with poor response to adoptive cell therapy with autologous TILs, improved their cytolytic activity and promoted expression of the stemness-associated TF TCF1, underlying its potential therapeutic use. HIGHLIGHTS- Adoptive transfer of Bcl11b KO CD8+ TILs surpasses WT in tumor burden reduction - Bcl11b ablation reprograms TILs and impairs the progression to Ttex state - Bcl11b KO CD8+ T cells have elevated cytotoxicity and kill only Ag-MHCI targets - BCL11B deletion in nonresponder ACT-TIL improves cytolytic activity and elevates TCF1 GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=64 SRC="FIGDIR/small/742578v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@c3b965org.highwire.dtl.DTLVardef@1c09d75org.highwire.dtl.DTLVardef@a19748org.highwire.dtl.DTLVardef@d2fd6b_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2026

Catch-bond engineering surpasses high-affinity maturation for T cell receptor therapies against solid tumors

The sensitivity of T cell receptors (TCRs) has traditionally been attributed to their affinity, a principle that has long underpinned both T cell biology and TCR engineering. Currently, high-affinity maturation remains the predominant strategy employed to enhance TCR sensitivity; however, this approach has been associated with severe off-target toxicities in clinical settings. In this study, using the only FDA-approved TCR-T therapy as a clinical reference, we demonstrate that force-induced catch bonds, rather than static affinity, primarily determine TCR sensitivity and facilitate the development of more effective TCR engineering strategies. Among polar and charged amino acids, histidine was determined to be the most effective residue for pinpointing engineering hotspots. TCRs engineered to form catch bonds exhibited superior performance compared to the FDA-approved TCR subjected to high-affinity maturation, improving the efficacy of TCR-T cell therapies against solid tumors without eliciting off-target toxicity or alloreactivity. Mechanistically, a correlation was observed between TCR sensitivity and the strength of catch bonds, whereas no such relationship was found with affinity. The duration of T cell-tumor cell interactions, immunological synapse formation, and the intensity of subsequent signaling are governed by catch bonds rather than by affinity. Structural and computational investigations have demonstrated that force-induced reconfiguration of the ligand-receptor interface, along with the formation of a novel hydrogen bond network, augments the specificity of interactions between the TCR and antigenic peptides. Furthermore, bispecific T cell engagers utilizing the TCR scaffold also formed catch bonds with tumor antigens, indicating intrinsic mechanosensory properties of the extracellular domains of TCRs and suggesting a novel therapeutic modality based on catch-bond-engineered TCRs.

immunology↗

bioRxiv2026

ERK signaling integrates multiple mechanisms to drive cortical evolutionary expansion

A critical first step in human evolutionary divergence from chimpanzees and other primates is the production of greatly increased numbers of cortical pyramidal neurons during development and over evolutionary time. This expansion underpins the enlarged human cerebral cortex and, consequently, higher-order cognition and consciousness. However, the cellular and molecular mechanisms driving this progressive increase in cortical neuron number remain incompletely understood. Here we show that elevated ERK signaling in human cortical radial glia (RGs), relative to mouse RGs, arises from evolutionary changes in the developmental expression of existing shared genes. Using the Emx1-Cre line to overexpress MEK1DD, a constitutively active mutant of rat MAP2K1, we found that enhanced ERK signaling in mouse cortical RGs upregulates cAMP-PKA signaling, along with promoting self-renewal, expanding the RG pool, and accelerating cell cycle progression. Conversely, overexpression of PKA signaling in mouse cortical RGs via in utero electroporation of constitutively active PRKACA mutants (L206R or W196G) reduces ERK activity, prolongs the cell cycle, suppresses SHH-SMO and YAP/TAZ pathway activity, and blocks ependymal gliogenesis. Together, our results demonstrate that ERK and PKA signaling in cortical RGs engage a dynamic balance of synergistic and antagonistic interactions. This interplay couples evolutionarily enhanced ERK and PKA activities to increased cortical RG numbers, prolonged cell cycle progression, and an extended neurogenic period, which collectively culminate in a marked increase in neuronal production. We conclude that heightened ERK pathway activity in cortical RGs serves as a central driver of progressive neocortical expansion across mammalian evolution. Significance StatementThe human brains extraordinary cognitive abilities stem from a dramatic increase in cortical neuron numbers during evolution. This study reveals that enhanced ERK signaling in human cortical radial glia neural stem cells, relative to other primates, is a key driver of this expansion. By manipulating this pathway in mice, we demonstrate that ERK coordinates multiple mechanisms--including self-renewal, cell cycle acceleration, and a dynamic interplay with PKA signaling--to boost neuronal output. These findings identify a core molecular axis underlying mammalian cortical evolution and provide a framework for understanding how the human cortex acquired its unique size and, consequently, its remarkable complexity.

developmental biology↗

bioRxiv2026

Widely used GWAS methods can be poorly suited to SNP-level localization under diffuse polygenic architecture in livestock

In livestock populations, genome-wide association studies (GWAS) can produce strong, apparently localized associations even when no truly discrete nearby causal effect exists. This occurs because small effective population sizes, strong family structure, long-range linkage disequilibrium (LD), and diffuse polygenic architecture can cause the effects of many variants to accumulate and be captured jointly across broad genomic intervals, making variant-level associations difficult to interpret biologically. Using real pig genotypes, we constructed a benchmark in which phenotypes were simulated under diffuse polygenic architecture across a genome partitioned into alternating effect and null windows, with central-null regions (at least 1 Mb away from effect-containing regions) positioned to detect long-range LD-driven signal propagation. We evaluated nine configurations of six GWAS methods (BOLT-LMM, REGENIE, fastGWA, FarmCPU, BLINK, and SLEMM) under this architecture. The central finding is that strong associations, of the kind normally read as evidence of nearby moderate- or large-effect variants, are produced by many of these methods even though the simulated signal is distributed across many tiny effects and cannot be localized to any single variant. The methods differed sharply in the extent of locus-level spillover: several produced large numbers of genome-wide significant loci within central-null regions, whereas the full-GRM mixed-model benchmark (SLEMM) produced no genome-wide significant loci in central-null regions. These results show that, under a highly polygenic architecture with livestock-like LD, GWAS tool choice has major consequences for biological interpretation. When the goal is to localize biologically meaningful signals rather than to flag association peaks that may merely reflect tiny effects accumulated through LD across a broad block, methods that control long-range LD spillover should be prioritized.

genetics↗

bioRxiv2026

AI-enabled rhodopsin design for blue-light enhanced bacterial growth

We developed an AI-guided design pipeline that generated and validated non-natural microbial rhodopsins with spectral properties not yet known in nature. The pipeline comprised a three-stage in silico design, a genetic algorithm (GA) for sequence generation, a stacked LASSO and XGBoost machine-learning (ML) regressor for spectral prediction and fitness ranking, and a Markov-based sequence plausibility filter to enforce proton pumping like characteristics. Four candidate rhodopsins (APR1, APR2, APR6, and APR7) targeting blue light absorption were designed and AlphaFold3 structural modelling predicted retinal binding pocket architecture consistent with outward proton-pumping function. Experimental characterisation confirmed that all four variants absorbed light at [~]410 nm and significantly promoted the growth of Cupriavidus necator under blue light illumination. This study demonstrates that AI-enabled design can engineer proteins with no natural precedent, generating light-harvesting rhodopsins with novel spectral properties while preserving biological function, marking a significant advance in programmable synthetic biology.

Synthetic Biology↗

bioRxiv2026

CRISPR/Cas9 knockout and editing of the major cysteine protease in Entamoeba histolytica

Entamoeba histolytica is the cause of amoebiasis, a diarrheal infection that is a significant source of morbidity and mortality. Despite its importance to human health, the basic mechanism of disease is poorly understood. E. histolytica is dramatically understudied, even in comparison to other understudied parasites, due to challenging features of its genome and the relative paucity of genetic tools. A major limitation is the historical lack of gene knockouts or manipulation of the endogenous genome. While CRISPR/Cas9 has led to major advances in the tractability of numerous parasites, until recently, it was not applied in E. histolytica, except for the demonstration of editing of an episomal plasmid. In this study, we further developed CRISPR/Cas9 and demonstrated the successful targeting of the endogenous cysteine protease 5 (CP5) gene, a major virulence factor. Further, we demonstrated successful CRISPR/Cas9-based editing of this locus, which represents the very first successful editing of the endogenous genome. In the course of these approaches, we developed the viral skip peptide approach as well as a suite of endogenous promoters to drive tunable levels of gene expression. We also performed the most extensive empirical testing of nuclear localization signals in E. histolytica that has been done. Thus, this work demonstrates effective CRISPR/Cas9-based manipulation of the endogenous genome, together with significant advances to the overall genetic toolkit that extend beyond CRISPR/Cas9. These great improvements in the tractability of E. histolytica thus set the stage for future studies to better define its virulence.

microbiology↗

bioRxiv2026

The Drosophila melanogaster Genetic Reference Panel, Version 3 (DGRP3)

Drosophila melanogaster is a leading animal model for understanding basic genetic principles for biomedical research and for quantitative, population and evolutionary genetics and genomics. The D. melanogaster Genetic Reference Panel (DGRP) of [~]200 inbred strains with full genome sequences is a publicly available resource for genome wide association (GWA) studies of quantitative traits, systems genetics, and population genomic analyses. However, the small size of the DGRP limits the power to map rare variants or variants with small effect sizes. Here, we describe the DGRP Version 3 (DGRP3), consisting of full genome sequences from 1,233 inbred lines, of which 1,037 are currently extant. The DGRP3 harbors extensive genetic diversity, with 8,760,339 molecular polymorphisms including single nucleotide polymorphisms, insertions, deletions, inversions, tandem duplications and complex rearrangements. We identified 80,894 damaging variants and 4,550 genes with at least one loss-of-function haplotype. We inferred 16 mitochondrial haplotype groups, determined the microbial composition, and quantified the numbers of sensory bristles for the DGRP3 lines. We performed GWA analyses for inbreeding depression, host control of microbiome composition, and numbers of sensory bristles, identifying novel candidate variants and genes for each. The accompanying online tool (flydgrp.org) implements state-of-the-art association mapping methods and provides results for users DGRP3 data.

genomics↗

bioRxiv2026

Inducible lipid storage and steatosis in the human choroid plexus associated with age and adiposity

Cells that store lipids for other cells or organs can contain "giant" or large lipid droplets (LLDs) greater than 2 {micro}m in diameter. In this study, human postmortem choroid plexus was evaluated for lipid droplets. Staining with hematoxylin and eosin (H&E), the lipophilic dye Oil red O, and anti-adipophilin antibodies established the presence of LLDs exceeding 10 {micro}m in diameter in choroid plexus epithelial cells (CPECs). Manual annotation of H&E stains from 105 cases revealed a significant association between age and the percentage of CPECs containing LLDs (reaching up to 69%) and involving LLDs in our largest annotated category (>5 {micro}m in diameter). The LLD association with age was replicated and extended to a total of 245 cases using a trained convolutional neural network, which further showed significant associations with body mass index at time of death (increasing with BMI), sex (higher in females >65 years old), and a near-significant association with Alzheimers Disease (lower in AD). Like HepG2 and derived hepatocytes, excess fatty acids in culture media readily induced LLDs and steatosis in human embryonic stem cell-derived CPECs. Akin to hepatocytes for the human body, we propose that CPECs store lipids for the human brain and become steatotic in the setting of excess adiposity.

pathology↗

bioRxiv2026

SynFit: Synergistic Contrastive Learning for Multi-Objective Protein Fitness Prediction and Optimization

Proteins function through a complex interplay of structural and biochemical properties, and mutations can reshape these properties to generate fitness landscapes spanning multiple functional objectives. A central challenge in protein engineering is the need to simultaneously optimize multiple properties. In biocatalysis, for example, practical enzyme development routinely requires the concurrent optimization of catalytic activity, selectivity, stability, and substrate generality. However, despite recent advances in computational protein design and fitness prediction, most existing approaches treat these properties independently and do not explicitly capture the dependencies and trade-offs that govern real-world protein performance. We present SynFit, a multi-objective learning framework that integrates pretrained protein language models with experimental fitness measurements for protein fitness prediction and engineering. SynFit learns both shared and property-specific protein sequence representations through a synergistic contrastive learning strategy, enabling the identification of variants that simultaneously optimize multiple functional properties. Across a large-scale multi-fitness deep mutational scanning benchmark, SynFit consistently outperforms state-of-the-art supervised models trained on individual objectives and more accurately identifies variants that balance competing functional constraints. We further applied SynFit to multi-objective enzyme design for a new-to-nature biocatalytic enantioselective borylation reaction, providing a diverse array of novel cytochrome c sextuple variants in a single round of design with simultaneously improved catalytic activity and enantioselectivity that rival the best variants obtained through directed evolution. Together, these results establish SynFit as a general framework for multidimensional protein fitness prediction and highlight its potential to enable efficient multi-objective optimization in protein engineering, particularly in biocatalysis.

bioinformatics↗

bioRxiv2026

Reduction of Weight Gain by Modulating Mitochondrial Energy Coupling Efficiency Using a Bromo-Coenzyme Q10 analog (6-Br-Q0C10)

Synthetic 6-Br-Q0C10 has been shown to have a partial electron transfer activity of native coenzyme Q in the isolated mitochondria. It reduces energy coupling efficiency by 30 %, suggesting that it may be useful in the management of obesity. The effect of 6-Br-Q0C10 on cell growth has been confirmed by several cell lines. Whether or not it behaves in the same way in the animal, however, has not yet been tested. Recently, we investigated the effect of 6-Br-Q0C10 on growth of rats. When 6-Br-Q0C10 was dissolved in different media, such as carboxymethyl cellulose, ethanol, and mixture of oil and butter and then feed to rats It shows no toxicity and little negative effects on growth as measured body weight gains over a period of time. When higher concentration (0.5 mg) of 6-Br-Q0C10 was given to each rat in 0.3 mL of oil/butter (70%/30%) mixture via intragastric injection daily for a period, a significant reduction in body weight gains was observed. These results validate the earlier observation that 6-Br-Q0C10 reduces the growth (30-60%) of all cell lines tested, in a time- and concentration dependent manner. These results strengthen the idea of using 6-Br-Q0C10 to manage obesity. It is also implying that 6-BrQ0C10 may slow the growth rate of cancer cells and thus prolong life. (This study was partially funded by NIH grants AA030221 and DA046258 to S.L.Chang.)

biochemistry↗

bioRxiv2026

CXCL13-CXCR5 Signaling in CD8⁺ T Cell Recruitment and Lymphoid Immune Organization in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) exhibits heterogeneity in immune infiltration and clinical outcomes, but the mechanisms governing recruitment and organization of tumor-reactive CD8 T cells remain incompletely defined. We investigated the role of the CXCL13-CXCR5 axis in shaping CD8 T cell recruitment, differentiation, and immune organization in high-risk, non-metastatic ccRCC. Human tumor, plasma, and matched adjacent kidney specimens were analyzed using ELISA, quantitative PCR, migration assays, multiplex immunofluorescence, single-cell RNA sequencing, spatial transcriptomics, and a syngeneic mouse model. CXCL13 was among the most upregulated chemokines in ccRCC relative to matched normal kidney and was embedded within a CD8 T cell-associated inflammatory transcriptional program. In transwell and microphysiological system (MPS) assays, CXCL13 promoted CD8 T cell migration, enriched CXCR5 cells among migrating CD8 T cells and showed reduced migration after CXCL13 or CXCR5 blockade. Single-cell analyses identified CXCR5 expression within stem-like CD8 T cell states associated with TCF7 and IL7R, whereas CXCL13 associated with later cytotoxic/exhausted states along a continuous differentiation landscape. Spatial transcriptomics demonstrated that stem-like CD8 T cells localized within structured lymphoid aggregates enriched for B cells, coordinated CXCL13/CXCR5 expression, and signaling programs. In vivo, tumor-derived CXCL13 suppressed tumor growth, increased intratumoral CD8 T cell infiltration, and enriched CXCR5TCF1CD8 stem-like T cells. In human tumors, higher CXCL13 expression correlated with increased CXCR5CD8 T cell infiltration and improved recurrence-free survival. These findings identify CXCL13 as a regulator of immune recruitment and niche organization and support the CXCL13-CXCR5 axis as a biomarker and possible therapeutic target in ccRCC.

cancer biology↗

bioRxiv2026

Coordinated phase separation and phase transition underlie synaptic ribbon condensate formation and plasticity

Mesoscale molecular apparatuses with diverse functions are widespread in cells. How mesoscale cellular apparatuses are formed and regulated is poorly understood. The synaptic ribbon in sensory neurons, which can dynamically adjust its size and shape in response to light or sound, is a mesoscale molecular assembly. In this study, we demonstrate that RIBEYE, the backbone protein of synaptic ribbons, via combined ordered and disordered interactions, forms micron-sized dynamic molecular assemblies. Integrated cryo-electron microscopy and tomography studies revealed that the N-terminal SAM domain and the C-terminal B domain of RIBEYE form distinct nanoscale filaments and further assemble into ribbon-like architectures via phase transition. Unexpectedly, the N-terminal intrinsically disordered region of RIBEYE softens the solid mesoscale ribbon structures via phase separation. The mesoscale size and shape of the RIBEYE condensate are bidirectionally tuned by physiological modulators such as Piccolino and CtBP1, linking synaptic ribbon structural plasticity to functional adaptability. Thus, our study demonstrates that combined phase transition and phase separation of nanoscale protein oligomers can build mesoscale functional cellular apparatuses.

biochemistry↗

bioRxiv2026

FOXA1 preserves cell polarity and restrains lysosome biogenesis in non-small cell lung adenocarcinoma

BackgroundThis study investigates the role of the pioneer transcription factor FOXA1 as a master gene in sustaining epithelial cell polarization in early-stage lung adenocarcinoma. The partial loss of FOXA1 is explored to determine if it will affect plasticity and progression of lung adenocarcinoma. The study also addresses the transcriptional circuitry that links polarity defects to lysosome homeostasis. MethodsA multiomics approach was used to define the status of the chromatin in epithelial and mesenchymal states of A549 adenocarcinoma cells obtained with a newly synthetized TGF-{beta} receptor inhibitor or TGF-{beta} respectively. The study leveraged ATAC-seq, RNA sequencing, Cut&Tag sequencing of FOXA1 and histone marks profiling. The functional impact of FOXA1 was examined by partial silencing in vitro and by heterozygous FOXA1 deletion in a KrasG12D mouse model. Three-dimensional organoid culture, high-resolution electron microscopy, spatial transcriptomics and multiplex immunohistochemistry assessed carcinoma cell polarity, proliferation, the tumor microenvironment and organelle content. Group differences were evaluated with two-tailed t tests or one-way analysis of variance. ResultsFOXA1 binding and expression were highest in cells harboring an epithelial phenotype. In mouse KrasG12D LUAD tumors FOXA1 marked polarized, CDH1-positive cells; heterozygous loss diminished CDH1, disrupted apical-basal architecture, lowered organoid-forming efficiency and remodeled the immune microenvironment. Spatial transcriptomics and ultrastructural analyses showed that FOXA1-deficient carcinoma cells accumulated lysosomes, down-regulated vesicle fusion genes of the SNARE family and activated the lysosomal CLEAR gene network. FOXA1 occupied enhancers of lysosome-associated genes and competed with the transcription factor TFE3, thereby suppressing transcription of cathepsin B and cathepsin C and restricting lysosome biogenesis. ConclusionsFOXA1 is a central regulator that preserves epithelial cell polarity and limits lysosome formation in lung adenocarcinoma. Targeting the FOXA1-TFE3-lysosome axis may affect tumor plasticity and provide new therapeutic opportunities.

cancer biology↗

bioRxiv2026

Fatty acids in the tumor microenvironment reprogram neutrophils to induce immunosuppression via adenosine

As solid tumors progress, the tumor microenvironment (TME) becomes increasingly immunosuppressive, impairing cytotoxic T-cell activity and limiting the efficacy of the immune checkpoint blockade. However, the mechanistic drivers of this immunosuppression remain poorly understood. Here, we identify a tumor-derived lipid-neutrophil-adenosine axis as a critical regulator of immune suppression in advanced colorectal cancer (CRC). We show that fatty acids enriched in tumor interstitial fluid reprogram neutrophils to generate adenosine via PPAR activation, leading to T-cell suppression. Using AB928, a dual A2aR/A2bR adenosine receptor antagonist currently in clinical trials, we restored T-cell proliferation, effector function, and tumor-killing capacity in vitro and in vivo. Importantly, AB928 synergized with anti-PD-1 therapy to enhance survival in an autochthonous model of metastatic CRC. Our findings define a metabolic immune evasion mechanism in the TME and provide a rationale for targeting neutrophil-derived adenosine signaling to improve immunotherapy responses in CRC and other solid tumors.

cancer biology↗

bioRxiv2026

Deep Learning Reveals Persistent Individual Signatures in Bat Echolocation Calls of the Greater Leaf-nosed Bat

Intraspecific variation is a prerequisite for natural selection and can manifest in various phenotypic traits, including vocal signals. However, classifying individuals based on their vocalizations, or acoustic individual identification (AIID), remains a significant challenge. This is particularly true for species that use rapidly varying echolocation calls for orientation. Here, we demonstrate that deep learning can overcome the limitation of traditional methods and reveal persistent individual signatures within bat echolocation calls. We recorded echolocation calls from 34 individuals of the greater leaf-nosed bat (Hipposideros armiger) under controlled laboratory conditions, with 19 individuals recorded repeatedly over three months. We show that a convolutional neural network (CNN) dramatically outperforms a traditional method, achieving an average identification accuracy of 84% for single calls and 91% for call sequences. In contrast, the traditional Discriminant Functional Analysis method achieved accuracies of only 39% and 47%, respectively. Through systematically altering the temporal structure of echolocation calls in input sequences, we found that temporal patterning enhances individual classification accuracy, suggesting it contributes to the encoding of individual-specific information. This study revealed that echolocation calls of H. armiger can contain stable, individual identity that were previously undetectable. Our findings highlight the potential of deep learning for non-invasive AIID and provide a methodological basis for future studies aiming to monitor animals in more dynamic environments.

zoology↗