Biology subjects

Zhou, X.

Publications and source records attributed to Zhou, X..

At least 127 records · Page 7Linked to original sources

bioRxiv2025

Integrated Bioinformatics analysis and Metabolomic Responses in finding novel therapeutic approach to treat viral myocarditis

BackgroundMyocarditis is one of the most common health problems in young people. Despite imaging techniques and endomyocardial biopsies advancing, there is still inadequate for myocarditis characterization. Some studies have shown that myocarditis is closely associated with mitochondrial dysfunction. Therefore, this study was aimed to identify mitochondrial-related biomarkers and gene regulatory networks in myocarditis and potential therapeutic targets. MethodsWe downloaded GSE95368 dataset from GEO to get myocarditis gene expression profiles, then used EdgeR and AI algorithm for bioinformatics analysis of DEGs functions. Established CVB3-induced mouse myocarditis model via intraperitoneal injection, and assessed energy metabolism differences using targeted metabolomics. CVB3 stimulus induced myocarditis in H9C2 cells. We assessed mitochondrial dysfunction (ATP, MMP) with commercial kits, MAPK8 release via ELISA, and MAPK8, p-PI3K, p-AKT levels by western blot. Furthermore, a total of 8 patients primarily diagnosed with myocarditis were enrolled, and levels of MAPK8 and CK in serum were detected. SP600125, an inhibitor of MAPK8, was administrated to CVB3-infected mice to study its potential protective effect in viral myocarditis. ResultsWe obtained 77 DEGs enriched in myocarditis. Analysis yielded 11 modules, MEpurple module genes linked to myocarditis progression were identified via WGCNA. MAPK8, NAMPT and ALB are associated with mitochondrial function. CVB3-infected mice showed cardiac inflammation and high MAPK8 expression in serum or heart tissues.The target metabolism results indicated altered central carbon metabolism distinguished CVB3 group from control, with higher D-Glucose-1-phosphate and D-Glucose-6-phosphate and lower L-Cystine, dCMP, IMP and Xylulose-5-phosphate levels. CVB3 treatment caused mitochondrial dysfunction in H9C2 cells (decreased ATP, MMP), and increased MAPK expression. Western blot showed MAPK8 consolidated the levels of p-PI3K and p-AKT. CK activity was notably higher in myocarditis patients than healthy individuals. MAPK8 levels in myocarditis patients serum also exceeded those in healthy individuals. Pearson analysis indicated that MAPK8 and CK may contribute to myocarditis progression via distinct mechanisms. In CVB3-infected mouse model with SP600125 treatment, cardiac inflammation and MAPK8, p-PI3k, p-AKT expression were reduced, confirming MAPK8s crucial role in viral myocarditis. ConclusionOur study identified MAPK8 as a key biomarker of myocarditis, and it may be a potential therapeutic target for myocarditis.

pathology↗

bioRxiv2025

A novel 18F-labeled brain penetrant PET ligand for imaging poly(ADP-ribose) polymerase-1

Poly(ADP-ribose) polymerase-1 (PARP-1) is a key mediator of DNA repair, and its inhibition has become a validated therapeutic strategy in homologous recombination-deficient cancers. However, tools for non-invasive assessment of PARP-1-specific expression remain limited. Here, we evaluated [18F]AZD9574, a next-generation PARP-1-selective PET radiotracer. [18F]AZD9574 was tested in a panel of breast, glioblastoma, prostate, and pancreatic cancer cell lines. Uptake correlated with PARP-1 expression and was dose-dependently blocked by a variety of clinically relevant PARP inhibitors, confirming its binding specificity. In 22Rv1 xenograft mouse models, the tracer demonstrated significant tumor accumulation that was specific to PARP-1, and ex vivo biodistribution confirmed organ uptake consistent with specific tumor binding and PARP-1 expression. Together, these findings establish [18F]AZD9574 as a promising PARP-1-targeted imaging agent with strong potential for advancing cancer research and therapeutic monitoring.

cancer biology↗

bioRxiv2025

Transcriptional condensates at super-enhancers mediate pH-dependent transcriptional control in innate immunity

Tissue acidification is a common feature of hypoxia, inflammation and solid tumor. Acidic pH regulates innate immune response in macrophages by weakening BRD4-containing transcriptional condensates. Yet how disruption of transcriptional condensates leads to gene-specific regulation of immune programs remain unclear. Here, we integrated ATAC-seq, ChIP-seq, and RNA-seq of primary murine macrophages and performed integrative epigenomics analyses to identify transcriptional regulators (TRs) with pH-sensitive regulatory potential and association to BRD4-dependent transcriptional condensates. We determined pH-dependent super-enhancers (SEs) by extended profiles of BRD4 binding and h3K27ac marks. We found RELA, IRF family, and STAT family as candidate TRs enriched at BRD4-associated, pH-sensitive SE regions. RELA and IRF3 preferentially occupied BRD4-associated and pH-sensitive SEs, and displayed markedly reduced binding under acidic conditions, aligning with BRD4 occupancy change. Correspondingly, immune-response genes within BRD4-associated, pH-sensitive SE regions, including Ch25h, Acp2, Gda, and Ifit family, were significantly higher expressed at pH 7.4 than at pH 6.5. Together, these results reveal a set of TRs involved in BRD4-associated, pH-sensitive transcriptional condensates that coordinate macrophage gene activation under physiological conditions, providing mechanistic insight into how acidic stress modulates transcriptional condensates and immune responses.

immunology↗

bioRxiv2025

Aneuploidy, polyploidy, and loss of heterozygosity distinguish serial bloodstream isolates of Candida albicans

BackgroundThe opportunistic pathogen Candida albicans is the leading species causing invasive Candida infections worldwide. Genomic variation is widespread in clinical isolates and complicates identification of genetic variants underlying antifungal drug resistance and tolerance. Our understanding of genomic and phenotypic diversity during invasive infections is limited and studies of serial isolates from individual patients are uncommon. We performed comparative analyses of 101 C. albicans bloodstream isolates from 55 patients in the Minnesota Minneapolis-Saint Paul region, including serial isolates from 19 patients. We analyzed the phylogenetic relationships of these isolates relative to 199 globally-collected public C. albicans genomes. ResultsThis studys regional isolates span the phylogenetic diversity of C. albicans; 6 isolates represent novel outliers to known clades. Serial isolates from individual patients were separated by limited single nucleotide polymorphisms. Nevertheless, we identified extensive large-scale genomic variation between serial isolates including polyploidy, aneuploidy, copy number variation, loss of heterozygosity, and chromosomal rearrangements. We demonstrated how a heterozygous ERG251 loss of function variant drives azole tolerance in a clinical isolate from a patient with a history of recurrent infections. Using serial isolates, we demonstrated that polyploidy provides an adaptive advantage in the presence of fluconazole despite the absence of overt antifungal drug resistance. ConclusionsOur analysis of serial isolates reveals the genomic plasticity of C. albicans during invasive infections and identifies variation driving antifungal drug tolerance. Our findings reveal limitations in current antifungal susceptibility testing and highlight the need to account for genomic and phenotypic variation during invasive Candida infections.

microbiology↗

bioRxiv2025

ProSiteHunter: A unified framework for sequence-based prediction of protein-nucleic acid and protein-protein binding sites

Accurate prediction of protein binding sites is essential for elucidating protein function, understanding molecular interaction mechanisms, and facilitating drug design. However, existing sequence-based approaches are often designed for specific binding-site types and therefore lack generality, whereas structure-based methods typically rely on high-quality structural models, limiting their applicability. Here, we introduce ProSiteHunter, a unified sequence-based framework for protein binding-site prediction, which integrates a fine-tuned protein language model (SiteT5) with a multi-source feature-fusion network that incorporates evolutionary, geometric, and statistical features, while employing bidirectional semantics, local associations, and global dependencies for comprehensive binding-site characterization. The method was systematically evaluated on diverse binding sites prediction tasks, where ProSiteHunter achieved a 39.1% average improvement in PRAUC for protein-DNA/RNA/protein tasks and a 7.4% PRAUC enhancement on the particularly challenging antibody-antigen task over state-of-the-art methods. Moreover, ProSiteHunter is capable of identifying local flexible sites that complement AlphaFold3 predictions and improving the accuracy of antibody-antigen interaction prediction. These results highlight ProSiteHunter as an efficient and unified approach for accurate and robust prediction of diverse protein binding sites.

bioinformatics↗

bioRxiv2025

An Empirical Study on Quantifying Physical Energy Expenditure during High-intensity Exercise

In the process of high-intensity exercise (HIE), the accurate evaluation of Physical Energy Expenditure (PEE) is of great significance to many occupational fields. However, due to the limitation of current technology, the quantitative ability of existing PEE evaluation methods in HIE situations is still insufficient. Based on the existing physiological coupling mechanism between cardiovascular parameters and energy metabolism, this study analyzed the dynamic changes of high-frequency blood pressure (BP) and heart rate (HR) during incremental load exercise and high-intensity interval training. The results show that although HR has a nonlinear response to the increase of exercise intensity, its time pattern-when analyzed synergistically with BP fluctuation-can provide reliable metabolic indicators. We used Doubly Labeled Water (DLW) as the gold standard for PEE determination and measured the total energy expenditure (TEE) in three consecutive days. During the monitoring period, high frequency invasive BP and HR monitoring was performed simultaneously, and the time integral value of SBP x HR and its ratio to TEE (i.e. Quotient value) were calculated. By dividing the corresponding SBP x HR integral value during HIE by the above quotient value, the PEE of this exercise can be estimated. Specifically, TEE can be accurately estimated by time integration of the product of SBP and HR. The short-term PEE rate can be solved by the differential equation constructed by the systolic blood pressure(SBP) trend function in this period, and can also be obtained by dividing the PEE in this period by the duration of this period. In this study, based on the results of invasive measurements, a new method for real-time monitoring of HIE using non-invasive cardiovascular parameters during PEE was proposed, providing new ideas and methodological support for applications in related fields.

physiology↗

bioRxiv2025

Optimal transport modeling uncovers spatial domain dynamics in spatiotemporal transcriptomics studies

Spatiotemporal transcriptomics is an emerging and powerful approach that adds a temporal dimension to spatial transcriptomics, enabling the characterization of dynamic changes in tissue architecture during development or disease progression. Here, we present SpaDOT (Spatial Domain Transition detection), a computational method designed to identify spatial domains and infer their temporal dynamics across time points for spatiotemporal transcriptomics studies. SpaDOT employs a variational autoencoder (VAE) framework to capture a low-dimensional representation of the data, incorporating hidden clustering variables to define distinct spatial domains. In the process, SpaDOT integrates a Gaussian Process prior and graph neighbor information to explicitly model both global spatial continuity and local structural heterogeneity among spatial locations within each time point, while using optimal transport (OT) to derive time-varying embeddings and infer the relationships between spatial domains across time points. Through simulation and real data applications, we demonstrate the superiority of SpaDOT in spatial domain detection, latent space preservation, and domain transition tracking over time. In real data applications, SpaDOT accurately captures dynamic domain transitions, including the disappearance and re-emergence of domains due to technical variation. Notably, SpaDOT uncovers key aspects of valvulogenesis in the developing heart, revealing the splitting of a single valve structure into two distinct functional valves -- the atrioventricular valve and the semilunar valve.

bioinformatics↗

bioRxiv2025

In Silico Optimisation of Regenerative Cell Therapy in the Infarcted Human Ventricles to Mitigate Arrhythmic Burden

Myocardial infarction remains a frequent cause of heart failure and mortality. Cell therapy has been shown promising in pre-clinical trials to regenerate the damaged tissue, but delivered cells may beat spontaneously and produce arrhythmias in the ventricles, particularly in the first weeks after delivery, which hinders clinical application. Previous studies have proposed ionic targets to supress the cells automaticity but, so far, the effects of such treatments on the cells calcium dynamics, as a key driver of contractile function, have been insufficiently evaluated. Furthermore, effective strategies are needed that can alleviate the injected cells pro-arrhythmic action potential phenotypes. The goal of our study was to identify mechanisms to mitigate arrhythmic pathways following cell delivery in the chronically infarcted human ventricles using multiscale modelling and simulation. First, we demonstrate credibility by simulating experimentally observed transient automaticity-induced ventricular tachycardia arrhythmias with a frequency of up to 140 beats per minute at two weeks post cell injection in three different infarct geometries. Next, our simulations show how the timeframe during which re-entry was inducible increases 1) from before to after cell delivery at day 0 from 0 to 640 ms, 60 to 100 ms, and 60 to 760 ms in the small, medium, and large scar, respectively, and 2) from day 0 to day 14 after virtual cell injection in the large scar by 175%. Finally, we show that a combination of blocking the funny current and upregulating the inward rectifier potassium current, the sodium potassium pump, and the rapid delayed outward rectifier potassium current can reduce both automaticity-induced and re-entrant arrhythmias while maximising calcium amplitudes. In conclusion, our simulations show that not only automaticity-induced but also re-entrant arrhythmias increase as injected cells mature in the ventricles and depend on the scar size. Furthermore, through modelling and simulation, we identify anti-arrhythmic strategies to improve therapy safety while maximising efficacy.

bioengineering↗

bioRxiv2025

Synthetic signaling platform uncovers and rewires cellular responses to PD-1 perturbation

Tyrosine phosphorylation motifs are central regulators of cell signaling, yet methods to selectively detect and reprogram these events have been lacking. Here we introduce Sphyder (Selective PHosphotYrosine DEtection and Rewiring), which enables precise detection of signaling at the resolution of individual phosphorylation motifs. Using Sphyder biosensors, we resolved phosphorylation dynamics and uncovered regulatory mechanisms of the checkpoint receptor PD-1 in living cells. Sphyder also provided a framework for reconstructing phosphosignaling pathways. With this approach, we redirected PD-1 signaling from immunosuppressive to immunoactivating outputs and engineered synthetic receptors that linked extracellular sensing to customized transcriptional programs. In addition, Sphyder biosensors revealed previously unrecognized mechanisms of the PD-1/VEGF bispecific antibody Ivonescimab, showing that it induces VEGF-dependent clustering, phosphorylation, and degradation of PD-1. These findings may underlie its promising clinical activity relative to conventional PD-1 blockade. Together, our study establishes a broadly applicable strategy for sensing and reprogramming cell signaling, while also providing mechanistic insights into a new class of immune checkpoint inhibitors of major clinical interest.

immunology↗

bioRxiv2025

A Daily Cycle of White Collar Complex Dephosphorylation Sustains Circadian Rhythmicity in Neurospora

As a photoreceptor, the transcription factor complex WCC acutely activates [~]5% of the genome in response to blue light, while as the circadian positive element in the dark WCC influences expression of about 40% of the transcriptome. Among WCC-regulated genes is frq which is both acutely light-activated through a pLRE and circadian-regulated through a C-box promoter element that is not active in constant light. The complex of FRQ, FRH, and CK1, the FFC, phosphorylates WCC at >95 sites, thereby repressing its activity and closing the circadian feedback loop in the dark. Although FFC has no described role in the light, we validated the expectation that FFC-driven WCC phosphorylation also silences C-box promoters in constant light, thereby confirming two classes of WCC targets, C-box-like that are normally repressed in the light and pLRE-like that remain light-active despite FFC-driven WCC phosphorylation. Genome-wide derepression of C-box-like promoters in frq-null fungi may explain reported non-circadian effects seen in some frq-null fungi including reduced virulence and conidiation. Reanalysis of WCC-mediated circadian activation and repression revealed that, while at dusk most WCC is phosphorylated and repressed, subsequent circadian activation is the result of transient dephosphorylation/derepression of just a small subset of this WCC pool; this small active pool drives expression of FRQ, nucleating the FFC, which rapidly re-phosphorylates the WCC pool to repress it, a phosphorylation/dephosphorylation cycle that can run for days without new WCC synthesis. The realization that both FFC and WCC are regulated primarily through phosphorylation rather than turnover leaves the circadian oscillator looking much like a phoscillator, emphasizing the primacy of post-translational regulation in timekeeping. SignificanceAt the core of circadian clocks of fungi and animals, a protein heterodimer drives expression of gene(s) whose products inactivate the heterodimer via phosphorylation. To sustain the cycle through multiple days, the activity of the heterodimer must be restored, but the means through which this happens have been unclear. In the clock model Neurospora, the White Collar Complex (WCC) is the heterodimer and FFC is the complex that inactivates it. We determined that WCC activity is restored principally by removal of the inhibitory phosphorylations and that for at least several days no new synthesis of WCC is required. The results confirm the existence of a large pool of inactive WCC in the cell and highlights the delicate balance between FCC-dependent phosphorylation/inactivation and phosphatase-dependent dephosphorylation/reactivation. Each morning, this balance allows transient activation of a fraction of the inactive WCC pool, thereby restarting the circadian cycle.

biochemistry↗

bioRxiv2025

PRIME: A Multi-Agent Environment for Orchestrating Dynamic Computational Workflows in Protein Engineering

Artificial intelligence (AI) is revolutionizing protein engineering, yet its practical application is often hindered by a fragmented toolchain and the specialized expertise required to orchestrate complex computational workflows. To address these challenges, we have developed PRIME, an autonomous protein engineering multi-agent system. The core innovation of PRIME is dynamic workflow synthesis: it interprets high-level engineering objectives, reasons over a curated library of more than 65 validated protein tools, and autonomously constructs custom computational pathways. Crucially, by grounding every step in verifiable tool execution, PRIME mitigates the risk of model hallucination. It also automates the complete pipeline for developing specialized AI models, from data acquisition through training. In a benchmark of 213 multi-step protein engineering tasks, PRIME exhibited superior performance, successfully completing the majority of tasks where state-of-the-art, general-purpose AI agents fail. We validated its capabilities in demanding real-world applications, including the fully autonomous training of a machine learning classifier and the de novo design of a therapeutic antibody against SARS-CoV-2. By abstracting technical complexity, PRIME empowers scientists to execute sophisticated computational experiments with unprecedented flexibility, establishing a new paradigm for autonomous scientific discovery. The PRIME agent and source code will be made publicly available.

bioinformatics↗

bioRxiv2025

Synthesis and In Vitro Characterization of OGA-2506 as a High Affinity Radioligand for O-GlcNAcase

O-GlcNAcase (OGA) is a glycoside hydrolase that regulates protein O-GlcNAcylation, a dynamic post-translational modification implicated in numerous cellular processes. Dysregulation of OGA alters cellular O-GlcNAc homeostasis and has been linked to neurodegenerative and other chronic diseases. The development of radioligands targeting OGA, particularly those derived from well-characterized tool compounds, could substantially advance drug discovery in this area. Herein, we report the radiosynthesis of a novel tritium (3H)-labeled radioligand 7 (code name [3H]OGA-2506) derived from a chiral piperidine scaffold, and its preliminary in vitro binding evaluation. Starting from iodine precursor 8, palladium-catalyzed tritiation afforded [3H]7 with excellent molar activity (1822 GBq/mmol) and high radiochemical purity (>99%). Saturation binding studies revealed that [3H]7 binds OGA with high affinity to rat striatum homogenates (Kd = 3.56 nM; Bmax = 42.62 nM). Competition assays yielded an IC50 of 5.55 nM, and preliminary autoradiography demonstrated heterogeneous regional distribution in the brain with specific binding. These findings highlight [3H]7 as a valuable tool for OGA binding studies and provide a foundation for the future development of novel positron emission tomography (PET) ligands to probe O-GlcNAc signaling in the brain.

pharmacology and toxicology↗

bioRxiv2025

ZNF180 modulates tumor intrinsic immunotherapy resistance in melanoma through driving plasticity

BackgroundBased on our previous study, we have identified ZNF180, a zinc finger protein, as a pro-tumorigenic regulator in primary melanoma and a marker for poor prognosis. Herein, we report that ZNF180-regulated pathway, hence ZNF180-regulome, underlies resistance towards immune checkpoint inhibitions (ICIs). MethodsTo investigate regulatory roles of ZNF180 to confer these immune suppressive phenotypes, we performed ZNF180 knock-down in melanoma cells in vitro with different genetic backgrounds, namely A375 (BRAF-mutant) and SKMEL147 (NRAS-mutant) cells, and performed RNA- and ATAC-sequencing. We performed integrative analysis of RNA- and ATAC-sequencing data with publicly available sequencing data from ICI-treated cohorts to construct comprehensive model of ZNF180-regulome and its impacts on immune microenvironment. Further, we performed ZNF180 silencing in immune competent Yumm1.7 murine model to confirm the changes in immune microenvironments. ResultsZNF180-regulome was predictive of ICI responses in independent bulk sequencing cohorts, and ZNF180+ tumors persisted after the therapy with immune-suppressive features such as MHC-I loss and CD155 expressions, the primary ligand to TIGIT inhibitory receptor. Further, ZNF180 silencing revealed its regulations on AP-1 transcription factors to drive melanoma reprogramming towards de-differentiated MITFlowAXLhigh cells, an established melanoma subtypes associated with recurrence and ICI resistance. In tandem, we observed that ZNF180+ tumor neighborhood significantly excluded with CD4 T-cells in metastatic tumor, and its silencing in immune competent murine model increased CD4 helper T-cell infiltrations with significant tumor regression in vivo. ConclusionCollectively, these results indicate ZNF180 is a tumor intrinsic regulator of melanoma plasticity to drive de-differentiated phenotypes with immune-suppressive features including loss of immunogenicity, T-cell inhibitory signals through TIGIT/CD155 checkpoint and exclusion of CD4 helper T-cells. As ZNF180-regulome manifests in non-metastatic melanoma in contrast to the current focus of standard-of-care ICI on the metastatic disease, these results establish ZNF180-regulome as a biomarker and novel therapeutic avenue for early-stage, non-metastatic melanoma to intervene ICI resistance.

cancer biology↗

bioRxiv2025

A universal surface functionalization technique to chemically enhance live microbial cells

Microbial surface functionalization is a powerful strategy for endowing microbes with novel, non-genetic functions. However, existing methods are often species-specific, limited in scope, and compromise cell viability. Here, we present a universal and modular platform for high-density, reproducible surface functionalization across diverse microbial species--including Gram-positive, Gram-negative, aerobic, and anaerobic bacteria--using multiple molecular classes such as fluorophores, enzymes, and nucleic acids. Our method preserves cell viability, and achieves 50x higher functionalization efficiency than previous methods with a standardized protocol applicable to any azide-containing molecule. Applications of the method show reproducible and tunable phenotypic outcomes at the single-cell level: fluorophore labeling yielded adjustable fluorescence, {beta}-lactamase conferred scalable antibiotic resistance, and DNA coatings modulated adhesion and aggregation. This platform provides quantitative, non-genetic control over microbial phenotypes and complements genetic engineering approaches. It enables new possibilities for microbial design in biotechnology, medicine, and environmental applications where genetic modification is impractical or undesirable.

microbiology↗

bioRxiv2025

RhoV Promotes Proliferation, Migration, and MAPK Activation in Pancreatic Ductal Adenocarcinoma

Background and AimsPancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy characterized by diagnosis at advanced stages, limited therapeutic options, and frequent resistance to therapies. Although oncogenic KRAS mutations are central drivers of PDAC, alternative pathways indisputably contribute to its tumorigenesis and progression. RhoV, a member of the Rho family of small GTPases, has been implicated in tumor development in other cancer types, such as breast cancer and lung adenocarcinoma; however, its role in PDAC remains unclear. MethodsIn this study, we investigated the expression and functional impact of RhoV on PDAC. Analysis of publicly available datasets and immunohistochemical profiling of 114 PDAC patient specimens were used to evaluate the expression of RhoV in PDAC and its prognostic impact. Overexpression and CRISPR-Cas9-mediated knockout of RhoV were established in three pancreatic cancer cell lines. Functional analyses, such as cell proliferation, migration, invasion, colony formation, spheroid growth, and mouse xenograft, were used to evaluate the role of RhoV in PDAC cells. ResultsRhoV overexpression was associated with reduced overall and recurrence-free survival in public datasets and our own patient cohort. Functional assays demonstrated that RhoV overexpression promoted PDAC cell proliferation, colony formation, and spheroid growth, whereas knockout of RhoV suppressed these changes. Moreover, RhoV enhanced PDAC cell migration and invasion in vitro, accompanied by downregulation of E-cadherin and upregulation of N-cadherin and vimentin, indicating induction of epithelial-mesenchymal transition. Mechanistically, RhoV overexpression activated key MAPK pathway components, including phosphorylation of ERK, JNK, and p38. In vivo, xenograft models confirmed that RhoV drives tumor growth and increases tumor burden. ConclusionThese results establish RhoV as a novel oncogenic factor in PDAC progression and highlight its potential as a biomarker and therapeutic target, warranting further investigation into combinatorial targeting strategies to overcome KRAS inhibitor resistance.

cancer biology↗

bioRxiv2025

Machine Learning Models Based on Histological Images from Healthy Donors Identify ImageQTLs and Predict Chronological Age

Histological images offer a wealth of data. Mining these data holds significant potential for enhancing disease diagnosis and prognosis, though challenges remain, especially in non-cancer contexts. In this study, we developed a statistical framework that links raw histological images and their derived features to the genotype, transcriptome, and chronological age of the samples. We first demonstrated an association between image features and genotypes, identifying 906 image quantitative trait loci (imageQTLs) significantly associated with image features. Next, we identified differentially expressed (DE) genes by stratifying samples into image-similar groups based on image features and performing DE comparisons between groups. Additionally, we developed a deep-learning model that accurately predicts gene expression in specific tissues from raw images and their features, highlighting gene sets associated with observed morphological changes. Finally, we constructed another deep-learning model to predict chronological age directly from raw images and their features, revealing relationships between age and tissue morphology, especially aspects derived from nucleus features. Both models are supported by a computational approach that greatly compresses gigapixel whole-slide images and extracts interpretable nucleus features, integrating both large-scale tissue morphology and smaller local structures. We have made all interpretable nucleus features, imageQTLs, DE genes, and deep-learning models available as online resources for further research. Significance StatementThis study establishes a comprehensive framework that links histological image features to genotype, transcriptome, and chronological age in large-scale healthy tissue datasets, providing valuable insights into tissue morphology. By identifying 906 significant, interpretable imageQTLs and conducting differential expression analysis based on image features, we enhance understanding of genetic and morphological interactions. Additionally, we developed predictive models for both gene expression and chronological age from raw histological images, introducing a novel approach to studying age-related tissue-specific changes and presenting the first model to demonstrate the predictability of age from histological images.

bioinformatics↗

bioRxiv2025

Structural Role of Stomatin in Organizing Functional Membrane Microdomains

Stomatin, originally discovered in red blood cells, is a member of the SPFH (Stomatin, Prohibitin, Flotillin, and HflK/C) protein family, which has long been proposed to scaffold functional membrane microdomains (FMMs) enriched in saturated lipids such as cholesterol and sphingomyelin. Stomatin has been reported to associate with a variety of proteins involved in diverse physiological processes, including ion channel regulation, membrane fusion, mechanosensory regulation and vesicle trafficking; however, the mechanisms by which it modulates these interactions remain poorly understood. Here, we determined the cryo-electron microscopy (cryo-EM) structures of stomatin, revealing its hexadecameric assemblies. The SPFH1 domains insert into the cytosolic leaflet of membranes and, together with the N-terminal hairpin, form a potential cholesterol-binding pocket. Liposome reconstitution experiments demonstrated that stomatin self-organizes into clusters, and Spectrum and Polarization Optical Tomography (SPOT) further showed that these clusters enhance membrane lipid order, supporting the proposed role of stomatin in organizing functional membrane microdomains (FMMs). Proteomic mass spectrometry analysis identified numerous stomatin-associated cargo proteins, including solute carrier (SLC) transporters, RAB GTPases, and integrins, suggesting that stomatin regulates solute transport and contributes to vesicle trafficking and cell migration. Together, these findings elucidate the structural and functional roles of stomatin and underscore its potential as a therapeutic target for modulating cancer cell migration and metastasis.

biophysics↗

bioRxiv2025

Cellular dynamics and epidermal specialization during Arabidopsis floral development at single-cell resolution

Cellular specialization underlies the functional diversification of floral organs, yet the regulatory networks driving epidermal differentiation remain poorly understood. Here, we constructed a single-nucleus transcriptomic atlas of developing Arabidopsis thaliana flowers by profiling over 70,000 nuclei. For annotation of single-cell identities and differentiation status, we additionally generated tissue- and stage-specific transcriptomic datasets using nine fluorescent marker lines spanning four floral developmental stages. Guided by this integrative approach, we focused specifically on the floral epidermis at single-cell resolution and resolved 22 transcriptionally distinct epidermal cell populations. Gene regulatory network analyses identified key transcription factors essential for epidermal differentiation, highlighting MYB16 as a central regulator within the petal epidermis. Developmental trajectory and chromatin-binding analyses demonstrated that MYB16 dynamically orchestrates gene expression programs involved in epidermal identity establishment, cuticle biosynthesis, and stress resilience. Moreover, we demonstrate MYB16 interacts with DRMY1, a regulator of organ growth robustness. Complementation assays confirmed the non-redundant role of MYB16 in epidermal cell fate specification, distinct from other MYB transcription factors. This study provides a comprehensive cellular and regulatory framework for floral epidermal specialization, advancing our understanding of how temporal transcriptional dynamics integrate with spatial cell fate decisions during flower development.

molecular biology↗