Biology subjects

Zhou, R.

Publications and source records attributed to Zhou, R..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

Computational Assessment of Circularization Impact on Saxitoxin G-quadruplex Aptamer Performance

Although high-affinity and high-specificity aptamers can be obtained by SELEX (Systematic Evolution of Ligands by Exponential Enrichment), and have good activity in vitro, their performance in vivo is poor. This is mainly because of the degradation of linear nucleic acids by nucleases in body fluids and the difficulty of maintaining stable 3D structures in complex body fluid environments, which seriously hinders the clinical application of aptamers. This makes circular aptamers, which can resist degradation and are more stable in complex body fluid environments, an attractive option. However, the cyclization process may have a considerable impact on the structure of the original linear aptamer, and blind cyclization may lead to a decrease in its affinity. Here, we developed a new method to guide the cyclization of saxitoxin (STX) aptamers based on molecular computation, and verified the activity of circular aptamers through bioactivity experiments to further verify the authenticity and reliability of our methods. Consistent with the computational analysis, although circularization disrupts the G4 structure, circular aptamer not only has a higher affinity than the linear one but also provides certain protection to mice and greatly prolongs their survival, which proves the accuracy and reliability of the circular structure designed by our computational method. Our findings provide important ideas for better guidance in the design of circular aptamers and demonstrate their great potential in therapeutic applications.

biochemistry↗

bioRxiv2025

Populus VariantDB v3.2 facilitates CRISPR and Functional Genomics Research

The success of CRISPR genome editing studies depends critically on the precision of guide RNA (gRNA) design. Sequence polymorphisms in outcrossing tree species pose design hazards that can render CRISPR genome editing ineffective. Despite recent advances in tree genome sequencing with haplotype resolution, sequence polymorphism information remains largely inaccessible to various functional genomics research efforts. The Populus VariantDB v3.2 addresses these challenges by providing a user-friendly search engine to query sequence polymorphisms of heterozygous genomes. The database accepts short sequences, such as gRNAs and primers, as input for searching against multiple poplar genomes, including hybrids, with customizable parameters. We provide examples to showcase the utilities of VariantDB in improving the precision of gRNA or primer design. The platform-agnostic nature of the probe search design makes Populus VariantDB v3.2 a versatile tool for the rapidly evolving CRISPR field and other sequence-sensitive functional genomics applications. The database schema is expandable and can accommodate additional tree genomes to broaden its user base.

plant biology↗

bioRxiv2025

Entamoeba histolytica Gal/GalNAc lectin intermediate subunit promotes inflammation and epithelial damage in intestinal amebiasis through its C3 region.

Entamoeba histolytica is a common enteric protozoan that sometimes transitions from a symbiont to a pathogen, causing intestinal amebiasis and extraintestinal abscesses in the host. The early-to-intermediate stages of intestinal amebiasis are characterized by an intense inflammatory response, during which host innate immune defenses play an important role. Here, using the cecal infection model of C3H/HeNCrl mice, we performed single-cell RNA sequencing of cecal tissues and identified the prominent pro-inflammatory function of host macrophages in intestinal amebiasis. On the amoebic cell surface, Igl is an intermediate subunit of galactose- and N-acetyl-D-galactosamine-inhibitable lectins, which contributes to parasite adherence. We proposed that E. histolytica Igl diffuses along with amoebic extracellular vesicles and contacts host macrophages, binding to the TLR4 co-receptor MD2 through its C3 region and initiating the TLR4/MyD88/NF-{kappa}B inflammatory signaling pathway in host cells. Moreover, by inducing macrophage inflammation and cytokine production, E. histolytica indirectly impairs intestinal epithelium integrity through the Igl protein. To our knowledge, this is the first report showing a host single-cell atlas in the field of amebiasis research. In response to the parasite invasion during intestinal amebiasis, our study provides new insights elucidating the inflammatory formation and epithelial damage of gut mucosal immune system, and also conduces to the identification of potential drug targets for these amoebas.

microbiology↗

bioRxiv2025

Epithelia mediate inflammation with myeloid cells in Crohn's disease patients under treatment

Many Crohn's disease patients fail to respond to biologic therapies targeting canonical immune pathways, and the mechanisms underlying treatment non-response remain poorly understood. Integrating single-cell and spatial transcriptomics, we generated a comprehensive mucosal atlas of 380,000 cells spanning the terminal ileum and ascending colon of healthy donors and Crohn's disease patients receiving biologics. We revealed site-specific programs centered on TNF-expressing macrophages embedded within epithelial-stromal networks: follicle-associated enterocytes dictated immune activation in the ileum, while FAP-expressing stromal cells served this role in the colon. Co-expression network analysis further identified lineage-specific programs associating non-response, including a novel epithelial marker BPIFB1 independent of known genetic risk loci. Co-expression marker Z-scores significantly differed between responders and non-responders in published datasets. Together, these findings define a non-responder-specific epithelial-stromal-immune ecosystem that sustains chronic inflammation, providing a framework for stratifying treatment resistance and informing therapeutic strategies in Crohn's disease and other barrier organ disorders.

immunology↗

bioRxiv2025

ZBP1 Senses Splicing Aberration through Z-RNA to promote Cell Death

RNA splicing, a highly regulated process performed by the spliceosome, is crucial for eukaryotic gene expression and cellular function. Numerous cellular stresses including oncogenic insults dysregulate RNA splicing, often provoking inflammatory responses and cell death. However, the molecular signal produced by spliceosome aberration and how cell sensed and respond to it remain elusive. Here we show that spliceosome inhibition induces the widespread formation of unique, left-handed nucleic acids, Z-form nucleic acids (Z-NAs) from the nucleus. These Z-NAs were double-stranded RNA (dsRNA), rather than DNA-RNA hybrids, that were predominantly derived from transcripts of mis-spliced intronic RNA. Spliceosome inhibition induced the egress of these Z-RNA from the nucleus to the cytoplasm in an active manner. Sensing of the accumulation of Z-RNA in the cytosol by the host sensor ZBP1 triggered cell death, mainly for RIPK3-MLKL dependent necroptosis. Collectively, these findings delineate a previously uncharacterized mechanism in which Z-NA sensing by ZBP1 responds to global aberrations of RNA splicing to trigger inflammatory cell death.

cell biology↗

bioRxiv2025

A Hyperbolic Discrete Diffusion 3D RNA Inverse Folding Model for functional RNA design

Generative design of functional RNAs presents revolutionary opportunities for diverse RNA-based biotechnologies and biomedical applications. To this end, RNA inverse folding is a promising strategy for generatively designing new RNA sequences that can fold into desired topological structures. However, three-dimensional (3D) RNA inverse folding remains highly challenging due to limited availability of experimentally derived 3D structural data and unique characteristics of RNA 3D structures. In this study, we propose RIdiffusion, a hyperbolic denoising diffusion generative RNA inverse folding model, for 3D RNA design tasks. By embedding geometric features of RNA 3D structures and topological properties into hyperbolic space, RIdiffusion efficiently recovers the distribution of nucleotides for targeted RNA 3D structures based on limited training samples using a discrete diffusion model. We perform extensive evaluations on RIdiffusion using different datasets and strict data-splitting strategies and the results demonstrate that RIdiffusion consistently outperforms baseline generative models for RNA inverse folding. This study introduces RIdiffusion as a powerful tool for the generative design of functional RNAs, even in structure-data-scarce scenarios. By leveraging geometric deep learning, RIdiffusion enhances performance and holds promise for diverse downstream applications.

bioinformatics↗

bioRxiv2025

AMPK- and cGAS-Mediated Dual Sensing of Glucose and dsDNA Synergizes to Enhance Antitumor Immunity

Intratumoral glucose availability is linked considerably to tumor growth, immune evasion, and metastasis. However, the precise molecular mechanisms by which glucose levels govern cellular and immune responses against tumors remain incompletely understood. Here, we explored the context of tumors of intersections between AMP-activated protein kinase (AMPK) and cGAS-STING signaling, a key pathway initiating antitumor immunity. We unexpectedly found that AMPK activation robustly enhances cGAS-STING signaling within cancer and immune cells, which potently impacts melanoma and colorectal cell senescence, organoid apoptosis, and the infiltration of CD4+ and CD8+ T lymphocytes. Using classic or newly developed AMPK agonist Aldometanib, TBK1S511E/S511E knock-in (KI) mice, glucose metabolic modulator, as well as AMPK1/2 dKO melanoma, we demonstrated that dual sensing of intratumoral glucose and dsDNA integrated by the AMPK-TBK1 cascade is essential for initiating antitumor immunity and suppressing cancer progressions. Notably, novel AMPK agonists or intervening in glucose glycolysis by Lonidamine synergized effectively with STING agonists, substantially inhibiting melanoma growth. Therefore, these findings unravel a concise mechanism integrating glucose metabolism and innate DNA sensing into cancer cell fate and propose an effective therapeutic strategy to enhance antitumor immunity. HIGHLIGHTSO_LIDual and synergistic sensing of glucose and dsDNA facilitates antitumor immunity in melanoma and colorectal cancer; C_LIO_LIAMPK substitutes intratumoral cGAS-STING-IRF3 signaling through TBK1 phosphorylation at S511; C_LIO_LIGlucose deficiency induces cancer cell senescence, apoptosis, and T lymphocyte infiltration via the AMPK-TBK1 cascade; C_LIO_LINewly developed AMPK agonists synergize with STING agonists to retrieve striking tumor suppression. C_LI

cancer biology↗

bioRxiv2025

Activity of Carbazole, Aminoguanidine and Diamine Anti-infectives against Toxoplasma gondii

We report the observation that carbazole anti-infectives developed as antibacterial and antifungal drug leads have activity against the tachyzoite-stage growth of the Apicomplexan parasite Toxoplasma gondii with IC50 values as low as 2 M. We show that a phenylthiazole aminoguanidine with antibacterial as well as antifungal activity inhibits growth with an IC50 value of 2.1 M. We also tested a series of 18 analogs of the diamine SQ109, a tuberculosis drug candidate which likewise has both antibacterial and antifungal activity, finding activity as low as 2.3 M. We tested all compounds for their activity in collapsing the {Delta}pH component of the promotive force, the results indicating that all compounds acted, at least in part, as protonophore uncouplers. Finally, we also investigated the correlation between the activity of all compounds against the yeast Saccharomyces cerevisiae and the bacterium Mycobacterium smegmatis, finding significant correlations between the collapse of the proton motive force and anti- fungal/antibacterial activity.

microbiology↗

bioRxiv2025

Broad-Spectrum Activity and Mechanisms of Action of SQ109 on a Variety of Fungi

ABSTRACTWe investigated the activity of the tuberculosis drug SQ109 against sixteen fungal pathogens: Candida albicans, C. auris, C. glabrata, C. guilliermondi, C. kefyr, C. krusei, C. lusitaniae, Candida parapsilosis, C. tropicalis, Cryptococcus neoformans, Rhizopus spp., Mucor spp., Fusarium spp., Coccidioides spp., Histoplasma capsulatum and Aspergillus fumigatus. MIC values varied widely (125 ng/mL to >64 {micro}g/mL) but in many cases we found promising (MIC[~]4 {micro}g/mL) activity as well as MFC/MIC ratios of [~]2. SQ109 metabolites were inactive. The activity of 12 analogs of SQ109 against Saccharomyces cerevisiae correlated with protonophore uncoupling activity, suggesting mitochondrial targeting, consistent with the observation that growth inhibition was rescued by agents which inhibit ROS species accumulation. SQ109 disrupted H+/Ca2+ homeostasis in S. cerevisiae vacuoles, and there was synergy (FICI[~]0.31) with pitavastatin, indicating involvement of isoprenoid biosynthesis pathway inhibition. SQ109 is, therefore, a potential antifungal agent with multi-target activity.

microbiology↗

bioRxiv2025

Modeling tumor dynamics and predicting response to chemo-, targeted-, and immune-therapies in a murine model of pancreatic cancer

We seek to establish a parsimonious mathematical framework for understanding the interaction and dynamics of the response of pancreatic cancer to the NGC triple chemotherapy regimen (mNab-paclitaxel, gemcitabine, and cisplatin), stromal-targeting drugs (calcipotriol and losartan), and an immune checkpoint inhibitor (anti-PD-L1). We developed a set of ordinary differential equations describing changes in tumor size (growth and regression) under the influence of five cocktails of treatments. Model calibration relies on three tumor volume measurements obtained over a 14-day period in a genetically engineered pancreatic cancer model (KrasLSLG12D-Trp53LSLR172H-Pdx1-Cre). Our model reproduces tumor growth in the control and treatment scenarios with an average concordance correlation coefficient (CCC) of 0.99{+/-}0.01. We conduct leave-one-out predictions (average CCC=0.74{+/-}0.06), mouse-specific predictions (average CCC=0.75{+/-}0.02), and hybrid, group-informed, mouse-specific predictions (average CCC=0.85{+/-}0.04). The developed mathematical model demonstrates high accuracy in fitting the experimental tumor data and a robust ability to predict tumor response to treatment. This approach has important implications for optimizing combination NGC treatment strategies.

bioinformatics↗

bioRxiv2024

Effect of Stroma-directed Drugs in Combination with Chemotherapy Against Pancreatic Cancer- a Preclinical Study

Cytotoxic chemotherapy plays an important role for extending the survival of patients with pancreatic ductal adenocarcinoma (PDAC). To enhance the efficacy of chemotherapy for eradicating the cancer cells, we have compared the standard care chemotherapy (combination of nab-paclitaxel, gemcitabine and cisplatin, NGC) versus NGC plus stroma-directed agents (calcipotriol and losartan, respectively) in a genetically engineered mouse model of PDAC. Over a 2-week study period, MRI was conducted to measure the tumor size and to test the sensitivity of imaging markers derived from diffusion-weighted imaging (DWI), dynamic contrast enhanced MRI (DCE) and magnetization transfer ratio (MTR) for assessing the tumor cellularity and stromal changes. Detailed immunohistochemistry and preliminary single cell RNA sequencing (scRNAseq) study were applied to tumor tissues collected upon euthanasia on day-14. Our major findings are: 1. Compared the untreated controls, NGC chemotherapy induced significant tumor growth inhibition and stromal changes including pronounced reduction of fibroblast associated protein (FAP) level accompanied by increased matrix collagen content, significantly reduced microvascular permeability revealed by DCE corroborated with reduced microvascular density. 2. Losartan+NGC significantly enhanced inhibition of tumor growth beyond NGC and increased lymphocytes infiltration in the tumor which may contribute to enhanced cancer cells eradication. 3. NGC treatment enriched the fraction of mesenchymal (M) subtype while reducing the epithelial (E) subtype of cancer cells compared to the controls, and this trend was reversed by calcipotriol+NGC. In conclusion, our study captured changes in cancer cell and tumor microenvironment in response to chemo stromal therapy versus chemotherapy alone with mechanistic insights.

cancer biology↗

bioRxiv2024

A novel HLA Class II presentation prediction algorithm deciphers immunogenic CD4 epitopes specific to KRAS G12C

Accurate prediction of peptide presentation by HLA molecules is important for generation of effective individualized cancer vaccines and immunotherapies. While presentation prediction algorithms for HLA class I have been successfully applied in the context of such therapies, improved prediction algorithms for class II are needed. EDGE-II is a novel algorithm based on a protein large language model that has a learned allele deconvolution network trained on existing and new immunopeptidomics data. It delivers state-of-the-art performance on prediction of peptide presentation by HLA class II and immunogenicity elicited by CD4+ T-cell epitopes. In a patient with a KRAS G12C positive tumor treated with a KRAS G12C targeting immunotherapy, EDGE-II identified KRAS G12C class II neoantigens that elicited clonally expanded CD4+ T cells with cytotoxic transcriptional profiles post-vaccination. EDGE-II could play an important role in the development of effective cancer immunotherapies by elucidating an enriched understanding of the immunopeptidome.

bioinformatics↗

bioRxiv2024

Comprehensive Longitudinal ctDNA Monitoring in Metastatic Cancer Patients Treated with an Individualized Neoantigen-directed Vaccine

PurposeCirculating-tumor DNA (ctDNA) is an emerging, minimally invasive diagnostic and prognostic biomarker for patients receiving a variety of cancer therapies. Comprehensive and robust longitudinal monitoring of ctDNA can provide an understanding of tumor burden, heterogeneity, and response or resistance to treatment. Experimental DesignctDNA of 28 metastatic cancer patients receiving an individualized neoantigen-directed immunotherapy was monitored longitudinally, up to two years, using a unique hybrid next generation sequencing assay targeting tumor-informed and tumor-naive variants. Patient-specific panels were designed targeting an average of 144 variants per patient. A tumor-naive universal panel was also designed for inclusion with patient-specific panels to monitor recurrently mutated tumor hotspots (e.g., KRAS and TP53) and genes implicated in immunotherapy resistance (B2M, TAP1/2). ResultsAnalytical characterization of the assay established linearity with a mean variant allele frequency (VAF) [≥]0.049%, and a variant-level limit of detection (LOD95) of 0.12%. Tumor-informed variants were detected in 26/28 patients, and de novo variants were observed in 25/28 patients. HLA LOH was also observed. Longitudinal ctDNA data provided key insights into patients responses to vaccine treatment. ConclusionsThe hybrid design of the ctDNA monitoring assay provides the sensitivity and specificity required for evaluating patient samples undergoing individualized therapy. It provides an improved capability to understand patient response to experimental therapies and further supports the utility of ctDNA as a cancer biomarker.

genomics↗

bioRxiv2024

CEACAM1 Targets ABCA1 to Mediate Atrial Fibrillation via Lipophagy-Dependent Ferroptosis

Atrial fibrillation (AF) is one of the most common arrhythmias, imposing a significant burden on individuals due to its association with cerebrovascular events. The mechanisms underlying AF involve cardiac structural remodeling, electrical remodeling, and metabolic remodeling, with oxidative stress playing a crucial role. Our previous studies demonstrated that upregulation of CEACAM1 can increase oxidative stress, inhibit cell proliferation, and potentially contribute to cellular damage, while ferroptosis is closely associated with AF. In this study, we observed a significant increase in CEACAM1 expression in an AF model. Knocking out CEACAM1 revealed changes in mitochondrial membrane potential, reactive oxygen species (ROS) levels, intracellular Ca2+ concentration, channel proteins, and glycolipid metabolic enzymes. This knockout reversed electrical, structural, and metabolic remodeling in AF. Further investigation showed that CEACAM1 knockout inhibited ferroptosis, as evidenced by ferroptosis-related indicators. Using colocalization analyses of lipid droplets, lysosomes, and autophagosomes, we discovered that CEACAM1 knockout suppressed autophagy and lipophagy during AF. Supplementation with free fatty acids (FFAs) in the AF model post-CEACAM1 knockout suggested that the inhibition of ferroptosis was linked to a reduction in FFAs. Transcriptomic and non-targeted metabolomic analyses, along with ABCA1 interference studies, indicated that CEACAM1 knockout mitigates AF by promoting ABCA1 expression. In summary, CEACAM1 targets ABCA1 to alleviate AF through the regulation of lipophagy-dependent ferroptosis, as demonstrated in both cellular and animal models. BackgroundFerroptosis is a regulated form of cell death, but its connection with atrial fibrillation(AF) remains unclear. Since CEACAM1 knockout reduces oxidative stress and protects cells, we investigated the relationship among CEACAM1, ferroptosis, and AF to uncover the regulatory mechanisms of ferroptosis in AF. MethodsWe established AF models using HL-1 cells, human pluripotent stem cells, and rats. CEACAM1 expression levels were assessed in these models, along with changes in mitochondrial membrane potential, ROS levels, intracellular Ca2+ concentration, channel proteins, glycolipid metabolic enzymes, and ferroptosis-related indicators following CEACAM1 knockout. Through transcriptomics, non-target metabolomics, and immunoprecipitation screening, we identified ABCA1 as a downstream gene of CEACAM1 involved in protecting against AF. Subsequently, ABCA1 interference experiments were conducted, and colocalization analyses of lipid droplets, lysosomes, and autophagosomes were performed after the application of ferroptosis activators, lipophagy inhibitors, and lipophagy activators. FFAs were added to the AF model to evaluate changes in lipophagy and ferroptosis following CEACAM1 knockout. ResultsIn the AF model using HL-1 myocytes, CEACAM1 knockout reverse electrical, structural, and metabolic remodeling while inhibiting ferroptosis, with ABCA1 as a downstream gene. In the AF model derived from pluripotent stem cells differentiated into atrial myocytes, CEACAM1 knockout suppressed autophagy and lipophagy during AF, thereby inhibiting ferroptosis, which correlated with reduced FFA release. This process was regulated by ABCA1. In the rat AF model, ABCA1, identified as a downstream gene of CEACAM1, was further confirmed to inhibit ferroptosis by regulating FFA levels. ConclusionThis study reveals that CEACAM1 knockout inhibits ferroptosis in AF models by upregulating ABCA1 and reducing FFA levels, providing a novel regulatory mechanism for ferroptosis in AF. O_FIG O_LINKSMALLFIG WIDTH=172 HEIGHT=200 SRC="FIGDIR/small/625561v1_ufig1.gif" ALT="Figure 1"> View larger version (57K): org.highwire.dtl.DTLVardef@809c82org.highwire.dtl.DTLVardef@1a339d6org.highwire.dtl.DTLVardef@12a20d4org.highwire.dtl.DTLVardef@d14927_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

Quantitative MRI Measurements Capture Pancreatic Cancer and Stroma Reactions to New KRAS Inhibitor

PurposeIn pancreatic ductal adenocarcinoma (PDAC), KRAS mutations drive both cancer cell growth and formation of a dense stroma. Small molecule KRAS inhibitors (KRASi) represent a promising new treatment hence clinical tools that can assess early response, detect resistance and/or predict prolonged survival are desirable to understand clinical biology of KRASi. We hypothesized that diffusion-weighted MRI (DWI) can detect cell death while dynamic contrast enhanced MRI (DCE) and magnetization transfer ratio (MTR) imaging are sensitive to tumor microenvironment changes, and these metrics shed insights into tumor size change induced by KRASi treatment. Experimental DesignMultiple preclinical PDAC models including a genetically engineered mouse model (KPC) received MRTX1133, a KRASi specific for KRASG12D mutation. Quantitative imaging markers were corroborated with immunohistochemistry (IHC) analyses. ResultsSignificant increase of tumor apparent diffusion coefficient (a DWI metric) was detected as early as 48h and persisted to Day7 after initiation of KRASi treatment and was strongly correlated with cell death and reduced cellularity, resulting in greatly prolonged median survival in treated mice. Capillary perfusion/permeability (a DCE metric) exhibited an inverse relationship with microvascular density. Distinct responses of KRASG12C versus KRASG12D tumors to MRTX1133 were captured by the MRI metrics corroborated with IHC. When tumors developed resistance to MRTX1133, the imaging marker values exhibited a reversal from those of responding tumors. ConclusionsMultiparametric MRI provides early biological insights of cancer and stromal response to KRASi treatment and sets the stage for testing the utility of these clinically ready MRI methods in patients receiving KRASi therapy. Translational relevanceEmerging small molecule KRAS inhibitors (KRASi) represent a new class of therapy for PDAC. Clinical tools that can provide early biological insights of KRASi therapy are desirable. In PDAC models, we examined a clinically ready imaging protocol that combines MRI-based tumor size, diffusion-weighted MRI (DWI), dynamic contrast enhanced MRI (DCE), and magnetization transfer ratio (MTR) for detection of early response as well as acquired resistance to MRTX1133, a KRASi being evaluated in clinical trials. Our data show that DWI and DCE metrics provided key insights of significant cell death and tumor microenvironment changes underlying tumor size regression as early as 48 hours after KRASi treatment initiation. These MRI metrics also captured resistance to KRASi developed over prolonged treatment. This study has high translational relevance by employing clinically applied MRI methods, an investigational new drug and a genetically engineered mouse model that recapitulates salient features of human PDAC.

cancer biology↗

bioRxiv2024

A Robust Computational Framework for the Optimization of CDK7 Inhibitors as Promising Cancer Therapy

Cyclin-dependent kinase 7 (CDK7) plays a crucial role in cell cycle regulation and transcription, establishing it as a promising target for cancer therapy. Although the covalent inhibitor THZ1 effectively targets CDK7, it presents risks such as short half-life and potential off-target side effects. To address these limitations, we employed a computational workflow integrating virtual screening, molecular dynamics (MD) simulations, and free energy perturbation (FEP) method to design non-covalent CDK7 inhibitors with enhanced selectivity and safety profiles. MD simulations elucidated THZ1s inhibitory mechanism and identified key molecular fragments within its structure. By incorporating fragments from known inhibitors, we introduced extensive non-covalent interactions within the binding pocket, leading to the identification of three novel non-covalent inhibitors with binding affinities comparable to or higher than that of THZ1. Our findings not only introduce promising CDK7 inhibitors but also present a robust computational framework that could accelerate the discovery of kinase-targeted therapeutics.

biophysics↗

bioRxiv2024

A Multi-Modal Deep Learning Framework with Both Sequence and Structure for Tumor Antigens Prediction

Tumor antigens are key targets in cancer immunotherapies that can be recognized by T cell receptor and induce immune responses. However, precision screening of immunogenic tumor antigens remains a great challenge due to human leukocyte antigen (HLA) restriction and tumor antigen escape. Here, we introduce MultiTAP (Multi-modal Tumor Antigen Predictor), a pioneering multi-modal framework with TCR-peptide-HLA sequence and structure features incorporating an attention mechanism designed to accurately identify tumor antigens with immunogenic properties. By constructing the multi-modal TCR-peptide-HLA Dataset (TPHD) and integrating its sequence and structure, we perform antigen feature enhancement using peptide-HLA (pHLA) structural features at the residue level, achieving interpretable prediction of immunogenicity for tumor antigens. Relative to existing baseline models, the MultiTAP framework has exhibited superior efficacy in predicting the immunogenicity of tumor antigens. Through comprehensive out-of-distribution (OOD) assessments, MultiTAP has maintained predictive robustness across diverse HLA phenotypes and the continuously evolving landscape of epitope distributions. Overall, MultiTAP presents a brand-new and promising approach for cancer immunotherapies that target tumor antigens.

biophysics↗

bioRxiv2024

CRISPR knockout of winter-biased SUT4 alters phenology, biomass accrual, and fertility of field-grown hybrid poplar

Climate uncertainty is intensifying the need for greater plasticity in carbohydrate reserve utilization to support winter survival and spring growth in woody perennials. In poplar, the single-copy SUT4, which encodes a tonoplast-localized sucrose transporter, and the SUT5/SUT6 genome duplicates, which encode plasma membrane-localized transporters, are expressed year-round, with SUT4 showing highest expression during cool seasons. Given its role in vacuolar sucrose efflux and winter-predominant expression, SUT4 may play a key role in modulating seasonal carbohydrate dynamics. While SUT4-knockdown and knockout effects have been studied under greenhouse conditions, their impact under field conditions remains unexplored. Here, we report a field-based study comparing CRISPR knockout mutants of winter-expressed SUT4 and SUT5/SUT6 in Populus tremula x alba. We show that sut4, but not sut56, mutants exhibited earlier autumn leaf senescence, delayed spring bud flush, reduced stem growth, and altered sugar partitioning in winter xylem and bark relative to controls. After two years in the field, all genotypes flowered before leaf flush in early spring; however, sut4 mutants produced sterile ovules despite developing normal-looking catkins. Metabolic profiling revealed disrupted sucrose and raffinose dynamics in elongating sut4 catkins, accompanied by transcriptomic signatures of elevated stress and downregulation of proanthocyanidin biosynthesis and circadian clock genes. These findings highlight the critical role of SUT4 in coordinating sugar allocation, stress responses, and seasonal development in poplar. Significance statementThis field study demonstrates that loss of SUT4, the most highly expressed sucrose transporter during cool seasons, disrupts phenology, growth, and fertility in poplar. Altered sugar and raffinose dynamics and transcriptomic signatures of stress and circadian clock gene dysregulation in the mutants underscore SUT4s role in coordinating sugar allocation and seasonal developmental transitions under natural environmental conditions.

plant biology↗