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Yadav, S.

Publications and source records attributed to Yadav, S..

At least 37 records · Page 2Linked to original sources

Pan-repository analysis reveals a drug-activating function of microbial bile acid conjugation

Microbially modified bile acids shape host physiology by regulating nutrient absorption, glucose homeostasis, circadian rhythms and thermoregulation. Here we identify a previously unrecognized drug-activating function of microbial bile acid conjugation. By systematically mining human LC-MS/MS datasets across public repositories and linking uncharacterized bile acid spectra to health-associated metadata, we discovered conjugates of the >75-year-old anti-inflammatory drug 5-aminosalicylic acid (5-ASA) with primary and secondary bile acids, including cholic, deoxycholic and lithocholic acids. These bile acid-drug conjugates were detected specifically in individuals treated with 5-ASA or its prodrugs. Multiple gut bacteria, including members of the Bacteroidota and Bacillota, generated cholyl-5-ASA in vitro, and bile salt hydrolase-associated transaminase activity was required for conjugate formation. In a mouse model of colitis, cholyl-5-ASA was associated with reduced intestinal inflammatory pathology and showed markedly enhanced activation of PPAR-{gamma} in cell-based reporter assays compared with 5-ASA alone. Consistent with this activity, cholyl-5-ASA elicited selective immunophenotypic changes in CD4 T cells in vitro, including increased Foxp3+ regulatory T cells. Together with prior evidence that 5-ASA efficacy depends on the microbiome, these findings support a model in which microbial bile acid conjugation represents a key activation step for 5-ASA therapy. More broadly, this work demonstrates how pan-repository metabolomics can uncover previously unrecognized microbiome-dependent chemical functions with direct therapeutic relevance.

biochemistry↗

Myeloid DRP1 Sulfenylation Drives Reparative Macrophage Polarization and Neovascularization in Ischemic Muscle

Reparative macrophage polarization and macrophage-derived reactive oxygen species (ROS) are required for ischemia-induced revascularization in peripheral artery disease (PAD). Our previous study showed that mitochondrial fission protein DRP1 promotes reparative polarization and metabolic reprogramming in macrophages and post-ischemic neovascularization. However, the redox-dependent mechanism governing DRP1 activation in this context remains elusive. Here, using a mouse hindlimb ischemia (HLI) model of PAD, we identify cysteine sulfenylation (CysOH) of DRP1 as a critical redox modification induced in ischemic bone marrow (BM)-derived cells. BM chimeric mice reconstituted with CRISPR/Cas9-generated "redox-dead" DRP1-C631A knock-in mutant (Drp1C/A) BM exhibited markedly reduced limb perfusion recovery and CD31 capillary density in ischemic muscles following HLI. These defects were associated with enhanced Ly6G neutrophil accumulation, pro-inflammatory F4/80CD80 M1 macrophages and reduced anti-inflammatory F4/80CD206 M2 macrophages in ischemic muscle. Mechanistically, using an in vitro PAD model, hypoxia-serum starvation (HSS) rapidly induced cytosolic ROS production and DRP1-CysOH formation in wild type macrophages. In contrast, Drp1C/A macrophages failed to undergo DRP1-CysOH-dependent mitochondrial fission under HSS, resulting in aberrant metabolic reprogramming characterized by enhanced glycolysis and mitochondrial ROS, pro-inflammatory p-NF-{kappa}B and M1-genes, and suppressed anti-inflammatory p-AMPK and M2-genes. Thus, our findings establish DRP1 sulfenylation as a previously unrecognized redox-sensing mechanism that links ischemia-induced ROS to reparative macrophage reprogramming and revascularization, identifying a novel therapeutic target for PAD.

cell biology↗

FoldVision: A compute-efficient atom-level 3D protein encoder

Protein function emerges from three-dimensional structure, yet many large-scale protein prediction pipelines still rely solely on linear sequence embeddings. Although multiple structure-aware protein networks have been proposed, they often omit atom-level details and struggle to capture the detailed chemistry of binding sites. Here, we introduce FoldVision, a compute-efficient 3D convolutional neural network that voxelizes every heavy atom, learns rotation-robust representations, and is pre-trained on over 500 000 AlphaFold-2 structures, which is more than two orders of magnitude less data than used to train modern protein language models. Despite its compact size of 123 million parameters, FoldVision outperforms or matches state-of-the-art protein encoders on four benchmarks that require fine structural resolution: enzyme-substrate classification, transporter-substrate classification, drug-kinase inhibition, and drug-target inhibition prediction. A simple ensemble with a sequence-based model consistently improves performance across all benchmarks beyond any individual model. This indicates that FoldVision learns structural signals that are complementary to those extracted by sequence-based models. This study demonstrates that full-atom protein 3D CNNs are both tractable and superior to protein language models alone for structure-dependent tasks.

biochemistry↗

Tceal7 is a BRG1-regulated target of calcineurin signaling that promotes myoblast differentiation

The transcriptional control of skeletal muscle differentiation requires the coordinated activity of lineage-defining transcription factors, signal-responsive regulators, chromatin modifiers, and ATP-dependent chromatin remodeling enzymes. Here, we identify TCEAL7, a member of the X-linked, poorly characterized TCEAL family of proteins, as a direct downstream target of BRG1-containing mammalian SWI/SNF (mSWI/SNF) complexes and calcineurin signaling during myoblast differentiation. Analyses of previously published datasets showed that pharmacological inhibition of mSWI/SNF bromodomains or knockdown of the BRG1 ATPase, but not knockdown of the homologue BRM ATPase, significantly reduced Tceal7 expression in differentiating C2C12 myoblasts. We demonstrate that BRG1 occupancy at the Tceal7 promoter increased during differentiation, paralleling the induction of Tceal7 expression and nuclear accumulation of TCEAL7 protein. BRG1 functions in part by integrating calcium-dependent cues via the phosphatase calcineurin (Cn); we also determined that Cn knockdown or pharmacological inhibition of Cn suppressed Tceal7 expression and impaired myoblast differentiation. The data suggest that both BRG1-driven chromatin remodeling and Cn signaling converge on Tceal7 regulation. Functionally, Tceal7 knockdown altered cell proliferation and disrupted myoblast differentiation, at least in part due to reduced expression of Myogenin, which encodes a transcription factor that is an essential differentiation determinant. RNA-seq analysis revealed broad dysregulation of myogenic, metabolic, and cell-cycle gene programs in Tceal7-deficient cells, including changes in cyclin-dependent kinase-regulated pathways consistent with prior reports linking TCEAL7 to cell-cycle control. Together, these findings identify TCEAL7 as a necessary component of the myogenic regulatory network whose expression is controlled by BRG1-dependent chromatin remodeling and Cn activity.

molecular biology↗

Characterizing cellular subpopulations critical to treatment response in autoimmune diseases

Single-cell RNA sequencing provides a powerful approach for characterizing cell types, states, and lineages within heterogeneous tissues. However, identifying cell subpopulations that drive phenotypes, particularly treatment responses, remains a challenge. In this study, we performed comprehensive analyses to identify treatment response-associated cell subpopulations in autoimmune diseases by mapping bulk response information onto single-cell data. We integrated single-cell and bulk biopsy data from 314 responders and 619 non-responders treated with six therapeutics targeting tumor necrosis factor (TNF), integrin, or interleukin pathways in inflammatory bowel diseases (IBD) and psoriasis (PsO). Our analyses captured 128,428 interactions among 3,617 differentially expressed genes (DEGs), 852 pathways, and nine cell types spanning immune, stromal, and epithelial compartments. The importance of epithelial barrier integrity and enterocyte-mediated permeability in responses and inflammatory signaling in macrophages in non-responses in all tested therapies were highlighted by the presence of shared DEGs and pathways in both Crohns disease (CD) and ulcerative colitis (UC). In PsO, keratinocytes drove non-response to integrin-targeting therapies via disrupted adhesion, migration, and sustained epidermal inflammation. Additionally we introduce SCTRAD (https://immbioinfoabbv.shinyapps.io/SCTRAD/), an online web-based platform that allows exploration of mechanisms that influence the heterogeneity of cellular responses through DEGs and pathways at the single-cell level, as well as analysis of the cell-type-specific drug-related gene network. Our findings provide a comprehensive analysis of the role of cellular heterogeneity in treatment outcomes and for advancing precision medicine strategies in autoimmune diseases.

immunology↗

Divergent myelopoiesis and macrophage polarization underlie host susceptibility to chronic Chlamydia trachomatis infection

Chronic genital infection with Chlamydia trachomatis is associated with immune suppression and pathogen persistence, but the mechanisms underlying this phenomenon remain poorly defined. Here, we show that chronic C. trachomatis genital infection differentially reprograms myelopoiesis and macrophage polarization in genetically distinct mouse strains. In BALB/c mice, infection expanded bone marrow progenitors with enhanced colony-forming potential but skewed their differentiation toward immunosuppressive M2 macrophages and myeloid-derived suppressor cells (MDSCs). These cells accumulated in the spleen, blood, and genital tract, secreted IL-10 and TGF{beta}, and suppressed T cell proliferation, thereby impairing IFN{gamma}-driven clearance. In contrast, C57BL/6 mice exhibited C/EBP{beta}-driven myelopoiesis favoring M1 polarization, elevated IL-12 and nitric oxide production, and robust Th1 responses that facilitated bacterial elimination. Together, these findings demonstrate that host genetic background dictates divergent innate programming during C. trachomatis infection, and that the balance between M1- and M2/MDSC-dominated myelopoiesis determines whether infection resolves or progresses to chronicity.

immunology↗

IGFBPs define distinct pro-tumorigenic CAF subtypes in lung cancer tumour-microenvironment

Cancer-associated fibroblasts (CAFs) play a significant role in influencing tumour outcomes; however, their heterogeneity and context-sensitive nature present a therapeutically challenging target. Here, we identify a group of Insulin-like growth factor binding proteins (IGFBPs), specifically IGFBP5, 6 and 7, as key regulators of CAF heterogeneity in lung cancer. Notably, these binding proteins are highly expressed in lung CAFs and independently modulate CAF phenotype. We demonstrate that tumour-derived cues, particularly TGF{beta}1 and IL6, affect IGFBP expression in CAFs. Transcriptome studies indicate that selectively knocking down these proteins directs CAFs towards different CAF subtypes. Functionally, CAFs with high levels of IGFBP5, 6, or 7 promote tumour growth in both ex vivo and in vivo settings and, critically, confer cisplatin resistance to tumour cells. Furthermore, the gene signatures associated with these proteins correlate with unfavourable prognosis. In conclusion, our study highlights the phenotypic plasticity of CAFs driven by these three distinct IGFBPs from the same family, consequently influencing the tumour microenvironment landscape.

cancer biology↗

Complete Genome Sequencing and Molecular Characterization of Indigenous Enterovirus A71 Genogroups D and G of India

Enterovirus A71 (EV-A71), a neurotropic member of the Picornaviridae family, comprises seven recognized genogroups (A-G). Despite prior identification of D and G genogroups in India, comprehensive full-genome characterization of these indigenous lineages remains unreported. We performed next-generation sequencing (NGS) and molecular phylogenetic analyses on two Indian isolates: R13223-IND-02 (genogroup D) and V11-2209-01 (genogroup G). Phylogenetic reconstruction revealed robust clustering of these strains within distinct clades, divergent from globally prevalent genogroups B and C, considering bootstrap support [≥]99%. Both D and G genogroups appear geographically restricted to India, while genogroup D persists as an endemic lineage. Comparative genomic analyses demonstrated extensive nucleotide divergence, including numerous non-synonymous substitutions across both structural (VP1-VP4) and non-structural (2A-3D) coding regions. These findings highlight the evolutionary independence and sustained circulation of D and G genogroups in India, suggesting a unique regional evolutionary trajectory. The findings hold significant global relevance, offering valuable insights for molecular surveillance, advancing pathogenesis research, and supporting the development of genogroup-specific vaccine strategies tailored to diverse epidemiological landscapes.

genomics↗

Small amphiphilic DNA for programmable transmembrane signaling and amplification

Interrogating the sequence-specific DNA/RNA content of a living cell without destroying it, is an elusive goal in biology and diagnostics with transformative potential. A DNA/RNA-based approach, however, must relay the recognition event across the intact lipid bilayer, a step that has long been considered impossible because hydrophilic, massively charged DNA/RNA is incompatible with the hydrophobic membrane interior. Here, we show that DNA branch migration can be driven across a lipid bilayer, converting an intracellular nucleic-acid sequence into an amplified, extracellular optical signal while preserving cell viability and compartmentalization, a synthetic transmembrane signal transduction analogous to natural receptors, such as G-protein-coupled receptors (GPCRs), but operating in reverse. We demonstrate this principle with Hybridization Across Lipid for Oligonucleotide Sensing (HALOS), an amphiphilic DNA hairpin comprising a toehold for recognition, a stem for stability, a loop, and cholesterols for transmembrane anchoring. Upon binding to a sequence-specific nucleic acid target, toehold-mediated strand invasion drives DNA branch migration across the bilayer, switching HALOS from a closed to an open conformation that relays the signal to the opposite face. Molecular dynamics simulations revealed that a cholesterol belt stabilizes the DNA stem within the membrane, preserving the hairpin structure necessary for transmembrane signaling. Notably, this branch migration proceeds despite the kinetic barrier of hybridization through the hydrophobic bilayer interior. By combining HALOS with an isothermal hybridization chain reaction (HCR), we established a platform that enables intracellular nucleic acid target detection and amplified fluorescent reporting from outside synthetic vesicles and live mammalian cells, achieving nanomolar-range sensitivity. These results establish DNA branch migration across lipid membranes as a design principle for programmable lysis-free molecular sensing in intact cells.

biophysics↗

Deoxycholic acid (DCA) alleviates LPS-induced Inflammatory Bone Loss via modulating the Gut-Bone homeostasis

Osteoporosis and other forms of inflammatory bone loss are marked by disrupted bone remodelling resulting from an imbalance between osteoclast-mediated bone resorption and osteoblast-driven bone formation. This imbalance is often exacerbated by chronic inflammation and gut microbiota dysbiosis. Recently, attention has turned to gut-associated metabolites (GAMs) such as secondary bile acids, particularly deoxycholic acid (DCA), which act as immunomodulators influencing both systemic inflammation and bone metabolism. In this study, we investigated the role of DCA in inflammatory bone loss using an in vivo model, with a focus on osteoblast and osteoclast function, gut barrier integrity, and gut-microbiota diversity. DCA administration significantly suppressed osteoclastogenesis along with enhancing osteoblastogenesis, indicating its dual regulatory role in bone remodelling. Furthermore, DCA treatment enhanced gut integrity, reversed dysbiosis and reduced systemic inflammation by downregulating osteoclastogenic cytokines (TNF-, IL-6, IL-17, RANKL, etc.). These findings suggest that DCA mitigates LPS-induced inflammatory bone loss through a multifaceted mechanism involving direct effects on bone cells and restoration of gut integrity and homeostasis. Our results highlight the therapeutic potential of targeting the gut microbiota-derived bile acid pathway, particularly DCA, as a novel strategy for managing osteoporosis and other inflammatory bone disorders. O_FIG O_LINKSMALLFIG WIDTH=131 HEIGHT=200 SRC="FIGDIR/small/678724v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@1702fddorg.highwire.dtl.DTLVardef@568b38org.highwire.dtl.DTLVardef@1ce463aorg.highwire.dtl.DTLVardef@164a04d_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 9.C_FLOATNO Graphical Abstract. Secondary bile acids act via FXR and TGR5 receptors on osteoclast and osteoblast cells and thereby regulate bone remodelling. C_FIG

cell biology↗

Advancing rust resistance in elite wheat with haplotype mapping and a novel introgression strategy

Wheat production is continually threatened by stripe and leaf rust because virulent races rapidly overcome single race-specific genes. Durable, broad-spectrum resistance is needed. Adult plant resistance (APR) provides partial, stable resistance from multiple minor-effect loci acting additively; pleiotropic loci like Lr34/Yr18 and Lr46/Yr29 add durability. We used an elite Australian panel (OzWheat=589) and a diverse landrace panel (Vavilov=295), genotyped with [~]30K SNPs and phenotyped across environments. Linkage disequilibrium partitioning defined 7,659 genome-wide haploblocks. To prioritise robust signals, we ranked haploblocks by haplotype effect variance and examined the top 100 per trait. For stripe rust, 52/100 were significant, with 32 shared across panels; for leaf rust, 50 were significant, 29 also detected in Vavilov. Several intervals co-localised with APR regions (Lr46/Yr29), and one 7BL interval intersected seedling gene Lr14a. To translate mapping into breeding decisions, we developed an introgression fitness index to quantify the value of resistant haplotypes in elite backgrounds. Using elite cultivar Scepter, we applied a genetic algorithm to select 50 donor parents carrying desirable haplotypes. Simulations showed that pyramiding these haplotypes can enhance resistance while maintaining elite genomic background. This study provides practical breeding tools, including haplotype catalogue and a novel selection index to accelerate rust-resistant wheat development.

genetics↗

SMTrackR: a R/Bioconductor package for mapping protein binding at individual DNA molecules

Single-molecule assays like NOMe-seq, dSMF and Nanopore are superior to DNase-seq and ATAC-seq as they do not nibble down DNA. Thus, they enable quantification of all three i.e., protein-free, Transcription Factor-bound and histone-complex-bound states. But a user-friendly tool to visualize and quantify such states is lacking. Here, we present, SMTrackR, a Bioconductor package to visualize protein-DNA binding states on individual sequenced DNA molecules. SMTrackR queries the single-molecule footprint database we built and hosted at Galaxy Server. It comprises of BigBed files generated from NOMe-seq, dSMF, and Nanopore (SMAC-seq) datasets. SMTrackR exploits UCSC REST API to query a BigBed file and plot footprint heatmap categorized in different binding states as well as report their occupancies. Additionally, this package generates a Gviz-enabled script to visualize these single-molecules on gene tracks. Availability and implementationThe SMTrackR tool is implemented the statistical programming language R and is available at the GitHub developer site, https://github.com/satyanarayan-rao/SMTrackR. The tool is also available in a web version https://smtrackr.iitr.ac.in. A function is provided to use local BigBed file for users who wish to use unpublished data. A fully automated pipeline to generate such BigBed files is available at https://github.com/satyanarayan-rao/SMF_for_SMThub and https://github.com/satyanarayan-rao/dSMF_for_SMThub.

bioinformatics↗

Local genomic estimates provide a powerful framework for haplotype discovery

Quantitative trait loci (QTL) discovery studies on diversity panels or breeding populations typically use genome-wide association studies (GWAS) to estimate marker effects. For plant and animal breeding applications, researchers increasingly recognize the potential benefits of identifying superior haplotypes (markers in linkage disequilibrium; LD) rather than relying on single markers, as traditional approaches inefficiently account for cumulative signals from incomplete LD with QTL or split effects when multiple markers are in high LD with QTL. Using the genomic prediction framework, the local genomic estimated breeding values (localGEBV) method was developed in animal breeding and has been adopted in crop haplotype mapping studies; however, no study has thoroughly quantified the utility of this method or systematically compared outcomes to traditional GWAS approaches. Here, we characterized a strategy to group markers in chromosomal segments based on LD (haplotype blocks or haploblocks), computed localGEBV as a linear contrast of marker effects within each haploblock, and utilised the variance of localGEBV to enhance QTL discovery compared to traditional GWAS. Marker effects for localGEBV were estimated with ridge-regression best linear unbiased prediction (rrBLUP) and BayesR, with results compared to two common GWAS approaches. Using the barley row-type trait, we demonstrated that localGEBV improved QTL discovery and phenotypic prediction compared to single markers. Furthermore, localGEBV results were robust to the choice of prior marker assumptions and blocking parameters, enabling flexibility in fine or broad-scale QTL mapping. Overall, our findings establish localGEBV as a haplotype-based strategy capable of leveraging localized genomic effects to improve QTL discovery and, potentially, genomic selection.

genetics↗

Cyrene: A Novel Geroprotective Compound that Extends Lifespan and Healthspan in C. elegans and Drosophila

As aging is the primary risk factor for many chronic diseases, geroscience aims to target aging to delay age-related decline. Here, we identify Cyrene (dihydrolevoglucosenone), a sustainable, biocompatible solvent, as a novel geroprotective compound. Cyrene extends lifespan and healthspan in C. elegans, improving locomotor function and resistance to oxidative, thermal, osmotic, genotoxic, and proteotoxic stress. It also confers protection in neurodegenerative models of Alzheimers, Parkinsons, and Huntingtons disease. Cyrene is effective when delivered during development or early adulthood and requires administration before day 8 to extend longevity. Its benefits are independent of bacterial metabolism and partially independent of the FOXO transcription factor DAF-16. Importantly, Cyrene also extends lifespan and enhances oxidative stress resistance in Drosophila melanogaster, demonstrating cross-species efficacy. These findings identify Cyrene as a novel geroprotective compound that promotes longevity, resilience, and neuroprotection. Conservation across species supports future work to dissect molecular mechanisms and test its potential in mammals.

developmental biology↗

Microbial Scl1 Activates TGFBR1 receptor kinase signalling to Drive Fibrosis-Inflammation Axis in Alcohol-Associated Liver Disease

Background and AimsAlcohol consumption alters gut microbiota, which can affect metabolism, immune regulation, and signalling pathways and lead to alcohol-associated liver disease (ALD). We investigated how alcohol-associated gut microbiota (AGMs) modulate liver kinome signalling to drive inflammation and fibrosis in ALD. MethodLiver kinome and metaproteome changes were studied in rats (n=6/group) colonized with stool of severe alcohol-related hepatitis (SAH) patients (SAH[->]healthy-rats) or healthy human donors (HD[->]ALD-rats). AGM-associated liver kinome changes were cross-correlated with bacterial genera. A bacterial protein; Streptococcal collagen-like protein 1 (Scl1) was identified with affinity for TGF{beta}R1. This was validated by molecular docking and immunoprecipitation-LCMS assay. Expression of Streptococcus pneumonia and pyogenes was done in stool of SAH patients (n=10). Also, Scl1 was quantified in patient stool (n=24) and liver tissue (n=19) samples. Validation was performed by assessing Scl1 level in plasma and Streptococcus level in stool samples before and after fecal microbiota transplantation (FMT) in SAH patients. ResultsStool metaproteomics showed significant increase in 10 bacterial genera (Streptococcus, Staphylococcus, and Clostridium) in SAH[->]Healthy-rats, mirroring changes seen in ALD-rats (FC>1.5, p<0.05). Clusters of Orthologous Groups analysis indicated increased post-translational modifications (PTMs) and decreased lipid metabolism in ALD-rats and SAH[->]Healthy-rats. Liver kinome profiling showed 85 upregulated kinases in SAH[->]Healthy-rats, with 34 overlapping with ALD-rats, associated with inflammation (Mapk14, Map3k10 and others), fibrosis (Tgfbr1, Igf1r, and others), lipid metabolism (Cdk14, Cdk18) and regeneration (Met, Bmpr1a and others). FMT from healthy human-donors to ALD-rats reversed the expression of Streptococcus (10-fold), Staphylococcus (3-fold), and Clostridium (5-fold), along with 18 kinases associated with inflammation (Btk, Camk4, Nuak1) and fibrosis (Tgfbr1, Col4a1, Fgfr2 and others). Strong association (r{superscript 2}>0.9, p<0.05) was seen between Streptococcus abundance and fibrosis and inflammation-related kinases. Level of Scl1 was significantly high in SAH and ALD-rat stool samples (FC>2, p<0.05). It showed strong affinity for TGF{beta}R1, as validated by molecular docking (>86%confidence) and immunoprecipitation assays (>100FC,p<0.05), indicating it as a potential ligand for TGF{beta}R1. Concordantly, expression of Scl1 was highest amongst all the known ligands for TGF{beta}R1 (p<0.05) suggesting Scl1 is a major contributor for TGF{beta}R1 activation and its downstream signalling in these patients. Following fecal microbiota transplantation, expression of Scl1 in plasma and Streptococcus levels in stool were significantly reduced by 2.1-folds and 1.9 folds respectively in SAH patients. Further, Scl1 levels SAH plasma is capable of predicting poor therapeutic response and 30-day mortality with high accuracy (AUC=0.92, cutoff >70 normalized abundance). ConclusionAlcohol induced gut dysbiosis alters the liver kinome, promoting inflammation, fibrosis, and lipid dysregulation. Streptococcal Scl1 is identified as a bacterial protein mimicking human collagen and capable of activating fibrotic signalling pathway through TGF{beta}R1in liver and is capable of predicting poor response in SAH. FMT from healthy donor restores microbial imbalance and harmful microbial-host interactions.

microbiology↗

AllerStack: Predicting Allergenic Proteins with a Stacked Ensemble Approach

Accurate prediction of protein allergenicity is essential for ensuring food and drug safety. While machine learning and deep learning models have been explored for this task, limitations remain in dataset scale, feature representation, and model architecture. Here, we introduce AllerStack, a two-stage stacked ensemble model integrating handcrafted and ESM2-based learned features for allergenicity classification. The model was developed using a balanced dataset comprising 11,930 allergenic and 11,930 non-allergenic proteins. We extracted amino acid composition, dipeptide composition, and physicochemical features using the Biopython library, alongside contextual embeddings from the pre-trained ESM2 protein language model. Diverse classifiers (QDA, SVM, KNN, and ANN) were trained separately on these features in the base layer. Their predictions were used as input to a meta-classifier based on XGBoost. AllerStack achieved high predictive performance with 96.87% accuracy, 96.86% F1-score, 93.75% Matthews correlation coefficient (MCC), and an AUC of 0.99. A publicly accessible web server (https://cosylab.iiitd.edu.in/allerstack/) enables real-time allergenicity prediction from protein sequences. AllerStack provides a robust, interpretable, and user-friendly platform for allergen detection in computational biology. HighlightsO_LIAn extensive dataset of 23,860 proteins. C_LIO_LICombines handcrafted and ESM2-derived features. C_LIO_LIStacked ensemble model with an accuracy of 96.87%. C_LIO_LISHAP-based model interpretability at the model and feature level. C_LIO_LIPublic web server, AllerStack (https://cosylab.iiitd.edu.in/allerstack/). C_LI

bioinformatics↗

Metabolomic Profiling of Ashwagandha (Withania somnifera): Linking Bioactive Compounds to Functional Therapeutic Roles

IntroductionWithania somnifera (Ashwagandha) is a widely used medicinal plant with established roles in traditional systems of medicine. Known for diverse pharmacological effects, including neuroprotection, hepatoprotection, enhancement of male fertility, and anti-inflammatory activity. Despite its longstanding use, a deeper understanding of its phytochemical composition and bioactive mechanisms is required to bridge traditional knowledge with modern therapeutic applications. MethodsA comprehensive metabolomics profiling of Withania somnifera was performed to identify and quantify its bioactive secondary metabolites. Focus was placed on major classes such as alkaloids, phenolic compounds, and terpenoids. Known compounds were annotated and categorized based on their abundance, chemical class, and reported biological functions. Particular attention was given to compounds implicated in neuroprotection, liver health, reproductive support, and inflammation-modulation. ResultsThe analysis revealed a rich but low-abundance of known metabolites. Alkaloids such as Gentianaine (8.44%) and Sauroxine (2.94%), and phenolics like Mulberrofuran A (14.58%) and Sulphuretin (9.61%), were among the most prominent. These compounds are associated with antioxidative, anti-inflammatory, and neuroregenerative activities. Terpenoids including Pinocarvone and Ergosterol contributed to hepatoprotective and anti-inflammatory properties. Compounds such as Gomphrenin-I, Sitosterol, Pfaffic acid, beta-Carotene and others (>3%) supported spermatogenesis, while Embelin and Kievitone enhanced oxidative stress response. Although most identified compounds were individually present in low percentages (<0.30%), their collective activity suggests synergistic effects. ConclusionMetabolomic analysis of Withania somnifera confirms high abundance of bioactive secondary metabolites that have hepatoprotective, neuroprotective, anti-oxidant and spermatogenesis-enhancing effects. These findings justify protective and beneficial effect of Withania in promoting stress relief, energy, and overall wellness. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/659832v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1ae8e5forg.highwire.dtl.DTLVardef@105300corg.highwire.dtl.DTLVardef@1958320org.highwire.dtl.DTLVardef@d3ba13_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

Proximity-based super-resolution imaging enabled by DNA base-stacking interactions

Super-resolution imaging has gained significant traction in recent years due to its unprecedented ability to visualize target biomolecules at nanometer resolution. Here, we demonstrate the capability to detect target pairs that are in close proximity by exploiting base-stacking interactions between two DNA strands, each labelling one target. Our DNA probes hybridize transiently with the each other only when both target molecules are proximal, thus creating a hybridization site for fluorophore-conjugated DNA strand, called imager. In this design, hybridization and co-axial base-stacking act synergistically to enable imager binding, with stacking interactions providing essential stabilization that allows for transient hybridization. This synergy generates the stochastic binding events required for DNA-PAINT imaging, which we call Stack-Proximity-PAINT (Stack-pPAINT). To gain mechanistic insights into hybridization of our probe, we performed atomistic equilibrium and steered molecular dynamics (MD) simulations. The simulations reveal that DNA base-stacking and fluorophore stacking together stabilize the imager. We utilized programmable DNA nanostructures to benchmark the applicability of Stack-pPAINT. As a cellular proof of concept, we visualized microtubular structures using Stack-pPAINT with antibodies targeting both alpha- and beta-tubulin molecules. This probe technology offers promising applications in cell biology research aimed at elucidating spatial interactomes at high resolution within cells.

biophysics↗