Biology subjects

Kumar, U.

Publications and source records attributed to Kumar, U..

At least 19 recordsLinked to original sources

bioRxiv2026

ARL15 promotes inflammatory fibroblast activation and disease severity in rheumatoid arthritis: integrated transcriptomic and collagen-induced arthritis model analyses

BackgroundADP-ribosylation factor-like protein 15 (ARL15) is a rheumatoid arthritis (RA) susceptibility gene identified through GWAS. Previous studies suggested a role for ARL15 in synovial fibroblast (SF) pathogenicity, but its contribution to inflammatory arthritis remains unclear. We investigated the inflammatory role of ARL15 and its therapeutic potential in RA. MethodsARL15 was overexpressed in MH7A cells followed by bulk RNA sequencing and pathway enrichment analyses. Therapeutic relevance was evaluated in collagen-induced arthritis (CIA) mouse model using anti-ARL15 monoclonal antibodies, ARL15-targeting siRNA, or isoquinoline. Arthritis scores, histopathology, micro-CT and serum cytokines were assessed. Publicly available single-cell RNA sequencing (scRNA-seq) datasets were analyzed to determine ARL15 expression in RASF subsets. ResultsARL15 overexpression induced a pro-inflammatory transcriptional program characterized by upregulation of IL1A, IL1B, IL6, IL8, CXCL1, CXCL10, and CCL20. Gene set enrichment analysis revealed activation of IL6-JAK-STAT, TNF, interferon-response, and KRAS signaling pathways, with suppression of oxidative phosphorylation, lipid metabolism, and mTORC1 signaling. In CIA mice, ARL15 inhibition significantly reduced arthritis severity, inflammatory infiltrates, and joint destruction while preserving cartilage and bone integrity. Serum TNF-, IL-6, and IL-1{beta} levels were markedly decreased following ARL15 blockade. Combination monoclonal antibody treatment demonstrated the greatest therapeutic benefit. scRNA-seq analysis showed broad ARL15 expression across RA fibroblast populations, with enrichment in inflammatory lining and SF subsets. ConclusionsARL15 is a pro-inflammatory regulator of SF activation and arthritis progression. Integrated transcriptomic, single-cell, and in vivo analyses identify ARL15 as a therapeutic target for RA and support further translational development of ARL15 based therapies.

immunology↗

bioRxiv2026

SMARTIE: A Machine-Learning approach for investigating RBP-RNA interactions identified by Editing

RNA-binding proteins (RBPs) play important roles in gene regulation. RNA editing-based approaches, such as TRIBE and STAMP, have gained wider use for identifying RNA targets of RBPs. These methods offer advantages over crosslinking-based approaches in terms of experimental simplicity and in vivo applicability. However, data analysis methods for these approaches remain underdeveloped, limiting sensitivity, and unbiased target prioritization. To address these limitations, we introduce SMARTIE (Systematic Machine-learning Approach for RBP Targets Identified by Editing), a machine-learning-based framework. SMARTIE robustly identifies and ranks RBP target RNAs from editing data by integrating statistical tests with replicate-aware and confidence-weighted features. Reanalysis of multiple published TRIBE datasets demonstrates the effectiveness of SMARTIE. It recovers targets of RBPs like Ataxin-2, TDP-43, Hrp48, Thor, GPATCH8, dFMRP and NonA. Notably, a model trained on TRIBE data generalizes to STAMP datasets, suggesting that SMARTIE learns universal signatures of editing-based RBP targeting there by enabling more accurate inference for RBP-RNA interactions. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/726004v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@8b77e5org.highwire.dtl.DTLVardef@6c9416org.highwire.dtl.DTLVardef@6e33a5org.highwire.dtl.DTLVardef@100b7b5_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2026

Bacterial Swarming-Guided Biomineralization Enables Pattern Formation in Engineered Living Materials

Engineered living materials (ELMs) harness the adaptive and self-replicating capabilities of biological systems to create functional materials for sensing, catalysis, and biomineralization. While most ELM strategies rely on static microbial assemblies, the role of bacterial motility in structuring living materials remains unexplored. Here, for the first time, we demonstrate how swarming motility in Escherichia coli MG1655 can be induced to guide spatio-temporally organized calcium phosphate mineralization. The mineralized calcium phosphate is characterized by scanning electron microscopy and elemental analysis. By systematically varying phosphate sources and their concentrations in calcium-rich media, we observe the emergence of regularly spaced concentric mineralized patterns. The previously undocumented observation of the concentric patterns was rationalized through a continuum model that captures the spatiotemporal coupling between swarm expansion and mineral deposition. The model shows that this coupling can generate recurrent front arrest and restart, leading to concentric ring formation. Finally, we show that altering the phosphate species results in distinct mineral morphologies. Together, this work establishes a novel framework for integrating bacterial swarming with biomineralization, enabling dynamic and programmable pattern formation in ELMs.

bioengineering↗

bioRxiv2025

An integrated workflow for structural virology with a 100 keV electron microscope

Cryo-EM has revolutionized structural biology, especially for flexible and heterogeneous samples, although access to high end microscopes that enable these studies remains a bottleneck. While 300 keV microscopes have been the go-to for high-resolution structural determination, they are expensive and restricted to institutional and national facilities needing specialized expertise, with access falling far short of the demand. Here, we present the user-managed operation of a cheaper 100 keV electron microscope within a structural biology laboratory enabling close integration with protein production, biochemical and biophysical studies. We provide details and considerations for the installation of the microscope, its day-to-day maintenance, and operations. Using virus surface glycoproteins as case studies, we illustrate the workflow from grid screening, data collection, and data processing, and provide examples of data quality. This user-administered setup provides a training platform for researchers at all levels, with beginners in cryo-EM achieving proficiency to independently operate the microscope within a month of regular use and training. We have demonstrated routine high-quality low-resolution reconstructions using a Ceta CMOS camera and high-resolution reconstructions enabling building of atomic models using a Falcon C direct detector. While there are several examples of facilities that manage cryo-EM and individual laboratories leveraging cryo-EM, we provide here the first demonstration of a modern group independently doing both successfully, something that has been talked about frequently but rarely seen.

biochemistry↗

bioRxiv2025

Urinary Exosomal miRNA Profiling Reveals Sensitive Non-Invasive Diagnosis of Bladder Cancer

UnstructuredmiRNAs represent a transformative advancement in both research and clinical management of urinary bladder cancer (UBC), emerging as clinically significant molecular targets with the potential to revolutionize existing diagnostic standards. This study exploited the robust stability of miRNAs and profiled urinary miRNAs in UBC patients and controls through miRNA sequencing, revealing an expanded and altered miRNA repertoire in cancer samples. Validation in an independent cohort revealed fold changes for miR-6724-5p, miR-1273h-5p, miR-7704, miR-200-5p, and miR-10400-5p ranged from [~]46 to [~]2,777 (p < 0.01). Stage-specific analyses highlighted dynamic miRNA expression linked to tumor progression. Diagnostic evaluation identified an optimal three-miRNA panel comprising miR-6724-5p, miR-10400-5p, and miR-7704, achieving diagnostic accuracies (AUC > 70%) and high sensitivity (>90%). These data demonstrate the potential of urinary mature miRNAs as robust biomarkers for non-invasive detection and monitoring of UBC in early stages, supporting their translation into clinical diagnostic assays pending larger prospective studies. StructuredO_ST_ABSBackgroundC_ST_ABSUrinary microRNAs (miRNAs) are promising candidates due to their molecular stability and disease-specific expression. miRNAs represent a transformative advancement in both research and clinical management of urinary bladder cancer (UBC), emerging as actionable molecular targets with the potential to revolutionize existing diagnostic standards. MethodsSmall RNA sequencing was performed on urine samples from UBC patients and healthy controls to profile miRNA expression. Mature miRNAs were prioritized by exclusion of precursor forms using computational filtering. Validation by quantitative RT-PCR was conducted on an independent, age-matched cohort (n = 45). Diagnostic potential of candidate miRNAs was assessed by receiver operating characteristic (ROC) curves and area under the curve (AUC) analyses. ResultsSequencing identified 865 known and 11 novel miRNAs, with UBC samples showing greater miRNA diversity (708 known miRNAs) compared to controls (540). Ten miRNAs were significantly dysregulated in UBC (p < 0.05). Validation revealed fold changes for miR-6724-5p, miR-1273h-5p, miR-7704, miR-200-5p, and miR-10400-5p ranged from [~]46 to [~]2,777 (p < 0.01). Stage-specific analyses highlighted dynamic miRNA expression linked to tumor progression. A three-miRNA panel (miR-6724-5p, miR-10400-5p, miR-7704) demonstrated superior diagnostic performance (AUC > 70%, sensitivity > 90%). ConclusionMature urinary miRNAs exhibit reproducible, stage-specific dysregulation in UBC and a combinatorial panel offers sensitive, specific non-invasive detection. These findings warrant further multicenter validation for clinical application.

cancer biology↗

bioRxiv2025

Non-Invasive Diagnostic Evaluation of Urinary Exosomal Let-7c Cluster Expression in Bladder Cancer Using Machine Learning Approaches

BackgroundBladder cancer (BCa) diagnosis typically relies on invasive cystoscopy, which is effective but costly and uncomfortable. Urinary microRNAs (miRNAs), especially exosomal ones, are promising non-invasive biomarkers due to their stability in biological fluids and disease specificity. However, challenges such as population variability, methodological inconsistencies and normalization issues hinder their clinical translation, emphasizing the need for innovative approaches to enhance diagnostic performance. ObjectiveTo evaluate the diagnostic potential of urinary exosomal let-7c cluster (let-7c-5p, miR-99a-5p and miR-125b-5p) in BCa patients by integrating miRNA expression data with Machine Learning (ML) models. MethodsUrine samples were collected from 66 participants, including 50 BCa patients and 16 healthy controls (HC). Exosomal miRNAs were isolated and quantified using Quantitative Real-Time-Polymerase-Chain-Reaction (qRT-PCR). Statistical analysis and hypothesis tests were conducted to explore the nature and diagnostic relevance of individual biomarkers. A logistic regression classifier was applied to evaluate both the combined and differential diagnostic capabilities of the selected biomarkers. Accuracy, precision, recall and AU-ROC scores were used to assess model performance. Bioinformatics analysis was performed to identify pathways associated with the features prioritized by the ML models, ensuring their relevance to BCa. ResultsThe result revealed significant differentiation between BCa patients and HC, with miR-99a-5p (p=0.013, AU-ROC=0.71) and miR-125b-5p (p=0.047, AU-ROC=0.64) demonstrating reliable diagnostic performance (let-7c-5p showed weaker discrimination, AU-ROC=0.65, p>0.1). The logistic regression ML model achieved an accuracy of 80.0% (AU-ROC=0.86, recall=100%) in distinguishing cancer from HC and 53.3% (AU-ROC=0.63) when applied to miRNA-only grade classification. When clinical variables were integrated with miRNA expression, performance improved to 73.3% accuracy (AU-ROC=0.61) for high-versus low-grade differentiation. Across Ta-T2, miR-99a-5p displayed relatively better separation, whereas let-7c-5p and miR-125b-5p showed weak stage-related differences. The integration of bioinformatics analysis confirmed the biological relevance of these miRNAs in BCa-related pathways, including PI3K-Akt, p53, NF-{kappa}B and RAS/MAPK signaling, with hub genes such as TP53, MYC, EGFR, and CCND1 identified, further validating the diagnostic utility of the selected biomarkers. ConclusionUrinary let-7c cluster miRNAs demonstrate promising diagnostic potential when analyzed with ML models, offering a non-invasive alternative to conventional methods. These findings highlight the promise of ML-based approaches alongside molecular markers for advancing clinical diagnostics in BCa.

molecular biology↗

bioRxiv2025

Longitudinal multi-omic evaluation of biomarkers of health and ageing over smoking cessation intervention

Smoking is one of the single most important preventable risk factors for cancer and other adverse health outcomes 1,2. Smoking cessation represents a key public health intervention with the potential to reduce its negative health outcomes 2-4. While epidemiological, cross-sectional, and individual longitudinal omic or biomarker studies have evaluated the impact of smoking cessation, no study to date has systematically profiled molecular and clinical changes in several organ systems or tissues longitudinally over the course of smoking cessation that could allow for more detailed assessment of response biomarkers and the identification of interindividual differences in the recovery of physiological functions. Here, we report the first human longitudinal multi-omic study of smoking cessation, evaluating 2,501 unique single or composite features from 1,094 longitudinal samples. Our comprehensive analysis, leveraging over half a million longitudinal data points, revealed a profound effect of smoking cessation on epigenetic biomarkers and microbiome features across multiple organ systems within 6 months of smoking cessation, alongside shifts in the immune and blood oxygenation system. Moreover, our multi-omic analysis provided unprecedented granularity that allows for identification of new cross-ome associations for mechanistic discovery. We anticipate that data and an interactive app from the Tyrol Lifestyle Atlas (eutops.github.io/lifestyle-atlas), comprising the current study and a parallel study arm evaluating the impact of diet on biomarkers of health and disease, will provide the basis for future discovery, biomarker benchmarking in their responsiveness to health-promoting interventions, and study of individualised response group, representing a major advance for personalised health monitoring using biomarkers.

systems biology↗

bioRxiv2025

Systemic multi-omic remodelling underlies health benefits of intermittent fasting

While intermittent fasting (IF) promotes longevity in animal models, its systemic effects in humans remain poorly understood. Here, we present a six-month longitudinal IF intervention in 114 women (BMI 25-35) with deep clinical, molecular, and microbiome profiling across >3,400 biospecimens from six tissues. Analyses spanning >2,200 multi-omic features and 11,000 microbial function predictions demonstrate coordinated clinical benefits, including improvements in body composition and cardiorespiratory fitness, and reveal coordinated molecular responses across tissues. Iron metabolism emerged as a central axis: transferrin increased while ferritin, haemoglobin, and erythrocytes decreased, changes that opposed ageing trajectories yet remained within physiological limits. Epithelial DNA methylation biomarkers (cervical, buccal) of cancer risk reduced, while blood clocks were largely unresponsive, underscoring tissue-specificity of the epigenome. Immune profiling uncovered dynamic, partially reversible shifts. Notably, we derived a new immunophenotyping-based ImmuneAge score that increased during fasting and tracked with inflammatory function, while the pro-inflammatory cytokine IL-17A declined selectively in postmenopausal women. Oral microbiota showed rapid restructuring, whereas gut microbiota shifted more subtly toward enhanced metabolic capacity. Together, these data provide unprecedented insight into the systemic and tissue-specific responses to IF in humans and identify iron homeostasis and immune remodelling as candidate mechanisms. Our findings are available through the Lifestyle Atlas (https://eutops.github.io/lifestyle-atlas). HighlightsO_LIIntermittent fasting remodels iron metabolism, opposing age-associated trajectories C_LIO_LIEpithelial but not blood methylation biomarkers respond to fasting C_LIO_LIFasting transiently elevates ImmuneAge and TNF-producing cytotoxic T cells C_LIO_LIOral microbiota restructure rapidly, while gut microbiota show subtler functional shifts C_LIO_LIIntegrative networks link iron, immunity, adiposity, and epithelial barrier function C_LI

systems biology↗

bioRxiv2025

Multi-modal atlas of lifestyle interventions reveals malleability of ageing-linked molecular features

Extending human healthspan requires understanding how lifestyle interventions impact molecular systems across tissues and time. Here, we present the TirolGESUND Lifestyle Atlas (ClinicalTrials.gov: NCT05678426), a longitudinal, multi-modal resource profiling 156 healthy women (aged 30-60 years) undergoing 6-month intermittent fasting (n=114) or smoking cessation (n=42) interventions. Participants were sampled up to four times across seven tissues and fluids, generating >3,450 biospecimens with harmonised DNA methylation, metabolomics, microbiome, and immune profiling, alongside skin histology, barrier measurements, and rich clinical metadata. We demonstrate the utility of this dataset through: (i) multi-omics-wide association studies linking traits to molecular features; (ii) integrative factor modelling revealing coordinated cross-tissue signatures; (iii) epigenetic-biomarker cross-omic associations, and (iv) CpG-level variance decomposition mapping stable, individual-specific, tissue-restricted, and intervention-responsive methylation patterns. We further show that ageing-linked features are selectively malleable: highly compliant intermittent fasting participants exhibited attenuated or even age-opposing molecular trajectories within six months. The atlas enables unprecedented within-cohort comparisons across omic layers and tissues, supporting discovery of context-dependent biomarkers, cross-system coordination, and intervention responsiveness. Data are available via an interactive portal, with sensitive data under controlled access (https://eutops.github.io/lifestyle-atlas/). This resource provides a foundation for exploring biomarker association and multi-tissue epigenetics, enabling hypothesis generation and benchmarking for systems biology and human healthspan research. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=186 HEIGHT=200 SRC="FIGDIR/small/673115v2_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@fec2d9org.highwire.dtl.DTLVardef@1aa5d13org.highwire.dtl.DTLVardef@1c4a6f2org.highwire.dtl.DTLVardef@1ac62fb_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIMulti-tissue multi-modal profiling of two clinically-relevant lifestyle interventions in 156 women aged 30-60 C_LIO_LIIntermittent fasting modifies ageing-linked molecular features in an age-opposing direction C_LIO_LICross-tissue epigenetic biomarker mapping links immunity, metabolism, and microbiome C_LIO_LITissue-specific epigenetic plasticity maps reveal candidate meQTLs, C_LIO_LIData sharing and interactive portal enable broad reuse for hypothesis generation and exploration C_LI

systems biology↗

bioRxiv2025

Dissecting ARL15 Function in Rheumatoid Arthritis: Insights from Ex Vivo and In Vitro Synovial Fibroblast Models

ARL15, coding for a small GTPase was identified as a non-HLA susceptibility gene in rheumatoid arthritis (RA) through a GWAS in a North Indian cohort. Serum adiponectin and ARL15 levels were higher in RA patients with the associated genotype. The present study aimed to delineate the functional role of ARL15 in RA pathobiology using gene knockdown (KD) combined with transcriptomic profiling in both ex-vivo RA synovial fibroblasts (RASF) and in vitro MH7A cell lines. In RASF, ARL15 KD led to the downregulation of COMP-an extracellular matrix stabilizer linked to severe RA-alongside upregulation of adiponectin and IFN response genes such as IFI6 and USP18. Furthermore, upregulation of NPTX1 and MX1, previously associated with disease modulation and treatment response was observed. Downregulation of CTGF, CD248, and PTX3 suggested involvement of ARL15 in inflammation and RA-associated cardiovascular risk. In contrast, ARL15 KD in MH7A cells displayed distinct gene signatures with upregulated cytokines (IL1A, IL8, CXCLs) and downregulated inflammatory regulators (DOCK2, TLR4, TGFB2), reflecting an inflammatory bias distinct from the patient-derived RASF. This divergence highlights the limitations of immortalized cell models in capturing patient heterogeneity and disease complexity. However, the dual-system approach underscores the multifaceted role of ARL15 in regulating connective tissue architecture, inflammation, and immune response. These key findings position ARL15 as a promising therapeutic target, warranting further investigation in RA animal models and genomic medicine. Taken together, this work provides a compelling rationale to pursue ARL15 targeted interventions in RA management.

immunology↗

bioRxiv2025

An efficient protocol to derive primordial germ cell like cells in vitro from murine embryonic stem cells.

Primordial germ cells (PGCs) are the precursors of germ cells, specified from a subset of epiblast stem cells at the post-implantation stage of mammalian embryonic development. Over the past decade, primordial germ cell-like cells (PGCLCs) have been successfully derived in vitro from mouse and human embryonic stem cells (ESCs). These PGCLCs can further differentiate into mature sperm upon transplantation into neonatal testes. Such advancements offer promising strategies to address male infertility, which affects approximately 15% of couples worldwide. The discovery of induced pluripotent stem cells (iPSCs), which possess similar potential to ESCs, further raises hope for patient-specific therapeutic interventions. However, a major challenge remains: the low efficiency of in vitro PGCLC differentiation. To overcome this, we developed an optimized PGCLC differentiation strategy using a Dppa3-mCherry knock-in reporter mouse ESC line, TDM11. By testing various culture conditions, we identified ascorbic acid as a potent inducer of PGCLC differentiation from ESCs, providing a potential avenue for enhancing in vitro germ cell derivation.

developmental biology↗

bioRxiv2024

Structural and antigenic characterization of novel and diverse Henipavirus glycoproteins

Henipaviruses, a genus within the Paramyxoviridae family, include the highly virulent Nipah and Hendra viruses that cause reoccurring outbreaks of deadly disease. Recent discoveries of several new Paramyxoviridae species, including the zoonotic Langya virus, have revealed much higher antigenic diversity than currently characterized and prompted the reorganization of these viruses into the Henipavirus and Parahenipavirus genera. Here, to explore the limits of structural and antigenic variation in both genera, collectively referred to here as HNVs, we constructed an expanded, antigenically diverse panel of HNV fusion and attachment glycoproteins from 56 unique HNV strains that better reflects global HNV diversity. We expressed and purified the fusion protein ectodomains and the attachment protein head domains and studied their biochemical, biophysical and structural properties. We performed immunization experiments in mice leading to the elicitation of antibodies reactive to multiple HNV fusion proteins. Cryo-electron microscopy structures of diverse fusion proteins elucidated molecular determinants of differential pre-fusion state metastability and higher order contacts. A crystal structure of the Gamak virus attachment head domain revealed an additional domain appended to the conserved 6-bladed, {beta}-propeller fold. Taken together, these studies expand the known structural and antigenic limits of the HNVs, reveal new cross-reactive epitopes within both genera and provide foundational data for the development of broadly reactive countermeasures.

biochemistry↗

bioRxiv2024

A whole-animal phenotypic drug screen identifies suppressors of atherogenic lipoproteins.

Lipoproteins are essential for lipid transport in all bilaterians. A single Apolipoprotein B (ApoB) molecule is the inseparable structural scaffold of each ApoB-containing lipoprotein (B-lps), which are responsible for transporting lipids to peripheral tissues. The cellular mechanisms that regulate ApoB and B-lp production, secretion, transport, and degradation remain to be fully defined. In humans, elevated levels of vascular B-lps play a causative role in cardiovascular disease. Previously, we have detailed that human B-lp biology is remarkably conserved in the zebrafish using an in vivo chemiluminescent reporter of ApoB (LipoGlo) that does not disrupt ApoB function. Thus, the LipoGlo model is an ideal system for identifying novel mechanisms of ApoB modulation and, due to the ability of zebrafish to generate many progeny, is particularly amenable to large-scale phenotypic drug screening. Here, we report a screen of roughly 3000 compounds that identified 49 unique ApoB-lowering hits. Nineteen hits passed orthogonal screening criteria and seven were subjected to extensive phenotyping. A licorice root component, enoxolone, significantly lowered B-lps only in animals that express a functional allele of the nuclear hormone receptor Hepatocyte Nuclear Factor 4 (HNF4). Consistent with this result, inhibitors of HNF4 also reduce B-lp levels. These data demonstrate that mechanism(s) of action can be rapidly determined from a whole animal zebrafish phenotypic screen. Given the well documented role of HNF4 in human B-lp biology, these data validate the LipoGlo screening platform for identifying small molecule modulators of B-lps that play a critical role in a leading cause of worldwide mortality.

physiology↗

bioRxiv2023

Intranasal CRMP2-Ubc9 Inhibitor Regulates NaV1.7 to Alleviate Trigeminal Neuropathic Pain

Dysregulation of voltage-gated sodium NaV1.7 channels in sensory neurons contributes to chronic pain conditions, including trigeminal neuropathic pain. We previously reported that chronic pain results in part from increased SUMOylation of collapsin response mediator protein 2 (CRMP2), leading to an increased CRMP2/NaV1.7 interaction and increased functional activity of NaV1.7. Targeting this feed-forward regulation, we developed compound 194, which inhibits CRMP2 SUMOylation mediated by the SUMO-conjugating enzyme Ubc9. We further demonstrated that 194 effectively reduces the functional activity of NaV1.7 channels in dorsal root ganglia neurons and alleviated inflammatory and neuropathic pain. Here, we employed a comprehensive array of investigative approaches, encompassing biochemical, pharmacological, genetic, electrophysiological, and behavioral analyses, to assess the functional implications of NaV1.7 regulation by CRMP2 in trigeminal ganglia (TG) neurons. We confirmed the expression of Scn9a, Dpysl2, and UBE2I within TG neurons. Furthermore, we found an interaction between CRMP2 and NaV1.7, with CRMP2 being SUMOylated in these sensory ganglia. Disrupting CRMP2 SUMOylation with compound 194 uncoupled the CRMP2/NaV1.7 interaction, impeded NaV1.7 diffusion on the plasma membrane, and subsequently diminished NaV1.7 activity. Compound 194 also led to a reduction in TG neuron excitability. Finally, when intranasally administered to rats with chronic constriction injury of the infraorbital nerve (CCI-ION), 194 significantly decreased nociceptive behaviors. Collectively, our findings underscore the critical role of CRMP2 in regulating NaV1.7 within TG neurons, emphasizing the importance of this indirect modulation in trigeminal neuropathic pain.

neuroscience↗

bioRxiv2023

Spatio-temporal evaluation of drought adaptation in wheat revealed NDVI and MTSI as powerful tools for selecting tolerant genotypes

ContextWater stress is fast becoming a major limiting factor for wheat production. Hence, identifying drought tolerant genotypes is critical for sustaining the food supply chain. However, there are no phenotypic markers or statistical models available that may be employed for the efficient selection of field grown drought tolerant wheat genotypes. ObjectivesWe evaluated wheat genotypes to (1) identify novel sources of drought tolerance (2) understand underlying adaptation mechanisms of drought tolerance (3) identify phenotypic markers and a stable model for the selection of drought tolerant genotypes MethodsOne hundred ninety-six diverse wheat genotypes were evaluated at three different locations in India: Banaras Hindu University (BHU), Varanasi (E1 and E3: control; E2 and E4: drought); Agharkar Research Institute (ARI), Pune (E5 and E7: control; E6 and E8: drought) and Borlaug Institute for South Asia (BISA), Jabalpur (E9 and E11: control; E10 and E12: drought) for various agronomic, physiological and yield traits for two consecutive years. Drought was imposed at the heading stage (Z59) by withholding irrigation for four weeks until the moisture reading reached <45% than the control (100%). ResultsThe performance of all genotypes significantly declined under drought at all the locations. Normalized difference vegetation index (NDVI) significantly correlated (r = 0.41** and 0.36**) with the grain yield under drought during maturity. At the same time, there was no association under control conditions (r = 0.07 and 0.10) at the BHU center during 2020-21 and 2021-22, respectively. Stress indices, such as geometric mean productivity (GMP) and stress tolerance index (STI), showed a high correlation (r= 0.89** and r = 0.88**, respectively) with the grain yield under drought and were effective in differentiating drought tolerant genotypes. GGE bi-plots discriminated the environments (observed obtuse angle between E3 with E6 and E9, E4 with E6 and E9) having negative relation and cross-over interaction for grain yield. Further, the multi-trait stability index (MTSI) identified 29 stable genotypes across all environments and was predicted as the most accurate model due to its fewer Root Mean Square Prediction Difference (RMSPD) values. ConclusionNDVI is a useful high throughput screening tool under drought and MTSI is an effective method for selecting stable wheat genotypes across different water stressed locations. ImplicationsThe identified tools (NDVI), method (MTSI), and tolerant genotypes appear to be valuable resources that together will be useful in the ongoing breeding programs to enhance the drought tolerance of wheat. HighlightsO_LIDrought stress significantly reduces wheat production globally. C_LIO_LINDVI serves as a useful tool for high throughput screening under drought for field-based experiments. C_LIO_LIAMMI, GGE, WAASBY and MTSI plots are effective in detecting GEI effects. C_LIO_LIMTSI is a reliable tool for selecting stable and high mean performers. C_LI

plant biology↗

bioRxiv2022

Single and multi-analyte deep learning-based analysis framework for class prediction in biological images

Measurement of biological analytes, characterizing flavor in fruits, is a cumbersome, expensive and time-consuming process. Fruits with higher concentration of analytes have greater commercial or nutritional values. Here, we tested a deep learning-based framework with fruit images to predict the class (sweet or sour and high or low) of analytes using images from two types of trees in a single and multi-analyte mode. We used fruit images from kinnow (n = 3,451), an edible hybrid mandarin and neem (n = 1,045), a tree with agrochemical and pharmaceutical properties. We measured sweetness in kinnows and five secondary metabolites in neem fruits (azadirachtin or A, deacetyl-salannin or D, salannin or S, nimbin or N and nimbolide or E) using a refractometer and high-performance liquid chromatography, respectively. We trained the models for 300 epochs, before and after hyper-parameters evolution, using 300 generations with 50 epochs/generation, estimated the best models and evaluated their performance on 10% of independent images. The validation F1score and test accuracies were 0.79 and 0.77, and 82.55% and 60.8%, respectively for kinnow and neem A analyte. A multi-analyte model enhanced the neem A models prediction to high class when the D:N:Ss combined class predictions were high:low:high and to low class when D:Ns combined class predictions were low:high respectively. The test accuracy increased further to ~70% with a 10-fold cross-validation error of 0.257 across ten randomly split train:validation:test sets proving the potential of a multi-analyte model to enhance the prediction accuracy, especially when the numbers of images are limiting.

plant biology↗

bioRxiv2022

TEX13B is important for germ cell development and male fertility

The recent epidemiological studies suggest that nearly one out of every 7 reproductive age couples face problem to conceive a child after trying for at least one year. Impaired fertility of the male partner is causative in approximately 50% of the infertile couples. However, the etiologies of large proportion of male infertility are still unclear. Our unpublished exome sequencing data identified several novel genes including TEX13B, which motivated us to further explore the role of TEX13B in male infertility in large infertile case control cohort. Hence in this study, we have examined the role of TEX13B in male infertility by whole gene sequencing 628 infertile and 427 control men and have demonstrated the functional role of Tex13b in spermatogonia GC1spg (GC1) cells. We identified 2 variants on TEX13B which are tightly associated with male infertility. TEX13B gene exclusively expressed in germ cells, but its molecular functions in germ cells are still unknown. Hence, we demonstrated the functional importance of Tex13b in GC1 cell line by genomic manipulation via CRISPR-Cas9 and mass spectrometry-based whole cell proteomics. The gene knock out in GC1 cell line clearly shows that Tex13b play an important role in germ cell growth and morphology. We demonstrate that Tex13b knockout or conditional overexpression in GC1 cells reprograms the metabolic status from an oxidative phosphorylation to glycolysis state and vice versa. In conclusion, our study clearly showed the importance of Tex13b in germ cells development and Its association with male infertility.

genetics↗

bioRxiv2021

Physical localization of 45S rDNA in Cymbopogon and the analysis of differential distribution of rDNA in homologous chromosomes of Cymbopogon winterianus.

Cymbopogon, commonly known as lemon grass, is one of the most important aromatic grasses having therapeutic and medicinal values. FISH signals on somatic chromosome spreads off Cymbopogon species indicated the localization of 45S rDNA on the terminal region of short arms of a chromosome pair. A considerable interspecific variation in the intensity of 45S rDNA hybridization signals was observed in the cultivars of Cymbopogon winterianus and Cymbopogon flexuosus. Furthermore, in all the varieties of Cymbopogon winterianus namely Bio-13, Manjari and Medini, a differential distribution of 45S rDNA was observed in a heterologous pair of chromosome 1. The development of Cymbopogon winterianus var. Manjari through gamma radiation may be responsible for breakage of fragile rDNA site from one of the chromosomes of this heterologous chromosome pair. While, in other two varieties of Cymbopogon winterianus (Bio-13 and Medini), this variability may be because of evolutionary speciation due to natural cross among two species of Cymbopogon which was fixed through clonal propagation. However, in both the situations these changes were fixed by vegetative method of propagation which is general mode of reproduction in the case of Cymbopogon winterianus.

genetics↗