Biology subjects

Jadhav, A.

Publications and source records attributed to Jadhav, A..

11 recordsLinked to original sources

bioRxiv2026

Development of Shelf-Stable Reagents and Assay Kits for Bioluminescence Applications using the Capillary-Assisted Vitrification Platform Stabilization Technology

Luminescence is a powerful method for detecting trace analytes and monitoring biological processes. However, most bioluminescence reagents, including luciferase and its substrates, are sensitive to temperature, limiting their useable shelf lives, and resulting in inconsistent performance. Enhancing the stability of these reagents could improve data quality, simplify workflows, and address cold chain storage issues. In this study, we demonstrate the application of the platform stabilization technology, capillary-assisted vitrification (CAV), as a tool to stabilize different luciferases and their substrates, and the application of the stabilized reagents in both in vitro and in vivo bioluminescent assays. We demonstrate that CAV-stabilized reagents can be stored and shipped ambiently, maintain consistent performance over time, and are suitable for use in cell viability quantification, tumor monitoring, in vivo imaging, microbial detection, and immunoassays. Additionally, different reagents can be co-formulated to make ready-to-use assay kits that can also be shipped and stored ambiently. Our results demonstrate that CAV stabilization is a viable alternative to traditional storage methods, with broad potential to improve bioluminescence workflows.

biochemistry↗

bioRxiv2026

A minimal thermodynamic theory for re-entrant liquid-liquid phase separation regulated by small molecules

Small molecules regulate biomolecular condensates in a biphasic manner, promoting liquid-liquid phase separation (LLPS) at low concentrations while suppressing it at higher concentrations. Despite increasing experimental evidence for such re-entrant behavior, a unified physical description remains lacking. Here, we identify a minimal thermodynamic mechanism for re-entrant LLPS by coupling Cahn-Hilliard dynamics to a concentration-dependent Flory interaction parameter containing competing LLPS-promoting and inhibitory contributions. The resulting model reproduces experimentally observed nonmonotonic condensate formation in Tau-tannic acid and TDP-43-bis-ANS systems, including the concentration-dependent emergence and dissolution of protein-rich domains. Spinodal analysis reveals finite concentration windows for phase instability and demonstrates that re-entrant mixing is encoded directly in the free-energy landscape. The framework further captures morphology transitions and diffusive coarsening within the phase-separated regime. These results establish a general mesoscale description of chemically regulated condensates and provide design principles for controlling phase separation through small-molecule modulators.

biophysics↗

bioRxiv2025

Joint representation of spliced and unspliced RNA expands information content in single-cell expression data

MotivationSingle-cell RNA-seq captures both mature (spliced) and nascent (unspliced) transcripts, yet standard preprocessing typically collapses these signals into a single expression matrix, obscuring recoverable transcriptional structure and introducing splicing-dependent artifacts in downstream embeddings in foundation models. We asked whether treating spliced and unspliced counts as distinct feature sets increases recoverable latent structure in unsupervised dimension reduction. ResultsAcross four datasets with paired spliced and unspliced count layers, we applied non-negative matrix factorization (NMF) to spliced-only, unspliced-only, summed, and concatenated representations. Using cross-validation, we estimated the revealable rank k* (largest stable rank achieving near-optimal held-out error). In all datasets, concatenated representations consistently supported higher k* than spliced-only or unspliced-only inputs and typically exceeded the summed representation, indicating that preserving splicing status exposes additional stable latent programs. Minimal overlap between spliced- and unspliced-derived factors corresponded to modality-specific gene set enrichment patterns consistent with complementary steady-state and nascent regulatory activity. These results establish splicing status as an informative axis of variation and motivate preserving spliced and unspliced layers as first-class features to maximize information recovery in single-cell analysis. Availability and ImplementationThe singlet R package is available at github.com/zdebruine/singlet. Code to reproduce all figures is available at github.com/Arya-86/nmf-spliced-unspliced. Supplementary informationSupplementary data are appended to this manuscript.

bioinformatics↗

bioRxiv2021

Integrated Omics Analysis Reveals Sirtuin Signaling is Central to Hepatic Response to a High Fructose Diet

BackgroundDietary high fructose (HFr) is a known metabolic disruptor contributing to development of obesity and diabetes in Western societies. Initial molecular changes from exposure to HFr on liver metabolism may be essential to understand the perturbations leading to insulin resistance and abnormalities in lipid and carbohydrate metabolism. We studied vervet monkeys (Clorocebus aethiops sabaeus) fed a HFr (n=5) or chow diet (n=5) for 6 weeks, and obtained clinical measures of liver function, blood insulin, cholesterol and triglycerides. In addition, we performed untargeted global transcriptomics, proteomics, and metabolomics analyses on liver biopsies to determine the molecular impact of a HFr diet on coordinated pathways and networks that differed by diet. ResultsWe show that integration of omics data sets improved statistical significance for some pathways and networks, and decreased significance for others, suggesting that multiple omics datasets enhance confidence in relevant pathway and network identification. Specifically, we found that sirtuin signaling and a peroxisome proliferator activated receptor alpha (PPARA) regulatory network were significantly altered in hepatic response to HFr. Integration of metabolomics and miRNAs data further strengthened our findings. ConclusionsOur integrated analysis of three types of omics data with pathway and regulatory network analysis demonstrates the usefulness of this approach for discovery of molecular networks central to a biological response. In addition, metabolites aspartic acid and docosahexaenoic acid (DHA), protein ATG3, and genes ATG7, HMGCS2 link sirtuin signaling and the PPARA network suggesting molecular mechanisms for altered hepatic gluconeogenesis from consumption of a HFr diet.

systems biology↗

bioRxiv2021

Predicting cross-tissue hormone-gene relations usingbalanced word embeddings

MotivationLarge volumes of biomedical literature present an opportunity to build whole-body human models comprising both within-tissue and across-tissue interactions among genes. Current studies have mostly focused on identifying within-tissue or tissue-agnostic associations, with a heavy emphasis on associations among disease, genes and drugs. Literature mining studies that extract relations pertaining to inter-tissue communication, such as between genes and hormones, are solely missing. ResultsWe present here a first study to identify from literature the genes involved in inter-tissue signaling via a hormone in the human body. Our models BioEmbedS and BioEmbedS-TS respectively predict if a hormone-gene pair is associated or not, and whether an associated gene is involved in the hormones production or response. Our models are classifiers trained on word embeddings that we had carefully balanced across different strata of the training data such as across production vs. response genes of a hormone (or) well-studied vs. poorly-represented hormones in the literature. Model training and evaluation are enabled by a unified dataset called HGv1 of ground-truth associations between genes and known endocrine hormones that we had compiled. Our models not only recapitulate known gene mediators of tissue-tissue signaling (e.g., at average 70.4% accuracy for BioEmbedS), but also predicts novel genes involved in inter-tissue communication in humans. Furthermore, the species-agnostic nature of our ground-truth HGv1 data and our predictive modeling approach, demonstrated concretely using human data and generalized to mouse, hold much promise for future work on elucidating inter-tissue signaling in other multi-cellular organisms. AvailabilityProposed HGv1 dataset along with our models predictions, and the associated code to reproduce this work are available respectively at https://cross-tissue-signaling.herokuapp.com/, and https://github.com/BIRDSgroup/BioEmbedS. Contactnmanik@cse.iitm.ac.in

bioinformatics↗

bioRxiv2019

Identification of activators of human fumarate hydratase by quantitative high-throughput screening

Fumarate hydratase (FH) is a metabolic enzyme that is part of the Krebs-cycle, and reversibly catalyzes the hydration of fumarate to malate. Mutations of the FH gene have been associated with fumarate hydratase deficiency (FHD), hereditary leiomyomatosis, renal cell cancer (HLRCC), and other diseases. Currently there are no high-quality small molecule probes for studying human fumarate hydratase. To address this, we developed a quantitative high throughput screening (qHTS) FH assay and screened a total of 57,037 compounds from in-house libraries in dose-response. While no inhibitors of FH were confirmed, a series of phenyl-pyrrolo-pyrimidine-diones were identified as activators of human fumarate hydratase. These compounds were not substrates of fumarate hydratase, were inactive in a malate dehydrogenase counter screen, and showed no detectable reduction-oxidation activity. The binding of two compounds from the series to human fumarate hydratase was confirmed by microscale thermophoresis. The low hit rate in this screening campaign confirmed that FH is a tough target to modulate, and the small molecule activators of human fumarate hydratase reported here may serve as a starting point for further optimization and development into cellular probes of human FH and potential drug candidates.

biochemistry↗

bioRxiv2018

Molecular basis for activation of lecithin:cholesterol acyltransferase by a compound that increases HDL cholesterol

Lecithin:cholesterol acyltransferase (LCAT) and LCAT-activating small molecules are being investigated as treatments for coronary heart disease (CHD) and familial LCAT deficiency (FLD). Herein we report the crystal structure of LCAT bound to a potent activator and an acyl intermediate-like inhibitor, thereby revealing an active conformation of LCAT and that the activator is bound exclusively to its membrane-binding domain (MBD). Functional studies indicate that the compound does not modulate the affinity of LCAT for HDL, but instead stabilizes residues in the MBD and likely facilitates channeling of substrates into the active site. By demonstrating that these activators increase the activity of an FLD variant, we show that compounds targeting the MBD have therapeutic potential. In addition, our data better define the acyl binding site of LCAT and pave the way for rational design of LCAT agonists and improved biotherapeutics for augmenting or restoring reverse cholesterol transport in CHD and FLD patients.

biochemistry↗

bioRxiv2018

CDK19 is a Regulator of Triple-Negative Breast Cancer Growth

Triple-negative breast cancer (TNBC) is a poor prognosis disease with no clinically approved targeted therapies. Here, using in vitro and in vivo RNA interference (RNAi) screens in TNBC patient-derived xenografts (PDX), we identify cyclin dependent kinase 19 (CDK19) as a potential therapeutic target. Using in vitro and in vivo TNBC PDX models, we validated the inhibitory effect of CDK19 knockdown on tumor initiation, proliferation and metastases. Despite this, CDK19 knockdown did not affect the growth of non-transformed mammary epithelial cells. Using CD10 and EpCAM as novel tumor initiating cell (TIC) markers, we found the EpCAMmed/high/CD10-/low TIC sub-population to be enriched in CDK19 and a putative cellular target of CDK19 inhibition. Comparative gene expression analysis of CDK19 and CDK8 knockdowns revealed that CDK19 regulates a number of cancer-relevant pathways, uniquely through its own action and others in common with CDK8. Furthermore, although it is known that CDK19 can act at enhancers, our CHIP-Seq studies showed that CDK19 can also epigenetically modulate specific H3K27Ac enhancer signals which correlate with gene expression changes. Finally, to assess the potential therapeutic utility of CDK19, we showed that both CDK19 knockdown and chemical inhibition of CDK19 kinase activity impaired the growth of pre-established PDX tumors in vivo. Current strategies inhibiting transcriptional co-factors and targeting TICs have been limited by toxicity to normal cells. Because of CDK19s limited tissue distribution and the viability of CDK19 knockout mice, CDK19 represents a promising therapeutic target for TNBC.

cancer biology↗

bioRxiv2017

Small Molecule Inhibitors of the Human Histone Lysine Methyltransferase NSD2 / WHSC1 / MMSET Identified from a Quantitative High-Throughput Screen with Nucleosome Substrate

The activity of the histone lysine methyltransferase NSD2 is thought to play a driving role in oncogenesis. Both overexpression of NSD2 and point mutations that increase its catalytic activity are associated with a variety of human cancers. While NSD2 is an attractive therapeutic target, no potent, selective and cell-active inhibitors have been reported to date, possibly due to the challenging nature of developing high-throughput assays for NSD2. To establish a platform for the discovery and development of selective NSD2 inhibitors, multiple assays were optimized and implemented. Quantitative high-throughput screening was performed with full-length wild-type NSD2 and a nucleosome substrate against a diverse collection of known bioactives comprising 16,251 compounds. Actives from the primary screen were further interrogated with orthogonal and counter assays, as well as activity assays with the clinically relevant NSD2 mutants E1099K and T1150A. Five confirmed inhibitors were selected for follow-up, which included a radiolabeled validation assay, surface plasmon resonance studies, methyltransferase profiling, and histone methylation in cells. The identification of NSD2 inhibitors that bind the catalytic SET domain and demonstrate activity in cells validates the workflow, providing a template for identifying selective NSD2 inhibitors.

cancer biology↗

bioRxiv2017

Chemical control of a CRISPR-Cas9 acetyltransferase

Lysine acetyltransferases (KATs) play a critical role in the regulation of transcription and other genomic functions. However, a persistent challenge is the development of assays capable of defining KAT activity directly in living cells. Towards this goal, here we report the application of a previously reported dCas9-p300 fusion as a transcriptional reporter of KAT activity. First we benchmark the activity of dCas9-p300 relative to other dCas9-based transcriptional activators, and demonstrate its compatibility with second generation short guide RNA architectures. Next, we repurpose this technology to rapidly identify small molecule inhibitors of acetylation-dependent gene expression. These studies validate a recently reported p300 inhibitor chemotype, and reveal a role for p300s bromodomain in dCas9-p300-mediated transcriptional activation. Comparison with other CRISPR-Cas9 transcriptional activators highlights the inherent ligand tuneable nature of dCas9-p300 fusions, suggesting new opportunities for orthogonal gene expression control. Overall, our studies highlight dCas9-p300 as a powerful tool for studying gene expression mechanisms in which acetylation plays a causal role, and provide a foundation for future applications requiring spatiotemporal control over acetylation at specific genomic loci.

biochemistry↗

bioRxiv2017

Assessing Inhibitors Of Mutant Isocitrate Dehydrogenase Using A Suite Of Pre-Clinical Discovery Assays

Isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2) are key metabolic enzymes that are mutated in a variety of cancers to confer a gain-of-function activity resulting in the accumulation and secretion of an oncometabolite, D-2-hydroxyglutarate (2-HG). Accumulation of 2-HG can result in epigenetic dysregulation and a block in cellular differentiation, suggesting these mutations play a role in neoplasia. Based on its potential as a cancer target, a number of small molecule inhibitors have been developed to specifically inhibit mutant forms of IDH (mIDH1 and mIDH2). Here, a panel of mIDH inhibitors were systematically profiled using biochemical, cell-based, and tier-one ADME techniques. We quantified the biochemical effect of each inhibitor on mIDH1 (R132H and R132C) and mIDH2 (R172Q). The effect of these inhibitors on 2-HG concentrations in seven cell lines representing five different IDH1 mutations in both 2D and 3D cell cultures was assessed. Target engagement of these inhibitors was analyzed utilizing cellular thermal shift assays (CETSA), the effects of inhibitors on reversing 2-HG-induced block on leukemic cellular differentiation. We conclude from our mIDH1 assay panel that AG-120 and a Novartis inhibitor exhibited excellent activity in all biochemical and most cellular assays. While AG-120 has superior DMPK properties, it lacks efficacy a leukemic differentiation model. In conclusion, we present a comprehensive suite of in vitro preclinical drug development assays that can be used as a tool-box to identify lead compounds for mIDH drug discovery programs, as well as what we believe is the most comprehensive publically available dataset on the top mIDH inhibitors.

cancer biology↗