Biology subjects

Mehta, S.

Publications and source records attributed to Mehta, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

In-Silico Characterization of TP53 Splice Mutations in Somatic and Germline Tumours

TP53 undergoes alternative splicing to produce multiple mRNA transcripts and protein isoforms, yet the effects of splice site mutations on isoform regulation, tumor-biology, and clinical outcome remain unclear. Analysis of 23,017 TP53 variants, including 18,562 somatic mutations (pan-cancer datasets - cBioPortal) and 4,455 germline variants (IARC database), identified recurrent donor (X32, X125, X224, X261, X331) and acceptor (X33, X126, X187, X225, X307, X332) splice site mutations. Germline variants showed nucleotide-specific transition biases. Most splice site mutations were associated with reduced TP53 mRNA expression; however, X32, X33, X126, and X261 maintained or elevated transcript levels. Splice mutations were associated with distinct transcriptional subsets marked by altered p53 target gene expression, elevated tumor mutation burden, increased genomic instability, and significantly reduced disease-free survival compared to missense mutations, with X126 and X331 being associated with poorest outcomes. These findings emphasize the clinical impact of TP53 splice site mutations and the need for functional classification.

cancer biology↗

bioRxiv2025

Benchmarking Spectral Library and Database Search Approaches for Metaproteomics Using a Ground-Truth Microbiome Dataset

Mass spectrometry-based metaproteomics, the identification and quantification of thousands of proteins expressed by complex microbial communities, has become pivotal for unraveling functional interactions within microbiomes. However, metaproteomics data analysis encounters many challenges, including the search of tandem mass spectra against a protein sequence database using proteomics database search algorithms. We used a ground-truth dataset to assess a spectral library searching method against established database searching approaches. Mass spectrometry data collected by data-dependent acquisition (DDA-MS) was analyzed using database searching approaches (MaxQuant and FragPipe), as well as using Scribe with Prosit predicted spectral libraries. We used FASTA databases that included protein sequences from microbial species present in the ground-truth dataset along with background protein sequences, to estimate error rates and assess the effects on detection, peptide-spectral match quality, and quantification. Using the Scribe search engine resulted in more proteins detected at a 1% false discovery rate (FDR) compared to MaxQuant or FragPipe, while FragPipe detected more peptides verified by PepQuery. Scribe was able to detect more low-abundance proteins in the microbiome dataset and was more accurate in quantifying the microbial community composition. This research provides insights and guidance for metaproteomics researchers aiming to optimize results in their analysis of DDA-MS data.

bioinformatics↗

bioRxiv2025

Acute session of three endurance exercise intensities alters subcutaneous adipose tissue transcriptome in regular exercisers

The primary aim of this study was to compare the acute effects of three exercise intensities on abdominal subcutaneous adipose tissue (aSAT) transcriptome in regular exercisers. A total of 45 adults who exercise regularly were assigned to perform a single session of either low-intensity continuous (LOW; 60min at 30% VO2max; n=15), moderate-intensity continuous (MOD; 45min at 65% VO2max; n=15), or high-intensity interval exercise (HIGH; 10x1min at 90% VO2max interspersed with 1min active recovery; n=15). aSAT biopsy samples were collected before and 1.5hours after the exercise session for bulk RNA sequencing and targeted protein immunoassays. HIGH upregulated genes involved in cytokine secretion, insulin signaling, and proteolysis while MOD and LOW upregulated genes regulating ECM remodeling, ribosome biogenesis, and oxidative phosphorylation pathways. Exercise-induced changes in aSAT angiogenic, MAPK cascade, and clock genes, ERK protein phosphorylation, and circulating cytokines were similar after all three exercise treatments. Network analysis identified exercise-responsive gene clusters linked to cardiometabolic health traits. Cell-type analysis highlighted a heterogeneous response of aSAT cell types to exercise, with distinct patterns observed across exercise intensities. Collectively, our data characterizes early responses in aSAT after a single session of exercise. Because adaptations to exercise training stem from an accrual of responses after each session of exercise, these early responses to exercise are likely important contributors to the long-term structural and functional changes that occur in adipose tissue in response to exercise training.

physiology↗

bioRxiv2025

A modular, Galaxy-based immunopeptidogenomic (iPepGen) analysis pipeline for discovery, verification, and prioritization of candidate cancer neoantigen peptides

Characterizing tumor-specific neoantigen peptides, derived from genomic or transcriptomic aberrations and presented to the immune system, is critical for immuno-oncology studies. To this end, the modular iPepGen immunopeptidogenomics pipeline provides these functions: (1) Neoantigen prediction and protein database generation from genomic or transcriptomic sequencing data; (2) Peptide identification (3) Verification from immunopeptidomic mass spectral data; (4) Neoantigen classification and visualization; (5) Candidate prioritization for further study. Easy access via a publicly available, scalable cloud-based gateway coupled with online, interactive training materials streamlines the adoption by cancer researchers who require immunopeptidogenomic analysis tools but lack advanced computational expertise and resources.

bioinformatics↗

bioRxiv2024

microGalaxy: A gateway to tools, workflows, and training for reproducible and FAIR analysis of microbial data

The explosion of microbial omics data has outpaced the ability of many researchers to analyze it, with complex tools and limited computational resources creating barriers to discovery. To address this gap, we present the Microbiology Galaxy Lab: a free, globally accessible, community-supported platform that combines state-of-the-art analytical power with user-friendly accessibility. Supported by the Galaxy and global microbiology communities, this platform integrates over 315 tool suites and 115 curated workflows, enabling comprehensive metabarcoding, (meta)genomic, (meta)transcriptomic, and (meta)proteomic data analysis within a FAIR-aligned environment. It also supports research in the health and infectious disease sectors, as well as in environmental microbiology. The platforms utility is exemplified through various use cases, including antimicrobial resistance tracking, biomarker prediction, microbiome classification, and functional annotation of key microbes. Built on reproducibility and community engagement, it supports creation, sharing, and updating of best-practice workflows. Over 35 tutorials and learning paths empower scientists, fostering an ecosystem that keeps resources at the forefront of microbial science. The Microbiology Galaxy Lab enables collective analysis, democratising research, thereby accelerating discovery across the global microbiology community (microbiology.usegalaxy.org, microbiology.usegalaxy.eu, microbiology.usegalaxy.org.au, microbiology.usegalaxy.fr).

bioinformatics↗

bioRxiv2024

Testing the Tests: Using Connectome-Based Predictive Models to Reveal the Systems Standardized Tests and Clinical Symptoms Are Reflecting

BackgroundSubstantial strides have been made in developing connectome-based predictive models that establish connections between external measures of cognition and/or symptoms obtained through testing performed in a clinical setting, and the human functional connectome. Often referred to as brain-behavior modeling such models offer insights into the functional brain organization supporting the test scores of these external measures1-7. Here, we depart from the conventional feed-forward approach and introduce a feed-back approach that provides new insight into the systems the external measures are reflecting and provides a framework for developing new test instruments that better target specific brain systems. MethodsIn fMRI data from 227 demographically and clinically diverse subjects (healthy participants and patients), we a priori define connectivity networks for the six cognitive constructs and employ kernel ridge regression in a predictive modeling framework to quantify each networks contribution to performance across a spectrum of standardized tests. ResultsThis approach provides a ranking of test scores according to the predictive power of each cognitive network, allowing one to choose the best test to probe a specific brain network. It yields a brain-driven process for forming new tests through selection of combinations of measures that probe the same brain systems. These new composite tests yield better external measures, as reflected by higher predictive power in brain-behavior modeling. We also evaluate the inclusion of specific subtests within a composite score, revealing instances where composite scores are reinforced or weakened by subtest inclusion regarding the specificity of the brain network they interrogate. ConclusionsThe brain-behavior modeling problem can be reconfigured to provide a biologically driven approach to the selection of external measures directed at specific brain systems. It opens new avenues of research by providing a framework for the development of measures, both cognitive and clinical, guided by quantitative brain metrics.

neuroscience↗

bioRxiv2024

Hyperexcitability precedes CA3 hippocampal neurodegeneration in a dox-regulatable TDP-43 mouse model of ALS-FTD.

Neuronal hyperexcitability is a hallmark of amyotrophic lateral sclerosis (ALS) but its relationship with the TDP-43 aggregates that comprise the predominant pathology in over 90% of ALS cases remains unclear. Emerging evidence in tissue and slice culture models indicate that TDP-43 pathology induces neuronal hyperexcitability suggesting it may be responsible for the excitotoxicity long believed to be a major driver of ALS neuron death. Here, we characterized hyperexcitability and neurodegeneration in the hippocampus of doxycycline-regulatable rNLS8 mice (NEFH-tTA x tetO-hTDP-43{Delta}NLS), followed by treatment with AAV encoded DREADDs and anti-seizure medications to measure the effect on behavioral function and neurodegeneration. We found that approximately half of the CA3 neurons in the dorsal hippocampus are lost between 4 and 6 weeks after TDP-43{Delta}NLS induction. Neurodegeneration was preceded by selective hyperexcitability in the mossy fiber - CA3 circuit, leading us to hypothesize that glutamate excitotoxicity may be a significant contributor to neurodegeneration in this model. Interestingly, hippocampal injection of AAV encoded inhibitory DREADDs (hM4Di) and daily activation with CNO ligand rescued anxiety deficits on elevated zero maze (EZM) but did not reduce neurodegeneration. Therapeutic doses of the anti-seizure medications, valproic acid and levetiracetam, did not improve behavior or prevent neurodegeneration. These results highlight the complexity of TDP-43 - induced alterations to neuronal excitability and suggest that whereas targeting hyperexcitability can meliorate some behavioral deficits, it may not be sufficient to halt or slow neurodegeneration in TDP-43-related proteinopathies. Significance StatementCytoplasmic aggregates of TAR DNA Binding Protein 43 (TDP-43) are the predominant pathology in over 90% of Amyotrophic lateral sclerosis (ALS) and the majority of frontotemporal lobar degeneration (FTLD-TDP) cases. Understanding how TDP-43 pathology promotes neurodegeneration may lead to therapeutic strategies to slow disease progression in humans. Recent reports in mouse and cell culture models suggest loss-of-normal TDP-43 function may drive neuronal hyperexcitability, a key physiological hallmark of ALS and possible contributor to neurodegeneration. In this study, we identified region-specific hyperexcitability that precedes neurodegeneration in the inducible rNLS8 TDP-43 mouse model. Suppressing hyperexcitability with chemogenetics improved behavioral function but did not reduce hippocampal neuron loss. Anti-seizure medications had no beneficial effects suggesting directly targeting hyperexcitability may not be therapeutically effective.

neuroscience↗

bioRxiv2024

Ultrack: pushing the limits of cell tracking across biological scales

Tracking live cells across 2D, 3D, and multi-channel time-lapse recordings is crucial for understanding tissue-scale biological processes. Despite advancements in imaging technology, achieving accurate cell tracking remains challenging, particularly in complex and crowded tissues where cell segmentation is often ambiguous. We present Ultrack, a versatile and scalable cell-tracking method that tackles this challenge by considering candidate segmentations derived from multiple algorithms and parameter sets. Ultrack employs temporal consistency to select optimal segments, ensuring robust performance even under segmentation uncertainty. We validate our method on diverse datasets, including terabyte-scale developmental time-lapses of zebrafish, fruit fly, and nematode embryos, as well as multi-color and label-free cellular imaging. We show that Ultrack achieves state-of-the-art performance on the Cell Tracking Challenge and demonstrates superior accuracy in tracking densely packed embryonic cells over extended periods. Moreover, we propose an approach to tracking validation via dual-channel sparse labeling that enables high-fidelity ground truth generation, pushing the boundaries of long-term cell tracking assessment. Our method is freely available as a Python package with Fiji and napari plugins and can be deployed in a high-performance computing environment, facilitating widespread adoption by the research community.

developmental biology↗

bioRxiv2024

Toll-Like-Receptor 5 protects against pulmonary fibrosis by reducing lung dysbiosis

Idiopathic pulmonary fibrosis (IPF) is a devastating pulmonary disease with no curative treatment other than lung transplantation. IPF results from maladaptive responses to lung epithelial injury, but the underlying mechanisms remain unclear. Here, we show that deficiency in the innate immune receptor, toll-like receptor 5 (TLR5), is associated with IPF in humans and with increased susceptibility to epithelial injury and experimental fibrosis in mice, while activation of lung epithelial TLR5 through a synthetic flagellin analogue protects from experimental fibrosis. Mechanistically, epithelial TLR5 activation induces antimicrobial gene expression and ameliorates dysbiosis after lung injury. In contrast, TLR5 deficiency in mice and IPF patients is associated with lung dysbiosis. Elimination of the microbiome in mice through antibiotics abolishes the protective effect of TLR5 and reconstitution of the microbiome rescues the observed phenotype. In aggregate, TLR5 deficiency is associated with IPF and dysbiosis in humans and in the murine model of pulmonary fibrosis. Furthermore, TLR5 protects against pulmonary fibrosis in mice and this protection is mediated by effects on the microbiome. One-sentence summaryDeficiency in the innate immune receptor TLR5 is a risk factor for pulmonary fibrosis, because TLR5 prevents microbial dysbiosis after lung injury.

immunology↗

bioRxiv2024

Brain age prediction and deviations from normative trajectories in the neonatal connectome

Structural and functional connectomes undergo rapid changes during the third trimester and the first month of postnatal life. Despite progress, our understanding of the developmental trajectories of the connectome in the perinatal period remains incomplete. Brain age prediction uses machine learning to estimate the brains maturity relative to normative data. The difference between the individuals predicted and chronological age--or brain age gap (BAG)--represents the deviation from these normative trajectories. Here, we assess brain age prediction and BAGs using structural and functional connectomes for infants in the first month of life. We used resting-state fMRI and DTI data from 611 infants (174 preterm; 437 term) from the Developing Human Connectome Project (dHCP) and connectome-based predictive modeling to predict postmenstrual age (PMA). Structural and functional connectomes accurately predicted PMA for term and preterm infants. Predicted ages from each modality were correlated. At the network level, nearly all canonical brain networks--even putatively later developing ones--generated accurate PMA prediction. Additionally, BAGs were associated with perinatal exposures and toddler behavioral outcomes. Overall, our results underscore the importance of normative modeling and deviations from these models during the perinatal period.

neuroscience↗

bioRxiv2024

Extracellular Matrix Instability and Chronic Inflammation Underlie Maladaptive Right Ventricular Pressure Overload Remodeling and Failure in Male Mice

BackgroundRight ventricular dysfunction (RVD) portends increased death risk for heart failure (HF) and pulmonary arterial hypertension (PAH) patients, regardless of left ventricular function or etiology. In both, RVD arises from the chronic RV pressure overload, and represents advanced cardiopulmonary disease. RV remodeling responses and survival rates of HF and PAH patients, however, differ by sex. Men develop more severe RVD and die at younger ages than do women. Mechanistic details of this sexual dimorphism in RV remodeling are incompletely understood. We sought to elucidate the cardiac pathophysiology underlying the sex-specific RV remodeling phenotypes, RV failure (RVF) versus compensated RVD. MethodsWe subjected male (M-) and female (F-) adult mice to moderate pulmonary artery banding (PAB) for 9wks. Mice underwent serial echocardiography, cardiac MRI, RV pressure-volume loop recordings, histologic and molecular analyses. ResultsM-PAB developed severe RVD with RVF, increased RV collagen deposition and degradation, extracellular matrix (ECM) instability, and activation and recruitment of macrophages. Despite the same severity and chronicity of RV pressure overload, F-PAB had more stable ECM, lacked chronic inflammation, and developed mild RVD without RVF. ConclusionsECM destabilization and chronic activation of recruited macrophages are associated with maladaptive RV remodeling and RVF in male PAB mice. Adaptive RV remodeling of female PAB mice lacked these histopathologic changes. Our findings suggest that these two pathophysiologic processes likely contribute to the sexual dimorphism of RV pressure overload remodeling. Further mechanistic studies are needed to assess their pathogenic roles and potential as targets for RVD therapy and RVF prevention. CLINICAL PERSPECTIVE What is new?O_LIIn a mouse model of pure PH, males but not females showed an association between ECM instability, chronic inflammation with activation of recruited macrophages, and severe RV dysfunction and failure. C_LI What are the clinical implications?O_LIIn male HF and PH patients, enhancing ECM stability and countering the recruitment and activation of macrophages may help preserve RV function such that RVF can be prevented or delayed. Further preclinical mechanistic studies are needed to assess the therapeutic potential of such approaches. C_LI RESEARCH PERSPECTIVE What new question does this study raise? What question should be addressed next?O_LIWhat mechanisms regulate RV ECM stability and macrophage recruitment and activation in response to chronic RV pressure overload? Are these regulatory mechanisms dependent upon or independent of sex hormone signaling? C_LI

physiology↗

bioRxiv2024

Sensitive Fluorescent Biosensor Reveals Differential Subcellular Regulation of PKC

The protein kinase C (PKC) family of serine/threonine kinases, which consist of three distinctly regulated subfamilies, have long been established as critical for a variety of cellular functions. However, how PKC enzymes are regulated at different subcellular locations, particularly at emerging signaling hubs such as the ER, lysosome, and Par signaling complexes, is unclear. Here, we present a sensitive Excitation Ratiometric (ExRai) C Kinase Activity Reporter (ExRai-CKAR2) that enables the detection of minute changes in subcellular PKC activity. Using ExRai-CKAR2 in conjunction with an enhanced diacylglycerol (DAG) biosensor capable of detecting intracellular DAG dynamics, we uncover the differential regulation of PKC isoforms at distinct subcellular locations. We find that G-protein coupled receptor (GPCR) stimulation triggers sustained PKC activity at the ER and lysosomes, primarily mediated by Ca2+ sensitive conventional PKC (cPKC) and novel PKC (nPKC), respectively, with nPKC showing high basal activity due to elevated basal DAG levels on lysosome membranes. The high sensitivity of ExRai-CKAR2, targeted to either the cytosol or Par-complexes, further enabled us to detect previously inaccessible endogenous atypical PKC (aPKC) activity in 3D organoids. Taken together, ExRai-CKAR2 is a powerful tool for interrogating PKC regulation in response to physiological stimuli.

bioengineering↗

bioRxiv2024

Light-gated Integrator for Highlighting Kinase Activity in Living Cells

Protein kinases are key signaling nodes that regulate fundamental biological and disease processes. Illuminating kinase signaling from multiple angles can provide deeper insights into disease mechanisms and improve therapeutic targeting. While fluorescent biosensors are powerful tools for visualizing live-cell kinase activity dynamics in real time, new molecular tools are needed that enable recording of transient signaling activities for post hoc analysis and targeted manipulation. Here, we develop a light-gated kinase activity coupled transcriptional integrator (KINACT) that converts dynamic kinase signals into "permanent" fluorescent marks. KINACT enables robust monitoring of kinase activity across scales, accurately recording subcellular PKA activity, highlighting PKA signaling heterogeneity in 3D cultures, and identifying PKA activators and inhibitors in high-throughput screens. We further leverage the ability of KINACT to drive signaling effector expression to allow feedback manipulation of the balance of GsR201C-induced PKA and ERK activation and dissect the mechanisms of oncogenic G protein signaling.

bioengineering↗

bioRxiv2024

Far-red chemigenetic biosensors for multi-dimensional and super-resolved kinase activity imaging

Fluorescent biosensors revolutionized biomedical science by enabling the direct measurement of signaling activities in living cells, yet the current technology is limited in resolution and dimensionality. Here, we introduce highly sensitive chemigenetic kinase activity biosensors that combine the genetically encodable self-labeling protein tag HaloTag7 with bright far-red-emitting synthetic fluorophores. This technology enables five-color biosensor multiplexing, 4D activity imaging, and functional super-resolution imaging via stimulated emission depletion (STED) microscopy.

bioengineering↗

bioRxiv2024

Histone variant H2BE enhances chromatin accessibility in neurons to promote synaptic gene expression and long-term memory

Regulation of histone proteins affects gene expression through multiple mechanisms including exchange with histone variants. However, widely expressed variants of H2B remain elusive. Recent findings link histone variants to neurological disorders, yet few are well studied in the brain. We applied new tools including novel antibodies, biochemical assays, and sequencing approaches to reveal broad expression of the H2B variant H2BE, and defined its role in regulating chromatin structure, neuronal transcription, and mouse behavior. We find that H2BE is enriched at promoters and a single unique amino acid allows it to dramatically enhance chromatin accessibility. Lastly, we show that H2BE is critical for synaptic gene expression and long-term memory. Together, these data reveal a novel mechanism linking histone variants to chromatin regulation, neuronal function, and memory. This work further identifies the first widely expressed H2B variant and uncovers a single histone amino acid with profound effects on genomic structure.

genetics↗

bioRxiv2023

Molecular Determinants and Signaling Effects of PKA RIα Phase Separation

Spatiotemporal regulation of intracellular signaling molecules, such as the 3,5-cyclic adenosine monophosphate (cAMP)-dependent protein kinase (PKA), ensures the specific execution of various cellular functions. Liquid-liquid phase separation (LLPS) of the ubiquitously expressed PKA regulatory subunit RI was recently identified as a major driver of cAMP compartmentation and signaling specificity. However, the molecular determinants of RI LLPS remain unclear. Here, we reveal that two separate dimerization interfaces combined with the cAMP-induced release of the PKA catalytic subunit (PKA-C) from the pseudosubstrate inhibitory sequence are required to drive RI condensate formation in cytosol, which is antagonized by docking to A-kinase anchoring proteins. Strikingly, we find that the RI pseudosubstrate region is critically involved in the formation of a non-canonical R:C complex, which serves to maintain low basal PKA activity in the cytosol by enabling the recruitment of active PKA-C to RI condensates. Our results suggest that RI LLPS not only facilitates cAMP compartmentation but also spatially restrains active PKA-C, thus highlighting the functional versatility of biomolecular condensates in driving signaling specificity.

cell biology↗

bioRxiv2023

A novel clinical metaproteomics workflow enables bioinformatic analysis of host-microbe dynamics in disease

Clinical metaproteomics has the potential to offer insights into the host-microbiome interactions underlying diseases. However, the field faces challenges in characterizing microbial proteins found in clinical samples, which are usually present at low abundance relative to the host proteins. As a solution, we have developed an integrated workflow coupling mass spectrometry-based analysis with customized bioinformatic identification, quantification and prioritization of microbial and host proteins, enabling targeted assay development to investigate host-microbe dynamics in disease. The bioinformatics tools are implemented in the Galaxy ecosystem, offering the development and dissemination of complex bioinformatic workflows. The modular workflow integrates MetaNovo (to generate a reduced protein database), SearchGUI/PeptideShaker and MaxQuant (to generate peptide-spectral matches (PSMs) and quantification), PepQuery2 (to verify the quality of PSMs), and Unipept and MSstatsTMT (for taxonomy and functional annotation). We have utilized this workflow in diverse clinical samples, from the characterization of nasopharyngeal swab samples to bronchoalveolar lavage fluid. Here, we demonstrate its effectiveness via analysis of residual fluid from cervical swabs. The complete workflow, including training data and documentation, is available via the Galaxy Training Network, empowering non-expert researchers to utilize these powerful tools in their clinical studies.

bioinformatics↗

bioRxiv2023

Comparative Genomic and Transcriptomic Analysis of Avirulent and Virulent Strains of Fusarium oxysporum f. sp. carthami: Insights into Pathogenesis and Virulence Determinants in Safflower Infections

Vascular wilt disease incited by Fusarium oxysporum f. sp. carthami (Foc) in Safflower poses a significant threat to its production in India. A comprehensive understanding of the molecular underpinning of compatible and incompatible interaction is of extreme economic importance. In the present study, the genome of a virulent (IARI-5175) and a avirulent (F-00845) Foc strain were sequenced and assembled using data generated from Illumina in combination with Nanopore technologies and HiC. Foc genomes were assembled into 88 and 23 scaffolds with an estimated total size of 46 Mb and 42 Mb respectively for IARI-5175 and F-00845 strains. Reference based mapping of Foc genome with F. oxysporum f. sp. lycopersici (Fol) resulted in chromosomal level ordering of genome and simultaneous identification of accessory genome. Additionally, two lineage specific chromosomes were also identified for virulent Foc strain IARI-5175. Genomic comparisons were made on the basis of effectors, CAZymes, secondary metabolites and mycotoxins to understand the global view pathogenicity in Foc. Moreover, the transcriptome of Foc during compatible and incompatible interaction was sequenced and analyzed leading to the identification of differentially regulated genes. Taken together our study laid a solid foundation to explore novel effector genes that play a crucial role in the establishment of disease and can further be used as targets to devise new strategies to curb wilt disease in safflower.

genomics↗