Biology subjects

Mathur, M.

Publications and source records attributed to Mathur, M..

14 recordsLinked to original sources

bioRxiv2026

No Strings Attached: Predicting Tricuspid Valve Deformation Without In Vivo Chordal Geometry

Predictive biomechanical models of the tricuspid valve require accurate representation of the chordae tendineae, yet subject-specific chordal geometry is difficult to reconstruct from non-invasive imaging. Here, we adopt a framework for generating functionally equivalent synthetic chordae without prior knowledge of in vivo chordal attachments. To this end, we first adapt an anatomy-informed hyperelastic shape-matching method that establishes correspondence between end-diastolic and end-systolic leaflet configurations using chordal-mimicking forces, a rigid contact template, and a Gaussian-smoothed locally corrective pressure field. We then generate synthetic chordal insertion sites using zone-based rejection sampling and calibrate the unloaded length of each chord by combining reaction forces with the chordal stress-stretch relationship. The framework was evaluated using Texas TriValve 1.1, a high-fidelity finite element model of a human tricuspid valve validated against beating-heart echocardiography. We found that shape matching reproduced the target end-systolic geometry with a mean inter-surface distance of 0.29 {+/-} 0.35 mm. Moreover, synthetic chordal insertions faithfully reproduce end-systolic leaflet deformations. We subsequently examined synthetic chordal configurations containing 202, 225, and 450 insertions, informed by measurements from eight explanted human tricuspid valves. Here, increasing insertion number reduced mean inter-surface distance from 0.63 {+/-} 0.52 mm to 0.49 {+/-} 0.44 mm and reduced contact area errors from 3.52% to 0.59%. Across all configurations, mean maximum principal stretch errors in leaflet belly regions remained below 2.4%, while areal strain errors ranged from 0.34% to 10.01%. These results demonstrate that anatomically informed shape matching coupled with stress-based chordal calibration can reproduce tricuspid valve closure without explicit subject-specific chordal geometry. This framework provides a foundation for generating synthetic subvalvular anatomy for future imaging-derived, predictive tricuspid valve models.

bioengineering↗

bioRxiv2025

Understanding the Mechanisms Behind the Annuloplasty Effect in Tricuspid Valve TEER: A Computational Study

BackgroundAn annuloplasty effect has been observed following tricuspid transcatheter edge-to-edge repair (TEER) and has been shown to have a therapeutic benefit. However, the mechanisms underlying the annuloplasty effect remain unknown. ObjectivesWe investigate the impact of TEER-induced annular forces on the annuloplasty effect. Additionally, we explored the impact of clip size, clip orientation, leaflet pair, and leaflet site on TEER-induced annular forces. MethodsWe simulated 36 TEER repairs in finite element models of three human tricuspid valves. We used either a NTW or XTW TriClip. The clip was placed between either the anterior-septal or anterior-posterior leaflet pairs, in either the central or near-annulus site. For each scenario, we quantified the reduction in annular area, septal-lateral (SL) diameter, and anterior-posterior (AP) diameter. We also report the total annular force, orientation of maximum annular force, total papillary muscle force, leaflet stress, and coaptation area ratio following TEER. ResultsTEER induced annular forces, which strongly predicted the annuloplasty effect as measured by reduction in annular area and SL diameter. The maximum annular force aligned with the orientation of the clip. Furthermore, XTW clips induced more annular force and leaflet stress than NTW clips. A central anterior-posterior site induced more force than a near-annulus anterior-posterior site, but showed no difference from an anterior-septal pair. ConclusionsTEER procedural parameters, such as clip size and site, strongly influence the magnitude of induced annular forces, which, in turn, correlate with the degree of annuloplasty effect.

bioengineering↗

bioRxiv2025

Human wastewater contamination drives the emergence of novel multidrug resistant bacteria in the Galapagos marine ecosystem.

Since the publication of Charles Darwins On the Origin of Species in 1859, the Galapagos archipelago has become emblematic of natural selection and evolution. While the lens of evolution in the Galapagos has traditionally focused on iconic megafauna, including finches, marine iguanas, and giant tortoises, the marine environment is also home to diverse microbial ecosystems that are constantly evolving under selective pressure from environmental factors such as human activity. We focused on the second most populated island within the archipelago -- San Cristobal -- an island that has experienced rapid urbanization and intense international tourism pressure. Using a lab-free approach, we spatiotemporally mapped wastewater contamination around San Cristobal. On-site metagenomic sequencing revealed a stark shift in genera and a higher count of antimicrobial resistance genes at wastewater-associated sites. Over 40% of lactose-fermenting Enterobacteriaceae isolates collected from sewage and wastewater outfall exhibited multidrug resistance (MDR). Long-read sequencing and de novo assembly of bacterial genomes and plasmids from MDR Escherichia coli revealed frequent and rapid reassortment of antimicrobial resistance genes on plasmids, generating unique antimicrobial resistance profiles. This study not only provides a framework for conducting antimicrobial resistance research in low-resource settings but also underscores the impact of wastewater contamination on the environmental AMR landscape and highlights potential threats to human and animal health.

microbiology↗

bioRxiv2024

Tricuspid valve maladaptation in sheep with biventricular heart failure: The posterior and septal leaflets

Tricuspid valve leaflets are dynamic tissues that can respond to altered biomechanical and hemodynamic loads. Each leaflet has unique structural and mechanical properties, leading to differential in vivo strains. We hypothesized that these intrinsic differences drive heterogeneous, disease-induced remodeling between the leaflets. Although we previously reported significant remodeling changes in the anterior leaflet, the responses among the other two leaflets have not been reported. Using a sheep model of biventricular heart failure, we compared the remodeling responses between all tricuspid leaflets. Our results show that the anterior leaflet underwent the most significant remodeling, while the septal and posterior leaflets exhibited similar but less pronounced changes. We found several between-leaflet differences in key structural and mechanical metrics that have been shown to contribute to valvular dysfunction. These findings underscore the need to consider leaflet-specific remodeling to fully understand tricuspid valve dysfunction and to develop targeted therapies for its treatment and more accurate computational models. STATEMENT OF SIGNIFICANCEOur study is significant as it advances our understanding of tricuspid valve remodeling by providing a comprehensive analysis of all three leaflets in a sheep model of biventricular heart failure. Unlike prior works that focused primarily on the anterior leaflet or generalized leaflet changes, we integrated morphological, histological, immunohistochemistry, biaxial mechanical testing, and two-photon microscopy to quantify differences between all three tricuspid valve leaflets (anterior, posterior, and septal) across multiple functional scales. This comprehensive approach highlights the unique remodeling response of each leaflet. Our findings offer critical insights for developing targeted therapeutic strategies and improving computational models of disease progression. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=119 SRC="FIGDIR/small/613284v2_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@1e8efaforg.highwire.dtl.DTLVardef@1cfee04org.highwire.dtl.DTLVardef@136956org.highwire.dtl.DTLVardef@68c488_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2024

In silico identification of putative causal genetic variants

Understanding the causal genetic architecture of complex phenotypes will fuel future research into disease mechanisms and potential therapies. Here, we illustrate the power of a novel framework: it detects, starting from summary statistics, and across the entire genome, sets of variants that carry non-redundant information on the phenotypes and are therefore more likely to be causal in a biological sense. The approach, implemented in open-source software, is also computationally efficient, requiring less than 15 minutes on a single CPU to perform genome-wide analysis. Through extensive genome-wide simulation studies, we show that the method can substantially outperform existing methods in false discovery rate control, statistical power and various fine-mapping criteria. In applications to a meta-analysis of ten large-scale genetic studies of Alzheimers disease (AD), we identified 82 loci associated with AD, including 37 additional loci missed by conventional GWAS pipeline. Massively parallel reporter assays and CRISPR-Cas9 experiments have confirmed the functionality of the putative causal variants our method points to. Finally, we retrospectively analyzed summary statistics from 67 large-scale GWAS for a variety of phenotypes. Results reveal the methods capacity to robustly discover additional loci for polygenic traits and pinpoint potential causal variants underpinning each locus beyond conventional GWAS pipeline, contributing to a deeper understanding of complex genetic architectures in post-GWAS analyses.

genetics↗

bioRxiv2023

Spinal cord injury: a systematic review and meta-analysis of microRNA alterations

Spinal cord injury (SCI) often results in life-long disability, lost wages, reduced quality of life, and high economic burden. A bottle neck in the performance of clinical trials exists, in part, due to a lack of diagnostic and prognostic markers of injury severity and neurologic recovery. In addition, while many interventions show promise in preclinical animal models, there are currently no neurorestorative treatments for SCI patients. The development of objective biological markers (biomarkers) and molecular targets for novel treatments for SCI represent two urgent unmet clinical needs. MicroRNAs (miRNAs) represent promising molecules as objective and informative molecules of injury severity and recovery and as potential therapeutic targets. miRNAs are small, stable, regulatory RNA molecules that are evolutionarily conserved across species. miRNAs represent powerful predictors of pathology, particularly with respect to neurologic disorders. Here, we present a systematic review and meta-analysis investigating the conserved inter- and intra-species miRNA changes that occur post-SCI and provide a comprehensive resource for the SCI community. Our analysis identifies a robust set of miRNAs that are involved in the pathophysiologic processes activated in response to SCI.

neuroscience↗

bioRxiv2023

TOM20 Gates PINK1 Activity And Mediates Its Tethering Of The TOM And TIM23 Translocases Upon Mitochondrial Stress

Mutations in PTEN-induced putative kinase 1 (PINK1) cause autosomal recessive early onset Parkinson disease (PD). PINK1 is a Ser/Thr kinase that regulates mitochondrial quality control by triggering mitophagy mediated by the ubiquitin ligase Parkin. Upon mitochondrial damage, PINK1 accumulates on the outer mitochondrial membrane (OMM) forming a high molecular weight complex with the translocase of the outer membrane (TOM). PINK1 then phosphorylates ubiquitin, which enables recruitment and activation of Parkin followed by autophagic clearance of the damaged mitochondrion. Thus, Parkin-dependent mitophagy hinges on the stable accumulation of PINK1 on the TOM complex. Yet, the mechanism linking mitochondrial stressors to PINK1 accumulation and whether the translocases of the inner membrane (TIMs) are also involved, remain unclear. Herein, we demonstrate that mitochondrial stress induces the formation of a PINK1-TOM-TIM23 supercomplex in human cultured cell lines, dopamine neurons, and midbrain organoids. Moreover, we show that PINK1 is required to stably tether the TOM to TIM23 complexes in response to stress, such that the supercomplex fails to accumulate in cells lacking PINK1. This tethering is dependent on an interaction between the PINK1 NT-CTE module and the cytosolic domain of the Tom20 subunit of the TOM complex, the disruption of which, by either designer or PD-associated PINK1 mutations, inhibits downstream mitophagy. Together, the findings provide key insight into how PINK1 interfaces with the mitochondrial import machinery, with important implications for the mechanisms of mitochondrial quality control and PD pathogenesis.

biochemistry↗

bioRxiv2023

Untangling the mechanisms of pulmonary hypertension-induced right ventricular stiffening in a large animal model

BackgroundPulmonary arterial hypertension (PHT) is a devastating disease with low survival rates. In PHT, chronic pressure overload leads to right ventricle (RV) remodeling and stiffening; thus, impeding diastolic filling and ventricular function. Multiple mechanisms contribute to RV stiffening, including wall thickening, microstructural disorganization, and myocardial stiffening. The relative importance of each mechanism is unclear. Our objective is to use a large animal model as well as imaging, experimental, and computational approaches to untangle these mechanisms. MethodsWe induced PHT in eight sheep via pulmonary artery banding. After eight weeks, the hearts underwent anatomic and diffusion tensor MRI to characterize wall thickening and microstructural disorganization. Additionally, myocardial samples underwent histological and gene expression analyses to quantify compositional changes and mechanical testing to quantify myocardial stiffening. All findings were compared to 12 control animals. Finally, we used computational modeling to disentangle the relative importance of each stiffening mechanism. ResultsFirst, we found that the RVs of PHT animals thickened most at the base and the free wall. Additionally, we found that PHT induced excessive collagen synthesis and microstructural disorganization, consistent with increased expression of fibrotic genes. We also found that the myocardium itself stiffened significantly. Importantly, myocardial stiffening correlated significantly with excess collagen synthesis. Finally, our model of normalized RV pressure-volume relationships predicted that myocardial stiffness contributes to RV stiffening significantly more than other mechanisms. ConclusionsIn summary, we found that PHT induces wall thickening, microstructural disorganization, and myocardial stiffening. These remodeling mechanisms were both spatially and directionally dependent. Using modeling, we show that myocardial stiffness is the primary contributor to RV stiffening. Thus, myocardial stiffening may be an important predictor for PHT progression. Given the significant correlation between myocardial stiffness and collagen synthesis, collagen-sensitive imaging modalities may be useful for non-invasively estimating myocardial stiffness and predicting PHT outcomes.

physiology↗

bioRxiv2022

CelltypeR: A framework to identify and characterize cell types in human midbrain organoids using flow cytometry

Motivated by the growing number of single cell RNA sequencing datasets (scRNAseq) revealing the cellular heterogeneity in complex tissues, particularly in brain and induced pluripotent stem cell (iPSC)-derived brain models, we developed a high-throughput, standardized approach for reproducibly characterizing cell types in complex neuronal tissues based on protein expression levels. Our approach combines a flow cytometry (FC) antibody panel targeting brain cells with a computational pipeline called CelltypeR, with functions for aligning and transforming datasets, optimizing unsupervised clustering, annotating and quantifying cell types, and statistical comparisons. We applied this workflow to human iPSC-derived midbrain organoids and identified the expected brain cell types, including neurons, astrocytes, radial glia, and oligodendrocytes. Defining gates based on the expression levels of our protein markers, we performed Fluorescence-Activated Cell Sorting of astrocytes, radial glia, and neurons, cell types were then confirmed by scRNAseq. Among the sorted neurons, we identified three subgroups of dopamine (DA) neurons; one reminiscent of substantia nigra DA neurons, the cell type most vulnerable in Parkinsons disease. Finally, we use our workflow to track cell types across a time course of organoid differentiation. Overall, our adaptable analysis framework provides a generalizable method for reproducibly identifying cell types across FC datasets.

neuroscience↗

bioRxiv2021

Nfeature: A platform for computing features of nucleotide sequences

In the past few decades, public repositories on nucleotides have increased with exponential rates. This pose a major challenge to researchers to predict the structure and function of nucleotide sequences. In order to annotate function of nucleotide sequences it is important to compute features/attributes for predicting function of these sequences using machine learning techniques. In last two decades, several software/platforms have been developed to elicit a wide range of features for nucleotide sequences. In order to complement the existing methods, here we present a platform named Nfeature developed for computing wide range of features of DNA and RNA sequences. It comprises of three major modules namely Composition, Correlation, and Binary profiles. Composition module allow to compute different type of compositions that includes mono-/di-tri-nucleotide composition, reverse complement composition, pseudo composition. Correlation module allow to compute various type of correlations that includes auto-correlation, cross-correlation, pseudo-correlation. Similarly, binary profile is developed for computing binary profile based on nucleotides, mono-nucleotides, di-/tri-nucleotide properties. Nfeature also allow to compute entropy of sequences, repeats in sequences and distribution of nucleotides in sequences. In addition to compute feature in whole sequence, it also allows to compute features from part of sequence like split, start, end, and rest. In a nutshell, Nfeature amalgamates existing features as well as number of novel features like nucleotide repeat index, distance distribution, entropy, binary profile, and properties. This tool computes a total of 29217 and 14385 features for DNA and RNA sequence, respectively. In order to provide, a highly efficient and userfriendly tool, we have developed a standalone package and web-based platform (https://webs.iiitd.edu.in/raghava/nfeature).

bioinformatics↗

bioRxiv2021

An Approach to Measuring Protein Turnover in Human Induced Pluripotent Stem Cell Organoids by Mass Spectrometry

Patient-derived organoids from induced pluripotent stem cells have emerged as a model for studying human diseases beyond conventional two-dimensional (2D) cell culture. Briefly, these three-dimensional organoids are highly complex, capable of self-organizing, recapitulate cellular architecture, and have the potential to model diseases in complex organs, such as the brain. For example, the hallmark of Parkinsons disease - proteostatic dysfunction leading to the selective death of neurons in the substantia nigra - present a subtle distinction in cell type specificity that is simply lost in 2D cell culture models. As such, the development of robust methods to study global proteostasis and protein turnover in organoids will remain a critical need as organoid models evolve. To solve this problem, we have designed a workflow to extract proteins from organoids and measure global protein turnover using mass spectrometry and stable isotope labeling using amino acids in cell culture (SILAC). This allowed us to measure the turnover rates of 844 proteins and compare protein turnover to previously reported data in primary cell cultures and in vivo models. Taken together, this method will facilitate the study of proteostasis in organoid models of human disease and will provide an analytical and statistical framework to measure protein turnover in organoids of all cell types.

neuroscience↗

bioRxiv2021

Microfabricated disk technology: rapid scale up in midbrain organoid generation

By providing a three-dimensional in vitro culture system with key features of the substantia nigra region in the brain, 3D neuronal organoids derived from human induced pluripotent stem cells (iPSCs) provide living neuronal tissue resembling the midbrain region of the brain. However, a major limitation of conventional brain organoid culture is that it is often labor-intensive, requiring highly specialized personnel for moderate throughput. Additionally, the methods published for long-term cultures require time-consuming maintenance to generate brain organoids in large numbers. With the increasing need for human midbrain organoids (hMOs) to better understand and model Parkinsons disease (PD) in a dish, there is a need to implement new workflows and methods to both generate and maintain hMOs, while minimizing batch to batch variation. In this study, we developed a method with microfabricated disks to scale up the generation of hMOs. This opens up the possibility to generate larger numbers of hMOs, in a manner that minimizes the amount of labor required, while decreasing variability and maintaining the viability of these hMOs over time. Taken together, producing hMOs in this manner opens up the potential for these to be used to further PD studies.

neuroscience↗

bioRxiv2021

Midbrain organoids with an SNCA gene triplication model key features of synucleinopathy

SNCA, the first gene associated with Parkinsons disease, encodes the -synuclein (-syn) protein, the predominant component within pathological inclusions termed Lewy bodies (LBs). The presence of LBs is one of the classical hallmarks found in the brain of patients with Parkinsons disease, and LBs have also been observed in patients with other synucleinopathies. However, the study of -syn pathology in cells has relied largely on two-dimensional culture models, which typically lack the cellular diversity and complex spatial environment found in the brain. Here, to address this gap, we use 3D midbrain organoids (hMOs), differentiated from human induced pluripotent stem cells derived from patients carrying a triplication of the SNCA gene and from CRISPR/Cas9 corrected isogenic control iPSCs. These hMOs recapitulate key features of -syn pathology observed in the brains of patients with synucleinopathies. In particular, we find that SNCA triplication hMOs express elevated levels of -syn and exhibit an age-dependent increase in -syn aggregation, manifested by the presence of both oligomeric and phosphorylated forms of -syn. These phosphorylated -syn aggregates were found in both neurons and glial cells and their time-dependent accumulation correlated with a selective reduction in dopaminergic neuron numbers. Thus, hMOs from patients carrying SNCA gene multiplication can reliably model key pathological features of Parkinsons disease and provide a powerful system to study the pathogenesis of synucleinopathies.

neuroscience↗

bioRxiv2020

The tricuspid valve also maladapts: A multiscale study in sheep with biventricular heart failure

ObjectivesWe set out to determine the tricuspid valves propensity to (mal)adapt in disease. BackgroundTricuspid regurgitation (TR) is generally considered secondary to right and/or left ventricular disease without organic failure. Interestingly, we and others have previously shown the mitral valve (mal)adapts in functional mitral regurgitation, which may warrant reconsideration of its functional etiology. Whether the tricuspid valve similarly (mal)adapts is mostly unknown. MethodsWe evaluated the (mal)adaptive response of tricuspid valve anterior leaflets (TVALs) from an ovine model in which over-pacing (19 {+/-} 6 days) induced biventricular heart failure and TR (tachycardia-induced cardiomyopathy, TIC, n=33) and compared findings to those from a control group (n=17). In both groups, we performed proteomics, immunohistochemistry, histology, two-photon microscopy, collagen assays, leaflet thickness and morphology measurements, and biaxial mechanical tests. ResultsWe found metabolically active resident valvular cells in TIC TVALs which expressed activation and turnover markers. In TIC TVALs, we observed a 140% increase in collagen content (p=0.016), increased collagen dispersion regionally (p=0.017), a 130% increase in leaflet area (p=0.002), a 140% increase in thickness (p=0.006), and a 130% increase in radial stiffness (p=0.006). ConclusionsOur data suggest that TVALs (mal)adapt during TIC on all scales. This response is likely initiated by activated valvular cells, resulting in collagen turnover, and ultimately leading to thickening, area increase, and stiffening. Our data motivates future studies on the exact pathways leading to tricuspid (mal)adaptation and pharmacological therapeutic strategies for TR. Condensed AbstractIn most cases, tricuspid regurgitation is presumed to originate from valve extrinsic factors. We challenge this paradigm and hypothesize that the tricuspid valve maladapts, rendering the valve at least partially culpable for its dysfunction. As such, we set out to demonstrate that the tricuspid valve, indeed, maladapts in an ovine model of heart disease. In the anterior leaflets, we found alterations on the protein and cell-level, leading to maladaptation in the form of tissue growth, thickening, and stiffening. Our findings may initially motivate mechanistic pathway studies, and in the future, leaflet-targeted pharmacological therapeutic options for tricuspid regurgitation.

bioengineering↗