Biology subjects

Chaudhury, A.

Publications and source records attributed to Chaudhury, A..

3 recordsLinked to original sources

bioRxiv2021

Inhibition of BKCa channels protects neonatal hearts against myocardial ischemia and reperfusion injury

BKCa channels are large-conductance calcium and voltage-activated potassium channels that are heterogeneously expressed in a wide array of cells. Activation of BKCa channels present in mitochondria of adult ventricular cardiomyocytes is implicated in cardioprotection against ischemia-reperfusion (IR) injury. However, the BKCa channels activity has never been detected in the plasma membrane of adult ventricular cardiomyocytes. In this study, we report the presence of the BKCa channel in the plasma membrane and mitochondria of neonatal murine and rodent cardiomyocytes which protects the heart on inhibition but not activation. Furthermore, K+ currents measured in neonatal cardiomyocyte (NCM) was sensitive to iberiotoxin (IbTx), suggesting the presence of BKCa channels in the plasma membrane. Neonatal hearts subjected to IR when post-conditioned with NS1619 during reoxygenation increased the myocardial infarction whereas IbTx reduced the infarct size. In agreement, isolated NCM also presented increased apoptosis on treatment with NS1619 during hypoxia and reoxygenation, whereas IbTx reduced TUNEL positive cells. In NCMs, activation of BKCa channels increased the intracellular reactive oxygen species post HR injury. Electrophysiological characterization of NCMs indicated that NS1619 increased the beat period, field, and action potential duration, and decreased the conduction velocity and spike amplitude. In contrast, IbTx had no impact on the electrophysiological properties of NCMs. Taken together, our data established that inhibition of plasma membrane BKCa channels in the NCM protects neonatal heart/cardiomyocytes from IR injury. Furthermore, the functional disparity observed towards the cardioprotective activity of BKCa channels in adults compared to neonatal heart could be attributed to their differential localization.

physiology↗

bioRxiv2020

Skeletonization of Plant Point Cloud Data in Stochastic Optimization Framework

Skeleton extraction from 3D plant point cloud data is an essential prior for myriads of phenotyping studies. Although skeleton extraction from 3D shapes have been studied extensively in the computer vision and graphics literature, handling the case of plants is still an open problem. Drawbacks of the existing approaches include the zigzag structure of the skeleton, nonuniform density of skeleton points, lack of points in the areas having complex geometry structure, and most importantly the lack of biological relevance. With the aim to improve existing skeleton structures of state-of-the-art, we propose a stochastic framework which is supported by the biological structure of the original plant (we consider plants without any leaves). Initially we estimate the branching structure of the plant by the notion of {beta}-splines to form a curve tree defined as a finite set of curves joined in a tree topology with certain level of smoothness. In the next phase, we force the discrete points in the curve tree to move towards the original point cloud by treating each point in the curve tree as a center of Gaussian, and points in the input cloud data as observations from the Gaussians. The task is to find the correct locations of the Gaussian centroids by maximizing a likelihood. The optimization technique is iterative and is based on the Expectation Maximization (EM) algorithm. The E-step estimates which Gaussian the observed point cloud was sampled from, and the M-step maximizes the negative log-likelihood that the observed points were sampled from the Gaussian Mixture Model (GMM) with respect to the model parameters. We experiment with several real world and synthetic datasets and demonstrate the robustness of the approach over the state-of-the-art.

plant biology↗

bioRxiv2019

CELF1 is an EIF4E binding protein that promotes translation of epithelial-mesenchymal transition effector mRNAs

Mounting evidence is revealing a granularity within gene regulation that occurs at the level of mRNA translation. Within mammalian cells, canonical cap-dependent mRNA translation is dependent upon the interaction between the m7G cap-binding protein eukaryotic initiation factor 4E (eIF4E) and the scaffolding protein eukaryotic initiation factor 4G (eIF4G), the latter of which facilitates pre-translation initiation complex assembly, mRNA circularization, and ultimately ribosomal scanning. In breast epithelial cells, we previously demonstrated that the CELF1 RNA-binding protein promotes the translation of epithelial to mesenchymal transition (EMT) effector mRNAs containing GU-rich elements (GREs) within their 3 untranslated regions (UTRs). Here we show that within this context, CELF1 directly binds to both the eIF4E cap-binding protein and Poly(A) binding protein (PABP), promoting translation of GRE-containing mRNAs in mesenchymal cells. Disruption of this CELF1/eIF4E interaction inhibits both EMT induction and experimental metastasis. Our findings illustrate a novel way in which non-canonical mechanisms of translation initiation underlie transitional cellular states within the context of development or human disease.

cancer biology↗