Biology subjects

Clippinger, S. R.

Publications and source records attributed to Clippinger, S. R..

4 recordsLinked to original sources

bioRxiv2020

Computational Tool for Ensemble Averaging of Single-Molecule Data

Molecular motors couple chemical transitions to conformational changes that perform mechanical work in a wide variety of biological processes. Disruption of this coupling can lead to diseases, and therefore there is a need to accurately measure mechanochemical coupling in motors in both health and disease. Optical tweezers, with nanometer spatial and millisecond temporal resolution, have provided valuable insights into these processes. However, fluctuations due to Brownian motion can make it difficult to precisely resolve these conformational changes. One powerful analysis technique that has improved our ability to accurately measure mechanochemical coupling in motor proteins is ensemble averaging of individual trajectories. Here, we present a user-friendly computational tool, Software for Precise Analysis of Single Molecules (SPASM), for generating ensemble averages of single-molecule data. This tool utilizes several conceptual advances, including optimized procedures for identifying single-molecule interactions and the implementation of a change point algorithm, to more precisely resolve molecular transitions. Using both simulated and experimental data, we demonstrate that these advances allow for accurate determination of the mechanics and kinetics of the myosin working stroke with a smaller set of data. Importantly, we provide our open source MATLAB-based program with a graphical user interface that enables others to readily apply these advances to the analysis of their own data. Statement of SignificanceSingle molecule optical trapping experiments have given unprecedented insights into the mechanisms of molecular machines. Analysis of these experiments is often challenging because Brownian motion-induced fluctuations introduce noise that can obscure molecular motions. A powerful technique for analyzing these noisy traces is ensemble averaging of individual binding interactions, which can uncover information about the mechanics and kinetics of molecular motions that are typically obscured by Brownian motion. Here, we provide an open source, easy-to-use computational tool, SPASM, with a graphical user interface for ensemble averaging of single molecule data. This computational tool utilizes several conceptual advances that significantly improve the accuracy and resolution of ensemble averages, enabling the generation of high-resolution averages from a smaller number of binding interactions.

biophysics↗

bioRxiv2020

Mechanical dysfunction induced by a hypertrophic cardiomyopathy mutation is the primary driver of cellular adaptation

Familial hypertrophic cardiomyopathy (HCM), a leading cause of sudden cardiac death, is primarily caused by mutations in sarcomeric proteins. The pathogenesis of HCM is complex, with functional changes that span scales from molecules to tissues. This makes it challenging to deconvolve the biophysical molecular defect that drives the disease pathogenesis from downstream changes in cellular function. Here, we examined a HCM mutation in troponin T, R92Q. We demonstrate that the primary molecular insult driving the disease pathogenesis is mutation-induced alterations in tropomyosin positioning, which causes increased molecular and cellular force generation during calcium-based activation. We demonstrate computationally that these increases in force are direct consequences of the initial molecular insult. This altered cellular contractility causes downstream alterations in gene expression, calcium handling, and electrophysiology. Taken together, our results demonstrate that molecularly driven changes in mechanical tension drive the early disease pathogenesis, leading to activation of adaptive mechanobiological signaling pathways.

biophysics↗

bioRxiv2019

Disrupted mechanobiology links the molecular and cellular phenotypes in familial dilated cardiomyopathy

Familial dilated cardiomyopathy (DCM) is a leading cause of sudden cardiac death and a major indicator for heart transplant. The disease is frequently caused by mutations of sarcomeric proteins; however, it is not well understood how these molecular mutations lead to alterations in cellular organization and contractility. To address this critical gap in our knowledge, we studied the molecular and cellular consequences of a DCM mutation in troponin-T, {Delta}K210. We determined the molecular mechanism of {Delta}K210 and used computational modeling to predict that the mutation should reduce the force per sarcomere. In mutant cardiomyocytes, we found that {Delta}K210 not only reduces contractility, but also causes cellular hypertrophy and impairs cardiomyocytes ability to adapt to changes in substrate stiffness (e.g., heart tissue fibrosis that occurs with aging and disease). These results link the molecular and cellular phenotypes and implicate alterations in mechanosensing as an important factor in the development of DCM.

biophysics↗

bioRxiv2019

Computational tool to study perturbations in muscle regulation and its application to heart disease

Striated muscle contraction occurs when myosin thick filaments bind to thin filaments in the sarcomere and generate pulling forces. This process is regulated by calcium, and it can be perturbed by pathological conditions (e.g., myopathies), physiological adaptations (e.g., {beta}-adrenergic stimulation), and pharmacological interventions. Therefore, it is important to have a methodology to robustly determine the mechanism of these perturbations and statistically evaluate their effects. Here, we present an approach to measure the equilibrium constants that govern muscle activation, estimate uncertainty in these parameters, and statistically test the effects of perturbations. We provide a MATLAB-based computational tool for these analyses, along with easy-to-follow tutorials that make this approach accessible. The hypothesis testing and error estimation approaches described here are broadly applicable, and the provided tools work with other types of data, including cellular measurements. To demonstrate the utility of the approach, we apply it to determine the biophysical mechanism of a mutation that causes familial hypertrophic cardiomyopathy. This approach is generally useful for studying the mechanisms of muscle diseases and therapeutic interventions that target muscle contraction.

biophysics↗