α-catenin is a key mechanosensor that forms force-dependent interactions with F-actin, thereby coupling the cadherin-catenin complex to the actin cytoskeleton at adherens junctions (AJs). However, the molecular mechanisms by which α-catenin engages F-actin under tension remained elusive. Here we show that the α1-helix of the α-catenin actin-binding domain (αcat-ABD) is a mechanosensing motif that regulates tension-dependent F-actin binding and bundling. αcat-ABD containing an α1-helix-unfolding mutation (H1) shows enhanced binding to F-actin in vitro. Although full-length α-catenin-H1 can generate epithelial monolayers that resist mechanical disruption, it fails to support normal AJ regulation in vivo. Structural and simulation analyses suggest that α1-helix allosterically controls the actin-binding residue V796 dynamics. Crystal structures of αcat-ABD-H1 homodimer suggest that α-catenin can facilitate actin bundling while it remains bound to E-cadherin. We propose that force-dependent allosteric regulation of αcat-ABD promotes dynamic interactions with F-actin involved in actin bundling, cadherin clustering, and AJ remodeling during tissue morphogenesis.

Molecular dynamics simulations, equilibrium binding measurements, and fluorescence imaging reveal the influence of a key salt bridge in the mechanical activation of α-catenin at intercellular adhesions. Simulations reveal possible α-catenin conformational changes underlying experimental fluorescence and equilibrium binding data.

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., b-adrenergic stimulation), and pharmacological interventions. Therefore, it is important to have a methodology to robustly determine the impact 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 elucidate the biophysical mechanism of a mutation that causes familial hypertrophic cardiomyopathy. This approach is generally useful for studying muscle diseases and therapeutic interventions that target muscle contraction.

25Striated muscle contraction occurs when myosin thick filaments bind to thin filaments in 26 the sarcomere and generate pulling forces. This process is regulated by calcium, and it 27 can be perturbed by pathological conditions (e.g., myopathies), physiological adaptations 28 (e.g., b-adrenergic stimulation), and pharmacological interventions. Therefore, it is 29 important to have a methodology to robustly determine the mechanism of these 30 perturbations and statistically evaluate their effects. Here, we present an approach to 31 measure the equilibrium constants that govern muscle activation, estimate uncertainty in 32 these parameters, and statistically test the effects of perturbations. We provide a 33 MATLAB-based computational tool for these analyses, along with easy-to-follow tutorials 34 that make this approach accessible. The hypothesis testing and error estimation 35 approaches described here are broadly applicable, and the provided tools work with other 36 types of data, including cellular measurements. To demonstrate the utility of the 37 approach, we apply it to determine the biophysical mechanism of a mutation that causes 38 familial hypertrophic cardiomyopathy. This approach is generally useful for studying the 39 mechanisms of muscle diseases and therapeutic interventions that target muscle 40 contraction. 41 42

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