Biology subjects

Sanchez, D. S.

Publications and source records attributed to Sanchez, D. S..

3 recordsLinked to original sources

bioRxiv2025

Cryo-electron microscopy ensemble optimization using individual particles and physical constraints

AO_SCPLOWBSTRACTC_SCPLOWBiomolecules are inherently dynamic, and understanding their conformational ensemble distributions is essential for understanding their dynamics and biological roles. Cryo-electron microscopy (cryo-EM), a technique that images individual biomolecules frozen in a thin layer of amorphous ice, has emerged as a leading method for determining the structure of biomolecules at atomic resolution. Recent advances in cryo-EM reconstruction have made significant progress in determining structure in heterogeneous conformational landscapes. In contrast to reconstruction, a different class of techniques has been used to infer population weights, referred to as ensemble reweighting. These methods have yet to be generalized to infer structural heterogeneity simultaneously. Here, we present a method for cryo-EM ensemble optimization that directly infers the optimal set of structures and their associated population weights from cryo-EM images using Bayesian optimization techniques. Our method iterates between optimizing the structures and weights using a likelihood defined in terms of cryo-EM particle images (not reconstructions) and projecting onto the domain of a physical prior through an approach inspired by projected gradient descent. We test the method on several systems, ranging from a four-atom toy model to a large protein system with real cryo-EM data. We find that our approach successfully recovers the structures and their associated weights across a wide range of experimental conditions, even when the number of structures does not match the actual number of metastable states. Our method paves the way for cryo-EM ensemble optimization of flexible biomolecules exhibiting complex, multimodal conformational landscapes.

biophysics↗

bioRxiv2025

Investigating active dynamics of contractile actomyosin gels with Micro Particle Image Velocimetry (Micro-PIV) analysis

Micro Particle Image Velocimetry (Micro-PIV), an advanced imaging technique, enables high-resolution velocity field measurements by tracking fluorescent tracers in microscopic environments. Here, we adapt conventional micro-PIV to study the rapidly contractile dynamics of active poroelastic gels. We demonstrate how frame-to-frame correlation improves signal-to-noise ratios and how the elastic nature of the solid phase of the gel can be included in the analysis. To do this, we average the gel displacement data under an axisymmetric assumption to extract radial strain profiles that reliably reveal local deformations of the gel. By analyzing gels of varying shapes, we further show that our method extends robustly to gels that are not completely circular or that do not displace symmetrically towards their geometric center. The analysis reveals common underlying features in the radial profiles of gel deformation. These strain profiles will allow the inference of the spatial and orientational distribution of motor-generated active stresses with appropriate constitutive models for the gel mechanics. Our findings emphasize the importance of tailored micro-PIV methodologies for analyzing complex fluids, particularly autonomously contracting poroelastic materials. This approach significantly enhances understanding of cytoskeletal dynamics and self-organization processes, with broad implications for cell motility, morphogenesis, and active matter physics.

biophysics↗

bioRxiv2024

Actin turnover and myosin contractility determine emergent Thickness Robustness of Cell-Mimicking Cortex

Cell shape deformation in eukaryotes, is primarily determined by the actin cortex, a thin network of actin filaments and myosin motors. This network is attached to the plasma membrane endowing cells with their mechanical stability and structural integrity. Since inside the cells hundreds of proteins are associated with the actin cortex, identifying the roles of the individual components and the mechanisms maintaining a functional cortex is highly challenging. Here, using a minimal set of components, we succeeded in recreating long-lasting dynamic treadmilling in an artificial actomyosin cortex on a bilayer membrane with cell-mimicking characteristics, both with and without myosin-II motors, replicating features observed in cells, such as myosin-induced increased cortical thickness and stress-dependent dynamics. We mechanistically reveal how treadmilling is regulated by actin network disassembly factors and myosin contractility, and the emergence of robustness of the cortical thickness to concentration fluctuations in cytoskeletal components. The robustness and responsiveness of the actin cortex which we found has a fundamental significance for the ability of Eukaryotic cells to maintain the mechanical integrity of their membrane, despite concentration fluctuation of the cytoskeleton components. Unlike complex biological cells, this system enables high-resolution and systematic studies of cortical dynamics under controlled conditions. It thus provides a cell-mimicking artificial system for designing interventions to modify the cellular cortex to improve our understanding of the basic mechanisms driving fundamental biological processes as well as for potential medical applications. SignificanceWe report a breakthrough in understanding the actin cortex, a key structure governing cell shape, stability, and motility. By reconstructing in-vitro a treadmilling actomyosin cortex on a lipid bilayer using minimal components, we replicate essential cellular features. This system reveals how cortical thickness is maintained despite concentration fluctuations, highlighting an actin turnover mechanism that buffers variability. The inclusion of myosin motors is found to modify the cortical dynamics, mimicking cellular properties such as the increased thickness and stress-dependent dynamics. Unlike complex living cells, this artificial system enables systematic studies of cortical behavior, with fine control over the components and high-resolution imaging. Our artificial system provides a platform for designing interventions to modify cortical dynamics, with broad implications for biology and medicine. One-Sentence SummaryIn-vitro recreation of a cell-like, membrane-bound cortical actin skeleton composed of a minimal set of building-blocks with continuous turnover and emergent robustness.

biophysics↗