Caveolin-1 dolines form a distinct and rapid caveolae-independent mechanoadaptation system.

In response to different types and intensities of mechanical force, cells modulate their physical properties and adapt their plasma membrane (PM). Caveolae are PM nano-invaginations that contribute to mechanoadaptation, buffering tension changes. However, whether core caveolar proteins contribute to PM tension accommodation independently from the caveolar assembly is unknown. Here we provide experimental and computational evidence supporting that caveolin-1 confers deformability and mechanoprotection independently from caveolae, through modulation of PM curvature. Freeze-fracture electron microscopy reveals that caveolin-1 stabilizes non-caveolar invaginations-dolines-capable of responding to low-medium mechanical forces, impacting downstream mechanotransduction and conferring mechanoprotection to cells devoid of caveolae. Upon cavin-1/PTRF binding, doline size is restricted and membrane buffering is limited to relatively high forces, capable of flattening caveolae. Thus, caveolae and dolines constitute two distinct albeit complementary components of a buffering system that allows cells to adapt efficiently to a broad range of mechanical stimuli.We thank R. Parton (Institute for Molecular Biosciences, Queensland), P. Pilch (Boston University School of Medicine) and L. Liu (Boston University School of Medicine) for kindly providing PTRFKO cells and reagents, S. Casas Tintó for kindly providing SH-Sy5y cells, P. Bassereau (Curie Institute, Paris) for kindly providing OT setup, V. Labrador Cantarero from CNIC microscopy Unit for helping with ImageJ analysis, O. Otto and M. Herbig for providing help with RTDC experiments, S. Berr and K. Gluth for technical assistance in cell culture, F. Steiniger for support in electron tomography, and A. Norczyk Simón for providing pCMV-FLAG-PTRF construct. This project received funding from the European Union Horizon 2020 Research and Innovation Programme through Marie Sklodowska-Curie grant 641639; grants from the Spanish Ministry of Science and Innovation (MCIN/AEI/10.13039/501100011033): SAF2014-51876-R, SAF2017-83130-R co-funded by ‘ERDF A way of making Europe’, PID2020-118658RB-I00, PDC2021-121572-100 co-funded by ‘European Union NextGenerationEU/PRTR’, CSD2009- 0016 and BFU2016-81912-REDC; and the Asociación Española Contra el Cáncer foundation (PROYE20089DELP) all to M.A.d.P. M.A.d.P. is member of the Tec4Bio consortium (ref. S2018/NMT¬4443; Comunidad Autónoma de Madrid/FEDER, Spain), co-recipient with P.R.-C. of grants from Fundació La Marató de TV3 (674/C/2013 and 201936- 30-31), and coordinator of a Health Research consortium grant from Fundación Obra Social La Caixa (AtheroConvergence, HR20-00075). M.S.-A. is recipient of a Ramón y Cajal research contract from MCIN (RYC2020-029690-I). The CNIC Unit of Microscopy and Dynamic Imaging is supported by FEDER ‘Una manera de hacer Europa’ (ReDIB ICTS infrastructure TRIMA@CNIC, MCIN). We acknowledge the support from Deutsche Forschungsgemeinschaft through grants to M.M.K. (KE685/7-1) and B.Q. (QU116/6-2 and QU116/9-1). Work in D.N. laboratory was supported by grants from the European Union Horizon 2020 Research and Innovation Programme through Marie Sklodowska-Curie grant 812772 and MCIN (DPI2017-83721-P). Work in C.L. laboratory was supported by grants from Curie, INSERM, CNRS, Agence Nationale de la Recherche (ANR-17-CE13-0020-01) and Fondation ARC pour la Recherche (PGA1-RF20170205456). Work in P.R.-C. lab is funded by the MCIN (PID2019-110298GB-I00), the EC (H20 20-FETPROACT-01-2016-731957). Work in X.T. lab is funded by the MICIN (PID2021-128635NB-I00), ERC (Adv-883739) and La Caixa Foundation (LCF/PR/HR20/52400004; co-recipient with P.R.-C.). IBEC is recipient of a Severo Ochoa Award of Excellence from the MINECO. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. The CNIC is supported by the Instituto de Salud Carlos III (ISCIII), the MCIN and the Pro CNIC Foundation, and is a Severo Ochoa Center of Excellence (grant CEX2020-001041-S funded by MICIN/AEI/10.13039/501100011033).S

Phosphorylated filamin A regulates actin-linked caveolae dynamics

Caveolae are relatively stable membrane invaginations that compartmentalize signaling, regulate lipid metabolism and mediate viral entry. Caveolae are closely associated with actin fibers and internalize in response to diverse stimuli. Loss of cell adhesion is known to induce rapid and robust caveolae internalization and trafficking toward a Rab11-positive recycling endosome; however, pathways governing this process are poorly understood. Here, we report that filamin A is required to maintain the F-actin-dependent linear distribution of caveolin-1. High spatiotemporal resolution particle tracking of caveolin-1-GFP vesicles by total internal reflection fluorescence (TIRF) microscopy revealed that FLNa is required for the F-actin-dependent arrest of caveolin-1 vesicles in a confined area and their stable anchorage to the plasma membrane. The linear distribution and anchorage of caveolin-1 vesicles are both required for proper caveolin-1 inwards trafficking. De-adhesion-triggered caveolae inward trafficking towards a recycling endosome is impaired in FLNa-depleted HeLa and FLNa-deficient M2-melanoma cells. Inwards trafficking of caveolin-1 requires both the ability of FLNa to bind actin and cycling PKCα-dependent phosphorylation of FLNa on Ser2152 after cell detachment. © 2011. Published by The Company of Biologists Ltd.Peer Reviewe

A deep learning-based tool for the automated detection and analysis of caveolae in transmission electron microscopy images

Caveolae are nanoscopic and mechanosensitive invaginations of the plasma membrane, essential for adipocyte biology. Transmission electron microscopy (TEM) offers the highest resolution for caveolae visualization, but provides complicated images that are difficult to classify or segment using traditional automated algorithms such as threshold-based methods. As a result, the time-consuming tasks of localization and quantification of caveolae are currently performed manually. We used the Keras library in R to train a convolutional neural network with a total of 36,000 TEM image crops obtained from adipocytes previously annotated manually by an expert. The resulting model can differentiate caveolae from non-caveolae regions with a 97.44% accuracy. The predictions of this model are further processed to obtain caveolae central coordinate detection and cytoplasm boundary delimitation. The model correctly finds negligible caveolae predictions in images from caveolae depleted Cav1-/- adipocytes. In large reconstructions of adipocyte sections, model and human performances are comparable. We thus provide a new tool for accurate caveolae automated analysis that could speed up and assist in the characterization of the cellular mechanical response

Caveolar domain organization and trafficking is regulated by Abl kinases and mDia1

54 páginas, 8 figurasCaveolin-1 (Cav1)/caveolae biology is intimately linked to actin dynamics and adhesion receptors. Caveolar domains are organized in hierarchical levels of complexity from curved or flatten caveolae to large, higher-order caveolar rosettes. We report that stress fibers controlled by Abl kinases and mDia1 determine the level of caveolar domain organization, which conditions the subsequent inward trafficking of caveolar domains induced upon loss of cell adhesion from the extracellular matrix. Abl-deficient cells show decreased content of stress fibers, a smaller stress-fiber co-aligned Cav1 pool and increased clustering of Cav1/caveolae at the cell surface. Defective caveolar linkage to stress fibers prevents the formation of big caveolar rosettes upon loss of cell adhesion, correlating with a lack of inward trafficking. Live imaging of stress fibers and Cav1 showed that the actin-linked Cav1 pool loses its spatial organization in the absence of actin polymerization and is dragged and clustered by depolymerizing filaments. We identify mDia1 as the actin polymerization regulator downstream of Abl kinases that controls the stress fiber-linked Cav1 pool. mDia1 knockdown results in Cav1/caveolae clustering and defective inward trafficking upon loss of cell adhesion. In contrast, cell elongation imposed by the excess of stress fibers induced by active mDia1 flattens caveolae. Furthermore, active mDia1 rescues the actin co-aligned Cav1 pool and Cav1 inward trafficking upon loss of adhesion in Abl-deficient cells. Thus, caveolar domain organization and trafficking are tightly coupled to adhesive and stress fiber regulatory pathwaysWe thank A. M. Pendergast, T. Koleske, J. Wehland, K. Rottner, S. Narumiya, R. Wedlich-Soldner and F. Sánchez-Madrid for valuable reagents. We thank S. Sánchez for excellent technical assistance, S. Calleja, I. Salanueva, C. Patiño, J. Bueno, I. Cotillo and the CNIC Microscopy Unit for technical assistance. We thank S. Bartlett and T. Pellinen for critical reading of the manuscript and R. Parton and A. G. Arroyo for helpful suggestions. AE was supported by the Ramón y Cajal Program (MICINN, Spanish Ministry of Science and Innovation), OM by a predoctoral fellowship from the Instituto de Salud Carlos III (MICINN). MAdP was supported by the MICINN through grants SAF2008-02100, RTICC RD06/0020/1033 and CSD 2009-00016, by EUROHORCS (European Heads Of Research Councils) and the European Science Foundation (ESF) through a EURYI (European Young Investigator) award, and by the EMBO Young Investigator Programme. OL was supported by grants SAF2008-00451, SAF2011-22988 and RD06/0020/1001 (MICINN). The CNIC is supported by the MICINN and the Pro-CNIC Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of this manuscriptPeer reviewe

An Abl-FBP17 mechanosensing system couples local plasma membrane curvature and stress fiber remodeling during mechanoadaptation

Cells remodel their structure in response to mechanical strain. However, how mechanical forces are translated into biochemical signals that coordinate the structural changes observed at the plasma membrane (PM) and the underlying cytoskeleton during mechanoadaptation is unclear. Here, we show that PM mechanoadaptation is controlled by a tension-sensing pathway composed of c-Abl tyrosine kinase and membrane curvature regulator FBP17. FBP17 is recruited to caveolae to induce the formation of caveolar rosettes. FBP17 deficient cells have reduced rosette density, lack PM tension buffering capacity under osmotic shock, and cannot adapt to mechanical strain. Mechanistically, tension is transduced to the FBP17 F-BAR domain by direct phosphorylation mediated by c-Abl, a mechanosensitive molecule. This modification inhibits FBP17 membrane bending activity and releases FBP17-controlled inhibition of mDia1-dependent stress fibers, favoring membrane adaptation to increased tension. This mechanoprotective mechanism adapts the cell to changes in mechanical tension by coupling PM and actin cytoskeleton remodeling