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DDC: 570 × Subject: cytoskeleton ×

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Now showing 1 - 3 of 3
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    Membrane Tension Orchestrates Rear Retraction in Matrix-Directed Cell Migration
    (Amsterdam : Elsevier, 2019) Hetmanski, J.H.R.; de, Belly, H.; Busnelli, I.; Waring, T.; Nair, R.V.; Sokleva, V.; Dobre, O.; Cameron, A.; Gauthier, N.; Lamaze, C.; Swift, J.; del, Campo, A.; Starborg, T.; Zech, T.; Goetz, J.G.; Paluch, E.K.; Schwartz, J.-M.; Caswell, P.T.
    In development, wound healing, and cancer metastasis, vertebrate cells move through 3D interstitial matrix, responding to chemical and physical guidance cues. Protrusion at the cell front has been extensively studied, but the retraction phase of the migration cycle is not well understood. Here, we show that fast-moving cells guided by matrix cues establish positive feedback control of rear retraction by sensing membrane tension. We reveal a mechanism of rear retraction in 3D matrix and durotaxis controlled by caveolae, which form in response to low membrane tension at the cell rear. Caveolae activate RhoA-ROCK1/PKN2 signaling via the RhoA guanidine nucleotide exchange factor (GEF) Ect2 to control local F-actin organization and contractility in this subcellular region and promote translocation of the cell rear. A positive feedback loop between cytoskeletal signaling and membrane tension leads to rapid retraction to complete the migration cycle in fast-moving cells, providing directional memory to drive persistent cell migration in complex matrices. © 2019 The AuthorsCell migration through 3D matrix is critical to developmental and disease processes, but the mechanisms that control rear retraction are poorly understood. Hetmanski et al. show that differential membrane tension allows caveolae to form at the rear of migrating cells and activate the contractile actin cytoskeleton to promote rapid retraction. © 2019 The Authors
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    Vinculin binding angle in podosomes revealed by high resolution microscopy
    (San Francisco, CA : Public Library of Science, 2014) Walde, M.; Monypenny, J.; Heintzmann, R.; Jones, G.E.; Cox, S.
    Podosomes are highly dynamic actin-rich adhesive structures formed predominantly by cells of the monocytic lineage, which degrade the extracellular matrix. They consist of a core of F-actin and actin-regulating proteins, surrounded by a ring of adhesion-associated proteins such as vinculin. We have characterised the structure of podosomes in macrophages, particularly the structure of the ring, using three super-resolution fluorescence microscopy techniques: stimulated emission depletion microscopy, structured illumination microscopy and localisation microscopy. Rather than being round, as previously assumed, we found the vinculin ring to be created from relatively straight strands of vinculin, resulting in a distinctly polygonal shape. The strands bind preferentially at angles between 116° and 135°. Furthermore, adjacent vinculin strands are observed nucleating at the corners of the podosomes, suggesting a mechanism for podosome growth.
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    A novel universal algorithm for filament network tracing and cytoskeleton analysis
    (Hoboken, NJ : Wiley, 2021) Flormann, Daniel A.D.; Schu, Moritz; Terriac, Emmanuel; Thalla, Divyendu; Kainka, Lucina; Koch, Marcus; Gad, Annica K.B.; Lautenschläger, Franziska
    The rapid development of advanced microscopy techniques over recent decades has significantly increased the quality of imaging and our understanding of subcellular structures, such as the organization of the filaments of the cytoskeleton using fluorescence and electron microscopy. However, these recent improvements in imaging techniques have not been matched by similar development of techniques for computational analysis of the images of filament networks that can now be obtained. Hence, for a wide range of applications, reliable computational analysis of such two-dimensional methods remains challenging. Here, we present a new algorithm for tracing of filament networks. This software can extract many important parameters from grayscale images of filament networks, including the mesh hole size, and filament length and connectivity (also known as Coordination Number). In addition, the method allows sub-networks to be distinguished in two-dimensional images using intensity thresholding. We show that the algorithm can be used to analyze images of cytoskeleton networks obtained using different advanced microscopy methods. We have thus developed a new improved method for computational analysis of two-dimensional images of filamentous networks that has wide applications for existing imaging techniques. The algorithm is available as open-source software.