26 research outputs found

    Dynamics of Membrane Tethers Reveal Novel Aspects of Cytoskeleton-Membrane Interactions in Axons

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    AbstractMechanical properties of cell membranes are known to be significantly influenced by the underlying cortical cytoskeleton. The technique of pulling membrane tethers from cells is one of the most effective ways of studying the membrane mechanics and the membrane-cortex interaction. In this article, we show that axon membranes make an interesting system to explore as they exhibit both free membrane-like behavior where the tether-membrane junction is movable on the surface of the axons (unlike many other cell membranes) as well as cell-like behavior where there are transient and spontaneous eruptions in the tether force that vanish when F-actin is depolymerized. We analyze the passive and spontaneous responses of axonal membrane tethers and propose theoretical models to explain the observed behavior

    Tightening the knot in phytochrome by single molecule atomic force microscopy

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    A growing number of proteins have been shown to adopt knotted folds. Yet the biological roles and biophysical properties of these knots remain poorly understood. We have used protein engineering and atomic force microscopy to explore single-molecule mechanics of the figure-of-eight knot in the chromophore-binding domain of the red/far red photoreceptor, phytochrome. Under load, apo phytochrome unfolds at forces of ~47 pN, while phytochrome carrying its covalently bound tetrapyrrole chromophore unfolds at ~73 pN. These forces are among the lowest measured in mechanical protein unfolding, hence the presence of the knot does not automatically indicate a super-stable protein. Our experiments reveal a stable intermediate along the mechanical unfolding pathway, reflecting sequential unfolding of two distinct subdomains in phytochrome, potentially the GAF and PAS domains. For the first time, our experiments allow direct determination of knot size under load. In the unfolded chain, the tightened knot is reduced to 17 amino acids, resulting in apparent shortening of the polypeptide chain by 6.2 nm. Steered molecular dynamics simulations corroborate this number. Finally, we found that covalent phytochrome dimers created for these experiments retain characteristic photoreversibility, unexpectedly arguing against dramatic rearrangement of the native GAF dimer interface upon photoconversion.Comment: 12 pages plus five figures; has been submitted to Biophysical J. Replacement on 9/16 is ONLY to correct a typo in the meta data; the uploaded file is identical to first versio

    The Mechanics of Filopodial Retraction

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    Single molecule mechanics of the kinesin neck

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    The sense is in the fingertips

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    Full distance-resolved folding energy landscape of one single protein molecule

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    Kinetic bulk and single molecule folding experiments characterize barrier properties but the shape of folding landscapes between barrier top and native state is difficult to access. Here, we directly extract the full free energy landscape of a single molecule of the GCN4 leucine zipper using dual beam optical tweezers. To this end, we use deconvolution force spectroscopy to follow an individual molecule’s trajectory with high temporal and spatial resolution. We find a heterogeneous energy landscape of the GCN4 leucine zipper domain. The energy profile is divided into two stable C-terminal heptad repeats and two less stable repeats at the N-terminus. Energies and transition barrier positions were confirmed by single molecule kinetic analysis. We anticipate that deconvolution sampling is a powerful tool for the model-free investigation of protein energy landscapes

    A new color augmentation method for deep learning segmentation of histological images

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    International audienceThis paper addresses the problem of labeled data insufficiency in neural network training for semantic segmentation of color-stained histological images acquired via Whole Slide Imaging. It proposes an efficient image augmentation method to alleviate the demand for a large amount of labeled data and improve the network's generalization capacity. Typical image augmentation in bioimaging involves geometric transformation. Here, we propose a new image augmentation technique by combining the structure of one image with the color appearance of another image to construct augmented images on-the-fly for each training iteration. We show that it improves performance in the segmentation of histological images of human skin, and also offers better results when combined with geometric transformation
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