Automated characterization of cell shape changes during amoeboid motility by skeletonization

<p>Abstract</p> <p>Background</p> <p>The ability of a cell to change shape is crucial for the proper function of many cellular processes, including cell migration. One type of cell migration, referred to as amoeboid motility, involves alternating cycles of morphological expansion and retraction. Traditionally, this process has been characterized by a number of parameters providing global information about shape changes, which are insufficient to distinguish phenotypes based on local pseudopodial activities that typify amoeboid motility.</p> <p>Results</p> <p>We developed a method that automatically detects and characterizes pseudopodial behavior of cells. The method uses skeletonization, a technique from morphological image processing to reduce a shape into a series of connected lines. It involves a series of automatic algorithms including image segmentation, boundary smoothing, skeletonization and branch pruning, and takes into account the cell shape changes between successive frames to detect protrusion and retraction activities. In addition, the activities are clustered into different groups, each representing the protruding and retracting history of an individual pseudopod.</p> <p>Conclusions</p> <p>We illustrate the algorithms on movies of chemotaxing <it>Dictyostelium </it>cells and show that our method makes it possible to capture the spatial and temporal dynamics as well as the stochastic features of the pseudopodial behavior. Thus, the method provides a powerful tool for investigating amoeboid motility.</p

Dynacortin facilitates polarization of chemotaxing cells

<p>Abstract</p> <p>Background</p> <p>Cell shape changes during cytokinesis and chemotaxis require regulation of the actin cytoskeletal network. Dynacortin, an actin cross-linking protein, localizes to the cell cortex and contributes to cortical resistance, thereby helping to define the cell shape changes of cytokinesis. Dynacortin also becomes highly enriched in cortical protrusions, which are sites of new actin assembly.</p> <p>Results</p> <p>We studied the effect of dynacortin on cell motility during chemotaxis and on actin dynamics <it>in vivo </it>and <it>in vitro</it>. Dynacortin enriches with the actin, particularly at the leading edge of chemotaxing cells. Cells devoid of dynacortin do not become as polarized as wild-type control cells but move with similar velocities as wild-type cells. In particular, they send out multiple pseudopods that radiate at a broader distribution of angles relative to the chemoattractant gradient. Wild-type cells typically only send out one pseudopod at a time that does not diverge much from 0° on average relative to the gradient. Though <it>dynacortin</it>-deficient cells show normal bulk (whole-cell) actin assembly upon chemoattractant stimulation, dynacortin can promote actin assembly <it>in vitro</it>. By fluorescence spectroscopy, co-sedimentation and transmission electron microscopy, dynacortin acts as an actin scaffolder in which it assembles actin monomers into polymers with a stoichiometry of 1 Dyn₂:1 actin under salt conditions that disfavor polymer assembly.</p> <p>Conclusion</p> <p>Dynacortin contributes to cell polarization during chemotaxis. By cross-linking and possibly stabilizing actin polymers, dynacortin also contributes to cortical viscoelasticity, which may be critical for establishing cell polarity. Though not essential for directional sensing or motility, dynacortin is required to establish cell polarity, the third core feature of chemotaxis.</p

2010 Automated characterization of cell shape changes during amoeboid motility by skeletonization

Abstract Background: The ability of a cell to change shape is crucial for the proper function of many cellular processes, including cell migration. One type of cell migration, referred to as amoeboid motility, involves alternating cycles of morphological expansion and retraction. Traditionally, this process has been characterized by a number of parameters providing global information about shape changes, which are insufficient to distinguish phenotypes based on local pseudopodial activities that typify amoeboid motility. Results: We developed a method that automatically detects and characterizes pseudopodial behavior of cells. The method uses skeletonization, a technique from morphological image processing to reduce a shape into a series of connected lines. It involves a series of automatic algorithms including image segmentation, boundary smoothing, skeletonization and branch pruning, and takes into account the cell shape changes between successive frames to detect protrusion and retraction activities. In addition, the activities are clustered into different groups, each representing the protruding and retracting history of an individual pseudopod. Conclusions: We illustrate the algorithms on movies of chemotaxing Dictyostelium cells and show that our method makes it possible to capture the spatial and temporal dynamics as well as the stochastic features of the pseudopodial behavior. Thus, the method provides a powerful tool for investigating amoeboid motility