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Data for Image based modeling of bleb site selection
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Collier, Sharon, Paschke, Peggy, Kay, Robert R. and Bretschneider, Till (2017) Data for Image based modeling of bleb site selection. [Dataset]
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readme.docx Available under License Creative Commons Attribution 4.0. Download (102Kb) |
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Archive (ZIP) (Raw image data, QuimP analysis files)
PaperDataJuly2017.zip Available under License Creative Commons Attribution 4.0. Download (547Mb) |
Official URL: https://wrap.warwick.ac.uk/90238/
Abstract
Cells often employ fast, pressure-driven blebs to move through tissues or against mechanical resistance, but how bleb sites are selected and directed to the cell front remains an open question. Previously, we found that chemotaxing Dictyostelium cells preferentially bleb from concave regions, where membrane tension facilitates membrane-cortex detachment. Now, through a novel modeling approach based on actual cell contours, we use cell geometry to predict where blebs will form in migrating cells. We find that cell geometry alone, and by implication, physical forces in the membrane, is sufficient to predict the location of blebs in rounded cells moving in a highly resistive environment. The model is less successful with more polarized cells moving against less resistance, but can be greatly improved by positing a front-to-back gradient in membrane-cortex adhesion. In accord with this prediction, we find that Talin, which links membrane and cortex, forms such a front-to-back gradient. Thus our model provides a means of dissecting out the role of physical forces in controlling where blebs form, and shows that in certain circumstances they could be the major determining factor.
Item Type: | Dataset | ||||||||||||
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Subjects: | Q Science > QH Natural history > QH301 Biology | ||||||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Chemistry Faculty of Science, Engineering and Medicine > Science > Computer Science |
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Type of Data: | Raw image data, and processed files including QuimP segmentation output | ||||||||||||
Library of Congress Subject Headings (LCSH): | Cytology, Cell membranes, Dictyostelium | ||||||||||||
Publisher: | University of Warwick, Department of Computer Science | ||||||||||||
Official Date: | 23 August 2017 | ||||||||||||
Dates: |
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Status: | Not Peer Reviewed | ||||||||||||
Publication Status: | Published | ||||||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||||||
Description: | We include all the raw image data and QuimP analysis used in the paper. Data is subdivided into folders according to percentage of agarose overlay used (either 2% or 0pt7%), each dataset is then further subdivided into folders for individual cells analysed. QuimP file types: - Parameter files (.paQP) Store segmentation parameters, frame rate, scale and pixel size - Snake contour data (.snQP) Segmentation infro: Node positions, Node speed between frames, fluorescence intensity for each channel, x and y coordinates where fluorescence was sampled along the contour - Frame statistics (.stQP) Statistics for each frame rather than for individual nodes - Map files (.maQP) Motility map of node speeds over time, convexity map of curvature over time, Fluorescence maps of cortical fluorescence over time - Scalable vector graphics output (.svg) Cell track showing cell outlines for all time frames overlayed |
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