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      Substrate composition directs slime molds behavior

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          Abstract

          Cells, including unicellulars, are highly sensitive to external constraints from their environment. Amoeboid cells change their cell shape during locomotion and in response to external stimuli. Physarum polycephalum is a large multinucleated amoeboid cell that extends and develops pseudopods. In this paper, changes in cell behavior and shape were measured during the exploration of homogenous and non-homogenous environments that presented neutral, and nutritive and/or adverse substances. In the first place, we developed a fully automated image analysis method to measure quantitatively changes in both migration and shape. Then we measured various metrics that describe the area covered, the exploration dynamics, the migration rate and the slime mold shape. Our results show that: (1) Not only the nature, but also the spatial distribution of chemical substances affect the exploration behavior of slime molds; (2) Nutritive and adverse substances both slow down the exploration and prevent the formation of pseudopods; and (3) Slime mold placed in an adverse environment preferentially occupies previously explored areas rather than unexplored areas using mucus secretion as a buffer. Our results also show that slime molds migrate at a rate governed by the substrate up until they get within a critical distance to chemical substances.

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          An efficient k-means clustering algorithm: analysis and implementation

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            Plasticity of cell migration: a multiscale tuning model

            Cell migration underlies tissue formation, maintenance, and regeneration as well as pathological conditions such as cancer invasion. Structural and molecular determinants of both tissue environment and cell behavior define whether cells migrate individually (through amoeboid or mesenchymal modes) or collectively. Using a multiparameter tuning model, we describe how dimension, density, stiffness, and orientation of the extracellular matrix together with cell determinants—including cell–cell and cell–matrix adhesion, cytoskeletal polarity and stiffness, and pericellular proteolysis—interdependently control migration mode and efficiency. Motile cells integrate variable inputs to adjust interactions among themselves and with the matrix to dictate the migration mode. The tuning model provides a matrix of parameters that control cell movement as an adaptive and interconvertible process with relevance to different physiological and pathological contexts.
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              Mechanical integration of actin and adhesion dynamics in cell migration.

              Directed cell migration is a physical process that requires dramatic changes in cell shape and adhesion to the extracellular matrix. For efficient movement, these processes must be spatiotemporally coordinated. To a large degree, the morphological changes and physical forces that occur during migration are generated by a dynamic filamentous actin (F-actin) cytoskeleton. Adhesion is regulated by dynamic assemblies of structural and signaling proteins that couple the F-actin cytoskeleton to the extracellular matrix. Here, we review current knowledge of the dynamic organization of the F-actin cytoskeleton in cell migration and the regulation of focal adhesion assembly and disassembly with an emphasis on how mechanical and biochemical signaling between these two systems regulate the coordination of physical processes in cell migration.
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                Author and article information

                Contributors
                fp@gatech.edu
                audrey.dussutour@univ-tlse3.fr
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                28 October 2019
                28 October 2019
                2019
                : 9
                : 15444
                Affiliations
                [1 ]ISNI 0000 0001 2097 4943, GRID grid.213917.f, School of Civil and Environmental Engineering, , Georgia Institute of Technology, ; Atlanta, GA USA
                [2 ]Research Centre on Animal Cognition (CRCA), Centre for Integrative Biology (CBI), Toulouse University, CNRS, UPS, Toulouse, France
                Author information
                http://orcid.org/0000-0003-1248-499X
                http://orcid.org/0000-0002-6083-4272
                Article
                50872
                10.1038/s41598-019-50872-z
                6817824
                31659267
                b405be38-2b86-4aee-84cd-dcc3f1733f3f
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 10 July 2019
                : 17 September 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000001, National Science Foundation (NSF);
                Award ID: CMMI#1552368
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100001665, Agence Nationale de la Recherche (French National Research Agency);
                Award ID: ANR-17-CE02-0019-01 -SMART- 644 CELL
                Award ID: ANR-17-CE02-0019-01 -SMART- 644 CELL
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                single-cell imaging,time series,amoeboid migration
                Uncategorized
                single-cell imaging, time series, amoeboid migration

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