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Mechanism of shape determination in motile cells

Author

Listed:
  • Kinneret Keren

    (and
    Technion- Israel Institute of Technology)

  • Zachary Pincus

    (and
    Cellular and Developmental Biology, Yale University, New Haven, Connecticut 06520, USA)

  • Greg M. Allen

    (and)

  • Erin L. Barnhart

    (and)

  • Gerard Marriott

    (University of Wisconsin at Madison, Madison, Wisconsin 53706, USA)

  • Alex Mogilner

    (University of California, Davis, California 95616, USA)

  • Julie A. Theriot

    (and
    Stanford University School of Medicine, Stanford, California 94305, USA)

Abstract

The shape of motile cells is determined by many dynamic processes spanning several orders of magnitude in space and time, from local polymerization of actin monomers at subsecond timescales to global, cell-scale geometry that may persist for hours. Understanding the mechanism of shape determination in cells has proved to be extremely challenging due to the numerous components involved and the complexity of their interactions. Here we harness the natural phenotypic variability in a large population of motile epithelial keratocytes from fish (Hypsophrys nicaraguensis) to reveal mechanisms of shape determination. We find that the cells inhabit a low-dimensional, highly correlated spectrum of possible functional states. We further show that a model of actin network treadmilling in an inextensible membrane bag can quantitatively recapitulate this spectrum and predict both cell shape and speed. Our model provides a simple biochemical and biophysical basis for the observed morphology and behaviour of motile cells.

Suggested Citation

  • Kinneret Keren & Zachary Pincus & Greg M. Allen & Erin L. Barnhart & Gerard Marriott & Alex Mogilner & Julie A. Theriot, 2008. "Mechanism of shape determination in motile cells," Nature, Nature, vol. 453(7194), pages 475-480, May.
  • Handle: RePEc:nat:nature:v:453:y:2008:i:7194:d:10.1038_nature06952
    DOI: 10.1038/nature06952
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    Cited by:

    1. Henry Cavanagh & Andreas Mosbach & Gabriel Scalliet & Rob Lind & Robert G. Endres, 2021. "Physics-informed deep learning characterizes morphodynamics of Asian soybean rust disease," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    2. Jacob C Kimmel & Amy Y Chang & Andrew S Brack & Wallace F Marshall, 2018. "Inferring cell state by quantitative motility analysis reveals a dynamic state system and broken detailed balance," PLOS Computational Biology, Public Library of Science, vol. 14(1), pages 1-29, January.
    3. Taeseok Daniel Yang & Jin-Sung Park & Youngwoon Choi & Wonshik Choi & Tae-Wook Ko & Kyoung J Lee, 2011. "Zigzag Turning Preference of Freely Crawling Cells," PLOS ONE, Public Library of Science, vol. 6(6), pages 1-9, June.
    4. Guangjie Cui & Yunbo Liu & Di Zu & Xintao Zhao & Zhijia Zhang & Do Young Kim & Pramith Senaratne & Aaron Fox & David Sept & Younggeun Park & Somin Eunice Lee, 2023. "Phase intensity nanoscope (PINE) opens long-time investigation windows of living matter," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    5. Chao Jiang & Hong-Yu Luo & Xinpeng Xu & Shuo-Xing Dou & Wei Li & Dongshi Guan & Fangfu Ye & Xiaosong Chen & Ming Guo & Peng-Ye Wang & Hui Li, 2023. "Switch of cell migration modes orchestrated by changes of three-dimensional lamellipodium structure and intracellular diffusion," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    6. Jacob M Kowalewski & Hamdah Shafqat-Abbasi & Mehrdad Jafari-Mamaghani & Bereket Endrias Ganebo & Xiaowei Gong & Staffan Strömblad & John G Lock, 2015. "Disentangling Membrane Dynamics and Cell Migration; Differential Influences of F-actin and Cell-Matrix Adhesions," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-23, August.
    7. James Burgess & Jeffrey J. Nirschl & Maria-Clara Zanellati & Alejandro Lozano & Sarah Cohen & Serena Yeung-Levy, 2024. "Orientation-invariant autoencoders learn robust representations for shape profiling of cells and organelles," Nature Communications, Nature, vol. 15(1), pages 1-14, December.

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