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Computational analysis of the tether-pulling experiment to probe plasma membrane-cytoskeleton interaction in cells

  • Kristopher R. Schumacher
  • , Aleksander S. Popel
  • , Bahman Anvari
  • , William E. Brownell
  • , Alexander A. Spector

Research output: Contribution to journalArticlepeer-review

Abstract

Tethers are thin membrane tubes that can be formed when relatively small and localized forces are applied to cellular membranes and lipid bilayers. Tether pulling experiments have been used to better understand the fine membrane properties. These include the interaction between the plasma membrane and the underlying cytoskeleton, which is an important factor affecting membrane mechanics. We use a computational method aimed at the interpretation and design of tether pulling experiments in cells with a strong membrane-cytoskeleton attachment. In our model, we take into account the detailed information in the topology of bonds connecting the plasma membrane and the cytoskeleton. We compute the force-dependent piecewise membrane deflection and bending as well as modes of stored energy in three major regions of the system: body of the tether, membrane-cytoskeleton attachment zone, and the transition zone between the two. We apply our method to three cells: cochlear outer hair cells (OHCs), human embryonic kidney (HEK) cells, and Chinese hamster ovary (CHO) cells. OHCs have a special system of pillars connecting the membrane and the cytoskeleton, and HEK and CHO cells have the membrane-cytoskeleton adhesion arrangement via bonds (e.g., PIP2), which is common to many other cells. We also present a validation of our model by using experimental data on CHO and HEK cells. The proposed method can be an effective tool in the analyses of experiments to probe the properties of cellular membranes.

Original languageEnglish (US)
Article number041905
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume80
Issue number4
DOIs
StatePublished - Oct 6 2009

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Statistical and Nonlinear Physics
  • Statistics and Probability

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