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Loops versus lines and the compression stiffening of cells

ORAL

Abstract

Tissues exhibit a nonlinear phenomenon known as compression stiffening: an increase in moduli with increasing uniaxial compressive strain. Does such a phenomenon exist in single cells, which are the building blocks of tissues? One expects an individual cell to compression soften since the semiflexible biopolymer cytoskeletal network maintains the mechanical integrity of the cell. To the contrary, we find that mouse embryonic fibroblasts (mEFs) compression stiffen. To understand this finding, we uncover potential mechanisms for compression stiffening. First, we study a single semiflexible polymer loop modeling the actomyosin cortex enclosing a viscous medium modeled as an incompressible fluid. Second, we study a two-dimensional semiflexible polymer network interspersed with area-conserving loops, which are a proxy for vesicles and fluid-based organelles. Third, we study two-dimensional fiber networks with angular-constraining crosslinks. We find for the fiber network with area-conserving loops model that the stress-strain curves are sensitive to the packing fraction and size distribution of the area-conserving loops, thereby creating a mechanical fingerprint across different cell types. We make comparisons of these models with fibrin network experiments interlaced with beads.

Presenters

  • Mahesh Chandrasekhar Gandikota

    Syracuse University

Authors

  • Mahesh Chandrasekhar Gandikota

    Syracuse University

  • Katarzyna Pogoda

    Institute of Nuclear Physics, Polish Academy of Sciences

  • Anne van Oosten

    Leiden Academic Centre for Drug Research, Leiden University

  • Tyler Engstrom

    Physics, William and Hobart Smith College, Hobart and William Smith Colleges

  • Alison Patteson

    Syracuse University, Physics, Syracuse University, Department of Physics, Syracuse University

  • Paul Janmey

    Institute for Medicine and Engineering, University of Pennsylvania

  • Jennifer Schwarz

    Syracuse University, Physics, Syracuse University