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Understanding cytoskeletal avalanches using mechanical stability analysis.
Floyd, Carlos; Levine, Herbert; Jarzynski, Christopher; Papoian, Garegin A.
Afiliação
  • Floyd C; Biophysics Program, University of Maryland, College Park, MD 20742.
  • Levine H; Center for Theoretical Biological Physics, Northeastern University, Boston, MA 02115.
  • Jarzynski C; Department of Physics, Northeastern University, Boston, MA 02115.
  • Papoian GA; Department of Bioengineering, Northeastern University, Boston, MA 02115.
Proc Natl Acad Sci U S A ; 118(41)2021 10 12.
Article em En | MEDLINE | ID: mdl-34611021
Eukaryotic cells are mechanically supported by a polymer network called the cytoskeleton, which consumes chemical energy to dynamically remodel its structure. Recent experiments in vivo have revealed that this remodeling occasionally happens through anomalously large displacements, reminiscent of earthquakes or avalanches. These cytoskeletal avalanches might indicate that the cytoskeleton's structural response to a changing cellular environment is highly sensitive, and they are therefore of significant biological interest. However, the physics underlying "cytoquakes" is poorly understood. Here, we use agent-based simulations of cytoskeletal self-organization to study fluctuations in the network's mechanical energy. We robustly observe non-Gaussian statistics and asymmetrically large rates of energy release compared to accumulation in a minimal cytoskeletal model. The large events of energy release are found to correlate with large, collective displacements of the cytoskeletal filaments. We also find that the changes in the localization of tension and the projections of the network motion onto the vibrational normal modes are asymmetrically distributed for energy release and accumulation. These results imply an avalanche-like process of slow energy storage punctuated by fast, large events of energy release involving a collective network rearrangement. We further show that mechanical instability precedes cytoquake occurrence through a machine-learning model that dynamically forecasts cytoquakes using the vibrational spectrum as input. Our results provide a connection between the cytoquake phenomenon and the network's mechanical energy and can help guide future investigations of the cytoskeleton's structural susceptibility.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Estresse Fisiológico / Estresse Mecânico / Citoesqueleto / Simulação por Computador / Fenômenos Biofísicos Limite: Humans Idioma: En Revista: Proc Natl Acad Sci U S A Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Estresse Fisiológico / Estresse Mecânico / Citoesqueleto / Simulação por Computador / Fenômenos Biofísicos Limite: Humans Idioma: En Revista: Proc Natl Acad Sci U S A Ano de publicação: 2021 Tipo de documento: Article