Determinants of maximal force transmission in a motor-clutch model of cell traction in a compliant microenvironment

Benjamin L. Bangasser, Steven S. Rosenfeld, David J. Odde

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155 Scopus citations


The mechanical stiffness of a cell's environment exerts a strong, but variable, influence on cell behavior and fate. For example, different cell types cultured on compliant substrates have opposite trends of cell migration and traction as a function of substrate stiffness. Here, we describe how a motor-clutch model of cell traction, which exhibits a maximum in traction force with respect to substrate stiffness, may provide a mechanistic basis for understanding how cells are tuned to sense the stiffness of specific microenvironments. We find that the optimal stiffness is generally more sensitive to clutch parameters than to motor parameters, but that single parameter changes are generally only effective over a small range of values. By contrast, dual parameter changes, such as coordinately increasing the numbers of both motors and clutches offer a larger dynamic range for tuning the optimum. The model exhibits distinct regimes: at high substrate stiffness, clutches quickly build force and fail (so-called frictional slippage), whereas at low substrate stiffness, clutches fail spontaneously before the motors can load the substrate appreciably (a second regime of frictional slippage). Between the two extremes, we find the maximum traction force, which occurs when the substrate load-and-fail cycle time equals the expected time for all clutches to bind. At this stiffness, clutches are used to their fullest extent, and motors are therefore resisted to their fullest extent. The analysis suggests that coordinate parameter shifts, such as increasing the numbers of motors and clutches, could underlie tumor progression and collective cell migration.

Original languageEnglish (US)
Pages (from-to)581-592
Number of pages12
JournalBiophysical journal
Issue number3
StatePublished - Aug 6 2013

Bibliographical note

Funding Information:
This project was supported by National Institutes of Health (NIH) grant RC1-CA-145044. This material is also based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant Number 00006595.


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