Measuring mechanical tension across vinculin reveals regulation of focal adhesion dynamics

Grashoff, Carsten; Hoffman, Brenton D.; Brenner, Michael D.; Zhou, Ruobo; Parsons, Maddy; Yang, Michael T.; McLean, Mark A.; Sligar, Stephen G.; Chen, Christopher; Ha, Taekjip; Schwartz, Martin A.

doi:10.1038/nature09198

Cited by 1,335 publications

(1,606 citation statements)

References 30 publications

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“…Finally, the driving force for growth of the plaque is assumed to be the chemical potential difference between plaque units recruited to the plaque and those in the cytosol. In particular, the work done by the contractile stress as the new units are recruited is expected to facilitate their incorporation in the plaque (22). Following this line of reasoning, we express …”

Section: Methodsmentioning

confidence: 99%

Multiscale model predicts increasing focal adhesion size with decreasing stiffness in fibrous matrices

Cao

Ban

Baker

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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We describe a multiscale model that incorporates force-dependent mechanical plasticity induced by interfiber cross-link breakage and stiffness-dependent cellular contractility to predict focal adhesion (FA) growth and mechanosensing in fibrous extracellular matrices (ECMs). The model predicts that FA size depends on both the stiffness of ECM and the density of ligands available to form adhesions. Although these two quantities are independent in commonly used hydrogels, contractile cells break cross-links in soft fibrous matrices leading to recruitment of fibers, which increases the ligand density in the vicinity of cells. Consequently, although the size of focal adhesions increases with ECM stiffness in nonfibrous and elastic hydrogels, plasticity of fibrous networks leads to a departure from the well-described positive correlation between stiffness and FA size. We predict a phase diagram that describes nonmonotonic behavior of FA in the space spanned by ECM stiffness and recruitment index, which describes the ability of cells to break cross-links and recruit fibers. The predicted decrease in FA size with increasing ECM stiffness is in excellent agreement with recent observations of cell spreading on electrospun fiber networks with tunable cross-link strengths and mechanics. Our model provides a framework to analyze cell mechanosensing in nonlinear and inelastic ECMs.focal adhesion | mechanosensing | cell contractility | matrix physical remodeling | Rho pathway F ocal adhesions (FAs) are large macromolecular assemblies through which mechanical force and regulatory signals are transmitted between the extracellular matrix (ECM) and cells. FAs play important roles in many cellular behaviors, including proliferation, differentiation, and locomotion, and pathological processes like tumorigenesis and wound healing (1-4). For this reason, intense efforts have been devoted to understanding how key signaling molecules and ECM characteristics influence the formation and growth of FAs. In particular, in vitro studies using elastic hydrogels have shown that forces generated by actomyosin contraction are essential for the stabilization of FAs (5, 6). Numerous observations have convincingly demonstrated that cells form larger FAs as well as develop higher intracellular traction forces on stiffer ECMs (7,8), evidencing the mechanosensitive nature of FAs which has been quantitatively modeled using different (continuum, coarse-grain, and molecular) approaches (9, 10).It must be pointed out that in all of the aforementioned investigations, the substrates considered were flat (2D) and linear elastic. However, in vivo, many cells reside within 3D fibrous scaffolds where the density and diameter of fibers can vary depending on the nature of the tissue (11-13). The local architecture of these fibrous networks may change significantly when cells exert forces on them, leading to phenomena such as nonlinear stiffening, reorientation, and physical remodeling of the ECM (14, 15). Our recent study on cells in synthetic fibrous matrices wit...

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Section: Methodsmentioning

confidence: 99%

Multiscale model predicts increasing focal adhesion size with decreasing stiffness in fibrous matrices

Cao

Ban

Baker

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

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“…As a postdoc in the lab of biomedical engineer Martin Schwartz at the University of Virginia in Charlottesville, Grashoff worked with col leagues to develop one of the first FRET based tension sensors, which they described in a 2010 paper 7 . "We had this idea that we would use this very elastic protein that you find in spider silk to link the two fluorophores to each other, " Gra shoff says.…”

Section: Reprinted From H Van Hoorn Et Almentioning

confidence: 99%

“…When they expressed the sensor protein in cells, they observed that vin culin experiences piconewton scale forces that change as focal adhesions assemble and disas semble during cell migration 7 .…”

Section: Reprinted From H Van Hoorn Et Almentioning

confidence: 99%

A measure of molecular muscle

Eisenstein¹

2017

Nature

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“…By inserting this module into a target molecule, they visualized the tension loaded on the molecule as the distance between the FPs (and thus as the FRET efficiency). Two years later, Grashoff et al modified the linker to a 40-amino-acid-long elastic peptide derived from the spider-silk flagelliform protein, and by inserting this new tension-sensing module (named TSMod) into vinculin, a member of the focal adhesion complex, they successfully visualized the tension force at the focal adhesion complex with piconewton sensitivity (62). After their report was published, many laboratories applied TSMod to various molecules to visualize mechanical stress in living cells (63,64).…”

Section: Visualization Of Physical Stresses In Vivomentioning

confidence: 99%

Future Perspective of Single-Molecule FRET Biosensors and Intravital FRET Microscopy

Hirata

Kiyokawa

2016

Biophysical Journal

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Fö rster (or fluorescence) resonance energy transfer (FRET) is a nonradiative energy transfer process between two fluorophores located in close proximity to each other. To date, a variety of biosensors based on the principle of FRET have been developed to monitor the activity of kinases, proteases, GTPases or lipid concentration in living cells. In addition, generation of biosensors that can monitor physical stresses such as mechanical power, heat, or electric/magnetic fields is also expected based on recent discoveries on the effects of these stressors on cell behavior. These biosensors can now be stably expressed in cells and mice by transposon technologies. In addition, two-photon excitation microscopy can be used to detect the activities or concentrations of bioactive molecules in vivo. In the future, more sophisticated techniques for image acquisition and quantitative analysis will be needed to obtain more precise FRET signals in spatiotemporal dimensions. Improvement of tissue/organ position fixation methods for mouse imaging is the first step toward effective image acquisition. Progress in the development of fluorescent proteins that can be excited with longer wavelength should be applied to FRET biosensors to obtain deeper structures. The development of computational programs that can separately quantify signals from single cells embedded in complicated three-dimensional environments is also expected. Along with the progress in these methodologies, two-photon excitation intravital FRET microscopy will be a powerful and valuable tool for the comprehensive understanding of biomedical phenomena.Since the discovery of green fluorescent protein (GFP) (1), scientists have been widely employing this gene-encoded fluorescent protein (FP) to investigate the spatiotemporal dynamics of molecules with subcellular resolution. One of the applications of FP engineering is the development of biosensors based on the principle of Förster (or fluorescence) resonance energy transfer (FRET) (2). FRET is a nonradiative energy transfer process between two fluorophores located in close proximity to each other, and its efficiency is strongly dependent on the distance between the fluorophores. More precisely, the energy transfer rate (k t ) from a donor to an acceptor fluorophore is calculated in the following Förster's equation;where J is the overlap of donor emission and acceptor excitation spectra, k 2 is an orientation factor of transition moment (a factor determined by the relative orientation of the two fluorophores), n is a refractive index, R is the distance between the donor and acceptor fluorophores, and k f is the donor fluorescence emission speed. Therefore, FRET efficiency is determined by the distance and orientation of the two fluorophores. To measure FRET efficiency, there are roughly two methods; ratiometric analysis and lifetime analysis. Ratiometric analysis utilizes fluorescence intensity of an acceptor (e.g., yellow FP (YFP)) and a donor (e.g., cyan FP (CFP)) upon the donor excitation. Because accept...

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Measuring mechanical tension across vinculin reveals regulation of focal adhesion dynamics

Cited by 1,335 publications

References 30 publications

Multiscale model predicts increasing focal adhesion size with decreasing stiffness in fibrous matrices

Multiscale model predicts increasing focal adhesion size with decreasing stiffness in fibrous matrices

A measure of molecular muscle

Future Perspective of Single-Molecule FRET Biosensors and Intravital FRET Microscopy

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