2019
DOI: 10.1038/s41467-019-11313-7
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Single-crosslink microscopy in a biopolymer network dissects local elasticity from molecular fluctuations

Abstract: Polymer networks are fundamental from cellular biology to plastics technology but their intrinsic inhomogeneity is masked by the usual ensemble-averaged measurements. Here, we construct direct maps of crosslinks—symbolic depiction of spatially-distributed elements highlighting their physical features and the relationships between them—in an actin network. We selectively label crosslinks with fluorescent markers, track their thermal fluctuations, and characterize the local elasticity and cross-correlations betw… Show more

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Cited by 14 publications
(5 citation statements)
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“…5d). In the linear regime, the filament is characterized by two spring constants transverse () and parallel () to the filament with 27,28 . The filament is clamped at one end with a fixed position and a fixed orientation θ .…”
Section: Resultsmentioning
confidence: 99%
“…5d). In the linear regime, the filament is characterized by two spring constants transverse () and parallel () to the filament with 27,28 . The filament is clamped at one end with a fixed position and a fixed orientation θ .…”
Section: Resultsmentioning
confidence: 99%
“…An ongoing endeavor in chemistry and materials science is to develop synthetic matter that recapitulates mechanical features of biological cells, tissues, and organs. Significant progress has been achieved on the subcellular and cellular levels 1 , 2 . Early studies revealed a strong shear-stiffening response universal to cytoskeletal and extracellular biopolymer networks (Fig.…”
Section: Introductionmentioning
confidence: 99%
“…In older theory of rubberlike elasticity, large crosslink fluctuations are predicted in a phantom network of chains that unlike entangled chains can cross one another freely 28 . When one makes the assumption that fluctuation amplitude reflects primarily local stiffness with only second-order damping from local viscosity, then it scales as the square root of inverse stiffness, 29 , where is elasticity and is the Boltzmann constant. Data analyzed this way extrapolate to identity between and at (Fig.…”
Section: Resultsmentioning
confidence: 99%