2016
DOI: 10.3762/bjnano.7.42
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Active multi-point microrheology of cytoskeletal networks

Abstract: SummaryActive microrheology is a valuable tool to determine viscoelastic properties of polymer networks. Observing the response of the beads to the excitation of a reference leads to dynamic and morphological information of the material. In this work we present an expansion of the well-known active two-point microrheology. By measuring the response of multiple particles in a viscoelastic medium in response to the excitation of a reference particle, we are able to determine the force propagation in the polymer … Show more

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Cited by 4 publications
(5 citation statements)
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“…al ., 2015 and Paust et. al ., 2016 [42, 43], without any attempts being made to determine G’(ω) and G’’(ω). Our results present the first effort in this direction, and suggest a major improvement over conventional techniques in active microrheology, which employ sinusoidal wave at a certain frequency, so that the response over a large bandwidth requires significantly long measurement times.…”
Section: Discussionmentioning
confidence: 99%
“…al ., 2015 and Paust et. al ., 2016 [42, 43], without any attempts being made to determine G’(ω) and G’’(ω). Our results present the first effort in this direction, and suggest a major improvement over conventional techniques in active microrheology, which employ sinusoidal wave at a certain frequency, so that the response over a large bandwidth requires significantly long measurement times.…”
Section: Discussionmentioning
confidence: 99%
“…It is also essential to characterize and control for non-specific interactions between the bead surface and the protein network, a concern that should be addressed in all types of bead-based measurements on proteins and protein networks ( Chae and Furst, 2005 ; Kirkness et al, 2018 ). OT-MR has been widely applied to characterize network mechanics of cytoskeletal proteins [including actin ( Gittes et al, 1997 ; Brau et al, 2007 ; Lee et al, 2010 ; Grebenkov et al, 2013 ; Atakhorrami et al, 2014 ; Gurmessa et al, 2017 , 2019 ; Ricketts et al, 2018 , 2019 ), intermediate filaments ( Neckernuss et al, 2015 ; Paust et al, 2016 ), and microtubules ( Ricketts et al, 2018 , 2019 )] and of extracellular proteins [including collagen ( Latinovic et al, 2010 ; Shayegan and Forde, 2013 ; Shayegan et al, 2013 ; Jones et al, 2015 ; Staunton et al, 2016 ) and fibrin ( Kotlarchyk et al, 2010 , 2011 ; Piechocka et al, 2010 ; Domínguez-García et al, 2020 )].…”
Section: Mechanics Of Higher-order Protein Fibers and Networkmentioning
confidence: 99%
“…It provides distinct information about the through-space mechanical coupling of the network by analyzing correlated motion between pairs of beads ( Crocker et al, 2000 ). Often one bead is actively displaced with OT and the motion of other (non-optically trapped) beads in the network is recorded, monitoring for example the amplitude and phase lag of their motion relative to the driven particle, which can be used to determine the mechanical transfer function of the network ( Paust et al, 2016 ; Hendricks and Goldman, 2017 ). For higher-frequency information, several beads can be optically trapped simultaneously, and their correlated motion determined either through active oscillation of one particle or through passive recording of their thermally driven dynamics in stationary traps ( Mizuno et al, 2008 ).…”
Section: Mechanics Of Higher-order Protein Fibers and Networkmentioning
confidence: 99%
See 1 more Smart Citation
“…We use established active microrheology techniques and analyzed the viscoelastic response of single MTs in Fourier space (4,(33)(34)(35), expressed by the frequency-dependent viscoelastic shear modulus G(u) ¼ G 0 (u) þ iG 00 (u) as the complex sum of the elastic and viscous moduli G' and G 00 . between the active driving force DF D generated by the oscillating optical trap and the resulting superposition of deformationsũ qn ðuÞ of the MT is assumed.…”
Section: The Viscoelastic Response Of Single Mts Depends On Their Defmentioning
confidence: 99%