Extracting, quantifying, and comparing dynamical and biomechanical properties of living matter through single particle tracking

Abstract

A panoply of new tools for tracking single particles and molecules has led to novel insights into physical properties of living matter governing cellular development and function, health and disease.

Variance sum rule for entropy production

“…1) inapplicable. Moreover, in many cases, only a spatial degree of freedom xt is monitored, e.g., in particle-tracking experiments ( 24 , 25 ) or in detecting cellular fluctuations ( 26 , 27 ). To apply the VSR in these situations, it is necessary to model the NESS by making assumptions about the interaction FtI and the underlying degrees of freedom.…”

The random walker's toolbox for analyzing single-particle tracking data

“…35 Yet frequently, deviations from this simple and universal random motion have been observed, hinting at more complex stochastic processes that underlie erratic trajectories. 3,[36][37][38] Assuming standard Brownian motion in such cases neglects the wealth of additional information contained in the acquired tracks and it may render retrieved diffusion constants meaningless as it refers to an oversimplified or inappropriate transport process.…”

“…being defined in analogy to the TA-MSD [eqn (3)]. The trajectory's fourth moment as defined in eqn ( 13) is implemented in the routine -ta_quad.m (alternatively it can be obtained with -ta_mom.m setting q = 4) and the gaussianity of a single trajectory, as defined in eqn (12), is implemented in routine -ta_gaussianity.m with d = 1,2 for one-and twodimensional trajectories, respectively.…”

“…The avalanche-like introduction of advanced, computercontrolled image acquisition methods has massively fostered the use of single-particle tracking (SPT) experiments to quantify transport processes. [1][2][3] Today, SPT is frequently used to probe and decipher transport and self-organization phenomena in complex dynamical systems on many length scales, from single molecules on bio-mimetic membranes, via micrometer-sized objects in living cells and colloidal suspensions, up to foraging animals or traveling humans. [4][5][6] In many cases, however, highly advanced measurement techniques and tracking algorithms are not complemented by subsequent analyses on the same quality level, leaving the data's full potential unexploited.…”

Trapped tracer in a non-equilibrium bath: dynamics and energetics

“…The shape of a cell is formed by the cytoskeleton-an active viscoelastic network (gel) of cross-linked filaments and motor proteins. 32,[51][52][53] Harnessing energy from ATP hydrolysis, motors generate force along the filaments, a phenomenon which renders the network dynamic and drives it out of equilibrium. 1,54 Naturally, a probe particle immersed inside the network exhibits distinct dynamical properties such as enhanced diffusion and a non-Boltzmann distribution of displacements as observed in numerous experiments.…”