Probing short-range protein Brownian motion in the cytoplasm of living cells

Abstract

The translational motion of molecules in cells deviates from what is observed in dilute solutions. Theoretical models provide explanations for this effect but with predictions that drastically depend on the nanoscale organization assumed for macromolecular crowding agents. A conclusive test of the nature of the translational motion in cells is missing owing to the lack of techniques capable of probing crowding with the required temporal and spatial resolution. Here we show that fluorescence-fluctuation analysis of raster scans at variable timescales can provide this information. By using green fluorescent proteins in cells, we measure protein motion at the unprecedented timescale of 1 μs, unveiling unobstructed Brownian motion from 25 to 100 nm, and partially suppressed diffusion above 100 nm. Furthermore, experiments on model systems attribute this effect to the presence of relatively immobile structures rather than to diffusing crowding agents. We discuss the implications of these results for intracellular processes.

Characterizing anomalous diffusion in crowded polymer solutions and gels over five decades in time with variable-lengthscale fluorescence correlation spectroscopy

“…Several strategies have been employed for varying the size of the FCS observation volume, notably decreasing the size of the incoming excitation beam with a variable beam expander 43 or (as done in this study, allowing to cover almost an order of magnitude in lengthscales) with a variable diameter iris 8 . For fluorophores restricted to two-dimensional diffusion, the observation lengthscale can also be changed by placing the diffusion plane slightly out of focus 70 , or by using the information captured in time-lapsed images [71][72][73] . Recently, the possibility to extend the range of FCS measurements to sub-diffraction observation volumes has been demonstrated by a number of groups, using stimulated emission depletion 44,49,74,75 , zero-mode waveguides 76 or near-field optical probes 77,78 .…”

Molecular simulations of cellular processes

“…The third challenge, here defined, shall try to overcome the limitations of the previous steps. Specifically, the force field and reaction scheme of a cell model, parameterized through the two-body approximation in challenge 2, shall be refined by using a large number of data measured under minimally perturbing conditions for the cell (Xia et al 2013;Di Rienzo et al 2014;Gnutt et al 2015;Luchinat and Banci 2017;Liu et al 2017) (Fig. 2c).…”

“…A negative rate, so called sub-diffusion, can originate from weak macromolecular associations and increase, for example, the search efficiency of enzymes for their DNA binding sites (Golding and Cox 2006;Guigas and Weiss 2008;Sereshki et al 2012;Lampo et al 2017). The different regimes can alternate on different timescales, reflecting the underlying heterogeneity of and interactions among cellular structures (Di Rienzo et al 2014;van den Berg et al 2017).…”

“…Computer simulations are often integrated with experiments performed in vivo to provide a microscopic interpretation of cellular phenomena (Hihara et al 2012;Coquel et al 2013;Di Rienzo et al 2014;Earnest et al 2017). Although powerful to predict macromolecule behavior, this technique, defined as the Bcomputational microscope^by Schulten (Lee et al 2009), has some limitations (Takada 2012;Piana et al 2014;Ivani et al 2016;Song et al 2017;Wang et al 2017a).…”

Visualization of barriers and obstacles to molecular diffusion in live cells by spatial pair-cross-correlation in two dimensions

“…In the compartmentalized environment of cells these transduction processes are regulated by a tight spatio-temporal control of molecular flow [1,2]. The regulation of this molecular flow requires a complex interplay between the structure of the surrounding cellular components [3][4][5] and a spatio-temporal control of molecularinteractions [6,7]. The consequence is a molecular transport that depends strictly on the molecular species, on the aggregations state, on the active state of the molecule and on the cell-cycle phase [8][9][10][11][12].…”