Coupling and Decoupling of Rotational and Translational Diffusion of Proteins under Crowding Conditions

Abstract

Molecular motion of biopolymers in vivo is known to be strongly influenced by the high concentration of organic matter inside cells, usually referred to as crowding conditions. To elucidate the effect of intermolecular interactions on Brownian motion of proteins, we performed (1)H pulsed-field gradient NMR and fluorescence correlation spectroscopy (FCS) experiments combined with small-angle X-ray scattering (SAXS) and viscosity measurements for three proteins, αB-crystalline (αBc), bovine serum albumin, and hen egg-white lysozyme (HEWL) in aqueous solution. Our results demonstrate that long-time translational diffusion quantitatively follows the expected increase of macro-viscosity upon increasing the protein concentration in all cases, while rotational diffusion as assessed by polarized FCS and previous multi-frequency (1)H NMR relaxometry experiments reveals protein-specific behavior spanning the full range between the limiting cases of full decoupling from (αBc) and full coupling to (HEWL) the macro-viscosity. SAXS was used to study the interactions between the proteins in solution, whereby it is shown that the three cases cover the range between a weakly interacting hard-sphere system (αBc) and screened Coulomb repulsion combined with short-range attraction (HEWL). Our results, as well as insights from the recent literature, suggest that the unusual rotational-translational coupling may be due to anisotropic interactions originating from hydrodynamic shape effects combined with high charge and possibly a patchy charge distribution.

Biomolecular interactions modulate macromolecular structure and dynamics in atomistic model of a bacterial cytoplasm

“…We find that, in general, rotational diffusion follows the same trend as for translational diffusion, including a very similar dependency on local crowding (Figure 5—figure supplement 1). A similar reduction of translational and rotational diffusion upon crowding on shorter, sub-microsecond time scales found here is consistent with experimental data from quasi-elastic neutron backscattering and NMR relaxometry (Roosen-Runge et al, 2011; Roos et al, 2016). However, our simulations are too short to probe the suggested protein species dependent decoupling of rotational and translational diffusion on longer time scales based on pulsed field gradient NMR measurements of dense protein solutions (Roos et al, 2016).…”

“…A similar reduction of translational and rotational diffusion upon crowding on shorter, sub-microsecond time scales found here is consistent with experimental data from quasi-elastic neutron backscattering and NMR relaxometry (Roosen-Runge et al, 2011; Roos et al, 2016). However, our simulations are too short to probe the suggested protein species dependent decoupling of rotational and translational diffusion on longer time scales based on pulsed field gradient NMR measurements of dense protein solutions (Roos et al, 2016).

10.7554/eLife.19274.021Figure 5.Rotational diffusion of macromolecules.( A ) Averaged angular velocity ( ω ) of macromolecules in MG m1 as a function of their Stokes radii ( R s ) (gray squares with IF1, ATRN, PDHD, PDHA, and PGK highlighted in purple, red, blue, yellow, and green, respectively) ( B ) Rotational correlation functions ( θ ) of macromolecules (IF1, ATRN, PDHD, PDHA, and PGK colored in purple, red, blue, yellow, and green, respectively).

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Slow-Down in Diffusion in Crowded Protein Solutions Correlates with Transient Cluster Formation

“…9 and do not require a PBC correction. 67 $$D_r=\frac{1}{lfalse(l+1false)\tau }$$ where l =2 and the overall rotational correlation time τ is obtained from the fast and slow correlation times as follows: $$\tau =S_R^2{\tau }_{Rs}+false(1-S_R^{2}false){\tau }_{Rf}$$Additionally, averages of the inverse tumbling times were also calculated as they are more relevant for comparison with many experiments such as dynamic light scattering 68 : $${\tau }_{\mathit{ini}}{\left(\frac{S_R^2}{{\tau }_{Rs}}+\frac{1-S_R^2}{{\tau }_{Rf}}\right)}^{-1}$$The correlation functions obtained at the highest concentrations were additionally fitted to a triple-exponential function since a double-exponential fit did not fully describe the data: $$C_{O}false(tfalse)=S_{Rs}^2{e}^{-\frac{t}{{\tau }_{Rs}}}+S_{Rm}^2{e}^{-\frac{t}{{\tau }_{Rm}}}+false(1-S_{Rs}^2-S_{Rm}^{2}false)e^{-\frac{t}{{\tau }_{Rf}}}$$ where τ Rf , τ Rm , and τ Rs are fast, medium and slow correlation times with the corresponding S Rm 2 and S Rs 2 weights.…”

Effect of crowding on protein-protein association in diffusion-limited regime

“…According to the above expression, k D is determined by both translational and rotational diffusion. Note that recent experimental studies for diffusion of molecular probes in complex polymer solutions, reveal a very novel decoupling phenomenon between the translational and rotational diffusion [19,20]. Namely, it was found experimentally that, for diffusion of proteins in polymer solutions, the SE relation for the translational diffusion remains well satisfied, while rotational diffusion exhibits large deviations from the traditional SED relation given by D r = k B T /8πη macro r 3 h .…”