Studying multiprotein complexes by multisignal sedimentation velocity analytical ultracentrifugation

Abstract

Protein interactions can promote the reversible assembly of multiprotein complexes, which have been identified as critical elements in many regulatory processes in cells. The biophysical characterization of assembly products, their number and stoichiometry, and the dynamics of their interactions in solution can be very difficult. A classical first-principle approach for the study of purified proteins and their interactions is sedimentation velocity analytical ultracentrifugation. This approach allows one to distinguish different protein complexes based on their migration in the centrifugal field without isolating reversibly formed complexes from the individual components. An important existing limitation for systems with multiple components and assembly products is the identification of the species associated with the observed sedimentation rates. We developed a computational approach for integrating multiple optical signals into the sedimentation coefficient distribution analysis of components, which combines the size-dependent hydrodynamic separation with discrimination of the extinction properties of the sedimenting species. This approach allows one to deduce the stoichiometry and to assign the identity of the assembly products without prior assumptions of the number of species and the nature of their interaction. Although chromophoric labels may be used to enhance the spectral resolution, we demonstrate the ability to work label-free for three-component protein mixtures. We observed that the spectral discrimination can synergistically enhance the hydrodynamic resolution. This method can take advantage of differences in the absorbance spectra of interacting solution components, for example, for the study of protein-protein, protein-nucleic acid or protein-small molecule interactions, and can determine the size, hydrodynamic shape, and stoichiometry of multiple complexes in solution.

Fig. 1.

Sedimentation coefficient distributions derived from sedimentation velocity profiles of a mixture of IgG and aldolase. (A Inset) The raw sedimentation signals acquired at different time points with interference (Top), absorbance at 280 nm (Middle), and absorbance at 250 nm (Bottom) at a rotor speed of 48,000 rpm at 26°C, with the signal profiles shown in units of fringes, OD₂₈₀, and OD₂₅₀, respectively, as a function of radius in centimeters. (A) c(s) distributions calculated separately for the refractive index data (solid trace), the absorbance at 280 nm (dotted trace), and the absorbance at 250 nm (dashed trace). For comparison, the apparent sedimentation coefficient distribution ls-g^*(s) (45) without diffusional deconvolution applied to the interference data set is shown (dashed-dotted trace). To facilitate comparison of the peak positions, the vertical dotted line indicates the peak of the c(s) distribution from the interference data. (B) Global multiwavelength analysis and decomposition into the component sedimentation coefficient distributions, c_k(s), for the IgG sample (red trace) and the aldolase (blue trace). The extinction coefficients for these two components at the three signals were predetermined from separate experiments with IgG and aldolase alone, which resulted in the sedimentation coefficient distributions indicated by the dotted traces. (C) Calculated component sedimentation coefficient distributions from a mixture (solid traces) of IgG (red trace), aldolase (blue trace), and BSA (green trace, 5-fold reduced scale) and comparison with the distributions obtained from the individual proteins (dotted traces).

Fig. 2.

Simulated sedimentation of two proteins, one with 50 kDa and 4.5 S (A) and the other with 100 kDa and 7 S (B), which formed a reversible 9 S complex sedimenting at a rotor speed of 50,000 rpm. Two signals were generated by assuming molar extinction coefficients of 50,000 and 30,000 for the 50-kDa protein and 100,000 and 30,000 for the 100-kDa protein, and Gaussian noise with a rms magnitude of 0.005 was added. Component sedimentation coefficient distributions, c_k(s), were calculated from multisignal analysis for components A (red traces) and B (blue traces). (A) The effect of concentration for an instantaneous reaction equimolar at 2× K_d (solid traces), with a 5-fold molar excess of component A over component B (dotted traces), and with a 5-fold molar excess of component B over component A (dashed traces). (In both cases, the concentrations were K_d and 5× K_d, respectively). (A Inset) The second signal for the limit of an instantaneous reaction at equimolar concentration (only every second profile shown). (B) The effect of finite dissociation rate constants, log₁₀(k_off) = -3.5 (dotted traces), -4 (dashed traces), and -5 (solid traces) under the conditions of equimolar concentrations.

Fig. 3.

Analysis of the interaction of peptides derived from the adaptor protein SLP-76 and PLCγ1. SLP-76 contains only one tyrosine and no tryptophan residues, allowing its spectral discrimination from PLCγ1. (A and B) Absorbance and interference optical signal distributions of a mixture of SLP-76 and PLCγ2 at time intervals of 2,500 sec at a rotor speed of 59,000 rpm and a temperature of 4°C, with systematic noise subtracted. The residuals are from the fit with the hybrid discrete/continuous model shown in D (see below). (C) Data in the same configuration as shown in A and B were collected for SLP-76 and PLCγ1 separately (data not shown), which led to the component distributions shown as a blue dashed trace for PLCγ1 (molar extinction coefficient, 20,060 OD₂₈₀/Mcm; F_k,w = 1.5) and a green dotted trace for SLP-76 (molar extinction coefficient, 2,550 OD₂₈₀/Mcm; F_k,w = 2.3). Alternatively, the data of SLP-76 and PLCγ1 alone could be modeled well as discrete sedimenting species with 0.6 and 0.75 S, respectively. Shown is an analysis of the mixture with component sedimentation coefficient distributions for SLP-76 (green solid trace) and PLCγ1 (blue solid trace), with a uniform frictional ratio of F_k,w = 2.0. (D) Analysis with subdivision of the s values in three ranges: (i) the buffer components at <0.4 S; (ii) the discrete free peptides with their predetermined extinction properties, molar masses, and predetermined s values of 0.6 and 0.75 S; and (iii) the continuous distribution of complexes >0.8 S, which can be constrained in their spectral properties to reflect stoichiometries of 1:1 (red trace) or 2:1 (blue trace). The interference optical data contain contributions from the sedimentation of a small buffer component (likely predominantly optically unmatched NaCl), which can be modeled well as discrete species at 0.08 and 0.3 S (black crosses with dropped lines). All units for s values are S at experimental conditions, the concentration of discrete species are in μM, and the c_k(s) distributions are in μM/S.

Fig. 4.

Sedimentation velocity analysis of HEL binding to the D1.3 antibody (29) at 50,000 rpm, scanned by absorbance at 280 nm, and by refractive index detection. Shown are c_k(s) from the mixture (solid traces) and from separate experiments (dashed traces) for both HEL (red traces) and D1.3 (blue traces).