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.protein interactions ͉ size distribution

A new adaptive grid-size algorithm for the simulation of sedimentation velocity profiles in analytical ultracentrifugation

“…It has significantly improved detection limits and resolution, and our ability to quantitatively describe complex sedimentation processes of macromolecular mixtures. In particular, the convenient use of LE solutions as model function in non-linear regression and/or as kernels in Fredholm integral equations enabled many new techniques, including direct boundary modeling with distributions of LE solutions, and direct boundary modeling with systems of LEs with chemically reacting species, which found wide-spread application in physical biochemistry, for example, in the study of protein-protein interactions [46,49,59,71], the detection of immunogenic oligomeric species of protein pharmaceuticals [10][11][12][13], global multi-signal sedimentation velocity analysis of reversible multi-protein complexes [23,57,[72][73][74], and other applications [52].…”

“…It allowed, for example, using LE solutions to be used as the kernel in Fredholm integral equations, such as in the sedimentation coefficient distribution c(s) (2) (where a(r,t) is the measured concentration evolution) [53][54][55], and multidimensional extensions such as the two-dimensional size-and-shape distributions [56], and multicomponent sedimentation coefficient distributions for multi-protein complexes [57]. Fitting these models to experimental data gives high-resolution, diffusion-deconvoluted macromolecular size-distributions.…”

“…Therefore, algorithms for solving the LE is an important topic that directly relates to the biophysical study of macromolecules by sedimentation velocity. It provides tools that are unique for studying interacting multicomponent mixtures in free solution [21,57].…”

Crystal Structure of the Tp34 (TP0971) Lipoprotein of Treponema pallidum

“…For some experiments, the two signals were absorbance at 280 nm and refractive index detection by laser interferometry; for others, the signals were absorbances at 280 and at 250 nm. Such data were analyzed according to the multisignal c k (s) methodology of Balbo et al (39), as implemented in the program SEDPHAT. Briefly, the sedimentation profiles obtained from experiments i and ii were used to calculate the unknown extinction coefficient of the protein at 250 nm or the unknown interferometric extinction coefficient.…”

A “Tagless” Strategy for Identification of Stable Protein Complexes Genome-wide by Multidimensional Orthogonal Chromatographic Separation and iTRAQ Reagent Tracking

“…1 Historically, stable protein complexes were identified one at a time, often as the result of purifying an enzyme activity of interest. In this traditional approach, complexes were inferred when multiple polypeptides comigrated together with an associated enzyme activity through multiple chromatographic separation steps, [2][3][4] demonstrating the same sedimentation velocities 5,6 or electrophoretic mobilities. 7 More recently, stable protein complexes have been identified using high-throughput mass spectrometric detection of collections of polypeptides that are stably associated with heterologous affinity-tagged polypeptides.…”