Studying multiprotein complexes by multisignal sedimentation velocity analytical ultracentrifugation
Studying multiprotein complexes by multisignal sedimentation velocity analytical ultracentrifugation
Published online before print December 21, 2004
Andrea Balbo , Kenneth H. Minor , Carlos A. Velikovsky , Roy A. Mariuzza , Cynthia B. Peterson , and Peter Schuck , ?
PNAS | January 4, 2005 | vol. 102
Protein Biophysics Resource, Division of Bioengineering and Physical Science, Office of Research Services, Office of the Director, National Institutes of Health, Bethesda, MD 20892; Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN 37996; and Center for Advanced Research in Biotechnology, University of Maryland Biotechnology Institute, Rockville, MD 20850
Communicated by Howard K. Schachman, University of California, Berkeley, CA, November 11, 2004 (received for review September 22, 2004)
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
The reversible formation of multiprotein complexes is ubiquitous, frequently leading to very large functional assemblies that control many cellular processes. Well known examples include immunological receptor?ligand interactions (1?4), the cardiac ryanodine receptor complex (5), signal transduction complexes (6?9), transcription regulation complexes (10), and replication machinery (11, 12). Significant biophysical insight has been gained, for example, by imaging techniques and mass spectroscopy. To fully understand the interactions of the building blocks of protein complexes, the role of intermediates, and the dynamics of the assembly processes of such complexes, it is of interest to study their formation from purified components in solution. Experimentally, such studies can be very difficult because, in many cases, mixed interactions of self-associating components and complexes of more than two proteins in multiple conformations are involved, confering cooperative interactions with high dynamic complexity. For example, the detailed understanding of signal transduction requires understanding of the multiprotein complexes that form close to the cell membrane as a result of ligand binding to cell-surface receptors, and it has been established that the energetics, kinetics, allosteric interactions, and multivalent interactions of the multiprotein complexes can be critical for signal transduction (9). In many systems, even deceptively simple questions, such as the stoichiometry of the complexes formed by only two protein components, can be very difficult to address, although they are often key observations for understanding protein function, such as the influence of expression levels on the dynamics of the assembly (6).
Sedimentation velocity has historically played a central role in measuring protein sizes and shapes (13, 14). It is based on first principles, and, because in the last decade the underlying differential equations have become tractable in routine analyses, it has reemerged as a powerful tool for protein interactions and the study of the size distribution of protein complexes (15?18). In the analysis of protein interactions, when a high gravitational force is applied to an initially uniform mixture of proteins, the reversibly formed complexes sediment in a bath of the slower sedimenting components. Under suitable conditions, this process allows transient complexes to persist or reassociate during the sedimentation process. A drawback of sedimentation velocity has been that the observed sedimentation coefficient of a macromolecular species only indirectly allows conclusions about its size, shape, and, for heterogeneous protein mixtures, its composition and stoichiometry. In the present paper, we propose the use of spectral information to overcome this limitation for multicomponent mixtures.
The pioneering work of Schachman and colleagues (19, 20) in the development of an absorbance optical system for the analytical ultracentrifuge made possible the selective detection of macromolecular components, which has proven to be extremely useful in the study of proteins and protein interactions. In 1966, Steinberg and Schachman (21) developed the simultaneous detection of absorbance and refractive index profiles for the analysis of protein?small molecule interactions in terms of constituent effective molecular weights and constituent sedimentation coefficients. In the last decades, global least-squares modeling of sedimentation equilibrium profiles observed at multiple characteristic wavelengths or optical signals was used for the study of protein?protein interactions. It is well known that this global multiwavelength analysis substantially increases the potential to distinguish different protein complexes (22?28). Unfortunately, size-dependent separation in sedimentation equilibrium is very limited because of the difficulties unraveling the Boltzmann exponentials of sedimentation equilibrium. In contrast, the resolution of the size-dependent migration of sedimentation boundaries in sedimentation velocity is far superior. It can be envisioned that exploiting the additional data dimensions provided by multiwavelength or multisignal detection should permit the hydrodynamic separation of protein complexes and simultaneously the identification of their composition through spectral discrimination of the components. This approach would have the potential to facilitate the first and frequently most important step in the characterization of many protein interactions: to unravel the stoichiometry of the different complexes formed. Furthermore, if the stoichiometry of a sedimenting protein complex can be determined from the spectral signature, the molar mass can be calculated, and sedimentation coefficients directly report on the translational frictional coefficient, which provides low-resolution shape information.
In the present work, we explored this potential and monitored the evolution of the macromolecular concentration profiles during sedimentation simultaneously by UV/visible spectrum absorption and refractive index-sensitive laser interferometry optics. We developed a computational approach to integrate these signals into a multicomponent sedimentation coefficient distribution, which utilizes the previously introduced technique for deconvoluting the effects of diffusion during sedimentation to increase the hydrodynamic resolution. As test systems, we studied the label-free sedimentation of binary and ternary protein mixtures.
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