Dynamics of Protein Assemblies by Analytical Ultracentrifugation

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One major thrust of our work has been the continued improvement of nonideal sedimentation velocity (nonideal SV) as a technique for measuring macromolecular size-distributions in highly concentrated solutions. The goal is to study proteins at concentrations closer to the intracellular environment, where weak interactions can govern a wide spectrum of behavior, including dynamic multi-protein complex formation and liquid-liquid phase transition. Our recent breakthrough in the analysis of polydisperse concentrated protein solutions came from the introduction of a mean-field approach to account for hydrodynamic interactions in the sedimentation particle mixtures. It is based on nonideality coefficients that arise from first-order approximations of concentration-dependent behavior, which, unfortunately, are limited to solutions with macromolecular volume occupancy below 5%. To remove this limitation, we have implemented higher-order approximations rooted in statistical fluid mechanics. In the past year, we have collected experimental data of sedimentation boundaries of bovine serum albumin at up to 150 mg/mL, and of undiluted serum. First results validate the sedimentation model. An experimental problem when working at high concentration is presented by optical aberrations in the strong refractive index gradients of the sedimentation boundary. This lensing effect can be minimized by short optical pathlengths, and therefore we have further improved the design of our 3D printed sample holders. We believe we have reached limits imposed by the need to seal the sample against high vacuum, achieve stability in high gravity, and the ability to create access ports for sample filling. We turned to a different approach to allow studying still higher protein concentrations: we have devised a technique for experimentally measuring the magnitude of optical aberrations, and developed a mathematical model of the optical distortions that we embedded it into our sedimentation data analysis. We have begun testing the performance of these approaches. A second major effort in our work on SV was directed at making sedimentation analysis more information-rich for the study of multi-protein interactions. We have previously pursued this goal by multi-signal approaches and creating temporal signals by photoswitching. However, another opportunity resides in the stratification of solution during the sedimentation process: Sedimenting systems of dynamically interacting proteins with complex life-times shorter than 1,000 sec exhibit richly patterned sedimentation profiles, with sedimentation boundaries that depend in complex ways on protein concentrations, equilibrium constants, and sedimentation coefficients associated with the different assembly states. We have previously developed effective particle theory that provides a physical explanation for sedimentation boundary patterns. In the current year we have integrated this theory into a new approach for interpreting SV data from sedimenting interacting systems. It allows taking advantage of the entire sedimentation pattern, rather than only the average sedimentation velocity, and thereby enhances the information content of SV experiments. We have implemented this into our data analysis software with a user interface that allows creation of customized binding models. Finally, we have continued to develop a fluorescence detection system for analytical ultracentrifugation, in collaboration with John Kakareka and Thomas Pohida (CIT). Both improvements in the optical setup as well as signal processing of index cells were achieved. To disseminate knowledge of analytical ultracentrifugation we have made this technique a major focus in our FEBS Practical Course that was held in January 2020 in Grenoble, France.