Sedimentation velocity analytical ultracentrifugation (SV-AUC) has become an important tool for the characterization of the purity of protein therapeutics. The work presented here addresses a need for methods orthogonal to size-exclusion chromatography for ensuring the reliable quantitation of immunogenic oligomers, for example, in antibody preparations. Currently the most commonly used approach for SV-AUC analysis is the diffusion-deconvoluted sedimentation coefficient distribution c(s) method, previously developed by us as a general purpose technique and implemented in the software SEDFIT. In both practical and theoretical studies, different groups have reported a sensitivity of c(s) for trace oligomeric fractions well below the 1% level. In the present work we present a variant of c(s) designed for the purpose of trace detection, with customized Bayesian regularization. The original c(s) method relies on maximum entropy regularization providing the most parsimonious distribution consistent with the data. In the present paper, we use computer simulations of an antibody system as example to demonstrate that the standard maximum entropy regularization, due to its design, leads to a theoretical lower limit for the detection of oligomeric traces and a consistent underestimate of the trace populations by ∼0.1% (dependent on the level of regularization). This can be overcome with a recently developed Bayesian extension of c(s) (Brown et al., Biomacromolecules, 8:2011–2024, 2007), utilizing the known regions of sedimentation coefficients for the monomer and oligomers of interest as prior expectation for the peak positions in the distribution. We show that this leads to more clearly identifiable and consistent peaks and lower theoretical limits of quantization by approximately an order of magnitude for some experimental conditions. Implications for the experimental design of SV-AUC and practical detection limits are discussed.
analytical ultracentrifugation; Bayesian analysis; hydrodynamic separation; sedimentation velocity; size-distribution; trace aggregates
Analytical ultracentrifugation has reemerged as a widely used tool for the study of ensembles of biological macromolecules to understand, for example, their size-distribution and interactions in free solution. Such information can be obtained from the mathematical analysis of the concentration and signal gradients across the solution column and their evolution in time generated as a result of the gravitational force. In sedimentation velocity analytical ultracentrifugation, this analysis is frequently conducted using high resolution, diffusion-deconvoluted sedimentation coefficient distributions. They are based on Fredholm integral equations, which are ill-posed unless stabilized by regularization. In many fields, maximum entropy and Tikhonov-Phillips regularization are well-established and powerful approaches that calculate the most parsimonious distribution consistent with the data and prior knowledge, in accordance with Occam’s razor. In the implementations available in analytical ultracentrifugation, to date, the basic assumption implied is that all sedimentation coefficients are equally likely, and that the information retrieved should be condensed to the least amount possible. Frequently, however, more detailed distributions would be warranted by specific detailed prior knowledge on the macromolecular ensemble under study, such as, the expectation of the sample to be monodisperse or paucidisperse, or the expectation for the migration to establish a bimodal sedimentation pattern based on Gilbert & Jenkins’ theory for the migration of chemically reacting systems. So far, such prior knowledge has remained largely unused in the calculation of the sedimentation coefficient or molecular weight distributions, or was only applied as constraints. In the present paper, we examine how prior expectations can be built directly into the computational data analysis, conservatively in a way that honors the complete information of the experimental data, whether or not consistent with the prior expectation. Consistent with analogous results in other fields, we find that use of available prior knowledge can have a dramatic effect on the resulting molecular weight, sedimentation coefficient and size-and-shape distributions, and significantly increase both their sensitivity and resolution. Further, the use of multiple alternative priors allows to probe the range of possible interpretations consistent with the data.
Analytical ultracentrifugation; sedimentation velocity; sedimentation equilibrium; maximum entropy; Fredholm integral equations; size-distribution; regularization
Analytical ultracentrifugation allows one to measure in real-time the concentration gradients arising from the application of a centrifugal force to macromolecular mixtures in solution. In the last decade, the ability to efficiently solve the partial differential equation governing the ultracentrifugal sedimentation and diffusion process, the Lamm equation, has spawned significant progress in the application of sedimentation velocity analytical ultracentrifugation for the study of biological macromolecules, for example, the characterization of protein oligomeric states and the study of reversible multi-protein complexes in solution. The present work describes a numerical algorithm that can provide an improvement in accuracy or efficiency over existing algorithms by more than one order of magnitude, and thereby greatly facilitate the practical application of sedimentation velocity analysis, in particular, for the study of multi-component macromolecular mixtures. It is implemented in the public domain software SEDFIT for the analysis of experimental data.
protein interactions; analytical ultracentrifugation; finite element methods; size distributions
Significant progress in the interpretation of analytical ultracentrifugation (AUC) data in the last decade has led to profound changes in the practice of AUC, both for sedimentation velocity (SV) and sedimentation equilibrium (SE). Modern computational strategies have allowed for the direct modeling of the sedimentation process of heterogeneous mixtures, resulting in SV size-distribution analyses with significantly improved detection limits and strongly enhanced resolution. These advances have transformed the practice of SV, rendering it the primary method of choice for most existing applications of AUC, such as the study of protein self- and hetero-association, the study of membrane proteins, and applications in biotechnology. New global multi-signal modeling and mass conservation approaches in SV and SE, in conjunction with the effective-particle framework for interpreting the sedimentation boundary structure of interacting systems, as well as tools for explicit modeling of the reaction/diffusion/sedimentation equations to experimental data, have led to more robust and more powerful strategies for the study of reversible protein interactions and multi-protein complexes. Furthermore, modern mathematical modeling capabilities have allowed for a detailed description of many experimental aspects of the acquired data, thus enabling novel experimental opportunities, with important implications for both sample preparation and data acquisition. The goal of the current commentary is to supplement previous AUC protocols, Current Protocols in Protein Science 20.3 (1999) and 20.7 (2003), and 7.12 (2008), and provide an update describing the current tools for the study of soluble proteins, detergent-solubilized membrane proteins and their interactions by SV and SE.
sedimentation equilibrium; sedimentation velocity; chemical equilibria; reversible interaction; size-distribution; multi-protein complex; analytical ultracentrifugation; protein hydrodynamics
The analytical ultracentrifuge (AUC) is a powerful biophysical tool that allows us to record macromolecular sedimentation profiles during high speed centrifugation. When properly planned and executed, an AUC sedimentation velocity or sedimentation equilibrium experiment can reveal a great deal about a protein in regards to size and shape, sample purity, sedimentation coefficient, oligomerization states and protein-protein interactions.
This technique, however, requires a rigorous level of technical attention. Sample cells hold a sectored center piece sandwiched between two window assemblies. They are sealed with a torque pressure of around 120-140 in/lbs. Reference buffer and sample are loaded into the centerpiece sectors and then after sealing, the cells are precisely aligned into a titanium rotor so that the optical detection systems scan both sample and reference buffer in the same radial path midline through each centerpiece sector while rotating at speeds of up to 60, 000 rpm and under very high vacuum
Not only is proper sample cell assembly critical, sample cell components are very expensive and must be properly cared for to ensure they are in optimum working condition in order to avoid leaks and breakage during experiments. Handle windows carefully, for even the slightest crack or scratch can lead to breakage in the centrifuge. The contact between centerpiece and windows must be as tight as possible; i.e. no Newton s rings should be visible after torque pressure is applied. Dust, lint, scratches and oils on either the windows or the centerpiece all compromise this contact and can very easily lead to leaking of solutions from one sector to another or leaking out of the centerpiece all together. Not only are precious samples lost, leaking of solutions during an experiment will cause an imbalance of pressure in the cell that often leads to broken windows and centerpieces. In addition, plug gaskets and housing plugs must be securely in place to avoid solutions being pulled out of the centerpiece sector through the loading holes by the high vacuum in the centrifuge chamber. Window liners and gaskets must be free of breaks and cracks that could cause movement resulting in broken windows.
This video will demonstrate our procedures of sample cell assembly, torque, loading and rotor alignment to help minimize component damage, solution leaking and breakage during the perfect AUC experiment.
Analytical ultracentrifugation (AUC) is a powerful technique for the characterization of hydrodynamic and thermodynamic properties. The intent of this article is to demonstrate the utility of sedimentation velocity (SV) studies to obtain hydrodynamic information for G-quadruplex systems and to provide insights into one part of this process, namely, data analysis of existing SV data. An array of data analysis software is available, mostly written and continually developed by established researchers in the AUC field, with particularly rapid advances in the analysis of SV data. Each program has its own learning curve and this article is intended as a resource in the data analysis process for beginning researchers in the field. We discuss the application of three of the most commonly used data analysis programs, DCDT+, Sedfit and SedAnal, to the interpretation of SV data obtained in our laboratory on two G-quadruplex systems.
analytical ultracentrifugation; sedimentation velocity; sedimentation coefficient; frictional ratio; hydrodynamic; solution conformation; G-quadruplex DNA; data analysis; DCDT+; Sedfit; SedAnal
Analytical ultracentrifugation (AUC) is a versatile and powerful method for the quantitative analysis of macromolecules in solution. AUC has broad applications for the study of biomacromolecules in a wide range of solvents and over a wide range of solute concentrations. Three optical systems are available for the analytical ultracentrifuge (absorbance, interference and fluorescence) that permit precise and selective observation of sedimentation in real time. In particular, the fluorescence system provides a new way to extend the scope of AUC to probe the behavior of biological molecules in complex mixtures and at high solute concentrations. In sedimentation velocity, the movement of solutes in high centrifugal fields is interpreted using hydrodynamic theory to define the size, shape and interactions of macromolecules. Sedimentation equilibrium is a thermodynamic method where equilibrium concentration gradients at lower centrifugal fields are analyzed to define molecule mass, assembly stoichiometry, association constants and solution nonideality. Using specialized sample cells and modern analysis software, researchers can use sedimentation velocity to determine the homogeneity of a sample and define whether it undergoes concentration-dependent association reactions. Subsequently, more thorough model-dependent analysis of velocity and equilibrium experiments can provide a detailed picture of the nature of the species present in solution and their interactions.
A multiwavelength UV/vis detector for the analytical ultracentrifuge (MWL-AUC) has been developed recently. In this work, β-carotene–gelatin composite particles are investigated with MWL-AUC. Band centrifugation with a Vinograd cell is used to ensure maximum sample separation. Spectral changes of the system are observed in dependence of the sedimentation coefficient and are attributed to a previously unknown inhomogeneity of the β-carotene chemical composition with both H- and J-aggregates coexisting in a mixture. In addition, our data suggest that pure H- and J-aggregates exist in a particle while their relative concentrations in a mixture determine the color characteristics of the sample. The unique abilities and properties of MWL-AUC include sedimentation coefficient distributions for all possible wavelengths, full UV/vis spectra of each different species in the mixture and 3D movies of the sedimentation process. These properties significantly extend the scope of the analytical ultracentrifuge technique and show that complex biopolymer multicomponent mixtures can be resolved into their individual species.
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The online version of this article (doi:10.1007/s00249-009-0412-6) contains supplementary material, which is available to authorized users.
Multi-signal sedimentation velocity analytical ultracentrifugation (MSSV) is a powerful tool for the determination of the number, stoichiometry, and hydrodynamic shape of reversible protein complexes in two- and three-component systems. In this method, the evolution of sedimentation profiles of macromolecular mixtures is recorded simultaneously using multiple absorbance and refractive index signals and globally transformed into both spectrally and diffusion-deconvoluted component sedimentation coefficient distributions. For reactions with complex lifetimes comparable to the time-scale of sedimentation, MSSV reveals the number and stoichiometry of co-existing complexes. For systems with short complex lifetimes, MSSV reveals the composition of the reaction boundary of the coupled reaction/migration process, which we show here may be used to directly determine an association constant. A prerequisite for MSSV is that the interacting components are spectrally distinguishable, which may be a result, for example, of extrinsic chromophores or of different abundances of aromatic amino acids contributing to the UV absorbance. For interacting components that are spectrally poorly resolved, here we introduce a method for additional regularization of the spectral deconvolution by exploiting approximate knowledge of the total loading concentrations. While this novel mass conservation principle does not discriminate contributions to different species, it can be effectively combined with constraints in the sedimentation coefficient range of uncomplexed species. We show in theory, computer simulations, and experiment, how mass conservation MSSV as implemented in SEDPHAT can enhance or even substitute for the spectral discrimination of components. This should broaden the applicability of MSSV to the analysis of the composition of reversible macromolecular complexes.
Fluorescence optical detection in sedimentation velocity analytical ultracentrifugation allows the study of macromolecules at nanomolar concentrations and below. This has significant promise, for example, for the study of systems of high-affinity protein interactions. Here we describe adaptations of the direct boundary modeling analysis approach implemented in the software SEDFIT that were developed to accommodate unique characteristics of the confocal fluorescence detection system. These include spatial gradients of signal intensity due to scanner movements out of the plane of rotation, temporal intensity drifts due to instability of the laser and fluorophores, and masking of the finite excitation and detection cone by the sample holder. In an extensive series of experiments with enhanced green fluorescent protein ranging from low nanomolar to low micromolar concentrations, we show that the experimental data provide sufficient information to determine the parameters required for first-order approximation of the impact of these effects on the recorded data. Systematic deviations of fluorescence optical sedimentation velocity data analyzed using conventional sedimentation models developed for absorbance and interference optics are largely removed after these adaptations, resulting in excellent fits that highlight the high precision of fluorescence sedimentation velocity data, thus allowing a more detailed quantitative interpretation of the signal boundaries that is otherwise not possible for this system.
In developing and manufacturing protein biopharmaceuticals, aggregation is a parameter that needs careful monitoring to ensure the quality and consistency of the final biopharmaceutical drug product. The analytical method of choice used to perform this task is size-exclusion chromatography (SEC). However, it is becoming more and more apparent that considerable care is required in assessing the accuracy of SEC data. One old analytical tool that is now reappearing to help in this assessment is analytical ultracentrifugation (AUC). Developments in AUC hardware and, more importantly, recent developments in AUC data analysis computer programs have converged to provide this old biophysical tool with the ability to extract very high resolution size information about the molecules in a given sample from a simple sedimentation velocity experiment. In addition, AUC allows sample testing to be conducted in the exact or nearly exact liquid formulation or reconstituted liquid formulation of the biopharmaceutical in the vial, with minimal surface area contact with extraneous materials. As a result, AUC analysis can provide detailed information on the aggregation of a biopharmaceutical, while avoiding many of the major problems that can plague SEC, thus allowing AUC to be used as an orthogonal method to verity SEC aggregation information and the associating properties of biopharmaceuticals.
Protein aggregation; analytical ultracentrifugation; size-exclusion chromatography; SEDFIT
Sedimentation velocity analytical ultracentrifugation has experienced a significant transformation, precipitated by the possibility of efficiently fitting Lamm equation solutions to the experimental data. The precision of this approach depends on the ability to account for the imperfections of the experiment, both regarding the sample and the instrument. In the present work, we explore in more detail the relationship between the sedimentation process, its detection, and the model used in the mathematical data analysis. We focus on configurations that produce steep and fast-moving sedimentation boundaries, such as frequently encountered when studying large multi-protein complexes. First, as a computational tool facilitating the analysis of heterogeneous samples, we introduce the strategy of partial boundary modeling. It can simplify the modeling by restricting the direct boundary analysis to species with sedimentation coefficients in a predefined range. Next, we examine factors related to the experimental detection, including the magnitude of optical aberrations generated by out-of-focus solution columns at high protein concentrations, the relationship between the experimentally recorded signature of the meniscus and the meniscus parameter in the data analysis, and the consequences of the limited radial and temporal resolution of the absorbance optical scanning system. Surprisingly, we find that large errors can be caused by the finite scanning speed of the commercial absorbance optics, exceeding the statistical errors in the measured sedimentation coefficients by more than an order of magnitude. We describe how these effects can be computationally accounted for in SEDFIT and SEDPHAT.
Analytical ultracentrifugation; Hydrodynamics; Direct boundary modeling; Lamm equation
Sedimentation velocity analytical ultracentrifugation has become a very popular technique to study size distributions and interactions of macromolecules. Recently, a method termed two-dimensional spectrum analysis (2DSA) for the determination of size-and-shape distributions was described by Demeler and colleagues (Eur Biophys J 2009). It is based on novel ideas conceived for fitting the integral equations of the size-and-shape distribution to experimental data, illustrated with an example but provided without proof of the principle of the algorithm. In the present work, we examine the 2DSA algorithm by comparison with the mathematical reference frame and simple well-known numerical concepts for solving Fredholm integral equations, and test the key assumptions underlying the 2DSA method in an example application. While the 2DSA appears computationally excessively wasteful, key elements also appear to be in conflict with mathematical results. This raises doubts about the correctness of the results from 2DSA analysis.
Analytical ultracentrifugation; Fredholm integral equations; 2DSA; Sedimentation velocity; Lamm equation; Size distribution
Gleaning information regarding the molecular physiology of macromolecular complexes requires knowledge of their component stoichiometries. In this work, a relatively new means of analyzing sedimentation velocity (SV) data from the analytical ultracentrifuge is examined in detail. The method depends on collecting concentration profile data simultaneously using multiple signals, like Rayleigh interferometry and UV spectrophotometry. If the cosedimenting components of a complex are spectrally distinguishable, continuous sedimentation-coefficient distributions specific for each component can be calculated to reveal the molar ratio of the complex’s components. When combined with the hydrodynamic information available from the SV data, a stoichiometry can be derived. Herein, the spectral properties of sedimenting species are systematically explored to arrive at a predictive test for whether a set of macromolecules can be spectrally resolved in a multisignal SV (MSSV) experiment. Also, a graphical means of experimental design and criteria to judge the success of the spectral discrimination in MSSV are introduced. A detailed example of the analysis of MSSV experiments is offered, and the possibility of deriving equilibrium association constants from MSSV analyses is explored. Finally, successful implementations of MSSV are reviewed.
analytical ultracentrifugation; biophysical methods; stoichiometry; multisignal sedimentation velocity; Arp2/3 complex; step by step instructions
The Notch signal transduction pathway controls cell fate determination during metazoan development. The Notch gene encodes a transmembrane receptor that is cleaved upon activation, liberating the Notch intracellular domain (NICD), which enters the nucleus and assembles transcriptional activation complexes that drive expression of Notch-responsive genes. The most conserved region of NICD is an ankyrin domain (Nank), which binds directly to the cytosolic effector protein Deltex (Dx), controlling intracellular Notch activity. However, the structural and energetic basis for this interaction remains unknown.
Here we analyze the thermodynamics and hydrodynamics of the Nank:Dx heteroassociation, and also a weaker Nank self-association, using sedimentation velocity analytical ultracentrifugation (AUC). By comparing g(s*) and c(s) distributions, and by direct fitting of sedimentation boundaries with thermodynamic association models, we were able to characterize the Nank:Dx heterodimer, measure its affinity, and map the interaction on the surface on Nank. N- and C-terminal deletions of whole ankyrin units implicate repeats three and four as key for mediating heteroassociation. An alanine scan across the interaction loops of Nank identify a conserved hot-spot in repeats three and four, centered at R127, as critical for Dx binding. In addition, we were able to detect weak but reproducible Nank homodimerization (Kd in the mM range). This association is disrupted by substitution of a conserved arginine (R107) with alanine, a residue previously implicated in a functionally relevant mode of interaction within dimeric transcription complexes. The distinct binding surfaces on Nank for homotypic versus Deltex interaction appear to be compatible with teterameric Notch2:Dx2 assembly.
Notch signaling; Deltex; ankyrin repeats; analytical ultracentrifugation; protein-protein interactions
In this study, we have investigated sedimentation velocity ultracentrifugation (AUC-SV), size exclusion chromatography (SEC), and circular dichroism (CD) methods for the detection and quantitation of protein aggregates using recombinant acid alpha-glucosidase (rhGAA) as a model. The results of this study showed that the formation and molecular weight distribution of rhGAA aggregated species were dependent upon the formulation conditions as well as the storage or stress conditions used to induce aggregation. The utility of CD as a probe for non-native, aggregated species was affirmed, as this method was sensitive to rhGAA aggregation levels of ≤4%. An extensive evaluation of AUC-SV variability was performed using nine levels of spiked rhGAA aggregate that were analyzed on six occasions. Based on our data, the precision of the AUC-SV results increased with increasing levels of aggregate, with a mean RSD of 37.2%. The limit of quantitation (LOQ) for the AUC-SV method, which was based on a Precision criterion of RSD <20%, was determined to be ≥3% aggregated rhGAA. The Precision and LOQ of the SEC method, determined using the same rhGAA sample set, was found to be 3.8% and ≥0.2%, respectively. In general, there was good agreement between the levels of aggregated rhGAA determined using the AUC-SV and SEC methods, with a slight positive bias noted for the AUC-SV results. These studies emphasize the value of applying multiple, well-characterized analytical tools in the evaluation of therapeutic protein aggregation.
aggregation; analytical ultracentrifugation; circular dichroism; size exclusion chromatography
The partial-specific volume of proteins is an important thermodynamic parameter required for the interpretation of data in several biophysical disciplines. Building on recent advances in the use of density variation sedimentation velocity analytical ultracentrifugation for the determination of macromolecular partial-specific volumes, we have explored a direct global modeling approach describing the sedimentation boundaries in different solvents with a joint differential sedimentation coefficient distribution. This takes full advantage of the influence of different macromolecular buoyancy on both the spread and the velocity of the sedimentation boundary. It should lend itself well to the study of interacting macromolecules and/or heterogeneous samples in microgram quantities. Model applications to three protein samples studied in either H2O, or isotopically enriched H218O mixtures, indicate that partial-specific volumes can be determined with a statistical precision of better than 0.5%, provided signal/noise ratios of 50–100 can be achieved in the measurement of the macromolecular sedimentation velocity profiles. The approach is implemented in the global modeling software SEDPHAT.
Determination of the stoichiometry of macromolecular assemblies is fundamental to an understanding of how they function. Many different biophysical methodologies may be used to determine stoichiometry. In the past, both sedimentation equilibrium and sedimentation velocity analytical ultracentrifugation have been employed to determine component stoichiometries. Recently, a method of globally analyzing multisignal sedimentation velocity data was introduced by Schuck and colleagues. This global analysis removes some of the experimental inconveniences and inaccuracies that could occur in the previously used strategies. This method uses spectral differences between the macromolecular components to decompose the well-known c(s) distribution into component distributions ck(s); i.e. each component k has its own ck(s) distribution. Integration of these distributions allows for the calculation of the populations of each component in cosedimenting complexes, yielding their stoichiometry. In our laboratories, we have used this method extensively to determine the component stoichiometries of several protein-protein complexes involved in cytoskeletal remodeling, sugar metabolism, and host-pathogen interactions. The overall method is described in detail in this work, as well experimental examples and caveats.
Analytical ultracentrifugation; sedimentation velocity; pyruvate dehydrogenase complex; Arp2/3 complex; human lactoferrin
We have investigated the potential of new methods of analysis of sedimentation velocity (SV) analytical ultracentrifugation (AUC) for the characterization of detergent-solubilized membrane proteins. We analyze the membrane proteins Ca++-ATPase and ExbB solubilized with DDM (dodecyl-β-d-maltoside). SV is extremely well suited for characterizing sample heterogeneity. DDM micelles (s20w = 3.1 S) and complexes (Ca++-ATPase: s20w = 7.3 S; ExbB: s20w = 4 S) are easily distinguished. Using different detergent and protein concentrations, SV does not detect any evidence of self-association for the two proteins. An estimate of bound detergent of 0.9 g/g for Ca++-ATPase and 1.5 g/g for ExbB is obtained from the combined analysis of SV profiles obtained using absorbance and interference optics. Combining s20w with values of the hydrodynamic radius, Rs = 5.5 nm for Ca++-ATPase or Rs = 3.4 nm for ExbB, allows the determination of buoyant molar masses, Mb. In view of their Mb and composition, Ca++-ATPase and ExbB are monomers in our experimental conditions. We conclude that one of the main advantages of SV versus other techniques is the possibility to ascertain the homogeneity of the samples and to focus on a given complex even in the presence of other impurities or aggregates. The relative rapidity of SV measurements also allows experiments on unstable samples.
Analytical ultracentrifugation; Membrane proteins; Ca++-ATPase; ExbB
For 25 years, the Gibbs Conference on Biothermodynamics has focused on the use of thermodynamics to extract information about the mechanism and regulation of biological processes. This includes the determination of equilibrium constants for macromolecular interactions by high precision physical measurements. These approaches further reveal thermodynamic linkages to ligand binding events. Analytical ultracentrifugation has been a fundamental technique in the determination of macromolecular reaction stoichiometry and energetics for 85 years. This approach is highly amenable to the extraction of thermodynamic couplings to small molecule binding in the overall reaction pathway. In the 1980’s this approach was extended to the use of sedimentation velocity techniques, primarily by the analysis of tubulin-drug interactions by Na and Timasheff. This transport method necessarily incorporates the complexity of both hydrodynamic and thermodynamic nonideality. The advent of modern computational methods in the last 20 years has subsequently made the analysis of sedimentation velocity data for interacting systems more robust and rigorous. Here we review three examples where sedimentation velocity has been useful at extracting thermodynamic information about reaction stoichiometry and energetics. Approaches to extract linkage to small molecule binding and the influence of hydrodynamic nonideality are emphasized. These methods are shown to also apply to the collection of fluorescence data with the new Aviv FDS.
Biothermodynamics; coupling; linkage; analytical ultracentrifugation; sedimentation velocity; nonideality; Aviv fluorescence detection system
Analytical ultracentrifugation is a widely used method for characterizing the solution behavior of macromolecules. However, the two commonly used detectors (absorbance and interference) impose some fundamental restrictions on the concentrations and complexity of the solutions that can be analyzed. The recent addition of a fluorescence detector for the XL-I analytical ultracentrifuge (AU-FDS) enables two different types of sedimentation experiments. First, the AU-FDS can detect picomolar concentrations of labeled solutes allowing the characterization of very dilute solutions of macromolecules, applications we call Normal Use Tracer Sedimentation (NUTS). The great sensitivity of NUTS analysis allows the characterization of small quantities of materials and high affinity interactions. Second, AU-FDS allows characterization of trace quantities of labeled molecules in solutions containing high concentrations and complex mixtures of unlabeled molecules, applications we call Biological On Line Tracer Sedimentation (BOLTS). The discrimination of BOLTS enables the size distribution of a labeled macromolecule to be determined in biological milieu such as cell lysates and serum. Examples are presented that embody features of both NUTS and BOLTS applications, along with our observations on these applications.
Progress in analytical ultracentrifugation (AUC) has been hindered by obstructions to hardware innovation and by software incompatibility. In this paper, we announce and outline the Open AUC Project. The goals of the Open AUC Project are to stimulate AUC innovation by improving instrumentation, detectors, acquisition and analysis software, and collaborative tools. These improvements are needed for the next generation of AUC-based research. The Open AUC Project combines on-going work from several different groups. A new base instrument is described, one that is designed from the ground up to be an analytical ultracentrifuge. This machine offers an open architecture, hardware standards, and application programming interfaces for detector developers. All software will use the GNU Public License to assure that intellectual property is available in open source format. The Open AUC strategy facilitates collaborations, encourages sharing, and eliminates the chronic impediments that have plagued AUC innovation for the last 20 years. This ultracentrifuge will be equipped with multiple and interchangeable optical tracks so that state-of-the-art electronics and improved detectors will be available for a variety of optical systems. The instrument will be complemented by a new rotor, enhanced data acquisition and analysis software, as well as collaboration software. Described here are the instrument, the modular software components, and a standardized database that will encourage and ease integration of data analysis and interpretation software.
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The online version of this article (doi:10.1007/s00249-009-0438-9) contains supplementary material, which is available to authorized users.
We have devised a protocol for the Brownian dynamics simulation of an analytical ultracentrifugation experiment that allows for an accurate and efficient prediction of the time-dependent concentration profiles, c(r, t) in the ultracentrifuge cell. The procedure accounts for the back-diffusion, described as a Brownian motion that superimposes to the centrifugal drift, and considers the sector-shaped geometry of the cell and the boundaries imposed by the meniscus and bottom.
Simulations are carried out for four molecules covering a wide range of the ratio of sedimentation and diffusion coefficients. The evaluation is done by extracting the molecular parameters that were initially employed in the simulation by analyzing the profiles with an independent tool, the well-proved SEDFIT software. The code of simulation algorithm has been parallelized in order to take advantage of current multi-core computers.
Our Brownian dynamics simulation procedure may be considered as an alternative to other predictors based in numerical solutions of the Lamm equation, and its efficiency could make it useful in the most relevant, inverse problem, which is that of extracting the molecular parameters from experimentally determined concentration profiles.
Oligomeric forms of the HC-Pro protein of the tobacco etch potyvirus (TEV) have been analyzed by analytical ultracentrifugation and single-particle electron microscopy combined with three-dimensional (3D) reconstruction. Highly purified HC-Pro protein was obtained from plants infected with TEV by using a modified version of the virus that incorporates a histidine tag at the HC-Pro N terminus (hisHC-Pro). The purified protein retained a high biological activity in solution when tested for aphid transmission. Sedimentation equilibrium showed that the hisHC-Pro preparations were heterogenous in size. Sedimentation velocity confirmed the previous observation and revealed that the active protein solution contained several sedimenting species compatible with dimers, tetramers, hexamers, and octamers of the protein. Electron microscopy fields of purified protein showed particles of different sizes and shapes. The reconstructed 3D structures suggested that the observed particles could correspond to dimeric, tetrameric, and hexameric forms of the protein. A model of the interactions required for oligomerization of the HC-Pro of potyviruses is proposed.
Analytical ultracentrifugation (AUC) and steady-state fluorescence anisotropy were used to measure the equilibrium dissociation constant (Kd) for formation of dimers by the amino-terminal domains (ATDs) of the GluA2 and GluA3 subtypes of AMPA receptor. Previous reports on GluA2 dimerization differed in their estimate of the monomer–dimer Kd by a 2,400-fold range, with no consensus on whether the ATD forms tetramers in solution. We find by sedimentation velocity (SV) analysis performed using absorbance detection a narrow range of monomer–dimer Kd values for GluA2, from 5 to 11 nM for six independent experiments, with no detectable formation of tetramers and no effect of glycosylation or the polypeptide linker connecting the ATD and ligand-binding domains; for GluA3, the monomer–dimer Kd was 5.6 µM, again with no detectable tetramer formation. For sedimentation equilibrium (SE) experiments, a wide range of Kd values was obtained for GluA2, from 13 to 284 nM, whereas for GluA3, the Kd of 3.1 µM was less than twofold different from the SV value. Analysis of cell contents after the ∼1-week centrifuge run by silver-stained gels revealed low molecular weight GluA2 breakdown products. Simulated data for SE runs demonstrate that the apparent Kd for GluA2 varies with the extent of proteolysis, leading to artificially high Kd values. SV experiments with fluorescence detection for GluA2 labeled with 5,6-carboxyfluorescein, and fluorescence anisotropy measurements for GluA2 labeled with DyLight405, yielded Kd values of 5 and 11 nM, consistent with those from SV with absorbance detection. However, the sedimentation coefficients measured by AUC using absorbance and fluorescence systems were strikingly different, and for the latter are not consistent with hydrodynamic protein models. Thus, for unknown reasons, the concentration dependence of sedimentation coefficients obtained with fluorescence detection SV may be unreliable, limiting the usefulness of this technique for quantitative analysis.