Workshop

Day 1 – July 22, 2024:

This workshop will provide a brief introduction to AUC and will highlight the different methods that are in the AUC toolbox. The methods that will be investigated will be:

  1. Sedimentation velocity (SV)
  2. Density matching
  3. Density Gradient Equilibrium (DGE), also known as Analytical Buoyant Density Equilibrium (ABDE)
  4. Band sedimentation (BS)
  5. Sedimentation equilibrium (SE)
  6. Multiwavelength (MW) as a tool for SV and DGE

For each method, we will provide an overview of its principles, the type of information it can provide, and a couple of examples where the technique has been used.

SAXS/SANS measurements provide extremely useful low-resolution scattering profiles meant to describe 3D structures. Moving toward higher resolution profiles often requires the use of MD simulation to extract relevant 3D geometrical information. Since MD simulations are based on the use of the underlying molecular force-fields (inter-atomic interaction parameters), SAXS /SANS data can help with refining simulation models. Additionally, SAXS/SANS is capable of resolving biomolecular structures from NMR and X-ray crystallography, the most frequently used structure determination techniques which, however, may or may not faithfully represent structure in solution.

In this workshop we will use UltraScan to measure nucleic acid load in lipid nanoparticles (LNPs). There are two orthogonal methods presented, both of which are based on sedimentation velocity experiments (SVEs) that can be used to characterize drug loading:

  1. Measuring density distributions based on D2O density matching
  2. Multi-wavelength AUC to characterize differential absorbances of the liposome shell versus the nucleic acid absorbance spectrum.

Determining the amount of drug loaded into a LNP is of utmost importance for many biopharma applications. Determining the precise loading with nucleic acids is critical for achieving clinically relevant formulations, and to avoid antigenic materials in vaccines or gene therapy formulations. This can be challenging for many techniques since overall LNP size and shape may not proportionally change with the cargo load. However, the density, or partical specific volume of LNPs is a sensitive predictor of loading state, regardless of particle size, and the absorbance profiles of liposomes and nucleic acids is a unique characteristic that can be followed by AUC.
SVEs can be used to determine the sedimentation and diffusion coefficients, and partial concentrations of all solutes present in a sample with high resolution. In this workshop we will demonstrate how multiple SVEs performed in different D2O:H2O ratios can be used to globally fit a partial specific volume (PSV) distribution for samples that are heterogeneous in density, and to combine this information with MW-AUC information to uniquely identify the LNP loading state. Furthermore, we can combine the PSV distributions with the corresponding sedimentation and diffusion coefficient distributions to derive accurate molar mass, particle size and anisotropy distributions. Software modules implemented in UltraScan specifically addressing MW-AUC and PSV distribution measurements by SVEs will be discussed.

GUSSI is a software program that is designed to ease the generation of figures from biophysical data formats.  It is particularly useful in combination with SEDFIT and SEDPHAT, as these latter programs send data directly to GUSSI. Covered in this workshop will be the basics of GUSSI’s layout and operation, including working with multiple data sets, manipulating colors and markers, and generating legends.  Advanced GUSSI concepts, including rudimentary line fitting, formatting files for input to GUSSI, and exploring the wide array of biophysical data types pre-formatted in the program will also be discussed.

In this workshop we will present important new features in UltraScan that support the analysis of multi-wavelength AUC data, both in SV and in ABDE mode. The features will address the following topics:

  1. Correction/elimination of time-invariant noise in primary intensity data by subtracting an averaged intensity profile
  2. Correction/elimination of time-invariant noise in multi-wavelength ABDE experiments (which are time-invariant data to start with) without using finite element modeling, by using multi-wavelength reference scans, allowing up to 15 equilibrium samples to be measured in a single experiment
  3. Creation of analyte intrinsic molar extinction profiles by globally fitting wavelength scans of a dilution series
  4. A new CSV file format converter/loader/exporter
  5. Quality assessment of multi-wavelength spectral deconvolutions using a new 3D viewer
  6. A new multi-wavelength ABDE peak integration routine for AAV capsid species quantification

The workshop will be a demonstration of these features. Participants can bring their own (suitable) data and follow along on their own computers.

This workshop is targeted to AUC users at all levels of expertise. This workshop will take the form of a presentation. A brief overview of AUC will be provided, with a specific focus on interacting systems and how they differ from non-interacting systems.

Topics will include:

  1. Experimental design (SV-AUC vs EQ-AUC, choice of optical system, etc.)
  2. Examining the raw data
  3. Local analysis (g(s*)/WDA vs c(s) vs van Holde-Weischet)
  4. Global analysis (Sw isotherms vs direct boundary fitting)
  5. Advanced analyses like Wyman plots/linkage, thermodynamics and deltaG, hydrodynamic modeling, nonideality considerations, etc.

The PSV is one of the primary hydrodynamic parameters which quantitatively characterizes solute–solvent interactions and is required for computational analysis and interpretation of the data from hydrodynamic experimental techniques such as AUC, SAXS/SANS, and FS spectroscopy. Particularly, in the downstream analysis of the AUC data (e.g. in the UltraScan suite of programs), the PSV is an input parameter required for reliable transformation of the sedimentation and diffusion distributions measured in AUC to molar mass distributions. While there is strong evidence that PSV depends on the solvation buffer conditions (most notably, on the ionic strength and pH), accurate buffer-dependent PSV values for different classes of biomolecules are not available. Our research, in which we addressed numerous approximations and shortfalls in existing methods to assess biomolecular PSV, lays solid foundation for further increase in our method’s resolution which would enable us to study more subtle aspects of the interplay between quantitative changes in the solvation buffer conditions and the macroscopic quantities like PSV. Our findings (computed buffer-specific PSV values) are of immediate use to the high-resolution analysis of AUC data.

Gene therapies deliver genetic material to host cells to silence or repress a mutated gene, replace it with a healthy gene, or introduce a new gene to help fight diseases. Multiple approaches, drug delivery vectors, and potential drug targets make this field versatile and successful. One of the most widely used vectors is adeno-associated viruses (AAVs), as they are not known to be pathogenic and result in a low immune response. AAV formulations consist of both loaded (containing genetic material) and empty (lacking genetic material) vectors, in varying ratios. Their production can contain contaminants such as partially loaded or aggregated vectors or unpackaged nucleic acids. This rapidly evolving field requires continuous development to improve the safety and efficiency of treatments, which requires objective characterization methods capable of identifying all components present in a formulation.
Analytical ultracentrifuge (AUC) offers exciting innovations that can revolutionize studies focusing on the molecular basis of diseases and their cures. Recent advances in AUC hardware and software have allowed for the development of two new methods that can overcome these quality control issues. The first is sedimentation velocity (SV) multi-wavelength AUC (MW-AUC) which allows for the accurate separation of spectrally different macromolecules (proteins, lipids, and nucleic acids), resulting in reliable identification of loaded vs. partial or empty AAVs and other contaminants, providing significantly improved quality control of gene therapies. The second is analytical buoyant density equilibrium (ABDE). This method is analogous to the techniques used during AAV purification, where density gradient forming solvents separate loaded AAVs, empty AAVs, and contaminants based on their densities and results in baseline separated peaks for each analyte (Figure 2). Combining ABDE with MW-AUC results in the accurate identification of each solute peak. Furthermore, ABDE experiments significantly improve throughput and sensitivity, significantly reducing the amount of sample volume and concentration compared to SV MW-AUC. These methods are innovative biophysical approaches that can be used to characterize many macromolecular assemblies in their physiological solution environment. They are universally applicable to other vector systems and other viral therapeutics, as well as including lipid nanoparticles, bacteriophage formulations, and other gene therapy systems.
In this workshop, we will discuss experimental design, and the tools implemented in UltraScan to process AAV samples with multi-wavelength SV and ABDE experiments, and demonstrate the superior resolution, improved throughput, and reduced sample requirements.

Knowing the stoichiometry of interacting macromolecules is vital to a comprehensive understanding of the interaction’s thermodynamics. An excellent means to discover stoichiometry is multisignal sedimentation velocity (MSSV). This method leverages the ability of modern ultracentrifuges to probe the sedimentation of macromolecules using different wavelengths of light and different detection modalities. This ability, coupled with knowledge of the components’ signal increments, allows a global analysis of MSSV experiments to be conducted, decomposing the resulting solute distributions into component distributions, allowing the molar ration of co-sedimenting solutes to be determined. When this datum is coupled with the hydrodynamic properties of the complex, an accurate value for stoichiometry can be derived. This workshop will cover experimental strategies and hands-on data analysis of MSSV experiments in SEDPHAT.

Analytical Ultracentrifugation is perfectly suited for the analysis of particle size distributions (PSDs). However, the characterization of polydisperse PSDs is making high demands to any characterization technique. For sedimentation analysis, it has to be taken into account that the sedimentation rate scales with the particle size squared. To tackle such challenging systems, MWL gravitational sweep (GS) experiments at a fixed radial position were developed which are based on a continuously increasing rotor speed. GS experiments are of particular importance when studying polydisperse PSDs due the much larger dynamic range compared to traditional sedimentation velocity (SV) experiments.

HDR-MULTIFIT can be used to analyze GS data and provides the ability to determine the optical properties of individual components in polydisperse mixtures and to relate this data to the hydrodynamic properties. For spherical NPs having well-defined refractive indices, high dynamic range (HDR) particle size analysis is possible. The analysis benefits from the direct fractionation of different particle sizes in the measurement cell during sedimentation, while the optimum signal to noise ratio for the whole PSD is achieved by automatically tuning the wavelength used for data evaluation.

Besides GS experiments, it is demonstrated that HDR-MULTIFIT can also be used for the post-processing of sedimentation coefficient distributions from sedimentation velocity experiments (derived by e.g., SEDFIT, SEDANAL, Ultrascan, DCDT+). Concentration coupling and the simultaneous determination of size and density are further capabilities offered by HDR-MULTIFIT.

The workshop will tackle the following topics:

  1. Determination of particle sizes and their distributions
  2. The influence of scattering and the role of Mie’s theory
  3. Correction of size distributions and their weighting
  4. Multiwavelength analysis of GS experiments
  5. Concentration coupling experiments for polydisperse distributions
  6. Simultaneous analysis of size, density and refractive index increment using density variation

Most importantly, this workshop will include a hands on training on HDR-MULTIFIT.

This workshop is targeted to those familiar with the fundamentals of AUC, and who are interested in learning how to globally fit SV-AUC data. New users are encouraged to also attend the preceding workshop: “Basics of studying interacting systems by AUC.” Direct boundary fitting provides many benefits over fitting Sw isotherms. SEDANAL is extremely flexible and users can build custom models to fit against. This workshop will aim to familiarize users with a workflow for using SEDANAL to analyze SV-AUC data from interacting systems. Participants are encouraged to follow along on their own laptops. A copy of SEDANAL and simulated datasets will be provided prior to the workshop. Participants are also encouraged to read Stafford & Sherwood’s 2004 Biophysical Chemistry paper describing SEDANAL. This workshop may also provide a useful primer for Walter Stafford and Jack Correia’s more advanced SEDANAL workshops.

Topics will include:

  1. SEDANAL installation
  2. Preprocessing data
  3. Building a model
  4. Fitting and simulating data to a model
  5. Error analysis
  6. Overall interpretation and revisiting experimental design

UltraScan Solution Modeler (US-SOMO)[1,2] processes atomic and lower-resolution bead model representations of biological and other macromolecules to compute various hydrodynamic parameters, such as the sedimentation and diffusion coefficients, relaxation times and intrinsic viscosity. This allows the researcher to validate structural models against experimental data. The tools available in US-SOMO have been shown to provide the best known computations of hydrodynamic parameters from experiment [3]. The US-SOMO hydrodynamics workshop will consist of two sessions. In the first session, attendees will be given an introduction to computational hydrodynamics and techniques. In the second session, users will utilize US-SOMO to compute hydrodynamics parameters from structures and to use automated batch processing to compute over multiple structures. A brief introduction to the US-SOMO web version https://somoweb.genapp.rocks will be presented.

It is suggested that attendees attend both sessions, as earlier material will not be covered again during the two session course. Registered attendees will receive detailed software installation instructions in the week prior to the workshop.

This 2 session workshop will be presented on Monday 22 July at 14:30-16:30 and 17:00-19:00 (sessions 3 and 4).

References:
[1] Brookes, E. and Rocco, M., 2018. Recent advances in the UltraScan SOlution MOdeller (US-SOMO) hydrodynamic and small-angle scattering data analysis and simulation suite. European Biophysics Journal, 47(7), pp.855-864. doi:10.1007/s00249-018-1296-0.
[2] Rocco, M., Brookes, E. & Byron, O. US-SOMO: Methods for Construction and Hydration of Macromolecular Hydrodynamic Models. In: Encyclopedia of Biophysics, Roberts, G. & Watts, A., European Biophysical Societies (eds). Springer, Berlin, Heidelberg (2021). doi: 10.1007/978-3-642-35943-9_292-1.
[3] Rocco M, Byron O., 2015, “Hydrodynamic Modeling and Its Application in AUC.”, Methods Enzymol. 2015;562:81-108. doi: 10.1016/bs.mie.2015.04.010.

The UltraScan GMP module completely automates AUC data processing, observing 21 CFR, Part 11 GMP requirements for electronic records 1). The GMP process includes a complete description of the experimental design, which is stored read-only in the UltraScan LIMS database, and proceeds with automated data acquisition on the Optima AUC. After data collection is complete, the program automatically imports the data in the original double precision floating point format into the UltraScan LIMS database, without the ASCII loss of precision incurred in the Beckman program. In the next step, the program automatically edits the data. Next, the data will be analyzed automatically according to an analysis and result refinement workflow that is pre-defined in the experimental design protocol in the database. The analysis is performed on a supercomputer in parallel for all datasets in the experiment. After analysis is completed, and finite element models have been refined with 2DSA, 2DSA-FMB, 2DSA-IT, 2DSA-MC, and PCSA, the program proceeds to the reporting stage, automatically generating a comprehensive GMP report that is stored read-only in the UltraScan LIMS database. The program applies a collection of validation tests and reports automatically generated graphs, spreadsheets, and report items. In this workshop the participants will learn how to design a GMP protocol and run that protocol on the Optima AUC at the Canadian Center for Hydrodynamics. Questions about reporting formats, experimental design, 21 CFR-part 11 adherence and UltraScan data acquisition will be discussed.
1) Savelyev A, Gorbet GE, Henrickson A, Demeler B. Moving analytical ultracentrifugation software to a good manufacturing practices (GMP) environment. PLoS Comput Biol. 2020 Jun 19;16(6):e1007942. doi: 10.1371/journal.pcbi.1007942. PMID: 32559250; PMCID: PMC7347214.

Isothermal titration calorimetry (ITC) is widely used to study molecular interactions. A single experiment yields an unprecedented wealth of thermodynamic information, including changes in free energy, enthalpy, and entropy. No other method can boast this informational efficiency. In this workshop, ITC theory, experimental design, and analysis will be covered. Particular focuses will be integration using NITPIC, analysis using SEDPHAT, and illustration using GUSSI. Advanced experiments that utilize the global analysis of several experiments to yield information on changes in heat capacity, cooperativity, proton involvement, and “intrinsic” enthalpy will also be covered. Students will be led through guided analysis tutorials using provided data sets.

Integral membrane proteins (MPs) are physiologically embedded in a lipid bilayer, which provides a hydrophobic environment compatible with their nonpolar, transmembrane surfaces. Both structural and solution studies of MPs often involve their extraction, solubilization, purification, and characterization in a wide variety of detergent micelles. In this workshop, we will describe the AUC characterization and analysis of detergent solubilized membrane proteins. Parameters that can be evaluated include MP homogeneity, protein molar mass, bound detergent, and protein-protein association constants.

The AUC challenge of solubilized membrane protein samples is principally that detergent-solubilized membrane proteins represent a multicomponent system, in which different components (protein, detergent, lipid, water?) interact to form the different types of sedimenting particles (species). The samples are therefore necessarily polydisperse, principally because of the presence of free detergent micelles in solution. Depending on the specific conditions, this complexity can be disentangled by taking advantage of several key distinctions between protein and detergent properties. For example, detergents and proteins have distinct optical properties (different extinction coefficients and increments of refractive index), and different buoyant properties (partial specific volumes). Moreover, membrane protein-protein interactions (as protein stability) can significantly depend on the type and concentration of detergent. In addition to a presentation of the theoretical considerations and mathematical formalism, we will discuss practical implementation and analysis of both sedimentation velocity and sedimentation equilibrium experiments and analysis of membrane protein/detergent solutions. Topics to be covered include the following:

Sedimentation Velocity

  • How to determine the parameters needed for data analysis (partial specific volumes and increment of refractive indexes)
  • Strategies for the design of the cells and experiments
  • How to analyze the data using sedfit/sedphat/gussi programs
  • How to evaluate size distribution and non-interacting species, sample homogeneity, protein association state, amounts of bound detergent, and the limits of these analysis.

Sedimentation Equilibrium

  • How to determine parameters needed for data analysis (partial specific volumes)
  • Strategies for experimental design, including how to density match and what to do if density matching using water is not feasible
  • How to globally analyze the data using WinNonlin
  • How to evaluate molecular weight distributions for reversible equilibrium

Three aspects of AUC experiment design will be discussed in detail:

  1. Hardware setup: selection of rotor, centerpiece, windows, cell assembly/cleaning, cell alignment
  2. Protocol description: rotor speed selection, temperature control, radial spacing, interval between scans
  3. Optical systems: how they work, advantages and disadvantages of each and which to choose

An AUC simulator will be used for the presentation and will be made available to the participants. In addition to walking you through setting up an experiment, the program simulates the signals for the rotor timing pulse, as well as for each optical system so that you can see how data are acquired. Sedview, a simple, but powerful, wide-distribution data analysis program is part of the simulator. This program allows you to see the consequences of various experimental design choices, provides model-independent data analysis, and overlays data from different detectors and different experiments. Students will see the effects of multiple components and self-association on the raw data and in the simple analysis.

Further information will follow soon.

The ability to simulate a sedimentation velocity (SV) experiment before actually conducting it is a critical aid to experimental planning. Among the many questions that can be addressed are: How long with the experiment take? How many scans will I get? How will the downstream analyses behave with a given set of parameters? In this workshop, I will cover the theoretical and mathematical underpinnings of SV simulations and compare the ways simulation is handled in several freeware programs. In depth instruction on the use of SViMULATE will be offered, including advanced noise-generation algorithms, using PDB files as the basis for simulation, interacting systems, and non-ideal sedimentation.

Day 2 – July 23, 2024:

  1. Basic relations
    (intrinsic) sedimentation coefficient, (intrinsic) diffusion coefficient, intrinsic viscosity, partial specific volume, translational friction properties, molar mass, hydrodynamic invariant
  2. Sedimentation velocity experiments
    a. Sedimentation-diffusion analysis
    physically consistent values of the molar mass, alternative methods (size-exclusion chromatography / asymmetrical flow field-flow fractionation—multi-angle laser light scattering (SEC / AF4—MALLS))
    b. (Self-)assemblies in solution
    degree of aggregation, stability against dilution, complexation of genetic material, encapsulation of drugs, hydration
    c. Nanoscale drug delivery systems
    solution complexity including nanoparticles (NPs), encapsulated and free drug, targeting dye moieties, presence or absence of surfactants, colocalization studies
  3. Sizing aspects (AUC, DLS, SEC / AF4—MALLS)
    hydrodynamic size estimates based on sedimentation analysis (AUC), sedimentation-diffusion analysis (AUC), diffusion measurements (DLS), and radii of gyration (MALLS)

The UltraScan GMP module completely automates AUC data processing, observing 21 CFR, Part 11 GMP
requirements for electronic records. The GMP process includes a complete description of the experimental design, which is stored read-only in the UltraScan LIMS database, and proceeds with automated data acquisition on the Optima AUC. After data collection is complete, the program automatically imports the data in the original double precision floating point format into the UltraScan LIMS database, without the ASCII loss of precision incurred in the Beckman program. In the next step, the program automatically edits the data. Next, the data will be analyzed automatically according to an analysis and result refinement workflow that is pre-defined in the experimental design protocol in the database. The analysis is performed on a supercomputer in parallel for all datasets in the experiment. After analysis is completed, and finite element models have been refined with 2DSA, 2DSA-FMB, 2DSA-IT, 2DSA-MC, and PCSA, the program proceeds to the reporting stage, automatically generating a comprehensive GMP report that is stored read-only in the UltraScan LIMS database. The program applies a collection of validation tests and reports automatically generated graphs, spreadsheets, and report items. We will discuss the following novel features moving UltraScan into cGMP environment: (1) a comprehensive protocol development tool, that will empower less experienced scientists to design experiments more efficiently, and accelerate protocol development for samples whose sedimentation behavior is initially unknown; (2) a fully automated reporting module that will eliminate analysis bias, enhance data understanding, streamline processes, and establish a consistent format for comparing various experiments of the same sample; (3) the audit trail and electronic signatures modules allowing for enhanced traceability of the GMP data processing.

Multi-wavelength analytical ultracentrifugation (MW-AUC) is a recent development made possible in the new Optima AUC. It extends the hydrodynamic information typically obtained by measuring the sample at multiple wavelengths. MW-AUC adds an orthogonal spectral dimension to the traditional hydrodynamic characterization, allowing the researchers to identify different spectral molecules in the sample. It is poised to become an essential analytical tool for studying macromolecular interactions due to its ability to exploit unique chromophores in analyte mixtures.

This workshop will take a detailed look at the ABDE method and its setup and compare the results with SV results. ABDE separates analytes in a sample based on their densities as they sediment and float to the isopycnic points in a density gradient. By allowing the sample to settle within the solution column at the isopycnic point, the amount of sample required is reduced compared to SV experiments. This method has gained significant interest, particularly in the field of gene therapy, where samples can be expensive. The workshop will focus on the analysis of adeno-associated viruses (AAVs) and will examine their analysis and method setup using multiwavelength SV and ABDE methods, analyzed using UltraScan.

Membrane proteins and glycoproteins make up a large portion of the protein complement in a mammalian cell. But they offer special challenges to the hydrodynamicist. Membrane proteins are often solubilized by detergents, amphipols, or nanodiscs that cosediment with the protein. Glycoproteins have covalently attached sugar moieties that can obscure the nature of the protein component. However, with judicious use of the AUC’s optical systems and proper analytic methods, these proteins can be characterized. This workshop will explore experimental design, data acquisition, and data analysis for both membrane proteins and glycoproteins. An emphasis will be hands-on instruction regarding the utility functions built into GUSSI for the analysis of these challenging proteins.

HullRad is an algorithm and computer program to calculate hydrodynamic properties such as sedimentation and diffusion coefficients of macromolecules from structural models. Output includes Stokes radius, radius of gyration, rotational correlation time, and ellipsoidal axial ratio which are useful parameters to estimate the size and shape of molecules in solution. The algorithm is implemented in Python and is available as a web server and as freely distributed code. Calculations are fast, and with locally installed code, it is feasible to calculate the hydrodynamic properties of thousands of structures in a very short time. Such calculations are useful for validation of model ensembles of unfolded, disordered, or highly flexible molecules. An alternate version, HullRadSAS, provides additional information about molecular hydration and hydrated radius of gyration for comparison to SAXS data. This workshop on HullRad will demonstrate different ways to run HullRad. An introduction to the rationale behind the HullRad algorithm will also be presented.

Notes:
Hands-on: Bring your laptops and PDB/mmCIF files of any structural models you are interested in. We will download HullRad and calculate hydrodynamic properties of your favorite molecules. If you have an ensemble collection of structural models, even better.

Analytical Ultracentrifugation (AUC) was originally invented for the analysis of nanoparticles. It is still a great tool for their analysis. However, nanoparticles pose special challenges to the researcher, which are typically not encountered in the analysis of proteins. These are:

  • Polydispersity
  • Hybrid character and therefore folded particle size and particle density distribution
  • Stabilization by charge, which cannot be shielded by buffers
  • A size which already leads to light scattering superimposing the signal by absorption
  • Shape distributions
  • Size dependent optical properties

The workshop will be in form of a presentation demonstrating solutions to these challenges as well as a discussion. These strategies can also be adapted to extremely polydisperse Biopolymers and complexes, which also have some of the above problems in common with nanoparticles. Users are encouraged to bring their own examples with them for discussion.

This workshop is targeted to participants interested in implementing SV-AUC in a cGMP environment. There is a major interest in using SV-AUC for characterization and release testing of gene and cell therapy products. BioAnalysis, LLC has developed a program (BASIS) which allows for data loading, data analysis using SEDFIT, integrating, reviewing, and reporting of SV-AUC data. The program was developed specifically for use in a cGMP environment and is 21 CFR Part 11 compliant, has undergone computer software validations, evaluated in numerous audits, and used for over 2 years at BioAnalysis, LLC. The objective of BASIS is to be a simple and efficient tool, and it offers many features that simplify and improve the overall user experience. This workshop will be a presentation that includes a walkthrough of the BASIS workflow.

A wide host of methods are available to the modern biophysicist to characterize the in vitro thermodynamics of interactions. Among these are microscale thermophoresis (MST), fluorescence polarization (FP), and biolayer interferometry (BLI). All of these methods are commonly used to determine the free energy of interaction of two or more macromolecules. Less usual is the study of the binding of small molecules to protein, but this can also be accomplished in some cases. The theoretical aspects of these methods will be summarized in this workshop, along with experimental strategies and analytic practices. Hands-on analyses of these data types using the software PALMIST will demonstrate the advanced fitting and error-analysis aspects of the program.

Outline:
AAV characterizations by following three types of analytical ultracentrifugation will be covered in this workshop.

  • Sedimentation Velocity (with or without multiwavelength detection) [1]
  • Band Sedimentation [2]
  • Equilibrium Density Gradient [3, 4]

Specific contents:
Reliable identification of full, empty, extra-filled, and partial particles.

  1. Accurate quantification of full and empty particles.
  2. Purity assessment.
  3. Deep characterization of full particles with different VP ratio.

References:
[1] Maruno T et al, Comprehensive Size Distribution and Composition Analysis of Adeno-Associated Virus Vector by Multiwavelength Sedimentation Velocity Analytical Ultracentrifugation. J. Pharm. Sci. 110, 3375-3384 (2021).
[2] Maruno T et al., Size Distribution Analysis of the Adeno-Associated Virus Vector by the c(s) Analysis of Band Sedimentation Analytical Ultracentrifugation with Multiwavelength Detection. J Pharm Sci. 112, 937-946 (2023).
[3] Hirohata K et al, Applications and Limitations of Equilibrium Density Gradient Analytical Ultracentrifugation for the Quantitative Characterization of Adeno-Associated Virus Vectors. Anal. Chem. 96, 642-651 (2024).
[4] Ohnishi et al., Enhancement of recombinant adeno-associated virus activity by improved stoichiometry and homogeneity of capsid protein assembly. Molecular Therapy: Methods & Clinical Development 31, (2023).

The UltraScan Solution Modeler (US-SOMO)[1] has, in addition to hydrodynamic parameter calculation from structure, native and wrapped tools for computation of simulated biological solution small angle scattering (BioSAS) data from structure, processing of BioSAS data and comparison of simulated data against experimental data. US-SOMO also contains powerful tools for the analysis of size exclusion coupled small angle X-ray scattering (SEC-SAXS) data [2]. In this two session workshop, we will begin with an introduction to BioSAS. This will begin with an overview of the basics of BioSAS and its importance to the researcher. Next, during the first session, we will introduce the attendees to the available BioSAS tools within US-SOMO. In the second session, the attendees will work through hands-on exercices using US-SOMO with a focus on the SEC-SAXS tools.

It is suggested that attendees attend both sessions, as earlier material will not be covered again during the 2 session course. Registered attendees will receive detailed software installation instructions in the week prior to the workshop.

This workshop will be presented on Tuesday 23 July from 14:30-16:30 and 17:00-19:00 (sessions 7 and 8).

References:
[1] Brookes, E. and Rocco, M., 2018. Recent advances in the UltraScan SOlution MOdeller (US-SOMO) hydrodynamic and small-angle scattering data analysis and simulation suite. European Biophysics Journal, 47(7), pp.855-864. doi:10.1007/s00249-018-1296-0.
[2] Brookes, E., Vachette, P., Rocco, M. and Pérez, J., 2016. US-SOMO HPLC-SAXS module: dealing with capillary fouling and extraction of pure component patterns from poorly resolved SEC-SAXS data. Journal of applied crystallography, 49(5), pp.1827-1841. doi: 10.1107/S1600576716011201.

This workshop will cover the analysis of multiwavelength (MWL) data from both the Beckman Optima AUC, and the Colfen and Schilling type multiwavelength instruments using the SEDANAL software. We will cover how to use the Preprocessor to deconvolute the individual concentration profiles of species for which the extinction spectra are known. We will also demonstrate how to determine each individual species’ extinction spectrum in unknown mixtures if the species exhibit sufficient resolution in the AUC using Wide Distribution Analysis (WDA). Direct whole boundary fitting of models to mixtures–either interacting or non-interacting–can be carried out with the SEDANAL Fitter given the extinction spectra of the various components involved. Students are encouraged to bring multiwavelength datasets to workshop for analysis. Students should prepare for this workshop by reading the following:
Johannes Walter, Peter J. Sherwood, Wei Lin, Doris Segets, Walter F. Stafford, and Wolfgang Peukert (2015) Simultaneous analysis of hydrodynamic and optical properties using analytical ultracentrifugation equipped with multiwavelength detection. Anal Chem 87:3396–3403
and
Sherwood, P.J. and Stafford W.F. SEDANAL: Model-Dependent and Model-Independent Analysis of Sedimentation Data” in Analytical Ultracentrifugation. Instrumentation, Software, and Applications, Eds. Uchiyama, S, Arisaka, F., Stafford, W.F., and Laue T.M., Springer Japan. Chapter 6, pp 99-101.

Please note:
The current version of SEDANAL along with the User Manual can be downloaded from http://sedanal.org/latest/.

AUC in the sedimentation-velocity (SV) mode is excellent for the determination of molar masses of macromolecules and the stoichiometries their complexes. A less-exploited strength of the method is its very high resolution in sedimentation-coefficient space. In carefully conducted SV experiments, differences in the sedimentation coefficients on the order of 0.01 S can be detected. This extremely high resolution can be leveraged to determine the existence and extent of a ligand-induced conformational change, even in moderately sized proteins. This workshop will focus on historical exploitation of this information, followed by the precepts of experimental design for SV studies to detect ligand-induced conformational changes. Finally, data-analysis will be discussed, and students will be guided through the analysis of real SV data sets using the software DiSECT.

Program overview and demonstration
Prerequisites: none (suitable for novice AUC users)
Description
Introduction to SEDNTERP and its use for calculating:

  • solvent density, viscosity, and refractive index
  • sample partial specific volume, hydration, and specific refractive increment (dn/dc)
  • standardized sedimentation or diffusion coefficients (s20,w or D20,w¬) from raw experimental values
  • sedimentation or diffusion coefficients extrapolated to zero concentration, and their concentration-dependence coefficients ks and kD
  • hydrodynamic parameters from SV or diffusion results:
    • anhydrous sphere radius, and corresponding maximum possible sedimentation and diffusion coefficients
    • sample frictional coefficient, f/f0 ratio, and Stokes radius
    • sample overall hydrodynamic shape and hydration characteristics (max hydration, Perrin P function, actual molecular size and shape for ellipsoid or cylinder models)

Since the early days of protein characterization, the development of AUC analysis for high concentration SV data has been a critical focus. The early Model E Schlieren optical system worked best from 5-20 mg/ml. With the advent of therapeutic antibodies delivered at up to 150 mg/ml, high concentration AUC techniques continue to be proven irreplaceable. This workshop will discuss two essential steps in FDS AUC data collection and analysis:

  1. Experimental setup of FDS SV runs at high concentrations.
  2. Analysis of FDS SV data with nonideal, associating models in SEDANAL.

We typically perform experiments in tracer mode with 100 nM Alexa-labeled mAbs in unlabeled mAb concentrations from 1 to 150 mg/ml. FDS optics do not need reference channels, so we run up to six samples in a four hole rotor with 3 mm centerpieces. For this reason, sample labeling and equilibration will be discussed. We process FDS data for meniscus and base regions, and globally fit with models that account for hydrodynamic k s and thermodynamic nonideality BM 1 , plus weak association. Therefore, basic SEDANAL procedures (data preprocessor and ModelEditor) will be presented. Lastly, we perform error analysis by bootstrap with replacement methods. Experiments can also be performed in human serum, which necessitates knowing serum protein concentrations and the use of matrix methods for k s and BM 1 cross term nonideality parameters. Data sets will be provided for student testing. SEDANAL runs in Windows 10 or 11, and on a Mac, requires Parallels, Boot Camp or VWware. Students should prepare for this workshop by reading Correia, et al. Eur. Biophys. J 49, 687, 2020.

Please note:
The current version of SEDANAL along with the User Manual can be downloaded from http://sedanal.org/latest/.

A tutorial
Prerequisites: at least some familiarity with c(s) analysis in SEDFIT (or similar size-distribution methods in ULTRASCAN)

Description
Although sedimentation coefficient distributions are widely used to identify what species (peaks) are present in a sample, it is usually difficult to determine the confidence limits for the properties of those species. In particular, SEDFIT provides no information about the precision of the peak fractions, which in many cases is the property of most interest. Furthermore, although SEDFIT can use Monte-Carlo approaches to try to assess a confidence region for each point (sedimentation coefficient) in the c(s) curve, that approach can be misleading because it doesn’t explicitly deal with the fact that there is uncertainty in the position of each peak. A third important point is that Monte-Carlo approaches assume the noise in the raw data is randomly distributed, which is never really true for AUC data.
This tutorial will show you how to use the user-friendly, public-domain program SVEDBERG to easily translate your c(s) distribution to a mixture model and then calculate confidence limits for the peak fractions, sedimentation coefficient, and the molar mass for each peak using any of three different statistical approaches (including the bootstrap method, which makes no assumptions about the noise in the data being random).
The workshop will also demonstrate how we can use SVEDBERG to sequentially release the built-in constraint of the c(s) method that every species has the same hydrodynamic shape (f/f0 ratio), and thereby learn how much information about the molar mass (or shape) of each species is truly present in the raw data.

It is important that you are registered so we can associate your registration (further information will follow soon) with the proposed workshop. You can update your selected workshop up to one week prior to the conference.

Anticipated workshop schedule:

Day Session Time
Monday, July 22th 1 9:00 – 11:00
2 11:30 – 13:30
3 14:30 – 16:30
4 17:00 – 19:00
Tuesday, July 23th 5 9:00 – 11:00
6 11:30 – 13:30
7 14:30 – 16:30
8 17:00 – 19:00