REGALS: a general method to deconvolve X-ray scattering data from evolving mixtures.

Steve P Meisburger,Da Xu,Nozomi Ando

doi:10.1107/s2052252521000555

Abstract

Mixtures of biological macromolecules are inherently difficult to study using structural methods, as increasing complexity presents new challenges for data analysis. Recently, there has been growing interest in studying evolving mixtures using small-angle X-ray scattering (SAXS) in conjunction with time-resolved, high-throughput or chromatography-coupled setups. Deconvolution and interpretation of the resulting datasets, however, are nontrivial when neither the scattering components nor the way in which they evolve are known a priori. To address this issue, the REGALS method (regularized alternating least squares) is introduced, which incorporates simple expectations about the data as prior knowledge, and utilizes parameterization and regularization to provide robust deconvolution solutions. The restraints used by REGALS are general properties such as smoothness of profiles and maximum dimensions of species, making it well suited for exploring datasets with unknown species. Here, REGALS is applied to the analysis of experimental data from four types of SAXS experiment: anion-exchange (AEX) coupled SAXS, ligand titration, time-resolved mixing and time-resolved temperature jump. Based on its performance with these challenging datasets, it is anticipated that REGALS will be a valuable addition to the SAXS analysis toolkit and enable new experiments. The software is implemented in both MATLAB and Python and is available freely as an open-source software package.

Highlights

Small-angle X-ray scattering (SAXS) is a widely used technique for obtaining structural information from macromolecules in solution (Putnam et al, 2007)
As described in the Methods section, we analyzed a dataset previously reported for the large subunit of Bacillus subtilis ribonucleotide reductase (BsRNR) (Parker et al, 2018), which eluted from the column in two main peaks during a linear gradient of 100 to 400 mM NaCl [Fig. 2(a)]
Based on the successful application of real-space REGALS to the challenging phenylalanine hydroxylase (PheH) titration dataset, we considered whether similar models might be applied to time-resolved SAXS

Summary

Introduction

Small-angle X-ray scattering (SAXS) is a widely used technique for obtaining structural information from macromolecules in solution (Putnam et al, 2007). Because of the fundamental limitations in the information content of the SAXS signal (Moore, 1980), multiple structures in a mixture cannot be resolved from each profile in an unambiguous manner This inherent ambiguity can be mitigated by combining multiple measurements and carefully incorporating prior knowledge. The individual components can be separated mathematically by analyzing the dataset as a whole using a physicochemical model for how the mixture evolves (Williamson et al, 2008; Cho et al, 2010; Minh & Makowski, 2013) or known scattering curves of each component (Konarev et al, 2003) Often, both the scattering curves and physicochemical model are unknown before the experiment is performed and must be inferred from the data themselves.

Objectives

Methods

Results

Conclusion