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

IUCrJ ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 225-237
Author(s):  
Steve P. Meisburger ◽  
Da Xu ◽  
Nozomi Ando

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.

2020 ◽  
Author(s):  
Steve P. Meisburger ◽  
Da Xu ◽  
Nozomi Ando

AbstractMixtures 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, we introduce the REGALS method (REGularized Alternating Least Squares), 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, which makes it well-suited for exploring datasets with unknown species. Here we apply REGALS to analyze 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, we anticipate 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.


2018 ◽  
Vol 2 (1) ◽  
pp. 69-79 ◽  
Author(s):  
Martin A. Schroer ◽  
Dmitri I. Svergun

Small-angle X-ray scattering (SAXS) has become a streamline method to characterize biological macromolecules, from small peptides to supramolecular complexes, in near-native solutions. Modern SAXS requires limited amounts of purified material, without the need for labelling, crystallization, or freezing. Dedicated beamlines at modern synchrotron sources yield high-quality data within or below several milliseconds of exposure time and are highly automated, allowing for rapid structural screening under different solutions and ambient conditions but also for time-resolved studies of biological processes. The advanced data analysis methods allow one to meaningfully interpret the scattering data from monodisperse systems, from transient complexes as well as flexible and heterogeneous systems in terms of structural models. Especially powerful are hybrid approaches utilizing SAXS with high-resolution structural techniques, but also with biochemical, biophysical, and computational methods. Here, we review the recent developments in the experimental SAXS practice and in analysis methods with a specific focus on the joint use of SAXS with complementary methods.


2014 ◽  
Vol 47 (4) ◽  
pp. 1190-1198 ◽  
Author(s):  
Stephan Niebling ◽  
Alexander Björling ◽  
Sebastian Westenhoff

Time-resolved small- and wide-angle X-ray scattering (SAXS and WAXS) methods probe the structural dynamics of proteins in solution. Although technologically advanced, these methods are in many cases limited by data interpretation. The calculation of X-ray scattering profiles is computationally demanding and poses a bottleneck for all SAXS/WAXS-assisted structural refinement and, in particular, for the analysis of time-resolved data. A way of speeding up these calculations is to represent biomolecules as collections of coarse-grained scatterers. Here, such coarse-graining schemes are presented and discussed and their accuracies examined. It is demonstrated that scattering factors coincident with the popular MARTINI coarse-graining scheme produce reliable difference scattering in the range 0 < q < 0.75 Å−1. The findings are promising for future attempts at X-ray scattering data analysis, and may help to bridge the gap between time-resolved experiments and their interpretation.


2020 ◽  
Vol 42 (1) ◽  
pp. 36-42
Author(s):  
Melissa Gräwert ◽  
Dmitri Svergun

The Beginner's Guide series covers key techniques and offers the scientifically literate but not necessarily expert audience a background briefing on the underlying science of a technique that is (or will be) widely used in molecular bioscience. The series covers a mixture of techniques, including some that are well established amongst a subset of our readership but not necessarily familiar to those in different specialisms. This Beginner's Guide introduces solution small-angle X-ray scattering (SAXS). Solution small-angle X-ray scattering (SAXS) is a powerful technique, which is complementary to different bioanalytical and structural methods. With straightforward data collection procedures and minimal restrictions in sample environment, information on size, shape and conformational flexibility of biological macromolecules and complexes in near native solutions can be rapidly obtained. Here, we highlight the recent developments that have advanced SAXS to a versatile tool with the capability to enrich almost any biochemical study.


2018 ◽  
Vol 25 (4) ◽  
pp. 1113-1122 ◽  
Author(s):  
Martin A. Schroer ◽  
Clement E. Blanchet ◽  
Andrey Yu. Gruzinov ◽  
Melissa A. Gräwert ◽  
Martha E. Brennich ◽  
...  

Radiation damage by intense X-ray beams at modern synchrotron facilities is one of the major complications for biological small-angle X-ray scattering (SAXS) investigations of macromolecules in solution. To limit the damage, samples are typically measured under a laminar flow through a cell (typically a capillary) such that fresh solution is continuously exposed to the beam during measurement. The diameter of the capillary that optimizes the scattering-to-absorption ratio at a given X-ray wavelength can be calculated a priori based on fundamental physical properties. However, these well established scattering and absorption principles do not take into account the radiation susceptibility of the sample or the often very limited amounts of precious biological material available for an experiment. Here it is shown that, for biological solution SAXS, capillaries with smaller diameters than those calculated from simple scattering/absorption criteria allow for a better utilization of the available volumes of radiation-sensitive samples. This is demonstrated by comparing two capillary diameters d i (d i = 1.7 mm, close to optimal for 10 keV; and d i = 0.9 mm, which is nominally sub-optimal) applied to study different protein solutions at various flow rates. The use of the smaller capillaries ultimately allows one to collect higher-quality SAXS data from the limited amounts of purified biological macromolecules.


2015 ◽  
Vol 22 (1) ◽  
pp. 180-186 ◽  
Author(s):  
Alvin Samuel Acerbo ◽  
Michael J. Cook ◽  
Richard Edward Gillilan

X-ray scattering of biological macromolecules in solution is an increasingly popular tool for structural biology and benefits greatly from modern high-brightness synchrotron sources. The upgraded MacCHESS BioSAXS station is now located at the 49-pole wiggler beamline G1. The 20-fold improved flux over the previous beamline F2 provides higher sample throughput and autonomous X-ray scattering data collection using a unique SAXS/WAXS dual detectors configuration. This setup achieves a combinedq-range from 0.007 to 0.7 Å−1, enabling better characterization of smaller molecules, while opening opportunities for emerging wide-angle scattering methods. In addition, a facility upgrade of the positron storage ring to continuous top-up mode has improved beam stability and eliminated beam drift over the course of typical BioSAXS experiments. Single exposure times have been reduced to 2 s for 3.560 mg ml−1lysozyme with an average quality factorI/σ of 20 in the Guinier region. A novel disposable plastic sample cell design that incorporates lower background X-ray window material provides users with a more pristine sample environment than previously available. Systematic comparisons of common X-ray window materials bonded to the cell have also been extended to the wide-angle regime, offering new insight into best choices for variousq-space ranges. In addition, a quantitative assessment of signal-to-noise levels has been performed on the station to allow users to estimate necessary exposure times for obtaining usable signals in the Guinier regime. Users also have access to a new BioSAXS sample preparation laboratory which houses essential wet-chemistry equipment and biophysical instrumentation. User experiments at the upgraded BioSAXS station have been on-going since commissioning of the beamline in Summer 2013. A planned upgrade of the G1 insertion device to an undulator for the Winter 2014 cycle is expected to further improve flux by an order of magnitude.


2020 ◽  
Author(s):  
Susanne Seibt ◽  
Timothy Ryan

With the advent of new in situ structural characterisation techniques including X-ray scattering, there has been an increased interest in investigations of the reaction kinetics of nucleation and growth of nanoparticles as well as self-assembly processes. In this chapter, we discuss the applications of microfluidic devices specifically developed for the investigation of time resolved analysis of growth kinetics and structural evolution of nanoparticles and nanofibers. We focus on the design considerations required for spectrometry and SAXS analysis, the advantages of using a combination of SAXS and microfluidics for these measurements, and discuss in an applied fashion the use of these devices for time-resolved research.


1996 ◽  
Vol 451 ◽  
Author(s):  
A. C. Finnefrock ◽  
L. J. Bullert ◽  
K. L. Ringland ◽  
P. D. Tingi ◽  
H. D. Abruña ◽  
...  

ABSTRACTWe report in situ time-resolved surface x-ray scattering measurements of the underpoten-tial deposition of Cu2+ on Pt(111) in the presence of Cl− in HClO4 solution. Chronoamperometric (current vs. time) measurements indicate that after a potential step, the electrode-position current decays to 1/e of its initial value in at most 0.12 seconds. In contrast, our simultaneous time-resolved surface x-ray scattering data reveal that the overlayer requires on the order of two seconds to develop long-range periodic order. These results demonstrate that the kinetics of surface ordering can be significantly different from the kinetics of charge-transfer and illustrate the power of time-resolved surface x-ray scattering for in situ studies of electrodeposition.


2006 ◽  
Vol 411 (1) ◽  
pp. 202-205 ◽  
Author(s):  
A. N. Ozerin ◽  
A. M. Muzafarov ◽  
L. A. Ozerina ◽  
D. S. Zavorotnyuk ◽  
I. B. Meshkov ◽  
...  

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