FiXR: a framework to reconstruct fiber cross‐sections from X‐ray fiber diffraction experiments. Issue 2 (10th February 2020) - Roig-Solvas, Biel; Brooks, Dana H.; Makowski, Lee
Abstract : A method is presented to reconstruct the 2D electron densities of fiber cross‐sections from disordered small‐angle X‐ray scattering measurements, combining fiber diffraction theory with physical constraints, like finite cross‐section size and non‐negative density, in a numerical optimization framework. Abstract : Ab initio reconstruction methods have revolutionized the capabilities of small‐angle X‐ray scattering (SAXS), allowing the data‐driven discovery of previously unknown molecular conformations, exploiting optimization heuristics and assumptions behind the composition of globular molecules. While these methods have been successful for the analysis of small particles, their impact on fibrillar assemblies has been more limited. The micrometre‐range size of these assemblies and the complex interaction of their periodicities in their scattering profiles indicate that the discovery of fibril structures from SAXS measurements requires novel approaches beyond extending existing tools for molecular discovery. In this work, it is proposed to use SAXS measurements, together with diffraction theory, to infer the electron distribution of the average cross‐section of a fiber. This cross‐section is modeled as a discrete electron density with continuous support, allowing representations beyond binary distributions. Additional constraints, such as non‐negativity or smoothness/connectedness, can also be added to the framework. The proposed approach is tested using simulated SAXS data from amyloid β fibril models and using measured data of Tobacco mosaic virus from SAXS experiments, recovering the geometry and density of the cross‐sections in all cases. The approach is further tested by analyzing SAXS data from different amyloid β fibril assemblies, with results that are in agreement with previously proposed models from cryo‐EM measurements. The limitations of the proposed method, together with an analysis of the robustness of the method and the combination with different experimental sources, are also discussed.