Low-signal limit of X-ray single particle diffractive imaging

Abstract

An outstanding question in X-ray single particle imaging experiments has been is the feasibility of imaging sub 10-nm-sized biomolecules under realistic experimental conditions where very few photons are expected to be measured in a single snapshot and instrument background may be significant relative to particle scattering. While analyses of simulated data have shown that the determination of an average image should be feasible using Bayesian algorithms such as the EMC algorithm for near-perfect diffraction patterns, this has yet to be demonstrated using experimental data containing realistic non-isotropic instrument background, sample variability and other experimental factors. In this work, we show that the orientation and phase retrieval steps work at photon counts diluted to the signal levels one expects from smaller molecules or with weaker pulses using data from experimental measurements of 60-nm PR772 viruses. Even when the signal is reduced to a fraction as little as 1/256, the virus electron density determined using ab initio phasing is of almost the same quality as the high-signal data.

An advanced workflow for single-particle imaging with the limited data at an X-ray free-electron laser

“…To reduce the influence of this background contribution, a background subtraction was applied. Several approaches for the background correction in SPI experiment analysis were developed earlier (Rose et al, 2018;Lundholm et al, 2018;Ayyer et al, 2019) and it was understood that the background-correction method may affect the reconstructed structure. Here we used a combined approach for the background determination, first a constant background was subtracted and then, on the reconstruction step, the contrast of diffraction patterns was additionally enhanced by applying deconvolution algorithms (see the next section for details).…”

3D diffractive imaging of nanoparticle ensembles using an x-ray laser

“…Each of these intensities represent an average of aligned copies of a subset of the patterns from the whole set. In addition to the EMC algorithm being highly noise-tolerant [7,29,30], one can also use it to examine the average models to understand what type of particles are in the dataset.…”

“…The fraction of good hits used for 3D structure reconstruction varied from 17 % for the cube samples to around 60 % for the octahedra (see Table 1). The 3D intensity distribution was obtained using these patterns before recovering the structures by performing phase retrieval using the difference map algorithm [7,33]. For computational efficiency, the 3D orientations were first determined using the low-resolution part of the detector where the highest resolution was 3.3 nm.…”

“…Single particle imaging at XFELs consists of collecting coherent diffraction patterns from individual particles intersecting bright XFEL pulses. Theoretical work predicts that currently available XFEL sources generate enough scattered photons from single macromolecules to solve for their unknown orientations and reconstruct 3D structures of large reproducible biomolecules [5][6][7]. Proof-of-principle SPI experiments on biological particles [8][9][10][11][12][13][14] have highlighted the challenges of the approach i.e.…”

Determination of the Structure of Biological Macromolecular Particles Using X-Ray Lasers. Achievements and Prospects

“…В работе [128] авторы модифицировали экспериментальные данные, снятые ранее на LCLS. Авторы попытались симулировать либо дифракцию от меньшей частицы, либо более слабую интенсивность дифракции.…”