Coherent diffractive imaging of proteins and viral capsids: simulating MS SPIDOCShow others and affiliations
2023 (English)In: Analytical and Bioanalytical Chemistry, ISSN 1618-2642, E-ISSN 1618-2650, Vol. 415, no 18 SI, p. 4209-4220Article in journal (Refereed) Published
Abstract [en]
MS SPIDOC is a novel sample delivery system designed for single (isolated) particle imaging at X-ray Free-Electron Lasers that is adaptable towards most large-scale facility beamlines. Biological samples can range from small proteins to MDa particles. Following nano-electrospray ionization, ionic samples can be m/z-filtered and structurally separated before being oriented at the interaction zone. Here, we present the simulation package developed alongside this prototype. The first part describes how the front-to-end ion trajectory simulations have been conducted. Highlighted is a quadrant lens; a simple but efficient device that steers the ion beam within the vicinity of the strong DC orientation field in the interaction zone to ensure spatial overlap with the X-rays. The second part focuses on protein orientation and discusses its potential with respect to diffractive imaging methods. Last, coherent diffractive imaging of prototypical T = 1 and T = 3 norovirus capsids is shown. We use realistic experimental parameters from the SPB/SFX instrument at the European XFEL to demonstrate that low-resolution diffractive imaging data (q < 0.3 nm−1) can be collected with only a few X-ray pulses. Such low-resolution data are sufficient to distinguish between both symmetries of the capsids, allowing to probe low abundant species in a beam if MS SPIDOC is used as sample delivery.
Place, publisher, year, edition, pages
Springer Nature, 2023. Vol. 415, no 18 SI, p. 4209-4220
Keywords [en]
SPI, X-ray, Native MS, Protein complex structure, Viral particles, Simulation, Modeling
National Category
Biophysics
Identifiers
URN: urn:nbn:se:uu:diva-500359DOI: 10.1007/s00216-023-04658-yISI: 000963181300001PubMedID: 37014373OAI: oai:DiVA.org:uu-500359DiVA, id: diva2:1750920
Funder
Swedish Research Council, 2018-00740Swedish Research Council, 2020-04825EU, Horizon 2020, 8014062023-04-142023-04-142025-02-20Bibliographically approved