Diffraction data from aerosolized Coliphage PR772 virus particles imaged with the Linac Coherent Light Source

Haoyuan Li, Reza Nazari, Brian Abbey, Roberto Alvarez, Andrew Aquila, Kartik Ayyer, Anton Barty, Peter Berntsen, Johan Bielecki, Alberto Pietrini, Maximilian Bucher, Gabriella Carini, Henry N. Chapman, Alice Contreras, Benedikt J. Daurer, Hasan DeMirci, Leonie Flűckiger, Matthias Frank, Janos Hajdu, Max F. HantkeBrenda G. Hogue, Ahmad Hosseinizadeh, Mark S. Hunter, H. Olof Jönsson, Richard A. Kirian, Ruslan P. Kurta, Duane Loh, Filipe R.N.C. Maia, Adrian P. Mancuso, Andrew J. Morgan, Matthew McFadden, Kerstin Muehlig, Anna Munke, Hemanth Kumar Narayana Reddy, Carl Nettelblad, Abbas Ourmazd, Max Rose, Peter Schwander, M. Marvin Seibert, Jonas A. Sellberg, Raymond G. Sierra, Zhibin Sun, Martin Svenda, Ivan A. Vartanyants, Peter Walter, Daniel Westphal, Garth Williams, P. Lourdu Xavier, Chun Hong Yoon, Sahba Zaare

Research output: Contribution to journalArticlepeer-review

Abstract

Single Particle Imaging (SPI) with intense coherent X-ray pulses from X-ray free-electron lasers (XFELs) has the potential to produce molecular structures without the need for crystallization or freezing. Here we present a dataset of 285,944 diffraction patterns from aerosolized Coliphage PR772 virus particles injected into the femtosecond X-ray pulses of the Linac Coherent Light Source (LCLS). Additional exposures with background information are also deposited. The diffraction data were collected at the Atomic, Molecular and Optical Science Instrument (AMO) of the LCLS in 4 experimental beam times during a period of four years. The photon energy was either 1.2 or 1.7 keV and the pulse energy was between 2 and 4 mJ in a focal spot of about 1.3 μm x 1.7 μm full width at half maximum (FWHM). The X-ray laser pulses captured the particles in random orientations. The data offer insight into aerosolised virus particles in the gas phase, contain information relevant to improving experimental parameters, and provide a basis for developing algorithms for image analysis and reconstruction.

Original languageEnglish (US)
Article number404
JournalScientific Data
Volume7
Issue number1
DOIs
StatePublished - Dec 2020
Externally publishedYes

ASJC Scopus subject areas

  • Statistics and Probability
  • Information Systems
  • Education
  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Library and Information Sciences

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