Single-shot diffraction data from the Mimivirus particle using an X-ray free-electron laser

نویسندگان

  • Tomas Ekeberg
  • Martin Svenda
  • M Marvin Seibert
  • Chantal Abergel
  • Filipe R N C Maia
  • Virginie Seltzer
  • Daniel P DePonte
  • Andrew Aquila
  • Jakob Andreasson
  • Bianca Iwan
  • Olof Jönsson
  • Daniel Westphal
  • Duško Odić
  • Inger Andersson
  • Anton Barty
  • Meng Liang
  • Andrew V Martin
  • Lars Gumprecht
  • Holger Fleckenstein
  • Saša Bajt
  • Miriam Barthelmess
  • Nicola Coppola
  • Jean-Michel Claverie
  • N Duane Loh
  • Christoph Bostedt
  • John D Bozek
  • Jacek Krzywinski
  • Marc Messerschmidt
  • Michael J Bogan
  • Christina Y Hampton
  • Raymond G Sierra
  • Matthias Frank
  • Robert L Shoeman
  • Lukas Lomb
  • Lutz Foucar
  • Sascha W Epp
  • Daniel Rolles
  • Artem Rudenko
  • Robert Hartmann
  • Andreas Hartmann
  • Nils Kimmel
  • Peter Holl
  • Georg Weidenspointner
  • Benedikt Rudek
  • Benjamin Erk
  • Stephan Kassemeyer
  • Ilme Schlichting
  • Lothar Strüder
  • Joachim Ullrich
  • Carlo Schmidt
  • Faton Krasniqi
  • Günter Hauser
  • Christian Reich
  • Heike Soltau
  • Sebastian Schorb
  • Helmut Hirsemann
  • Cornelia Wunderer
  • Heinz Graafsma
  • Henry Chapman
  • Janos Hajdu
چکیده

Free-electron lasers (FEL) hold the potential to revolutionize structural biology by producing X-ray pules short enough to outrun radiation damage, thus allowing imaging of biological samples without the limitation from radiation damage. Thus, a major part of the scientific case for the first FELs was three-dimensional (3D) reconstruction of non-crystalline biological objects. In a recent publication we demonstrated the first 3D reconstruction of a biological object from an X-ray FEL using this technique. The sample was the giant Mimivirus, which is one of the largest known viruses with a diameter of 450 nm. Here we present the dataset used for this successful reconstruction. Data-analysis methods for single-particle imaging at FELs are undergoing heavy development but data collection relies on very limited time available through a highly competitive proposal process. This dataset provides experimental data to the entire community and could boost algorithm development and provide a benchmark dataset for new algorithms.

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عنوان ژورنال:

دوره 3  شماره 

صفحات  -

تاریخ انتشار 2016