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

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

Edité par CCSD ; Nature Publishing Group -

International audience. 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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