Friday, February 04, 2011

Compressive auto-indexing in femtosecond nanocrystallography

Stefano Marchesini sent me the following:
Hi Igor,
there is a recent paper in Nature that might be of interest to you:

several terabytes of data were processed using fairly standard crystallographic software, but we are investigating better ways. The connection with compressive sensing is made here:
The model was very simple and needs work, I include the code used for the figures of that paper, in case you are interested, (it takes too much paperwork to publish it myself).


The Nature paper is :Femtosecond X-ray protein nanocrystallography by Henry N. Chapman, Petra Fromme, Anton Barty, Thomas A. White, Richard A. Kirian, Andrew Aquila, Mark S. Hunter, Joachim Schulz, Daniel P. DePonte, Uwe Weierstall, R. Bruce Doak, Filipe R. N. C. Maia, Andrew V. Martin, Ilme Schlichting, Lukas Lomb, Nicola Coppola, Robert L. Shoeman, Sascha W. Epp, Robert Hartmann, Daniel Rolles, Artem Rudenko, Lutz Foucar, Nils Kimmel, Georg Weidenspointner, Peter Holl, Mengning Liang, Miriam Barthelmess, Carl Caleman, Sébastien Boutet, Michael J. Bogan, Jacek Krzywinski, Christoph Bostedt, Saša Bajt, Lars Gumprecht, Benedikt Rudek, Benjamin Erk, Carlo Schmidt, André Hömke, Christian Reich, Daniel Pietschner, Lothar Strüder, Günter Hauser, Hubert Gorke, Joachim Ullrich, Sven Herrmann, Gerhard Schaller, Florian Schopper, Heike Soltau, Kai-Uwe Kühnel, Marc Messerschmidt, John D. Bozek, Stefan P. Hau-Riege, Matthias Frank, Christina Y. Hampton, Raymond G. Sierra, Dmitri Starodub, Garth J. Williams, Janos Hajdu, Nicusor Timneanu, M. Marvin Seibert, Jakob Andreasson, Andrea Rocker, Olof Jönsson, Martin Svenda, Stephan Stern, Karol Nass, Robert Andritschke, Claus-Dieter Schröter, Faton Krasniqi, Mario Bott, Kevin E. Schmidt, Xiaoyu Wang, Ingo Grotjohann, James M. Holton, Thomas R. M. Barends, Richard Neutze, Stefano Marchesini, Raimund Fromme, Sebastian Schorb, Daniela Rupp, Marcus Adolph, Tais Gorkhover, Inger Andersson, Helmut Hirsemann, Guillaume Potdevin,Heinz Graafsma,Björn Nilsson; John C. H. Spence et al. the abstract reads:
X-ray crystallography provides the vast majority of macromolecular structures, but the success of the method relies on growing crystals of sufficient size. In conventional measurements, the necessary increase in X-ray dose to record data from crystals that are too small leads to extensive damage before a diffraction signal can be recorded1, 2, 3. It is particularly challenging to obtain large, well-diffracting crystals of membrane proteins, for which fewer than 300 unique structures have been determined despite their importance in all living cells. Here we present a method for structure determination where single-crystal X-ray diffraction ‘snapshots’ are collected from a fully hydrated stream of nanocrystals using femtosecond pulses from a hard-X-ray free-electron laser, the Linac Coherent Light Source4. We prove this concept with nanocrystals of photosystem I, one of the largest membrane protein complexes5. More than 3,000,000 diffraction patterns were collected in this study, and a three-dimensional data set was assembled from individual photosystem I nanocrystals (~200 nm to 2 μm in size). We mitigate the problem of radiation damage in crystallography by using pulses briefer than the timescale of most damage processes6. This offers a new approach to structure determination of macromolecules that do not yield crystals of sufficient size for studies using conventional radiation sources or are particularly sensitive to radiation damage.
The connecting paper (to compressive sensing) is: Compressive auto-indexing in femtosecond nanocrystallography by Filipe R. N. C. Maia, Chao Yang, Stefano Marchesini. The abstract reads:
Ultrafast nanocrystallography has the potential to revolutionize biology by enabling structural elucidation of proteins for which it is possible to grow crystals with 10 or fewer unit cells on the side. The success of nanocrystallography depends on robust orientation-determination procedures that allow us to average diffraction data from multiple nanocrystals to produce a three dimensional (3D) diffraction data volume with a high signal-to-noise ratio. Such a 3D diffraction volume can then be phased using standard crystallographic techniques. "Indexing" algorithms used in crystallography enable orientation determination of diffraction data from a single crystal when a relatively large number of reflections are recorded. Here we show that it is possible to obtain the exact lattice geometry from a smaller number of measurements than standard approaches using a basis pursuit solver.
And the code is here. Thanks Stefano !

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