Research Article: SPIND-TC: an indexing method for two-color X-ray diffraction data

Date Published: May 01, 2020

Publisher: International Union of Crystallography

Author(s): Xuanxuan Li, Chufeng Li, Haiguang Liu.


An auto-indexing method for two-color X-ray diffraction data is presented, which has been tested on both simulated and experimental protein diffraction data. The indexing yield is increased significantly compared with the previous approach using conventional indexers.

Partial Text

Over the past few years, serial femtosecond crystallography (SFX) has demonstrated the capabilities of determining three-dimensional macromolecular structures from microcrystals (Chapman et al., 2011 ▸; Boutet et al., 2012 ▸; Barends et al., 2014 ▸; Kupitz et al., 2014 ▸). Using femtosecond pulses of bright X-ray free-electron lasers (XFELs), diffraction signals are recorded from protein crystals at room temperature in the ‘diffraction-before-destruction’ approach (Solem, 1986 ▸; Neutze et al., 2000 ▸). This scheme avoids the structure alteration in the cryogenic cooling process (Fraser et al., 2011 ▸; Keedy et al., 2014 ▸), which is frequently adopted to protect protein crystals from radiation damage in macromolecular diffraction experiments at synchrotron facilities.

SPIND-TC is developed based on the sparse-pattern indexing algorithm SPIND, which finds the optimal orientation of a crystal using the prior knowledge of the unit cell as a reference. The core idea is summarized as follows:

Two-color modes of XFEL provide new opportunities and also bring challenges for serial crystallography. In two-color experiments, the data collection rate is doubled since one image contains two diffraction patterns. For small energy separation, such as  1%, which is feasible at LCLS, it is anticipated that such two-color data can be indexed by monochromatic methods as well as SPIND-TC. This was confirmed by a simulation test with 9 and 9.1 keV energy, where all images could be successfully indexed by MOSFLM and SPIND-TC. The problem for such data is the peak integration for the overlapped spots in the low-resolution region, which requires accurate orientation refinement and careful intensity deconvolution. On the other hand, such data can be analyzed using the pink-beam diffraction method, which uitlizes broader energy bandwidth (up to 5% ) (Meents et al., 2017 ▸).




Leave a Reply

Your email address will not be published.