Automatic crystal centring procedure at the SSRF macromolecular crystallography beamline

X-ray diffraction is a common technique for determining crystal structures. The average time needed for the solution of a protein structure has been drastically reduced by a number of recent experimental and theoretical developments. Since high-throughput protein crystallography benefits from full automation of all steps that are carried out on a synchrotron beamline, an automatic crystal centring procedure is important for crystallographic beamlines. Fully automatic crystal alignment involves the application of optical methods to identify the crystal and move it onto the rotation axis and into the X-ray beam. Crystal recognition has complex dependencies on the illumination, crystal size and viewing angles due to effects such as local shading, inter-reflections and the presence of antifreezing elements. Here, a rapid procedure for crystal centring with multiple cameras using region segment thresholding is reported. Firstly, a simple illumination-invariant loop recognition and classification model is used by slicing a low-magnification loop image into small region segments, then classifying the loop into different types and aligning it to the beam position using feature vectors of the region segments. Secondly, an edge detection algorithm is used to find the crystal sample in a high-magnification image using region segment thresholding. Results show that this crystal centring method is extremely successful under fluctuating light states as well as for poorly frozen and opaque samples. Moreover, this crystal centring procedure is successfully integrated into the enhanced Blu-Ice data collection system at beamline BL17U1 at the Shanghai Synchrotron Radiation Facility as a routine method for an automatic crystal screening procedure.

X射线衍射是确定晶体结构的常用技术。近期的一些实验和理论进展极大地缩短了解析蛋白质结构所需的平均时间。由于高通量蛋白质晶体学受益于在同步辐射光束线上进行的所有步骤的完全自动化，自动晶体对中程序对晶体学光束线很重要。全自动晶体对准涉及应用光学方法来识别晶体，并将其移动到旋转轴上以及X射线束中。由于局部阴影、相互反射以及防冻元件的存在等影响，晶体识别对照明、晶体大小和视角有复杂的依赖性。在此，报道了一种使用区域分割阈值法用多个相机进行晶体对中的快速程序。首先，通过将低放大倍数的环图像切割成小区域片段，使用一种简单的光照不变的环识别和分类模型，然后将环分类为不同类型，并使用区域片段的特征向量将其与光束位置对齐。其次，使用边缘检测算法通过区域分割阈值法在高放大倍数图像中找到晶体样品。结果表明，这种晶体对中方法在光照状态波动以及冷冻效果差和不透明的样品情况下都非常成功。此外，这种晶体对中程序作为自动晶体筛选程序的常规方法，成功地集成到上海同步辐射装置的BL17U1光束线的增强型Blu - Ice数据采集系统中。