This proposal is to develop and test an integrated assembly of robotics subsystems dedicated to high-throughput protein crystallography at a synchrotron facility. The long-term goal is the implementation of an automated environment for the efficient manipulation of large numbers of single crystal protein samples for x-ray diffraction intensity collection at synchrotron-based biological crystallography facilities. Specific subtasks include the design and implementation of manual, semi- automated, and automated remote control systems for sample manipulation on the goniometer and in x-ray beam, development of algorithms for automated centering of target features, design and testing of a subsystem to load and unload conventional cryogenically-frozen protein crystal samples, development of protocols for screening large numbers of crystals for data collection, development and testing of new sample holders for efficient crystal harvesting, storage, manipulation, and data collection, and finally, adaptation of the hardware to the alignment of microcrystals. Although there are currently more than a dozen synchrotron beamlines in the U.S. dedicated to protein crystallography, the throughput is limited by the speed of manual manipulation (loading, centering, and unloading). At the Macromolecular Crystallography Facility at Advanced Light Source, one current beamline, two new beamlines under construction, and several new beamlines being designed, will benefit from the use of automated stages -initially a simple x,y,z movement with motors under manual control - for centering protein crystals. The proposed integrated approach for automated manipulation of protein crystals will be more efficient (in terms of time and synchrotron floor space), and will substantially increase throughput and reliably in handling samples. This proposal is in direct response to the recommendations of the NIH and DOE in designing automated systems for use at synchrotron facilities and in developing technologies necessary for advancing high-throughput structural genomics initiatives.