Spectroscopic imaging of protein crystals in crystallization drops.

Automatic imaging and scoring of crystallization drops is an essential step in high-throughput crystallography. Presently, white-light images of crystallization drops are acquired robotically and the images are analyzed and scored using pattern recognition algorithms. However, the scoring part remains unreliable as crystals and microcrystals are not always recognized by existing feature-extraction and recognition algorithms. We propose a fundamental shift in crystal monitoring through spectroscopic imaging of crystallization drops. This method converts the problem of automatic crystal detection from one of pattern recognition into one of intensity (concentration) analysis. The latter can be more robust and reliable.