LEGINON: A SYSTEM FOR FULLY AUTOMATED ACQUISITION OF 1000 ELECTRON MICROGRAPHS A DAY C.S. Potter, H. Chu * , B. Frey, C. Green, N. Kisseberth, T.J. Madden, K. L. Miller, K. Nahrstedt * , J. Pulokas, A. Reilein, D. Tcheng ** , D. Weber and B. Carragher Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign 405 N. Mathews, Urbana, IL 61801 * Dept. of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801 ** National Center for Supercomputing Applications, Urbana, IL 61801 Abstract We have developed a system to automatically acquire large numbers of acceptable quality images from specimens of negatively stained catalase, a biological protein which forms crystals. In this paper we will describe the details of the system architecture and analyze the performance of the system as compared to a human operator. The ultimate goal of the system if to automate the process of acquiring cryo-electron micrographs. PACS: 07.78; 07.05.P; 61.16.B; 87.64.Dz Keywords: Microscopic methods, instrument control, automated data acquisition, three- dimensional electron microscopy 1. INTRODUCTION Molecular microscopy is, and will continue to be, one of the most important structural approaches in cell biological investigations. Currently, the technique requires the acquisition of very large numbers of high quality images from an electron microscope controlled by an experienced microscopist. This is a labor-intensive and slow methodology and it is clear that this situation must change if important biological problems are to be addressed in an expeditious manner. There is increasing interest in the field for fully automating the entire process of acquiring high quality transmission electron micrographs. Typically, a microscopist identifies potential features of interest by visual inspection of a low magnification field of view. High magnification images of these identified features are then acquired using techniques which minimize the exposure of the specimen to electron beam damage. As a result, the high magnification image is never visually examined prior to acquisition. The quality of the high magnification image is assessed only after acquisition when the image can be analyzed and a decision made as to whether it warrants further processing. An experienced microscopist assimilates this quality assessment information and uses it to refine the choice of potentially relevant low magnification features. A simple brute force method in which the entire low magnification field of view is systematically examined is impractical because the field of view