News and Publications

Automated Molecular Imaging

Elucidating the structure and mechanism of action of molecular machines is an emerging frontier in understanding how the information in the genome is transformed into cellular activities. Molecular machines are associations of individual components (e.g., proteins, nucleic acids, lipids) in the form of large complexes; examples include ribosomes, transcription complexes, track-motor complexes, and membrane-embedded pumps and channels. These machines are large and may also be conformationally and compositionally dynamic or present in comparatively low numbers, factors that make them extremely challenging (or impossible) objects for study by x-ray crystallography and nuclear magnetic resonance methods. They are, however, ideal objects for using electron microscopy to determine their structures, and this approach has provided insights into the working of many macromolecular complexes at both high and moderate resolutions.

Although molecular microscopy has enormous potential, it is time-consuming and labor intensive. The techniques needed to produce a 3-dimensional electron density map of a macromolecular structure normally require manual operation of an electron microscope by a skilled operator and manual supervision of the sometimes complex software used for analysis and calculation of 3-dimensional maps. Typically, it takes weeks to months to collect and analyze a data set to reconstruct a map at 10- to 20-Å resolution. Scientists generally agree that increasing the resolution to a range where secondary structure will be discernable in the map (~7 Å) will require a 10-fold increase in the amount of data collected and analyzed. Clearly, molecular microscopy will not be practical as a mainstream technique unless the imaging and analysis can be automated and the overall throughput greatly improved.

We are trying to develop a completely automated system for molecular microscopy (Fig. 1). Our goal is to automate all processes, from inserting the electron microscopy grid to calculating the final 3-dimensional map. In the past several years, we developed a system called Leginon to automatically acquire electron cryomicrographs. The system is designed to emulate all the decisions and actions of a highly trained microscopist in collecting data on a vitreous ice specimen. The tasks include identifying suitable areas of vitreous ice at low magnification, determining the presence and location of the specimen on the grid, automatically adjusting imaging parameters (e.g., focus, astigmatism), and acquiring images at high magnification. The system was tested with a variety of specimens that represent typical challenges in the field of electron cryomicroscopy. The results indicated that the overall performance of the system is equivalent to that of an experienced microscopist.

In 2002, we established the National Resource for Automated Molecular Microscopy (NRAMM). This new biotechnology resource center is funded by the National Center for Research Resources, National Institutes of Health. The overall mission is to develop, test, and apply technology to completely automate the processes involved in using electron cryomicroscopy to solve macromolecular structures. The focus of NRAMM is the development of specimen handling, automated acquisition, automated processing, and information handling.

Projects in specimen handling are all related to improving the handling and monitoring of specimens by developing innovative new engineering devices. The projects include developing methods for high-throughput screening of negatively stained ordered arrays and for controlling the stability of cryostage specimen holders.

The fundamental core technology of the NRAMM is the development of a generalized system for automated image acquisition. The focus of automated processing is automation of the data processing that occurs after image acquisition, including the automated identification and segmentation of individual macromolecular complexes from electron micrographs.

The storage, organization, distribution, and archiving of information is a critical aspect of the overall goal of automated data acquisition and processing, and the success of every other project in the NRAMM depends on this core project.

Our goal for the next several years is to transform electron microscopy into a high-throughput, mainstream method for structure determination. Success in this endeavor will do more than greatly facilitate molecular microscopy. It will also expand the scope of accessible problems and push experimental frontiers by making possible investigations that are currently deemed too high risk because of the unreasonable effort involved.

Publications

Zhu, Y., Carragher, B., Mouche, F., Potter, C.S. Automatic particle detection through efficient Hough transforms. IEEE Trans. Med. Imaging, in press.