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Automation for Cryo-TEM: from Specimen Grid to 3D Map

Published online by Cambridge University Press:  02 July 2020

B. Carragher
Affiliation:
Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801
D. Fellmann
Affiliation:
Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801
N. Kisseberth
Affiliation:
Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801
R.A. Milligan
Affiliation:
Department of Cell Biology, The Scripps Research Institute, La Jolla, CA, 92037
C.S. Potter
Affiliation:
Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801
J. Pulokas
Affiliation:
Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801
Y. Zhu
Affiliation:
Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801
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Abstract

Cryo-electron microscopy is becoming an increasingly powerful tool for solving the structure of protein complexes and has the potential to address problems that cannot be solved using other methods. The field however suffers from several major disadvantages related to the time required to acquire, process and analyze the data and the tedium of using the current prevailing methods. We have for some time been working towards the goal of developing a system that will result in a 3D map of a macromolecular structure automatically and within hours of inserting a specimen into a transmission electron microscope. We propose that these automated methods for data collection and analysis will have a significant impact in transferring the cryo-electron microscopy technology to the general biological community as well as in increasing the volume of data that can be collected during a single session at the microscope.

The Leginon system that we have developed is designed to emulate all of the decisions and actions of a highly trained microscopist in collecting data from a vitreous ice specimen. These include identifying suitable areas of vitreous ice at low magnification, determining the presence and location of specimen on the grid, automatically adjusting imaging parameters (focus, astigmatism) under low dose conditions and acquiring images at high magnification to either film or a digital camera.

Type
Instrument Automation (Organized by W. Deruijter and C. Potter)
Copyright
Copyright © Microscopy Society of America 2001

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References

1.Potter, C.S.et al.,Ultramicroscopy 77(1999)153161.CrossRefGoogle Scholar
2.Carragher, B.et al., Journal of Structural Biology 132(2000)3345.CrossRefGoogle Scholar
3. This research is supported by the National Science Foundation (DBI-9730056, DBI-9904547) and the National Institutes of Health (GM61939-01).Google Scholar