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Automation in Single-Particle Electron Microscopy

Automation in Single-Particle Electron Microscopy. Jian Guan Hafenstein Lab. The definition of Automation. “automation is a comprehensive and versatile strategy that can deliver biological information on an unprecedented scale beyond the scope available with classical manual approaches”.

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Automation in Single-Particle Electron Microscopy

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  1. Automation in Single-Particle Electron Microscopy Jian Guan Hafenstein Lab

  2. The definition of Automation “automation is a comprehensive and versatile strategy that can deliver biological information on an unprecedented scale beyond the scope available with classical manual approaches” Automation in Single-Particle Electron Microscopy: Connecting the Pieces, Lyumkis D, et al. Methods in Enzymology, Volume 483,2010

  3. Huge number of Particles Demands Website of National Center for Macromolecular Imaging (NCMI) Automation

  4. Software systems with various degrees of automation and robustness • AutoEM semi-automated FEI Tecnai series EM • Leginon advanced automation Philips CM series and FEI Tecnai • Serial EM automation tomography FEI and JEOL • TOM Toolbox FEI • Batch Tomography for cryo-tomography FEI • JADAS JEOL James Conway EPU (FEI version of Leginon) Susan Hafensein

  5. Outline • General Information • Work flow • Grid Searching • Selective squares on the grid according to ice thickness • Centering the holes • Focus and Astigmatism Correction • Modularity and Flexibility of JADAS • Examples • Speed of data collection

  6. General Information JADAS JEOL Automated Data Acquisition System (JADAS) software was developed by JEOL collaboration with NCMI Baylor college of Medicine Developed for current generation of JEOL instruments. Written with C# programming language. Runs only on Windows OS with at least 1GB memory EPU Stands for “E pluribus Unum”, Latin phrase for “out of many, one” FEI version of Leginon Using Python programming language Compatible with both Linux and Windows OS

  7. Work flow JADAS

  8. Grid Searching JADAS 100-150X

  9. Grid Searching Leginon 165X-320X 500-1000 squares

  10. Selective squares on the grid according to ice thickness The thickness of a vitreous ice layer can be estimated as (Eusemann et al., 1982; Lepault et al., 1982) t < K ln(I0/I) I0 is the intensity of a bright-field image in the absence of ice and I is the intensity of the image in the presence of an ice layer of thickness t. K is a constant that is dependent on the geometry of the microscope. Thickness Range: 500 to 1500 Å

  11. Intensity Based Hole selection GUI automatic local search for JADAS

  12. Ice filter for EPU (Leginon)

  13. Centering the holes Jadas

  14. Focus and Astigmatism Correction

  15. Ligenon and JADAS can analyze a diffractogramfor stigmatism correction also. When the specimen is on a holey carbon film, the software can automatically adjust the objective lens stigmatorby measuring the ellipticity of the contrast transfer function rings to correct the astigmatism.

  16. Modularity and Flexibility of JADAS • Coupling with other tools developed elsewhere. EMEN2 • integrate image processing function from EMAN to assess the data quality in real time • Off-the-shelf remote logon software (e.g. WebEX: http://www.webex.com/) to monitor the data • collection process and even operate JADAS remotely.

  17. Examples EPU JADAS

  18. Speed of data collection JADAS Using JEM3200FSC, record 30-40 4k×4k CCD images per hour, if each image has 100 particles One day: 960 images 96000 particles EPU one hour to set up a run for days or weeks, one million particles in a four-day session on an FEI Titan Krios™ microscope. One day: 250000 particles

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