4. TRD#3: An automated and streamlined pipeline for in-situ molecular microscopy Abstract Our goal for this TRD is to integrate all of the techniques required for in situ molecular microscopy into a robust and reliable pipeline, and make it available to the scientific community. In situ molecular microscopy, that is reconstructing molecules inside cells or tissue, requires the integration of several challenging methods and techniques. Regions of interest need to be identified using cryo light micrsocopy (cryoLM), the specimen needs to be thinned down around this region of interest using a focused ion beam scanning electron microscope (FIB-SEM) in order to make it amenable to subsequent cryo electron tomography (cryoET). We will develop a variety of approaches for specimen preparation including some that are high-risk but of potentially high-impact. We will expand the Appion pipeline to integrate and track images, analysis and metadata across all three imaging modalities. Providing streamlined and transparent access to this pipeline is an essential aspect of making these methods accessible to general users. We will incorporate the ability to integrate light microscopy and SEM images into our image tracking database and enable relevant image processing techniques using our web based pipeline; the database that underlies both Leginon and Appion will be key to tracking these multiple imaging modalities and related actions and metadata. Several important biological projects will drive improvements in the design, development, automation and streamlining of this pipeline, and we anticipate a range of Collaborative and Service projects will make excellent use of the pipeline as soon as it is available. We will work closely with several groups with deep experience with in situ microscopy (Elizabeth Villa, Carolyn Larabell, and Michael Marko) to guide this project in the right direction. We will hold an annual weeklong workshop to train users in these methods and we will help to disseminate the overall pipeline to other labs in the scientific community, just as we do now for our Leginon and Appion systems.
| Baldwin, Philip R; Tan, Yong Zi; Eng, Edward T et al. (2018) Big data in cryoEM: automated collection, processing and accessibility of EM data. Curr Opin Microbiol 43:1-8 |
| Lopez-Redondo, Maria Luisa; Coudray, Nicolas; Zhang, Zhening et al. (2018) Structural basis for the alternating access mechanism of the cation diffusion facilitator YiiP. Proc Natl Acad Sci U S A 115:3042-3047 |
| Cheng, Anchi; Eng, Edward T; Alink, Lambertus et al. (2018) High resolution single particle cryo-electron microscopy using beam-image shift. J Struct Biol 204:270-275 |
| Kim, Laura Y; Rice, William J; Eng, Edward T et al. (2018) Benchmarking cryo-EM Single Particle Analysis Workflow. Front Mol Biosci 5:50 |
| Zhang, Zhening; Liang, Wenguang G; Bailey, Lucas J et al. (2018) Ensemble cryoEM elucidates the mechanism of insulin capture and degradation by human insulin degrading enzyme. Elife 7: |
| Twomey, Edward C; Yelshanskaya, Maria V; Vassilevski, Alexander A et al. (2018) Mechanisms of Channel Block in Calcium-Permeable AMPA Receptors. Neuron 99:956-968.e4 |
| Stewart-Jones, Guillaume B E; Chuang, Gwo-Yu; Xu, Kai et al. (2018) Structure-based design of a quadrivalent fusion glycoprotein vaccine for human parainfluenza virus types 1-4. Proc Natl Acad Sci U S A 115:12265-12270 |
| Xu, Kai; Acharya, Priyamvada; Kong, Rui et al. (2018) Epitope-based vaccine design yields fusion peptide-directed antibodies that neutralize diverse strains of HIV-1. Nat Med 24:857-867 |
| Bepler, Tristan; Morin, Andrew; Noble, Alex J et al. (2018) Positive-unlabeled convolutional neural networks for particle picking in cryo-electron micrographs. Res Comput Mol Biol 10812:245-247 |
| Rice, William J; Cheng, Anchi; Noble, Alex J et al. (2018) Routine determination of ice thickness for cryo-EM grids. J Struct Biol 204:38-44 |
Showing the most recent 10 out of 159 publications
