A number of new technologies have been developed from our work over the last few years that are now at the core of our discovery efforts in the areas of HIV/AIDS and cancer biology. Two advances especially important for our work at the intersection of structural biology and virology. We extended our efforts in subvolume averaging of cryo-electron tomographic volumes by applying automated, iterative, missing wedge-corrected 3D image alignment and classification methods to distinguish multiple conformations that are present simultaneously. Our methods allow for measuring the spatial distribution of the vector elements representing distinct conformational states of trimeric envelope glycoproteins, especially when they are present in mixtures. We showed that identifying and removing spikes with the lowest SNRs improves the overall accuracy of alignment between individual envelope glycoproteins, and that alignment accuracy, in turn, determines the success of image classification in assessing conformational heterogeneity in heterogeneous mixtures. We validated these procedures for computational separation by successfully separating and reconstructing distinct 3D structures for unliganded and antibody-liganded as well as open and closed conformations of envelope glycoproteins present simultaneously in mixtures. In a different development, we established methods to overcome the limitations in single particle cryo-EM methods related to assigning molecular orientations based solely on 2D projection images. Tomographic data collection schemes provide powerful constraints for accurate determination of molecular orientations that are necessary for 3D reconstruction. We proposed a new "Constrained Single Particle Tomography" approach as a general strategy for 3D structure determination in cryo-EM. A key component of our approach is the effective use of images recorded in a tilt series to extract high-resolution information by correcting for the contrast transfer function (CTF) of each tilted image. By incorporating geometric constraints into the refinement of image orientations to improve the accuracy of orientation determination, we reduced model-bias artifacts and demonstrate substantial improvement in resolution in comparison to methods that utilize sub-volume averaging.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Investigator-Initiated Intramural Research Projects (ZIA)
Project #
1ZIABC010826-07
Application #
8763238
Study Section
Project Start
Project End
Budget Start
Budget End
Support Year
7
Fiscal Year
2013
Total Cost
$697,073
Indirect Cost
Name
National Cancer Institute Division of Basic Sciences
Department
Type
DUNS #
City
State
Country
Zip Code
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