We will develop the methodology to obtain electron microscope image data routinely at a resolution around 2.5 Angstroms from protein crystals, and use this ability to extend the resolution in the map of bacteriorhodopsin from 3.5 Angstroms to 2.5 Angstroms. Electron crystallography has developed to the point where atomic models can be developed for protein structures based on electron diffraction and image data. The model for bacteriorhodopsin, the first protein for which EM data was used to interpret the atomic structure, was based on a three-dimensional density map with a resolution of 3.5 Angstroms in the best direction. Although this model has been highly useful in interpreting a wealth of biophysical data on the structure and function of the protein, a fully detailed understanding of both the structural and functional principles will require extension of the density map to at least 2.5 Angstroms resolution. The use of conventional refinement procedures, based on diffraction intensity measurements, faces the problem that electron scattering at lower resolution, below about 2.5 Angstroms, is strongly dependent on the redistribution of electrons that occurs in interatomic bond formation. Calculation of diffraction intensities from the model, to compare with the experimental diffraction intensities, should thus include information about the nature and orientation of bonds, information that is not available at the early stages of structure refinement. We will solve this problem by extending the resolution of the density map to 2.5 Angstroms by direct phase determination from images that contain information at higher resolution than previously available. Advances in specimen preparation provide samples that diffract to beyond 2.5 Angstroms, and the current intermediate voltage electron microscopes provide resolution that routinely exceeds 2.5 Angstroms. Although image resolution with bR beyond 3.5 Angstroms has already been demonstrated, the quality of the images still falls well below the ideal level. We will work to identify factors that limit the signal-to-noise ratio at high resolution, and derive techniques to overcome these limitations.
| Sazzed, Salim; Song, Junha; Kovacs, Julio A et al. (2018) Tracing Actin Filament Bundles in Three-Dimensional Electron Tomography Density Maps of Hair Cell Stereocilia. Molecules 23: |
| Kamennaya, Nina A; Zemla, Marcin; Mahoney, Laura et al. (2018) High pCO2-induced exopolysaccharide-rich ballasted aggregates of planktonic cyanobacteria could explain Paleoproterozoic carbon burial. Nat Commun 9:2116 |
| Howes, Stuart C; Geyer, Elisabeth A; LaFrance, Benjamin et al. (2018) Structural and functional differences between porcine brain and budding yeast microtubules. Cell Cycle 17:278-287 |
| Glaeser, Robert M (2018) PROTEINS, INTERFACES, AND CRYO-EM GRIDS. Curr Opin Colloid Interface Sci 34:1-8 |
| Kellogg, Elizabeth H; Hejab, Nisreen M A; Poepsel, Simon et al. (2018) Near-atomic model of microtubule-tau interactions. Science 360:1242-1246 |
| Zhang, Rui; LaFrance, Benjamin; Nogales, Eva (2018) Separating the effects of nucleotide and EB binding on microtubule structure. Proc Natl Acad Sci U S A 115:E6191-E6200 |
| Nogales, Eva (2018) Cytoskeleton in high resolution. Nat Rev Mol Cell Biol 19:142 |
| Downing, Kenneth H; Glaeser, Robert M (2018) Estimating the effect of finite depth of field in single-particle cryo-EM. Ultramicroscopy 184:94-99 |
| Nogales, Eva (2018) Cryo-EM. Curr Biol 28:R1127-R1128 |
| Han, Bong-Gyoon; Watson, Zoe; Cate, Jamie H D et al. (2017) Monolayer-crystal streptavidin support films provide an internal standard of cryo-EM image quality. J Struct Biol 200:307-313 |
Showing the most recent 10 out of 136 publications
