COMPUTATIONAL METHODS IN ELECTRON TOMOGRAPHY AND VOLUME DATA ANALYSIS

Hanspeter Winkler
Florida State University
Institute of Molecular Biophysics

Electron tomography combined with cryo-electron microscopy is capable of visualizing macromolecules, macromolecular assemblies or whole cells in a state that is close to the native conditions. One of the problems in electron tomography is, that the angular tilt range is limited, and as a consequence the reconstruction is missing some data, called the "missing wedge", a region in reciprocal space where structure factors cannot be obtained experimentally. Additionally, the images in a tilt series must first be aligned to a common coordinate frame before computing a tomogram. Quality of alignment and coverage in reciprocal space both affect the resolution in the computed tomograms. A further enhancement is possible by correcting the images for the transfer characteristics of the microscope. In tomography, contrast transfer function correction must account for the defocus variation in images of tilted specimens.


Tomographic data is processed by extracting structural motifs from the raw tomograms, by selective alignment of the subvolumes, multivariate statistical analysis, classification, and class-averaging, resulting in an increased signal-to-noise ratio and substantial data reduction. The problem of the missing data in reciprocal space is addressed by using constrained correlation and weighted averaging in reciprocal space to minimize adverse effects. To summarize, the volumetric data analysis provides a means to characterize heterogeneous populations of structural motifs, to discriminate among different species of macromolecules, conformational states, or interactions between macromolecules.


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