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M M Golas

Publications and source records attributed to M M Golas.

2 recordsLinked to original sources

Corrim-based alignment for improved speed in single-particle image processing.

The technique of single-particle electron cryomicroscopy is currently making possible the 3D structure determination of large macromolecular complexes at constantly increasing levels of resolution. Work at resolution now attainable requires many thousands of individual images to be processed computationally. The most time-consuming step of the image-processing procedure is usually the iterative alignment of individual particle images against a set of reference images derived from a preliminary 3-D structure. We have developed an improved multireference alignment procedure based on interpolated cross-correlation images (corrims) that results in an approximately 8-fold acceleration of the iterative alignment steps. These corrims can be used to restrict the number of image-alignment calculations by narrowing down the set of reference images. Another improvement in alignment speed has been achieved by optimising the software and its implementation on many parallel processors. This new corrim-based refinement has been found to work well with two different alignment algorithms, the commonly used "fast alignment by separate translational/rotational searches" and "exhaustive alignment by polar coordinates."

Algorithms↗

Automatic CTF correction for single particles based upon multivariate statistical analysis of individual power spectra.

Three-dimensional electron cryomicroscopy of randomly oriented single particles is a method that is suitable for the determination of three-dimensional structures of macromolecular complexes at molecular resolution. However, the electron-microscopical projection images are modulated by a contrast transfer function (CTF) that prevents the calculation of three-dimensional reconstructions of biological complexes at high resolution from uncorrected images. We describe here an automated method for the accurate determination and correction of the CTF parameters defocus, twofold astigmatism and amplitude-contrast proportion from single-particle images. At the same time, the method allows the frequency-dependent signal decrease (B factor) and the non-convoluted background signal to be estimated. The method involves the classification of the power spectra of single-particle images into groups with similar CTF parameters; this is done by multivariate statistical analysis (MSA) and hierarchically ascending classification (HAC). Averaging over several power spectra generates class averages with enhanced signal-to-noise ratios. The correct CTF parameters can be deduced from these class averages by applying an iterative correlation procedure with theoretical CTF functions; they are then used to correct the raw images. Furthermore, the method enables the tilt axis of the sample holder to be determined and allows the elimination of individual poor-quality images that show high drift or charging effects.

Algorithms↗