The interpretation of scanning electron micrographs

The problem of the interpretation of images of biological objects in the scanning electron microscope is discussed. The influence of preparative techniques, drying and coating methods on the final image is illustrated by reference to higher plant protoplasts. Methods for confirming the presence of new structural detail are suggested. An attempt is made to illustrate and introduce the need for a higher standard of interpretative and critical skill in the presentation of results obtained by means of scanning electron microscopy.     

The reconstruction of structure from electron micrographs of randomly oriented particles

A new method for enhancing and reconstructing the three dimensional structure of randomly oriented particles from their electron micrographs is developed. The method requires as an input many pictures of randomly oriented identical particles. The analysis is based on the calculation and accumulation of the spatial correlation of the densities on the electron micrographs, from which the spherical harmonic coefficients of the structure can be found. The process of enhancement of the spatial correlation and the averaging out of background noise enables reconstructions by use of pictures with low signal-to-noise ratio. The theory is presented and implemented in a computer program package. Simulated electron micrographs of ellipses, rods and a model of hexameric glutamate dehydrogenase are analyzed to demonstrate reconstructions using the computer programs.     

Three-dimensional reconstruction of a human metaphase chromosome from electron micrographs

A complete human metaphase chromosome has been reconstructed from a series of electron microscopical projections obtained by tilting the specimen stage at 3 degree intervals from –60 to +60 degrees. The reconstructed structure is about 3.0 m long, 1.6 m wide, and 0.8 m thick. The mass distribution was fairly homogeneous within the chromatids and neither a hollow nor a dense core was observed. The distribution and course of fibers observed are most consistent with a looping model of chromosome structure.     

Image reconstruction using electron micrographs of insect flight muscle. Use of thick transverse sections to supplement data from tilted thin longitudinal sections.

Three-dimensional reconstruction using electron micrographs of thin sections is a powerful technique for determining cross-bridge structure. Tilt restrictions in the electron microscope prevent data collection beyond tilt angles of 60 degrees, giving rise to a "missing cone" of transform data. We show here how much of this data can be obtained using micrographs of thick transverse sections, and the effect this data has on reconstructed images of the insect flight muscle MYAC layer. As a byproduct, the analysis showed that section thinning resulting from prolonged electron irradiation had occurred in the thin longitudinal section used for the previously published MYAC layer reconstruction (Taylor et al., 1984). Comparison of projection density maps calculated from the thin longitudinal section reconstruction and the thick section data show that the data within the missing cone that is not accessible by tilting sharpens the boundaries of the components, flattens the density profile across the thick filament, and enlarges the molecular envelope of the thin filament. We conclude that the reconstructed images of the MYAC layer provide a picture of the structural principles underlying the system but that transform data within the missing cone are necessary to describe accurately the envelopes and profiles of these structural elements.     

Automatic particle selection from electron micrographs using machine learning techniques

The 3D reconstruction of biological specimens using Electron Microscopy is currently capable of achieving subnanometer resolution. Unfortunately, this goal requires gathering tens of thousands of projection images that are frequently selected manually from micrographs. In this paper we introduce a new automatic particle selection that learns from the user which particles are of interest. The training phase is semi-supervised so that the user can correct the algorithm during picking and specifically identify incorrectly picked particles. By treating such errors specially, the algorithm attempts to minimize the number of false positives. We show that our algorithm is able to produce datasets with fewer wrongly selected particles than previously reported methods. Another advantage is that we avoid the need for an initial reference volume from which to generate picking projections by instead learning which particles to pick from the user. This package has been made publicly available in the open-source package Xmipp.     

A Bayesian method for classification of images from electron micrographs

Particle classification is an important component of multivariate statistical analysis methods that has been used extensively to extract information from electron micrographs of single particles. Here we describe a new Bayesian Gibbs sampling algorithm for the classification of such images. This algorithm, which is applied after dimension reduction by correspondence analysis or by principal components analysis, dynamically learns the parameters of the multivariate Gaussian distributions that characterize each class. These distributions describe tilted ellipsoidal clusters that adaptively adjust shape to capture differences in the variances of factors and the correlations of factors within classes. A novel Bayesian procedure to objectively select factors for inclusion in the classification models is a component of this procedure. A comparison of this algorithm with hierarchical ascendant classification of simulated data sets shows improved classification over a broad range of signal-to-noise ratios.     

Computer-assisted DNA length measurements from electron micrographs with special reference to partial denaturation mapping

A convenient semi-automatic procedure is described for the measurement, manipulation and display of electron microscopic partial denaturation data. Preliminary work on a completely automatic system is also discussed.     

An approach to automated particle picking from electron micrographs based on reduced representation templates

Reduced representation templates are used in a real-space pattern matching framework to facilitate automatic particle picking from electron micrographs. The procedure consists of five parts. First, reduced templates are constructed either from models or directly from the data. Second, a real-space pattern matching algorithm is applied using the reduced representations as templates. Third, peaks are selected from the resulting score map using peak-shape characteristics. Fourth, the surviving peaks are tested for distance constraints. Fifth, a correlation-based outlier screening is applied. Test applications to a data set of keyhole limpet hemocyanin particles indicate that the method is robust and reliable.     

Direct three-dimensional reconstruction of a corneal stromal lamella from electron micrographs

A direct three-dimensional reconstruction was made of single lamella from the posterior stroma. The reconstruction uses an iterative technique based on a good approximation for the zeroth-order density distribution. The basic information was obtained from rotation electron micrographs. The special methods used to align the micrographs are also given. Advantage was made of the known reconstruction region and the known shape and size of the fibrils. The results show that fibrils weave in and out without intertwining.     

The restoration of electron micrographs blurred by drift and rotation

We have investigated the restoration of electron micrographs exhibiting blurring due to drift and rotation. Blurring due to drift arises in micrographs taken of a specimen which is moving relative to the image plane. A related problem is that of rotational blurring which arises in micrographs of thin sections of helical particles viewed in cross section. The twist of the particle within the finite thickness of the section causes the image to appear rotationally blurred about the helical axis. Restoration algorithms were evaluated by applying them to the restoration of blurred model images degraded by additive Gaussian noise. Model images were also used to investigate how an incorrect estimate of the point spread function describing the blur would effect the restoration. Images were, if necessary, geometrically transformed to a space in which the point spread function of the blur can be considered as linear and space invariant as, under these conditions, the restoration algorithms are greatly simplified. In the case of the rotationally blurred images this procedure was accomplished by transforming the image to polar coordinates. The restoration techniques were successfully applied to blurred micrographs of bacteriophage T4 and crystals of catalase. The quality of the restoration was judged by comparisons of the restored images to undegraded images. Application to micrographs of rotationally blurred cross sections of helical macrofibers of sickle hemoglobin resulted in a reduction in the amount of rotational blurring.