The Three-Dimensional Distribution of αA-Crystalline in Rat Lenses and Its Possible Relation to Transparency

Lens transparency depends on the accumulation of massive quantities (600–800 mg/ml) of twelve primary crystallines and two truncated crystallines in highly elongated “fiber” cells. Despite numerous studies, major unanswered questions are how this heterogeneous group of proteins becomes organized to bestow the lens with its unique optical properties and how it changes during cataract formation. Using novel methods based on conical tomography and labeling with antibody/gold conjugates, we have profiled the 3D-distribution of the αA-crystalline in rat lenses at ∼2 nm resolutions and three-dimensions. Analysis of tomograms calculated from lenses labeled with anti-αA-crystalline and gold particles (∼3 nm and ∼7 nm diameter) revealed geometric patterns shaped as lines, isosceles triangles and polyhedrons. A Gaussian distribution centered at ∼7.5 nm fitted the distances between the ∼3 nm diameter gold conjugates. A Gaussian distribution centered at ∼14 nm fitted the Euclidian distances between the smaller and the larger gold particles and another Gaussian at 21–24 nm the distances between the larger particles. Independent of their diameters, tethers of 14–17 nm in length connected files of gold particles to thin filaments or clusters to ∼15 nm diameter “beads.” We used the information gathered from tomograms of labeled lenses to determine the distribution of the αA-crystalline in unlabeled lenses. We found that αA-crystalline monomers spaced ∼7 nm or αA-crystalline dimers spaced ∼15 nm center-to-center apart decorated thin filaments of the lens cytoskeleton. It thus seems likely that lost or gain of long-range order determines the 3D-structure of the fiber cell and possible also cataract formation

Effects of Intracellular Calcium and Actin Cytoskeleton on TCR Mobility Measured by Fluorescence Recovery

Background: The activation of T lymphocytes by specific antigen is accompanied by the formation of a specialized signaling region termed the immunological synapse, characterized by the clustering and segregation of surface molecules and, in particular, by T cell receptor (TCR) clustering. Methodology/Principal Findings: To better understand TCR motion during cellular activation, we used confocal microscopy and photo-bleaching recovery techniques to investigate the lateral mobility of TCR on the surface of human T lymphocytes under various pharmacological treatments. Using drugs that cause an increase in intracellular calcium, we observed a decrease in TCR mobility that was dependent on a functional actin cytoskeleton. In parallel experiments measurement of filamentous actin by FACS analysis showed that raising intracellular calcium also causes increased polymerization of the actin cytoskeleton. These in vitro results were analyzed using a mathematical model that revealed effective binding parameters between TCR and the actin cytoskeleton. Conclusion/Significance: We propose, based on our results, that increase in intracellular calcium levels leads to actin polymerization and increases TCR/cytoskeleton interactions that reduce the overall mobility of the TCR. In a physiological setting, this may contribute to TCR re-positioning at the immunological synapse

Fast computation of 3D radon transform via a direct Fourier method.

Abstract MOTIVATION: Arrays of three-dimensional (3D) data are ubiquitous in structural biology, biomedicine and clinical imaging. The Radon transform can be implied in their manipulation mainly for the solution of the inverse tomographic problem, since experimental data are often collected as projections or as samples of the Radon space. In electron tomography, new applications of the transform may become convenient if a fast and accurate transformation algorithm is adopted. RESULTS: A direct Fourier method (DFM) is proposed to compute the 3D Radon transform from a sampled function with compact support. This paper describes an already known two-step algorithm and illustrates its DFM implementation by coordinate transformations in 2D Fourier space. The algorithm is easily inverted to obtain a density distribution from the Radon transform. The main applications are in the field of electron tomography, especially in processes of angular refinement, since whatever projection of a structure can be retrieved from its Radon transform in a fast and accurate way. The times required to compute a number of projections with use of the Radon transform are compared with those required by other algorithms. Further uses of the Radon transform can be foreseen in applications based on 'projection onto convex sets' (POCS). AVAILABILITY: Software is available free of charge upon request to the authors. CONTACT: [email protected]

The variance of icosahedral virus models is a key indicator in the structure determination. A model free reconstruction of viruses, suitable for refractory particles.

A model-free method to determine the three-dimensional structure of icosahedral viruses is described. The novel strategy is based upon the approximate principle that correct virus structures have high variance as do all other well-detailed structures, even wrong ones. The original projections of individual particles are reduced to a radius of 25 pixels and are used to compute single particle reconstruction models by assigning them 1800 different Euler triads. The variance of the models obtained from all projections is stored in maps and a decimation process is carried out. In a first stage, thresholds are adopted for the variance values, and in a second stage, carried out by correspondence analysis and classification, 30 clusters of models are sorted out. The clusters are refined to yield models contained in boxes of 643 voxels. The refined models with highest variance and closest similarity represent the correct solution. Once enlarged, these models can be used to align all available projections in their original scale in a customary projection-matching process. The method has proved successful in determining the structures of poliovirus, of the empty and filled capsids of L-A virus, and of a modified capsid of hepatitis B virus

The three-dimensional distribution of αA-crystalline in rat lenses and its possible relation to transparency.

Lens transparency depends on the accumulation of massive quantities (600-800 mg/ml) of twelve primary crystallines and two truncated crystallines in highly elongated "fiber" cells. Despite numerous studies, major unanswered questions are how this heterogeneous group of proteins becomes organized to bestow the lens with its unique optical properties and how it changes during cataract formation. Using novel methods based on conical tomography and labeling with antibody/gold conjugates, we have profiled the 3D-distribution of the αA-crystalline in rat lenses at ∼2 nm resolutions and three-dimensions. Analysis of tomograms calculated from lenses labeled with anti-αA-crystalline and gold particles (∼3 nm and ∼7 nm diameter) revealed geometric patterns shaped as lines, isosceles triangles and polyhedrons. A Gaussian distribution centered at ∼7.5 nm fitted the distances between the ∼3 nm diameter gold conjugates. A Gaussian distribution centered at ∼14 nm fitted the Euclidian distances between the smaller and the larger gold particles and another Gaussian at 21-24 nm the distances between the larger particles. Independent of their diameters, tethers of 14-17 nm in length connected files of gold particles to thin filaments or clusters to ∼15 nm diameter "beads." We used the information gathered from tomograms of labeled lenses to determine the distribution of the αA-crystalline in unlabeled lenses. We found that αA-crystalline monomers spaced ∼7 nm or αA-crystalline dimers spaced ∼15 nm center-to-center apart decorated thin filaments of the lens cytoskeleton. It thus seems likely that lost or gain of long-range order determines the 3D-structure of the fiber cell and possible also cataract formation

Icosahedral viruses; Electron microscopy; Structure variance

VIVA (from virus variance), a library to reconstruct icosahedral viruses based on the variance of structural model