Conical electron tomography of a chemical synapse: polyhedral cages dock vesicles to the active zone.

In this study, we tested the hypothesis that the structure of the active zone of chemical synapses has remained uncertain because of limitations of conventional electron microscopy. To resolve these limitations, we reconstructed chemical synapses of rat neocortex, the archetypical "average" synapse, by conical electron tomography, a method that exhibits an isotropic in plane resolution of approximately 3 nm and eliminates the need to impose symmetry or use averaging methods to increase signal-to-noise ratios. Analysis of 17 reconstructions by semiautomatic density segmentation indicated that the active zone was constructed of a variable number of distinct "synaptic units" comprising a polyhedral cage and a corona of approximately seven vesicles. The polyhedral cages measured approximately 60 nm in diameter, with a density of approximately 44/microm2 and were associated with vesicles at the active zone ("first tier"). Vesicles in this first-tier position represented approximately 7.5% of the total number of vesicles in the terminal and were contiguous, hemifused (approximately 4% of total), or fully fused (approximately 0.5% of total) to the plasma membrane. Our study supports the hypothesis that rat neocortical synapses are constructed of variable numbers of distinct synaptic units that facilitate the docking of vesicles to the active zone and determine the number of vesicles available for immediate release.

JUST (Java User Segmentation Tool) for semi-automatic segmentation of tomographic maps.

We are presenting a program for interactive segmentation of tomographic maps, based on objective criteria so as to yield reproducible results. The strategy starts with the automatic segmentation of the entire volume with the watershed algorithm in 3D. The watershed regions are clustered successively by supervised classification, allowing the segmentation of known organelles, such as membranes, vesicles and microtubules. These organelles are processed with topological models and input parameters manually derived from the tomograms. After known organelles are extracted from the volume, all other watershed regions can be organized into homogeneous assemblies on the basis of their densities. To complete the process, all voxels in the volume are assigned either to the background or individual structures, which can then be extracted for visualization with any rendering technique. The user interface of the program is written in Java, and computational routines are written in C. For some operations, involving the visualization of the tomogram, we refer to existing software, either open or commercial. While the program runs, a history file is created, that allows all parameters and other data to be saved for the purposes of comparison or exchange. Initially, the program was developed for the segmentation of synapses, and organelles belonging to these structures have thus far been the principal targets modeled with JUST. Since each organelle is clustered independently from the rest of the volume, however, the program can accommodate new models of different organelles as well as tomograms of other types of preparations of tissue, such as cytoskeletal components in vitreous ice.