The transmission electron microscope has been an important instrument for biomedical research for almost fifty years, revealing fine structural details in tissue sections essential for understanding how cells function and the mechanisms of disease unobtainable by any other imaging device. The microscope provides two-dimensional (2D) projections of specimens. Conventionally, data analysis is done on individual projections. However, spatial resolution in a 2D projection is severely restricted by the absence of depth information. Over the last few decades tomographic methods have been developed to generate 3D volume reconstructions from a series of 2D projections. An obvious advantage of electron microscope tomography (EMT) is that it offers the opportunity to examine the positions and relationships of structures smaller than the thinnest tissue sections that can be cut. Since most cellular and extracellular structures detectable in tissue sections by electron microscopy are much smaller than the section thickness, as are immunogold labels for specific proteins, cell biologists in neuroscience and other biomedical fields are eager to apply EMT to a vast number of previously unapproachable problems. However, few laboratories presently can use EMT on tissue sections. The primary reasons are that the software packages available for data analysis are difficult for mainstream biologists to use, and they also have limited capabilities. Over the last five years this laboratory has been developing a software package, EM3D that utilizes an innovative approach to segmentation and surface-model generation, thereby providing spatial resolution at the full scale of the reconstructed volume. It is convenient to use even for novices, and it has been successfully employed to unravel highly complicated subcellular architecture in tissue sections from neuromuscular junctions leading to novel hypotheses concerning mechanisms of synaptic transmission. The overall goals of the research in this application are to add new features to EM3D and to create a stable release for the neuroscience community and members of other biomedical fields.
The specific aims are to: (1) consolidate EM3D, (2) generate an improved reconstruction algorithm, (3) develop a method for automated surface-modeling, (4) make a tool for membrane surface-model flattening, and (5) devise a procedure for automatic compartmental segmentation.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH068065-02
Application #
6741514
Study Section
Special Emphasis Panel (ZRG1-SSS-E (95))
Program Officer
Hirsch, Michael D
Project Start
2003-05-01
Project End
2008-02-29
Budget Start
2004-03-01
Budget End
2005-02-28
Support Year
2
Fiscal Year
2004
Total Cost
$493,362
Indirect Cost
Name
Stanford University
Department
Biology
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
Jung, Jae H; Szule, Joseph A; Stouder, Kylee et al. (2018) Active Zone Material-Directed Orientation, Docking, and Fusion of Dense Core Vesicles Alongside Synaptic Vesicles at Neuromuscular Junctions. Front Neuroanat 12:72
Jung, Jae Hoon; Szule, Joseph A; Marshall, Robert M et al. (2016) Variable priming of a docked synaptic vesicle. Proc Natl Acad Sci U S A 113:E1098-107
Szule, Joseph A; Jung, Jae Hoon; McMahan, Uel J (2015) The structure and function of 'active zone material' at synapses. Philos Trans R Soc Lond B Biol Sci 370:
Harlow, Mark L; Szule, Joseph A; Xu, Jing et al. (2013) Alignment of synaptic vesicle macromolecules with the macromolecules in active zone material that direct vesicle docking. PLoS One 8:e69410
Szule, Joseph A; Harlow, Mark L; Jung, Jae Hoon et al. (2012) Regulation of synaptic vesicle docking by different classes of macromolecules in active zone material. PLoS One 7:e33333
Nagwaney, Sharuna; Harlow, Mark Lee; Jung, Jae Hoon et al. (2009) Macromolecular connections of active zone material to docked synaptic vesicles and presynaptic membrane at neuromuscular junctions of mouse. J Comp Neurol 513:457-68
Ress, David B; Harlow, Mark L; Marshall, Robert M et al. (2004) Methods for generating high-resolution structural models from electron microscope tomography data. Structure 12:1763-74