Resource for the Visualization of Biological Complexity (RVBC)

SPIDER and the Web

SPIDER is an extensive software package specifically designed for 3D reconstruction and image processing in electron microscopy (Frank, et al., 1996). Web is the graphics interface for displaying and interacting with image files created in SPIDER. SPIDER has been evolving in Dr. Franks lab since the late 1970s and contains appropriate tools for single particle reconstruction, classification analysis, and electron tomography, as well as enhancing, analyzing, and segmenting 2-D and 3-D images. SPIDER and Web are continually expanded, upgraded and maintained. They are available to outside users on several computer platforms at a nominal cost, and are currently licensed in about 160 laboratories worldwide. A professional staff is available to provide assistance to users. Full documentation of the over 500 operations in SPIDER and Web can be found on the SPIDER website. Recently, as a part of our core development research, we introduced SPIRE (SPIDER Reconstruction Engine), which consists of a graphical user interface for executing SPIDER batch files, as well as a project database for managing and organizing the many output files created by SPIDER during reconstruction projects.

Ramos

(Rapid motif search, Rath, et al., 2003) is a fast 3D search program used for finding a given motif in its various manifestations inside an EM density map, using the locally normalized cross-correlation function (CCF). It is implemented in SPIDER, and documented in the SPIDER webpages. The locally (i.e., under the footprint of the motif) normalized CCF performs superior to a globally normalized CCF since it optimizes the numerical scaling of the correlated objects. Making use of recent formulations proposed by Roseman (2003) that make it possible to compute the locally-normalized CCF using Fourier techniques, computation using Ramos is 50-100 times faster than real-space implementations of motif searching.

Sterecon

Sterecon (Stereoscopic reconstruction) is used for performing visually-traced, contour-based 3-D segmentation from microscope images (Marko and Leith, 1996). In addition to its use for segmentation, the contour data also provides the 3D coordinates needed to calculate absolute volumes, surface areas, perimeters, etc. The system can handle images from TEM sections (thick or thin, single or serial), serial histological sections, SEM stereo pairs, confocal LM z-series volumes, EM tomographic volumes or stereo micrographs. It is distinguished from other contour-based 3-D reconstruction programs in that contours can be drawn in 3-D while viewing micrographs stereoscopically. Stereoscopic tracing within a 3-D image is very helpful when branching or multiple structures are being studied. Correct continuity of structures is immediately recognized in a single 3-D image, without the need to refer backwards and forwards in a series of 2-D serial sections. Zoom and pan functions are available during the tracing process to enable fine details, as well as large-scale structures to be traced in the same image. Tracing is done using a 3-D cursor, either on parallel planes (for space-filling objects) or as free 3-D lines (for filamentous objects). Sterecon also has capability for tiling surfaces formed by the traced contours, or contours can be exported to commercial rendering software. At present, Sterecon is only available for SGI workstations, but a Linux release is planned.

Tinkerbell

Tinkerbell (Li et al.,1997) is a volume editing application. The user navigates within a 3-D reconstruction using a 3-D cursor that has a pre-defined shape and volume. As the cursor is moved in the original volume, the subvolume defined by the cursor is copied to an initially-empty second volume with the same overall dimensions. A segmented volume can thus be built up. Alternatively, the cursor can be used to remove parts of the original volume, leaving behind the features of interest. For display during editing, Tinkerbell uses texture mapping for rapid volume rendering. Adjustment of threshold and opacity helps the user view 3-D structures in depth. The orientation of the volume can be changed during editing, and there is an option for stereoscopic viewing. Tinkerbell is available for suitably-equipped SGI and Linux workstations.

External software used at the RVBC

Currently, NAG Iris Explorer (www.nag.co.uk/Welcome_IEC.html) is often used to create surface-rendered models and animations from single-particle reconstructions. For correlation and fitting of atomic maps to 3-D envelopes determined by EM, we use the molecular modeling programs O (http://www.bioxray.dk/~mok/o-files.html) and Insight II (http://www.accelrys.com/insight/). NAMD and CHARM (http://charm.cs.uiuc.edu/research/moldyn/) are used for study of molecular dynamics using parallel processing.

Tomographic reconstructions are also often rendered using Iris Explorer after segmentation using Sterecon and pre-processing using SPIDER. Vital Images VoxelView (www.vitalimages.com/vv.html) is sometimes used for volume rendering. Animations are often done using Adobe Premiere. We are also beginning to use Amira (www.amiravis.com) for visualization and rendering. We find Image J (http://rsb.info.nih.gov/ij/) to be useful when sharing tomographic reconstructions with collaborators.

References

Frank, J., Radermacher, M., Penczek, P., Zhu, J., Li, Yanghong, Ladjadj, M., and Leith, A. (1996). SPIDER and WEB: processing and visualization of images in 3D electron microscopy and related fields. J. Struct. Biol., 116: 190-199.

Li, Y., Leith, A., and Frank, J. (1997) Tinkerbell--a tool for interact rive segmentation of 3D data. J. Struct. Biol., 120:266-275.

Marko, M., Leith, A. (1996) Sterecon--three-dimensional reconstruction from stereoscopic contouring. J. Structural Biol. 116, 93-98.

Rath, B.K., Hegerl, R., Leith, A., Shaikh, T.R., Wagenknecht, T. and Frank, J. (2003) Fast 3D motif search of EM density maps using a locally normalized cross-correlation function. J. Struct. Biol. 144: 95-103.

Roseman. A. (2003) Particle finding in electron micrographs using the fast local correlation algorithm. Ultramicroscopy 94:225-236 (2003).