Jsubtomo is a program for sub-tomogram averaging based on Bsoft (http://bsoft.ws/). It uses template matching based on constrained cross correlation to locate and align sub-tomograms. Some examples of projects that have used Jsubtomo include:
- Arranz et al. (2012). The structure of native influenza virion ribonucleoproteins. Science, 338(6114), 1634–1637.
- Bowden et al. (2013). Orthobunyavirus ultrastructure and the curious tripodal glycoprotein spike. PLoS pathogens, 9(5), e1003374.
- Huiskonen et al. (2010). Electron cryotomography of Tula hantavirus suggests a unique assembly paradigm for enveloped viruses. Journal of Virology, 84(10), 4889–4897.
- Karotki et al. (2011). Eisosome proteins assemble into a membrane scaffold. Journal of Cell Biology, 195(5), 889–902.
- Liljeroos et al. (2011). Electron cryotomography of measles virus reveals how matrix protein coats the ribonucleocapsid within intact virions. Proceedings of the National Academy of Sciences of the United States of America, 108(44), 18085–18090.
- Maurer et al. (2013). The structure of herpesvirus fusion glycoprotein B-bilayer complex reveals the protein-membrane and lateral protein-protein interaction. Structure. 10.1016/j.str.2013.05.018
- Pietilä et al. (2012). Virion architecture unifies globally distributed pleolipoviruses infecting halophilic archaea. Journal of Virology, 86(9), 5067–5079.
If you find Jsubtomo useful for your work, please cite: Huiskonen et al. (2010). Electron cryotomography of Tula hantavirus suggests a unique assembly paradigm for enveloped viruses. Journal of Virology, 84(10), 4889–4897.
Target volume refers to the original (sub)tomogram, template volume to the map used as a search probe. Particles refer to occurrences of the template volume in the target, and have specific view and location parameters.
Treatment of symmetry
The symmetry of the target volume can be taken into account by creating a list of views using with jviews. We have used this approach to correlate a template structure against all the 12 vertexes in subtomograms of an icosahedral virus and to restrict the search into an icosahedral asymmetric unit. Symmetry of the template can be used to limit the angular search space.
Download the latest version from Downloads page. Unpack the program package to your Bsoft installation directory. The current version of Jsubtomo (1.2.0) has been tested using Bsoft 1.8.0 and will not work with older versions.
tar -xvf jsubtomo.tar
Compile and link the programs
Modes of use
Three different modes exist: search, refine and extract. Only one mode can be used at the time. In addition, there are several parameters, some of which are mode-specific, some general. Each mode is described below with examples of use. N.B. the program can also be used without running any mode, for example to select a subset of particles.
Inputs: Target volume (image.map / input.star), template volume (template.map)
Algorithm: Cross correlation search is performed for all rotations of the template. A mask can be given to define the missing information in the Fourier space (e.g. missing wedge). For each rotation of the template, all translations above threshold correlation are returned. Overlaps are discarded (selection number is set to zero) or can be filtered away completely with -remove and -renumber options.
Output: The best correlating particle is returned at each position (output.star).
Example: Search for the occurrences of a template with in a tomogram. Origin of the template is at 25,25,25.
jsubtomo -v 7 -mode search -origin 25,25,25 -angles 10,10,10 -bin 2 \ -symmetry C6 -threshold 0.1 -Template template.map -output search.star tomogram.map > search.log &
Optionally, select particles using a more stringent threshold than the initial threshold, remove unselected and renumber
jsubtomo -v 7 -fom 0.23 -renumber -remove -output search_sel.star search.star
Inputs: Input orientations and locations (input.star), template volume (template.map)
Algorithm: Cross correlation search is performed for rotations of the template limited around the starting angle and position. At each iteration, the angular step size and range are halved.
Output: The best correlating orientation and shift is returned for each particle (output.star)
Example: Refine the selected peaks from search mode to 2 degree accuracy (8-degree starting step size with 3 iterations)
jsubtomo -v 7 -mode refine -iterate 3 -origin 25,25,25 -angles 8,8,8 \ -alphalimit 10 -thetaphilimit 10 -shiftlimit 5 -refinepeaks -Template template.map \ -output refine.star search_sel.star > refine.log &
Inputs: Input orientations and locations (input.star) (+ template volume [template.map])
Algorithm: Applies rotations and shifts to transform the target volume to the reference view of the template (optionally applies the inverse transformation to place the template onto the target volume)
Output: Transformed target volumes (or templates) (with -wedge option, also rotated masks are written)
Example: Extract particles for averaging </pre>jsubtomo -mode extract -transform -partextension map -size 50,50,50 refine.star</pre>
jave -output average.map *part???.map
Place the average on the target volume for visualization
jsubtomo -mode extract -transform -inverse -Template average.map -partextension map -origin 25,25,25 refine.star
- Walk-through 1 using simulated data (template matching of randomly orientated particles)
- Walk-through 2 using simulated data (particles bound to a spherical membrane, manual picking)
- Walk-through 3 using simulated data (particles bound to a spherical membrane, template matching using estimated orientations)
See Manuals and Tutorials for a more extensive list of Jsubtomo tutorials.