A Robust Algorithm for the Reconstruction of Helical Filaments Using Single-particle Methods

Some of the earliest methods for three-dimensional reconstruction from electron microscopic images were developed for helical objects. Single-particle methods have been used with great success for the three-dimensional reconstruction of macromolecular assemblies that have no internal symmetry or closed point group symmetries. An approach is presented for the application of single-particle methods to helical filaments that surmounts many of the difficulties of helical image analysis, including indexing, unbending and the need to find long helically symmetric filament segments. It is shown using both human Rad51 and E. coli RecA nucleoprotein filaments that this approach converges without user intervention to a stable solution, and that it has the potential to overcome many of the problems associated with image analysis of disordered helical polymers. The method can be applied transparently to structures where Bessel overlap would greatly complicate helical analysis. In addition, the procedure allows for the ab initio determination of helical symmetry, when no prior knowledge exists.