Multivariate statistical analysis of three-dimensional cross-bridge motifs in insect flight muscle

Multivariate statistical analysis has been applied to the problem of identifying similar 3-D motifs within tomograms of insect flight muscle. The method is an extension of the widely used application of this technique to 2-D images. The additional degrees of freedom that the 3-D case imposes has been reduced to a translational alignment and a 180° rotation about the filament axis because of the very regular motif arrangement in the filament lattice. The problem of finding unbiased references for the alignment has been addressed by using derived functions for the multivariate statistical analysis that are invariant to the alignment parameters. Hierarchical ascendant classification has been explored as an unsupervised classification method. The results show improved signal to noise ratio in the class averages with retention of density distributions consistent with the known numbers of myosin heads and actin monomers present within the filament lattice.