Computer-Assisted Analysis of Flagellar Structure

The identification of polypeptides as subunits of specific axonemal structures has arisen because of analysis of flagellar mutants of Chlamydomonas reinhardtii by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). This approach has been particularly useful in sorting out the complexity of the inner dynein arms. Methods such as cross-correlation analysis and rotational averaging of structures possessing ninefold axial-symmetry have been used to average transverse sections of insect sperm flagella. Averages of doublet cross sections have been obtained to make qualitative comparisons between inner and outer dynein arm mutants in Chlamydomonas. Described in this chapter are the steps involved in obtaining averages of axonemal components and the methods for making statistical comparisons between them. There is illustration of specimen preparation and electron microscopy. There is image analysis; the programs involve digitization, display, and quantitative analysis of images. The hardware used for the analysis includes a Dage MTI video camera. Images of axonemes containing outer doublets in cross section are found relatively quickly and easily in sections of pellets. Axonemes are chosen for analysis if they have a complete set of nine outer-doublet microtubules, an intact central pair, and protofilaments that are visible in at least one outer-doublet microtubule. The individual doublets at each position are aligned, averaged, and normalized, and statistical comparisons made to determine if there are doublet-specific differences in dynein structure in a mutant strain. There is analysis of longitudinal sections. Statistical comparisons of different samples are performed by a nested analysis of variance, using the sums of squared deviations computed from the means, standard deviations, and sample number for each individual sample, then test is done for the significance of differences in specified areas of the dynein arms or at each pixel in a given pair of images by taking into account the intra- and inter-sample variability.