Microtubule-based Endoplasmic Reticulum Motility in Xenopus laevis: Activation of Membrane-associated Kinesin during Development

The endoplasmic reticulum (ER) in animal cells uses microtubule motor proteins to adopt and maintain its extended, reticular organization. Although the orientation of microtubules in many somatic cell types predicts that the ER should move toward microtubule plus ends, motor-dependent ER motility reconstituted in extracts of Xenopus laevis eggs is exclusively a minus end-directed, cytoplasmic dynein-driven process. We have used Xenopus egg, embryo, and somatic Xenopus tissue culture cell (XTC) extracts to study ER motility during embryonic development in Xenopus by video-enhanced differential interference contrast microscopy. Our results demonstrate that cytoplasmic dynein is the sole motor for microtubule-based ER motility throughout the early stages of development (up to at least the fifth embryonic interphase). When egg-derived ER membranes were incubated in somatic XTC cytosol, however, ER tubules moved in both directions along microtubules. Data from directionality assays suggest that plus end-directed ER tubule extensions contribute ∼19% of the total microtubule-based ER motility under these conditions. In XTC extracts, the rate of ER tubule extensions toward microtubule plus ends is lower (∼0.4 μm/s) than minus end-directed motility (∼1.3 μm/s), and plus end-directed motility is eliminated by a function-blocking anti-conventional kinesin heavy chain antibody (SUK4). In addition, we provide evidence that the initiation of plus end-directed ER motility in somatic cytosol is likely to occur via activation of membrane-associated kinesin.

Statistical analysis of shape of objects based on landmark data.

Two objects with homologous landmarks are said to be of the same shape if the configurations of landmarks of one object can be exactly matched with that of the other by translation, rotation/reflection, and scaling. The observations on an object are coordinates of its landmarks with reference to a set of orthogonal coordinate axes in an appropriate dimensional space. The origin, choice of units, and orientation of the coordinate axes with respect to an object may be different from object to object. In such a case, how do we quantify the shape of an object, find the mean and variation of shape in a population of objects, compare the mean shapes in two or more different populations, and discriminate between objects belonging to two or more different shape distributions. We develop some methods that are invariant to translation, rotation, and scaling of the observations on each object and thereby provide generalizations of multivariate methods for shape analysis.