A workflow for Live Imaging and Quantitative Analysis of Acentrosomal Microtubule Networks in Drosophila Oocytes

The microtubule (MT) cytoskeleton is essential for many cellular functions, including cell shape, polarity, migration, and division. While centrosomes function as the main MT-organizing center (MTOC) in dividing animal cells, many differentiated cells, including Drosophila oocytes, rely on acentrosomal pathways to assemble MT networks. In contrast to the extensive knowledge of MT organization in proliferating cells, little is known about how MT networks assemble without centrosomes. Drosophila oocytes provide a powerful model to study acentrosomal MT organization and dynamics. However, their dense MT network challenges conventional imaging. Live imaging enables real-time visualization of MT growth and orientation, yet standardized, analysis methods remain limited. Here, we present a live-imaging-based protocol to analyze MT growth dynamics in Drosophila oocytes using End-Binding Protein 1 (EB1)-Green Fluorescent Protein (GFP), a plus-end tracking protein that labels sites of active MT polymerization. High-resolution Airyscan confocal microscopy enables the detection of EB1 comets, while custom Fiji macros and Python scripts provide streamlined, reproducible quantification of comet density, velocity, length, and orientation. We validated this method by comparing control oocytes with those subjected to a cold-induced MT depolymerization, as well as Patronin mutants (CAMSAP in humans), a conserved MT minus-end stabilizer and a core component of non-centrosomal microtubule organizing centers (ncMTOC), as a positive control for impaired MT dynamics. Our analyses revealed region-specific MT dynamics, including anterior enrichment of EB1 comets and characteristic orientation biases, and confirmed the workflow's sensitivity to detecting subtle perturbations in MT growth. This approach provides a reliable, user-friendly framework for studying MT behavior in oocytes. The step-by-step protocol enables investigation of MT regulators in this context and may be adaptable to other differentiated cell types, such as neurons and epithelial cells, with appropriate optimization. More broadly, it supports mechanistic studies and genetic screens examining how diverse MT architectures underlie specialized cellular functions.