Abstract

ABSTRACTWhen macroautophagy (autophagy) is induced by nutrient starvation or rapamycin treatment, Atg (autophagy-related) proteins are assembled at a restricted region close to the vacuole. Subsequently, the phagophore expands to form a closed autophagosome. In Saccharomyces cerevisiae cells overexpressing precursor Ape1 (prApe1), a specific autophagosome cargo protein, the phagophore can be visualized as a cup-shaped structure labeled with green fluorescent protein (GFP)-tagged Atg8. Previously, our group has shown that the maximum length of GFP-Atg8-labeled structures reflects the magnitude of bulk autophagy. In that study, the morphological parameters of the autophagy-related structures were extracted manually, requiring a great deal of time. Moreover, only well-expanded phagophores were subjected to further analysis. Here we report Qautas (Quantitative autophagy-related structure analysis system), a high-throughput and comprehensive system for morphological analysis of autophagy-related structures using a combination of image processing and machine learning. We describe both the manual method and Qautas in detail.

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