No abstract

Autophagy is a cellular degradation system widely conserved among eukaryotes. During autophagy, cytoplasmic materials fated for degradation are compartmentalized in double membrane–bound organelles called autophagosomes. After fusing with the vacuole, their inner membrane–bound structures are released into the vacuolar lumen to become autophagic bodies and eventually degraded by vacuolar hydrolases. Atg15 is a lipase essential for disintegration of autophagic body membranes and has a transmembrane domain at the N-terminus and a lipase domain at the C-terminus. However, the roles of both domains in vivo are not well understood. In this study, we found that the N-terminal domain alone can travel to the vacuole via the multivesicular body pathway, and that targeting of the C-terminal lipase domain to the vacuole is required for degradation of autophagic bodies. Moreover, we found that the C-terminal domain could disintegrate autophagic bodies when it was transported to the vacuole via the Pho8 pathway instead of the multivesicular body pathway. Finally, we identified H435 as one of the residues composing the putative catalytic triad, and W466 as an important residue for degradation of autophagic bodies. This study may provide a clue to understanding how the C-terminal lipase domain recognizes autophagic bodies to degrade them. [Media: see text] [Media: see text]

When 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.