Front Cell Dev Biol. 2025 ;13 1554958
Cheng Han,
Shanshan Fu,
Dachao Tang,
Yuting Chen,
Dan Liu,
Zihao Feng,
Yujie Gou,
Chi Zhang,
Weizhi Zhang,
Leming Xiao,
Jiayi Zhang,
Cong Yi,
Yu Xue,
Di Peng.
In Saccharomyces cerevisiae, Atg1 is a core autophagy-related (Atg) protein kinase (PK) in regulating macroautophagy/autophagy, by physically interacting with numerous other proteins, or by phosphorylating various substrates. It is unclear how many Atg1-interacting partners and substrates are also involved in regulating autophagy. Here, we conducted transcriptomic, proteomic and phosphoproteomic profiling of Atg1-dependent molecular landscapes during nitrogen starvation-triggered autophagy, and detected 244, 245 and 217 genes to be affected by ATG1 in the autophagic process at mRNA, protein, and phosphorylation levels, respectively. Based on the Atg1 interactome, we developed a novel artificial intelligence (AI) framework, inference of autophagy regulators from multi-omic data (iAMD), and predicted 12 Atg1-interacting partners and 17 substrates to be potentially functional in autophagy. Further experiments validated that Rgd1 and Whi5 are required for bulk autophagy, as well as physical interactions and co-localizations with Atg1 during autophagy. In particular, we demonstrated that 2 phosphorylation sites (p-sites), pS78 and pS149 of Whi5, are phosphorylated by Atg1 to regulate the formation of Atg1 puncta during autophagy initiation. A working model was illustrated to emphasize the importance of the Atg1-centered network in yeast autophagy. In addition, iAMD was extended to accurately predict Atg proteins and autophagy regulators from other PK interactomes, indicating a high transferability of the method. Taken together, we not only revealed new autophagy regulators from the Atg1 interactome, but also provided a useful resource for further analysis of yeast autophagy.
Keywords: Atg1; artificial intelligence; autophagy-related; deep learning; phosphorylation; protein kinase