Atg9-centered multi-omics integration reveals new autophagy regulators in Saccharomyces cerevisiae.

自噬 相互作用体 生物 细胞生物学 ATG8型 酿酒酵母 计算生物学
作者
Di Peng,Chen Ruan,Shanshan Fu,Cheng-Wen He,Jing-Zhen Song,Hui Li,Yiran Tu,Dachao Tang,Lan Yao,Shaofeng Lin,Ying Shi,Weizhi Zhang,Hao Zhou,Le Zhu,Cong Ma,Cheng Chang,Jie Ma,Zhiping Xie,Chenwei Wang,Yu Xue
出处
期刊:Autophagy [Informa]
卷期号:17 (12): 4453-4476
标识
DOI:10.1080/15548627.2021.1898749
摘要

In Saccharomyces cerevisiae, Atg9 is an important autophagy-related (Atg) protein, and interacts with hundreds of other proteins. How many Atg9-interacting proteins are involved in macroautophagy/autophagy is unclear. Here, we conducted a multi-omic profiling of Atg9-dependent molecular landscapes during nitrogen starvation-induced autophagy, and identified 290 and 256 genes to be markedly regulated by ATG9 in transcriptional and translational levels, respectively. Unexpectedly, we found most of known Atg proteins and autophagy regulators that interact with Atg9 were not significantly changed in the mRNA or protein level during autophagy. Based on a hypothesis that proteins with similar molecular characteristics might have similar functions, we developed a new method named inference of functional interacting partners (iFIP) to integrate the transcriptomic, proteomic and interactomic data, and predicted 42 Atg9-interacting proteins to be potentially involved in autophagy, including 15 known Atg proteins or autophagy regulators. We validated 2 Atg9-interacting partners, Glo3 and Scs7, to be functional in both bulk and selective autophagy. The mRNA and protein expressions but not subcellular localizations of Glo3 and Scs7 were affected with or without ATG9 during autophagy, whereas the colocalizations of the 2 proteins and Atg9 were markedly enhanced at early stages of the autophagic process. Further analyses demonstrated that Glo3 but not Scs7 regulates the retrograde transport of Atg9 during autophagy. A working model was illustrated to highlight the importance of the Atg9 interactome. Taken together, our study not only provided a powerful method for analyzing the multi-omics data, but also revealed 2 new players that regulate autophagy.Abbreviations: ALP: alkaline phosphatase; Arf1: ADP-ribosylation factor 1; Atg: autophagy-related; Co-IP: co-immunoprecipitation; Cvt: cytoplasm-to-vacuole targeting; DEM: differentially expressed mRNA; DEP: differentially expressed protein; DIC: differential interference contrast; E-ratio: enrichment ratio; ER: endoplasmic reticulum; ES: enrichment score; FC: fold change; FPKM: fragments per kilobase of exon per million fragments mapped; GAP: GTPase-activating protein; GFP: green fluorescent protein; GO: gene ontology; GSEA: gene set enrichment analysis; GST: glutathione S-transferase; HA: hemagglutinin; iFIP: inference of functional interacting partners; KO: knockout; LR: logistic regression; OE: over-expression; PAS: phagophore assembly site; PPI: protein-protein interaction; RFP: red fluorescence protein; RNA-seq: RNA sequencing; RT-PCR: real-time polymerase chain reaction; SCC: Spearman's correlation coefficient; SD-N: synthetic minimal medium lacking nitrogen; THANATOS: The Autophagy, Necrosis, ApopTosis OrchestratorS; Vsn: variance stabilization normalization; WT: wild-type.
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