Systematic prediction of autophagy-related proteins using Arabidopsis thaliana interactome data

Cheng, Lixin1,2,3; Zeng, Yonglun1,2; Hu, Shuai1,2; Zhang, Ning3; Cheung, Kenneth C. P.1,2; Li, Baiying1,2; Leung, Kwong-Sak4; Jiang, Liwen1,2,5

2020-12-04

10.1111/tpj.15065

PLANT JOURNAL   影响因子和分区

0960-7412

1365-313X

Autophagy is a self-degradative process that is crucial for maintaining cellular homeostasis by removing damaged cytoplasmic components and recycling nutrients. Such an evolutionary conserved proteolysis process is regulated by the autophagy-related (Atg) proteins. The incomplete understanding of plant autophagy proteome and the importance of a proteome-wide understanding of the autophagy pathway prompted us to predict Atg proteins and regulators in Arabidopsis. Here, we developed a systems-level algorithm to identify autophagy-related modules (ARMs) based on protein subcellular localization, protein-protein interactions, and known Atg proteins. This generates a detailed landscape of the autophagic modules in Arabidopsis. We found that the newly identified genes in each ARM tend to be upregulated and coexpressed during the senescence stage of Arabidopsis. We also demonstrated that the Golgi apparatus ARM, ARM13, functions in the autophagy process by module clustering and functional analysis. To verify the in silico analysis, the Atg candidates in ARM13 that are functionally similar to the core Atg proteins were selected for experimental validation. Interestingly, two of the previously uncharacterized proteins identified from the ARM analysis, AGD1 and Sec14, exhibited bona fide association with the autophagy protein complex in plant cells, which provides evidence for a cross-talk between intracellular pathways and autophagy. Thus, the computational framework has facilitated the identification and characterization of plant-specific autophagy-related proteins and novel autophagy proteins/regulators in higher eukaryotes.

Arabidopsis autophagy colocalization analysis functional module gene expression protein– protein interaction

SCI ; EI

英语

通讯

National Natural Science Foundation of China[31670179][91854201] ; Research Grants Council of Hong Kong[AoE/M-05/12][CUHK14130716][14102417][14100818][14101219][C4012-16E][C400217G][C4033-19E][R4005-18]

Plant Sciences

Plant Sciences

WOS:000595469600001

WILEY

PLANT & ANIMAL SCIENCE

Web of Science

1.Chinese Univ Hong Kong, Ctr Cell & Dev Biol, Sch Life Sci, Hong Kong, Peoples R China
2.Chinese Univ Hong Kong, Key Lab Agrobiotechnol, Hong Kong, Peoples R China
3.Southern Univ Sci & Technol, Jinan Univ, Shenzhen Peoples Hosp, Affiliated Hosp 1,Clin Med Coll 2, Shenzhen, Peoples R China
4.Chinese Univ Hong Kong, Dept Comp Sci & Engn, Hong Kong, Peoples R China
5.CUHK Shenzhen Res Inst, Shenzhen, Peoples R China

Cheng, Lixin,Zeng, Yonglun,Hu, Shuai,et al. Systematic prediction of autophagy-related proteins using Arabidopsis thaliana interactome data[J]. PLANT JOURNAL,2020,105(3).

Cheng, Lixin.,Zeng, Yonglun.,Hu, Shuai.,Zhang, Ning.,Cheung, Kenneth C. P..,...&Jiang, Liwen.(2020).Systematic prediction of autophagy-related proteins using Arabidopsis thaliana interactome data.PLANT JOURNAL,105(3).

Cheng, Lixin,et al."Systematic prediction of autophagy-related proteins using Arabidopsis thaliana interactome data".PLANT JOURNAL 105.3(2020).