Quantitative proteome-based systematic identification of SIRT7   substrates

doi:10.1002/pmic.201600395

CORC > 北京大学 > 生命科学学院

	Quantitative proteome-based systematic identification of SIRT7 substrates
	Zhang, Chaohua ; Zhai, Zichao ; Tang, Ming ; Cheng, Zhongyi ; Li, Tingting ; Wang, Haiying ; Zhu, Wei-Guo
刊名	PROTEOMICS
	2017
关键词	Bioinformatics Quantitative proteomics SIRT7 Substrates Systematic RNA-POLYMERASE-I HISTONE ACETYLATION HEPATOCELLULAR-CARCINOMA NUCLEOSOMAL DNA TRANSCRIPTION STRESS CANCER DEACETYLATION SUPPRESSES APOPTOSIS
DOI	10.1002/pmic.201600395
英文摘要	SIRT7 is a class III histone deacetylase that is involved in numerous cellular processes. Only six substrates of SIRT7 have been reported thus far, so we aimed to systematically identify SIRT7 substrates using stable-isotope labeling with amino acids in cell culture (SILAC) coupled with quantitative mass spectrometry (MS). Using SIRT7(+/+) and SIRT7(-/-) mouse embryonic fibroblasts as our model system, we identified and quantified 1493 acetylation sites in 789 proteins, of which 261 acetylation sites in 176 proteins showed >= 2-fold change in acetylation state between SIRT7(-/-) and SIRT7(+/+) cells. These proteins were considered putative SIRT7 substrates and were carried forward for further analysis. We then validated the predictive efficiency of the SILAC-MS experiment by assessing substrate acetylation status in vitro in six predicted proteins. We also performed a bioinformatic analysis of the MS data, which indicated that many of the putative protein substrates were involved in metabolic processes. Finally, we expanded our list of candidate substrates by performing a bioinformatics-based prediction analysis of putative SIRT7 substrates, using our list of putative substrates as a positive training set, and again validated a subset of the proteins in vitro. In summary, we have generated a comprehensive list of SIRT7 candidate substrates.; National Key Basic Research Program of China [2011CB504200, 2013CB911000, 2013CB911001]; National Natural Science Foundation of China [31070691, 81321003, 91319302, 81472627, 31371337]; Discipline Construction Funding of Shenzhen; Shenzhen Municipal Commission of Science and Technology Innovation [JCYJ20160427104855100]; SCI(E); ARTICLE; 13-14; 17
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/472380]
专题	生命科学学院
推荐引用方式 GB/T 7714	Zhang, Chaohua,Zhai, Zichao,Tang, Ming,et al. Quantitative proteome-based systematic identification of SIRT7 substrates[J]. PROTEOMICS,2017.
APA	Zhang, Chaohua.,Zhai, Zichao.,Tang, Ming.,Cheng, Zhongyi.,Li, Tingting.,...&Zhu, Wei-Guo.(2017).Quantitative proteome-based systematic identification of SIRT7 substrates.PROTEOMICS.
MLA	Zhang, Chaohua,et al."Quantitative proteome-based systematic identification of SIRT7 substrates".PROTEOMICS (2017).