Multiparameter Optimization of Two Common Proteomics Quantification Methods for Quantifying Low-Abundance Proteins

doi:10.1021/acs.jproteome.8b00769

	Multiparameter Optimization of Two Common Proteomics Quantification Methods for Quantifying Low-Abundance Proteins
	Zhang, Chengqian1 ; Shi, Zhaomei1 ; Han, Ying1 ; Ren, Yan 2,3; Hao, Piliang1
	2019-01
发表期刊	JOURNAL OF PROTEOME RESEARCH (IF:3.8[JCR-2023],4.1[5-Year])
ISSN	1535-3893
卷号	18 期号:1 页码:461-468
发表状态	已发表
DOI	10.1021/acs.jproteome.8b00769
摘要	Quantitative proteomics has been extensively applied in the screening of differentially regulated proteins in various research areas for decades, but its sensitivity and accuracy have been a bottleneck for many applications. Every step in the proteomics workflow can potentially affect the quantification of low-abundance proteins, but a systematic evaluation of their effects has not been done yet. In this work, to improve the sensitivity and accuracy of label-free quantification and tandem mass tags (TMT) labeling in quantifying low-abundance proteins, multiparameter optimization was carried out using a complex 2-proteome artificial sample mixture for a series of steps from sample preparation to data analysis, including the desalting of peptides, peptide injection amount for LC-MS/MS, MS1 resolution, the length of LC-MS/MS gradient, AGC targets, ion accumulation time, MS2 resolution, precursor coisolation threshold, data analysis software, statistical calculation methods, and protein fold changes, and the best settings for each parameter were defined. The suitable cutoffs for detecting low-abundance proteins with at least 1.5-fold and 2-fold changes were identified for label-free and TMT methods, respectively. The use of optimized parameters will significantly improve the overall performance of quantitative proteomics in quantifying low-abundance proteins and thus promote its application in other research areas.
关键词	quantitative proteomics label-free quantification tandem mass tags low-abundance proteins mass spectrometry
收录类别	SCI ; SCIE
语种	英语
资助项目	National Natural Science Foundation of China[31500670]
WOS研究方向	Biochemistry & Molecular Biology
WOS类目	Biochemical Research Methods
WOS记录号	WOS:000455285900042
出版者	AMER CHEMICAL SOC
WOS关键词	LABEL-FREE QUANTIFICATION ; STRATEGY ; IDENTIFICATION ; CHROMATOGRAPHY ; SEPARATIONS ; EXPRESSION ; MIXTURES ; TAGS ; CELL
原始文献类型	Article
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/30101
专题	生命科学与技术学院_公共科研平台_组学分析平台
通讯作者	Ren, Yan; Hao, Piliang
作者单位	1.ShanghaiTech Univ, Sch Life Sci & Technol, 393 Middle Huaxia Rd, Shanghai 201210, Peoples R China 2.BGI Shenzhen, Beishan Ind Zone 11th Bldg, Shenzhen 518083, Guangdong, Peoples R China 3.BGI Shenzhen, China Natl GeneBank, Jinsha Rd, Shenzhen 518120, Peoples R China
第一作者单位	生命科学与技术学院
通讯作者单位	生命科学与技术学院
第一作者的第一单位	生命科学与技术学院
推荐引用方式 GB/T 7714	Zhang, Chengqian,Shi, Zhaomei,Han, Ying,et al. Multiparameter Optimization of Two Common Proteomics Quantification Methods for Quantifying Low-Abundance Proteins[J]. JOURNAL OF PROTEOME RESEARCH,2019,18(1):461-468.
APA	Zhang, Chengqian,Shi, Zhaomei,Han, Ying,Ren, Yan,&Hao, Piliang.(2019).Multiparameter Optimization of Two Common Proteomics Quantification Methods for Quantifying Low-Abundance Proteins.JOURNAL OF PROTEOME RESEARCH,18(1),461-468.
MLA	Zhang, Chengqian,et al."Multiparameter Optimization of Two Common Proteomics Quantification Methods for Quantifying Low-Abundance Proteins".JOURNAL OF PROTEOME RESEARCH 18.1(2019):461-468.