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Multi-parameter optimization of two common proteomics quantification methods for quantifying low-abundance proteins

ABSTRACT: To improve the sensitivity and accuracy of label-free quantification and tandem mass tags (TMT) labeling in quantifying low-abundance proteins, multi-parameter 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 co-isolation threshold, data analysis software, statistical calculation methods and protein fold changes. Five subprojects were included for this project.

ORGANISM(S): Homo Sapiens Mus Musculus

SUBMITTER: Piliang Hao

PROVIDER: PXD011574 | iProX | Fri Nov 02 00:00:00 GMT 2018

REPOSITORIES: iProX

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

Zhang Chengqian C Shi Zhaomei Z Han Ying Y Ren Yan Y Hao Piliang P

Journal of proteome research 20181126 1

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 t ...[more]

PMID: 30394099

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