Deep Coverage of Global Protein Expression and Phosphorylation in Breast Tumor Cell Lines Using TMT 10-plex Isobaric Labeling

使用 TMT 10 重同质异位素标记深度覆盖乳腺肿瘤细胞系中的整体蛋白质表达和磷酸化

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作者:Fang-Ke Huang, Guoan Zhang, Kevin Lawlor, Arpi Nazarian, John Philip, Paul Tempst, Noah Dephoure, Thomas A Neubert

Abstract

Labeling peptides with isobaric tags is a popular strategy in quantitative bottom-up proteomics. In this study, we labeled six breast tumor cell lysates (1.34 mg proteins per channel) using 10-plex tandem mass tag reagents and analyzed the samples on a Q Exactive HF Quadrupole-Orbitrap mass spectrometer. We identified a total of 8,706 proteins and 28,186 phosphopeptides, including 7,394 proteins and 23,739 phosphosites common to all channels. The majority of technical replicates correlated with a R2 ≥ 0.98, indicating minimum variability was introduced after labeling. Unsupervised hierarchical clustering of phosphopeptide data sets successfully classified the breast tumor samples into Her2 (epidermal growth factor receptor 2) positive and Her2 negative groups, whereas mRNA abundance did not. The tyrosine phosphorylation levels of receptor tyrosine kinases, phosphoinositide-3-kinase, protein kinase C delta, and Src homology 2, among others, were significantly higher in the Her2 positive than the Her2 negative group. Despite ratio compression in MS2-based experiments, we demonstrated the ratios calculated using an MS2 method are highly correlated (R2 > 0.65) with ratios obtained using MS3-based quantitation (using a Thermo Orbitrap Fusion mass spectrometer) with reduced ratio suppression. Given the deep coverage of global and phosphoproteomes, our data show that MS2-based quantitation using TMT can be successfully used for large-scale multiplexed quantitative proteomics.

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