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Highly reproducible improved label-free quantitative analysis of cellular phosphoproteome by optimization of LC-MS/MS gradient and analytical column construction.

ABSTRACT: Expanding the sequencing depth of the peptides with a statistically significant quantitative change derived from a biological stimulation is critical. Here we demonstrate that optimization of LC gradient and analytical column construction can reveal over 30,000 unique peptides and 23,000 phosphopeptides at high confidence. The quantitative reproducibility of different analytical workflows was evaluated by comparing the phosphoproteome of CD3/4 stimulated and unstimulated T-cells as a model system. A fritless, 50cm-long column packed with 1.9?m particles operated with a standard pressure HPLC significantly improved the sequencing depth 51% and decreased the selected ion chromatogram peak spreading. Most importantly, under the optimal workflow we observed an improvement of over 300% in detection of significantly changed phosphopeptides in the stimulated cells compared with the other workflows. The discovery power of the optimized column configuration was illustrated by identification of significantly altered phosphopeptides harboring novel sites from proteins previously established as important in T cell signaling including A-Raf, B-Raf, c-Myc, CARMA1, Fyn, ITK, LAT, NFAT1/2/3, PKC?, PLC?1/2, RAF1, and SOS1. Taken together, our results reveal the analytical power of optimized chromatography using sub 2?m particles for the analysis of the T cell phosphoproteome to reveal a vast landscape of significantly altered phosphorylation changes in response to T cell receptor stimulation.

SUBMITTER: Ahsan N

PROVIDER: S-EPMC5542054 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Highly reproducible improved label-free quantitative analysis of cellular phosphoproteome by optimization of LC-MS/MS gradient and analytical column construction.

Ahsan Nagib N Belmont Judson J Chen Zhuo Z Clifton James G JG Salomon Arthur R AR

Journal of proteomics 20170617

Expanding the sequencing depth of the peptides with a statistically significant quantitative change derived from a biological stimulation is critical. Here we demonstrate that optimization of LC gradient and analytical column construction can reveal over 30,000 unique peptides and 23,000 phosphopeptides at high confidence. The quantitative reproducibility of different analytical workflows was evaluated by comparing the phosphoproteome of CD3/4 stimulated and unstimulated T-cells as a model syste ...[more]

PMID: 28634120

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Project description:BackgroundComprehensive characterization of the phosphoproteome in living cells is critical in signal transduction research. But the low abundance of phosphopeptides among the total proteome in cells remains an obstacle in mass spectrometry-based proteomic analysis. To provide a solution, an alternative analytic strategy to confidently identify phosphorylated peptides by using the alkaline phosphatase (AP) treatment combined with high-resolution mass spectrometry was provided. While the process is applicable, the key integration along the pipeline was mostly done by tedious manual work.ResultsWe developed a software toolkit, iPhos, to facilitate and streamline the work-flow of AP-assisted phosphoproteome characterization. The iPhos tookit includes one assister and three modules. The iPhos Peak Extraction Assister automates the batch mode peak extraction for multiple liquid chromatography mass spectrometry (LC-MS) runs. iPhos Module-1 can process the peak lists extracted from the LC-MS analyses derived from the original and dephosphorylated samples to mine out potential phosphorylated peptide signals based on mass shift caused by the loss of some multiples of phosphate groups. And iPhos Module-2 provides customized inclusion lists with peak retention time windows for subsequent targeted LC-MS/MS experiments. Finally, iPhos Module-3 facilitates to link the peptide identifications from protein search engines to the quantification results from pattern-based label-free quantification tools. We further demonstrated the utility of the iPhos toolkit on the data of human metastatic lung cancer cells (CL1-5).ConclusionsIn the comparison study of the control group of CL1-5 cell lysates and the treatment group of dasatinib-treated CL1-5 cell lysates, we demonstrated the applicability of the iPhos toolkit and reported the experimental results based on the iPhos-facilitated phosphoproteome investigation. And further, we also compared the strategy with pure DDA-based LC-MS/MS phosphoproteome investigation. The results of iPhos-facilitated targeted LC-MS/MS analysis convey more thorough and confident phosphopeptide identification than the results of pure DDA-based analysis.

Dataset Information

Highly reproducible improved label-free quantitative analysis of cellular phosphoproteome by optimization of LC-MS/MS gradient and analytical column construction.

Publications

Highly reproducible improved label-free quantitative analysis of cellular phosphoproteome by optimization of LC-MS/MS gradient and analytical column construction.

Similar Datasets

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