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iPhos: a toolkit to streamline the alkaline phosphatase-assisted comprehensive LC-MS phosphoproteome investigation

BACKGROUND: Comprehensive 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 alter...

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Autores principales: Yang, Tzu-Hsien, Chang, Hong-Tsun, Hsiao, Eric SL, Sun, Juo-Ling, Wang, Chung-Ching, Wu, Hsin-Yi, Liao, Pao-Chi, Wu, Wei-Sheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4290636/
https://www.ncbi.nlm.nih.gov/pubmed/25521246
http://dx.doi.org/10.1186/1471-2105-15-S16-S10
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author Yang, Tzu-Hsien
Chang, Hong-Tsun
Hsiao, Eric SL
Sun, Juo-Ling
Wang, Chung-Ching
Wu, Hsin-Yi
Liao, Pao-Chi
Wu, Wei-Sheng
author_facet Yang, Tzu-Hsien
Chang, Hong-Tsun
Hsiao, Eric SL
Sun, Juo-Ling
Wang, Chung-Ching
Wu, Hsin-Yi
Liao, Pao-Chi
Wu, Wei-Sheng
author_sort Yang, Tzu-Hsien
collection PubMed
description BACKGROUND: Comprehensive 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. RESULTS: We 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). CONCLUSIONS: In 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.
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spelling pubmed-42906362015-01-15 iPhos: a toolkit to streamline the alkaline phosphatase-assisted comprehensive LC-MS phosphoproteome investigation Yang, Tzu-Hsien Chang, Hong-Tsun Hsiao, Eric SL Sun, Juo-Ling Wang, Chung-Ching Wu, Hsin-Yi Liao, Pao-Chi Wu, Wei-Sheng BMC Bioinformatics Research BACKGROUND: Comprehensive 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. RESULTS: We 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). CONCLUSIONS: In 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. BioMed Central 2014-12-08 /pmc/articles/PMC4290636/ /pubmed/25521246 http://dx.doi.org/10.1186/1471-2105-15-S16-S10 Text en Copyright © 2014 Yang et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Yang, Tzu-Hsien
Chang, Hong-Tsun
Hsiao, Eric SL
Sun, Juo-Ling
Wang, Chung-Ching
Wu, Hsin-Yi
Liao, Pao-Chi
Wu, Wei-Sheng
iPhos: a toolkit to streamline the alkaline phosphatase-assisted comprehensive LC-MS phosphoproteome investigation
title iPhos: a toolkit to streamline the alkaline phosphatase-assisted comprehensive LC-MS phosphoproteome investigation
title_full iPhos: a toolkit to streamline the alkaline phosphatase-assisted comprehensive LC-MS phosphoproteome investigation
title_fullStr iPhos: a toolkit to streamline the alkaline phosphatase-assisted comprehensive LC-MS phosphoproteome investigation
title_full_unstemmed iPhos: a toolkit to streamline the alkaline phosphatase-assisted comprehensive LC-MS phosphoproteome investigation
title_short iPhos: a toolkit to streamline the alkaline phosphatase-assisted comprehensive LC-MS phosphoproteome investigation
title_sort iphos: a toolkit to streamline the alkaline phosphatase-assisted comprehensive lc-ms phosphoproteome investigation
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4290636/
https://www.ncbi.nlm.nih.gov/pubmed/25521246
http://dx.doi.org/10.1186/1471-2105-15-S16-S10
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