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

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Title:	iPhos: A toolkit to streamline the alkaline phosphatase-assisted comprehensive LC-MS phosphoproteome investigation
Authors:	吳忻怡;Yang, Tzu-Hsien;Chang, Hong-Tsun;Hsiao, Eric SL;Sun, Juo-Ling;Wang, Chung-Ching;Wu, Hsin-Yi;Liao, Pao-Chi;Wu, Wei-Sheng
Contributors:	總教學中心通識教育中心
Keywords:	Adenocarcinoma - drug therapy;Adenocarcinoma - enzymology;Algorithms;Alkaline Phosphatase - metabolism;Alzheimer's disease;Bioinformatics;Biomedical and Life Sciences;Chromatography;Chromatography, Liquid - methods;Computational Biology/Bioinformatics;Computer Appl. in Life Sciences;Dasatinib;Data mining;Experiments;Extraction;Humans;Immunoprecipitation;Kinases;Life Sciences;Liquid chromatography;Lists;Lung cancer;Lung Neoplasms - drug therapy;Lung Neoplasms - enzymology;Mass spectrometry;Medical research;Microarrays;Peer review;Peptides;Phosphatase;Phosphopeptides - analysis;Phosphorylation;Programming languages;Protein Kinase Inhibitors - pharmacology;Proteins;Proteome - analysis;Proteomics - methods;Pyrimidines - pharmacology;Retention time;Signal processing;Signal Transduction;Software;Strategy;Studies;Tandem Mass Spectrometry - methods;Thiazoles - pharmacology;Tumor Cells, Cultured
Date:	2014-12-08
Issue Date:	2026-04-23 12:54:05 (UTC+8)
Publisher:	BioMed Central Ltd.;London: BioMed Central
Abstract:	摘要： 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. 其他題名： BMC Bioinformatics 出版者： London: BioMed Central 出版日期： 2014-12-08 出處： BMC bioinformatics, 2014-12, Vol.15 (Suppl 16), p.S10-S10, Article S10 資源來源： Publicly Available Content Database (Proquest) 版權： Yang et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver ( ) applies to the data made available in this article, unless otherwise stated. 版權： 2014 Yang et al.; licensee BioMed Central Ltd. 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. 版權： Copyright © 2014 Yang et al.; licensee BioMed Central Ltd. 2014 Yang et al.; licensee BioMed Central Ltd. 識別號： ISSN: 1471-2105 識別號： EISSN: 1471-2105 識別號： DOI: 10.1186/1471-2105-15-S16-S10 識別號： PMID: 25521246
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