Abstract
Isobaric labeling has become an essential method for quantitative mass spectrometry based experiments. This technique allows high-throughput proteomics while providing reasonable coverage of protein measurements across multiple samples. Here, the analysis of isobarically labeled mass spectrometry data with a special focus on quality control and potential pitfalls is discussed. The protocol is based on our fully integrated IsoProt workflow. The concepts discussed are nevertheless applicable to the analysis of any isobarically labeled experiment using alternative computational tools and algorithms.
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References
Geiger T, Cox J, Ostasiewicz P, Wisniewski JR, Mann M (2010) Super-SILAC mix for quantitative proteomics of human tumor tissue. Nat Methods 7:383–385
Ross PL, Huang YN, Marchese JN et al (2004) Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents. Mol Cell Proteomics 3:1154–1169
Thompson A, Schäfer J, Kuhn K, Kienle S, Schwarz J, Schmidt G, Neumann T, Johnstone R, Mohammed AKA, Hamon C (2003) Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS. Anal Chem 75:1895–1904
Griss J, Vinterhalter G, Schwämmle V (2019) IsoProt: a complete and reproducible workflow to analyze iTRAQ/TMT experiments. J Proteome Res 18:1751–1759
Kim S, Pevzner PA (2014) MS-GF+ makes progress towards a universal database search tool for proteomics. Nat Commun 5:5277
Barsnes H, Vaudel M (2018) SearchGUI: a highly adaptable common interface for proteomics search and de novo engines. J Proteome Res 17:2552–2555
Ritchie ME, Diyagama D, Neilson J, van Laar R, Dobrovic A, Holloway A, Smyth GK (2006) Empirical array quality weights in the analysis of microarray data. BMC Bioinformatics 7:261
Storey JD (2002) A direct approach to false discovery rates. J R Stat Soc B 64:479–498
Paulo JA, Jedrychowski MP, Chouchani ET, Kazak L, Gygi SP (2018) Multiplexed isobaric tag-based profiling of seven murine tissues following in vivo nicotine treatment using a minimalistic proteomics strategy. Proteomics 18:e1700326
Mertins P, Mani DR, Ruggles KV et al (2016) Proteogenomics connects somatic mutations to signalling in breast cancer. Nature 534:55–62
Bramer LM, Irvahn J, Piehowski PD, Rodland KD, Webb-Robertson B-JM (2020) A review of imputation strategies for isobaric labeling-based shotgun proteomics. J Proteome Res 20(1):1–13. https://doi.org/10.1021/acs.jproteome.0c00123
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Griss, J., Schwämmle, V. (2021). Analysis of Label-Based Quantitative Proteomics Data Using IsoProt. In: Cecconi, D. (eds) Proteomics Data Analysis. Methods in Molecular Biology, vol 2361. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1641-3_4
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DOI: https://doi.org/10.1007/978-1-0716-1641-3_4
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Publisher Name: Humana, New York, NY
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Online ISBN: 978-1-0716-1641-3
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