iTRAQ-based quantitative analysis of protein mixtures with large fold change and dynamic range

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Abstract

Quantitation of changes in protein abundance is key to understanding the alterations that biological systems undergo and to discovering novel biomarkers. Currently, HPLC-MS/MS can be used to quantify changes in protein expression levels [Ong, S. E. and Mann, M., Nat. Chem. Biol. 2005, 1, 252-262]. Nevertheless, quantitative analysis of protein mixtures by HPLC-MS/MS is still hampered by the wide range of protein expression levels, the high dynamic range of protein concentrations and the lack of reliable quantitation algorithms [D'Ascenzo, M., et al. Brief. Funct. Genomic. Proteomic. 2008, 7, 127-135; Lin, W. T., et al., J. Proteome Res. 2006, 5, 2328-2338; Matthiesen, R., et al. J. Proteome Res. 2005, 4, 2338-2347; Yu, C. Y., et al. Nucleic Acids Res. 2007, 35, W707-W712]. In this context, we describe two different samples (4-protmix and 8-protmix) suitable for relative protein quantitation using iTRAQ. Using the 4-protmix, relative protein changes of up to 24-fold were measured. The 8-protmix allowed the quantitation of the relative protein changes in a mixture of proteins within the range of two orders of magnitude in concentration and ten-fold differences in relative abundance. We propose that the two samples are suited to test the iTRAQ quantitative proteomic workflow. We analyzed the iTRAQ samples with a LTQ Orbitrap using "higher energy collision-induced dissociation" fragmentation [Olsen, J. V., et al., Nat. Methods 2007, 4, 709-712] and quantified with Proteome Discoverer v.1.1 (Thermo Fisher Scientific). We believe that the presented protein mixtures will be useful to assess the performance of the iTRAQ-based quantitation proteomic strategy in any laboratory. © 2009 Wiley-VCH Verlag GmbH & Co. KGaA.

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Casado-Vela, J., Martínez-Esteso, M. J., Rodriguez, E., Borrás, E., Elortza, F., & Bru-Martínez, R. (2010). iTRAQ-based quantitative analysis of protein mixtures with large fold change and dynamic range. Proteomics, 10(2), 343–347. https://doi.org/10.1002/pmic.200900509

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