Absolute Quantification of Toxicological Biomarkers via Mass Spectrometry
With the advent of “–omics” technologies there has been an explosion of data generation in the field of toxicology, as well as many others. As new candidate biomarkers of toxicity are being regularly discovered, the next challenge is to validate these observations in a targeted manner. Traditionally, these validation experiments have been conducted using antibody-based technologies such as Western blotting, ELISA, and immunohistochemistry. However, this often produces a significant bottleneck as the time, cost, and development of successful antibodies are often far outpaced by the generation of targets of interest. In response to this, there recently have been several developments in the use of triple quadrupole (QQQ) mass spectrometry (MS) as a platform to provide quantification of proteins. This technology does not require antibodies; it is typically less expensive and quicker to develop assays and has the opportunity for more accessible multiplexing. The speed of these experiments combined with their flexibility and ability to multiplex assays makes the technique a valuable strategy to validate biomarker discovery.
Key wordsCatalase Mass spectrometry Quantification Proteomics Biomarkers
The authors would like to thank Agilent Technologies, Santa Clara, for generating much of the data and figures used in this example. We would like to also thank all members of the PredTox Consortium. Funding is acknowledged under the FP6 Integrated Project, InnoMed. The UCD Conway Institute and the Proteome Research Centre is funded by the Programme for Research in Third Level Institutions (PRTLI), as administered by the Higher Education Authority (HEA) of Ireland.
- 3.Abbatiello SE, Mani DR, Schilling B, MacLean B, Zimmerman LJ, Feng X, Cusack MP, Sedransk N, Hall SC, Addona T, Allen S, Dodder NG, Ghosh M, Held JM, Hedrick V, Inerowicz HD, Jackson A, Keshishian H, Kim JW, Lyssand JS, Riley CP, Rudnick P, Sadowski P, Shaddox K, Smith D, Tomazela D, Wahlander A, Waldemarson S, Whitwell CA, You J, Zhang S, Kinsinger CR, Mesri M, Rodriguez H, Borchers CH, Buck C, Fisher SJ, Gibson BW, Liebler D, MacCoss M, Neubert TA, Paulovich A, Regnier F, Skates SJ, Tempst P, Wang M, Carr SA (2013) Design, implementation and multisite evaluation of a system suitability protocol for the quantitative assessment of instrument performance in Liquid Chromatography-Multiple Reaction Monitoring-MS (LC-MRM-MS). Mol Cell Proteomics 12(9):2623–2639. doi: 10.1074/mcp.M112.027078 CrossRefPubMedPubMedCentralGoogle Scholar
- 7.Wilhelm M, Schlegl J, Hahne H, Moghaddas Gholami A, Lieberenz M, Savitski MM, Ziegler E, Butzmann L, Gessulat S, Marx H, Mathieson T, Lemeer S, Schnatbaum K, Reimer U, Wenschuh H, Mollenhauer M, Slotta-Huspenina J, Boese JH, Bantscheff M, Gerstmair A, Faerber F, Kuster B (2014) Mass-spectrometry-based draft of the human proteome. Nature 509(7502):582–587. doi: 10.1038/nature13319 CrossRefPubMedGoogle Scholar
- 11.MacLean B, Tomazela DM, Shulman N, Chambers M, Finney GL, Frewen B, Kern R, Tabb DL, Liebler DC, MacCoss MJ (2010) Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics 26(7):966–968. doi: 10.1093/bioinformatics/btq054 CrossRefPubMedPubMedCentralGoogle Scholar