Abstract
Targeted metabolomics aims to analyze a set of pre-selected metabolites from biologically relevant metabolic pathways. The triple quadrupole mass spectrometry (QqQ-MS) based multiple reaction monitoring (MRM) technique is the most widely approach used for targeted metabolomics, and features high selectivity and sensitivity, good reproducibility and wide dynamic range in quantitative analysis. Here, we describe an MRM based targeted metabolomics workflow for the quantitative analysis of 200 polar metabolites in central carbon metabolic pathways, including the data acquisition method and the automated data processing procedures using our in-house R package MRMAnalyzer. The workflow described in this chapter combines a hydrophilic interaction liquid chromatography (HILIC) separation and positive/negative ion polarity switching based MS detection, and is able to acquire data from multiple types of biological samples such as bacteria, cultured mammalian cells, animal tissues and biofluids (e.g., serum and urine). Finally, the MRMAnalyzer software can automatically process the generated large-scale data set with high efficiency. We hope it is a valuable and efficient workflow for researchers to facilitate the respective biological studies using targeted metabolomics.
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References
Patti GJ, Yanes O, Siuzdak G (2012) Metabolomics: the apogee of the omics trilogy. Nat Rev Mol Cell Biol 13(4):263–269
Nicholson JK, Lindon JC (2008) Systems biology: Metabonomics. Nature 455(7216):1054–1056
Fiehn O (2002) Metabolomics - the link between genotypes and phenotypes. Plant Mol Biol 48(1–2):155–171
Wishart DS (2016) Emerging applications of metabolomics in drug discovery and precision medicine. Nat Rev Drug Discov 15(7):473–484
Fernie AR, Trethewey RN, Krotzky AJ, Willmitzer L (2004) Metabolite profiling: from diagnostics to systems biology. Nat Rev Mol Cell Biol 5(9):763–769
Dettmer K, Aronov PA, Hammock BD (2007) Mass spectrometry-based metabolomics. Mass Spectrom Rev 26(1):51–78
Zhu ZJ, Schultz AW, Wang JH, Johnson CH, Yannone SM, Patti GJ, Siuzdak G (2013) Liquid chromatography quadrupole time-of-flight mass spectrometry characterization of metabolites guided by the METLIN database. Nat Protoc 8(3):451–460
Dudley E, Yousef M, Wang Y, Griffiths WJ (2010) Targeted metabolomics and mass spectrometry. Adv Protein Chem Struct Biol 80:45–83
Kitteringham NR, Jenkins RE, Lane CS, Elliott VL, Park BK (2009) Multiple reaction monitoring for quantitative biomarker analysis in proteomics and metabolomics. J Chromatogr B 877(13):1229–1239
Lu W, Bennett BD, Rabinowitz JD (2008) Analytical strategies for LC-MS-based targeted metabolomics. J Chromatogr B 871(2):236–242
Cai Y, Weng K, Guo Y, Peng J, Zhu Z-J (2015) An integrated targeted metabolomic platform for high-throughput metabolite profiling and automated data processing. Metabolomics 11(6):1575–1586
Tsugawa H, Arita M, Kanazawa M, Ogiwara A, Bamba T, Fukusaki E (2013) MRMPROBS: a data assessment and metabolite identification tool for large-scale multiple reaction monitoring based widely targeted metabolomics. Anal Chem 85(10):5191–5199
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
Wong JW, Abuhusain HJ, McDonald KL, Don AS (2012) MMSAT: automated quantification of metabolites in selected reaction monitoring experiments. Anal Chem 84(1):470–474
Yuan M, Breitkopf SB, Yang XM, Asara JM (2012) A positive/negative ion-switching, targeted mass spectrometry-based metabolomics platform for bodily fluids, cells, and fresh and fixed tissue. Nat Protoc 7(5):872–881
Zhou J, Liu H, Liu Y, Liu J, Zhao X, Yin Y (2016) Development and evaluation of a parallel reaction monitoring strategy for large-scale targeted metabolomics quantification. Anal Chem 88(8):4478–4486
Xia J, Psychogios N, Young N, Wishart DS (2009) MetaboAnalyst: a web server for metabolomic data analysis and interpretation. Nucleic Acids Res 37:W652–W660
Acknowledgments
The work was financially supported by National Natural Science Foundation of China (Grant No. 21575151) and State High-Tech Development Plan Award (the “863 program”, Grant No. 2014AA020526). Z.-J. Z. is supported by Thousand Youth Talents Program.
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1 Electronic Supplementary Materials
Supplementary Table 1
The general information of 200 metabolites, including metabolite name, formula, HMDB ID, METLIN ID, KEGG ID and the concentration of each metabolite in 200STD_mix. (XLSX 24 kb)
Supplementary Table 2
The in house ID, MRM transition and retention time for each defined metabolite. (CSV 19 kb)
Supplementary Table 3
The detailed MRM parameters of 200 metabolites contains metabolite name, precursor ion, product ion polarity and IDs. (CSV 14 kb)
Supplementary Table 4
The information of 10 metabolites in RTQC sample including in house ID, metabolite name, formula, precursor ion, product ion, fragmentor, CE, polarity and RT. (CSV 742 bytes)
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Cai, Y., Zhu, ZJ. (2019). A High-Throughput Targeted Metabolomics Workflow for the Detection of 200 Polar Metabolites in Central Carbon Metabolism. In: Baidoo, E. (eds) Microbial Metabolomics. Methods in Molecular Biology, vol 1859. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-8757-3_15
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DOI: https://doi.org/10.1007/978-1-4939-8757-3_15
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