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Metabolites 2018, 8(3), 44; https://doi.org/10.3390/metabo8030044

Validation and Automation of a High-Throughput Multitargeted Method for Semiquantification of Endogenous Metabolites from Different Biological Matrices Using Tandem Mass Spectrometry

1
Metabolomics Unit, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, HiLIFE, Tukholmankatu 8, Biomedicum 2U, 00290 Helsinki, Finland
2
Roche Diagnostics GmbH, Nonnenwald 2, 82377 Penzberg, Germany
3
Computational Systems Medicine group, University of Helsinki, 00290 Helsinki, Finland
4
Technical Research Center of Finland, P.O. Box 1000, 02044 Espoo, Finland
5
Network Pharmacology for Precision Medicine Group, University of Helsinki, 00290 Helsinki, Finland
6
Finnish Customs Laboratory, Tekniikantie 13, 02150 Espoo, Finland
*
Author to whom correspondence should be addressed.
Received: 20 June 2018 / Revised: 27 July 2018 / Accepted: 3 August 2018 / Published: 5 August 2018
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Abstract

The use of metabolomics profiling to understand the metabolism under different physiological states has increased in recent years, which created the need for robust analytical platforms. Here, we present a validated method for targeted and semiquantitative analysis of 102 polar metabolites that cover major metabolic pathways from 24 classes in a single 17.5-min assay. The method has been optimized for a wide range of biological matrices from various organisms, and involves automated sample preparation and data processing using an inhouse developed R-package. To ensure reliability, the method was validated for accuracy, precision, selectivity, specificity, linearity, recovery, and stability according to European Medicines Agency guidelines. We demonstrated an excellent repeatability of retention times (CV < 4%), calibration curves (R2 ≥ 0.980) in their respective wide dynamic concentration ranges (CV < 3%), and concentrations (CV < 25%) of quality control samples interspersed within 25 batches analyzed over a period of one year. The robustness was demonstrated through a high correlation between metabolite concentrations measured using our method and the NIST reference values (R2 = 0.967), including cross-platform comparability against the BIOCRATES AbsoluteIDQp180 kit (R2 = 0.975) and NMR analyses (R2 = 0.884). We have shown that our method can be successfully applied in many biomedical research fields and clinical trials, including epidemiological studies for biomarker discovery. In summary, a thorough validation demonstrated that our method is reproducible, robust, reliable, and suitable for metabolomics studies. View Full-Text
Keywords: high-throughput; targeted; semiquantitation; metabolomics; LC-MS; multianalyte method; validation; cross-platform comparability; automation; biomarkers high-throughput; targeted; semiquantitation; metabolomics; LC-MS; multianalyte method; validation; cross-platform comparability; automation; biomarkers
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Nandania, J.; Peddinti, G.; Pessia, A.; Kokkonen, M.; Velagapudi, V. Validation and Automation of a High-Throughput Multitargeted Method for Semiquantification of Endogenous Metabolites from Different Biological Matrices Using Tandem Mass Spectrometry. Metabolites 2018, 8, 44.

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