1. Validation and Automation of a High-Throughput Multitargeted Method for Semiquantification of Endogenous Metabolites from Different Biological Matrices Using Tandem Mass Spectrometry
- Author
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Alberto Pessia, Gopal Peddinti, Vidya Velagapudi, Meri Kokkonen, Jatin Nandania, University of Helsinki, Institute for Molecular Medicine Finland, Institute for Molecular Medicine Finland, University of Helsinki, and Helsinki Institute of Life Science HiLIFE
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0301 basic medicine ,Calibration curve ,Endocrinology, Diabetes and Metabolism ,Metabolite ,MODELS ,lcsh:QR1-502 ,High-throughput ,VIRUS-INFECTION ,Tandem mass spectrometry ,Biochemistry ,lcsh:Microbiology ,MITOCHONDRIAL MYOPATHY ,03 medical and health sciences ,chemistry.chemical_compound ,Automation ,Metabolomics ,SDG 3 - Good Health and Well-being ,Liquid chromatography–mass spectrometry ,Multianalyte method ,Validation ,URINE ,Sample preparation ,Biomarker discovery ,Molecular Biology ,Semiquantitation ,Chromatography ,Chemistry ,ta1182 ,PLATFORM ,Repeatability ,Targeted ,3. Good health ,LC-MS ,030104 developmental biology ,Cross-platform comparability ,DISCOVERY ,TARGETED METABOLOMICS ,CELLS ,REPLICATION ,1182 Biochemistry, cell and molecular biology ,HUMAN SERUM ,Biomarkers - 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 &ge, 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.
- Published
- 2018
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