PT - JOURNAL ARTICLE AU - Jatin Nandania AU - Gopal Peddinti AU - Alberto Pessia AU - Meri Kokkonen AU - Vidya Velagapudi TI - Validation and automation of a high-throughput multi-targeted method for semi-quantification of endogenous metabolites from different biological matrices using tandem mass spectrometry AID - 10.1101/352468 DP - 2018 Jan 01 TA - bioRxiv PG - 352468 4099 - http://biorxiv.org/content/early/2018/06/20/352468.short 4100 - http://biorxiv.org/content/early/2018/06/20/352468.full AB - The use of metabolomics profiling to understand 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 semi-quantitative analysis of 102 polar metabolites that covers 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 in-house 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 excellent repeatability of the 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 high correlation between metabolite concentrations measured using our method and 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.