Optimal Normalization Method for GC-MS/MS-Based Large-Scale Targeted Metabolomics

Abstract It is a challenge to perform target screening of metabolites on a large scale in metabolomics study using gas chromatography with mass spectrometry ( GC-MS ). Some metabolites can hardly be detected and identified in biosamples due to their low MS response or poor specificity. Moreover, synthesis and degradation of derivatized metabolites in samples made it difficult to achieve fine method stability. Our method screens 475 metabolites in a single run using GC-MS/MS in MRM mode, and both internal standard and quality control-based normalization strategies were used to correct the peak intensity. A total of 91 and 161 metabolites were detected in plasma and urine, respectively. The method was validated to have fine linearity range and intra-day and inter-day stability. The method was applied to a pilot study, and this study investigated the metabolic perturbation in rats after fluorochloridone ( FLC ) administration. 18 metabolites exhibited statistical significance in rat urine, and they were confirmed to be associated with FLC treatment, where the upregulation of glucose, lactose, and galactose is potentially linked to oxidative stress reaction. This study has proved its value in large-scale detection of metabolites in biosamples using GC-MS/MS with high sensitivity, specificity, and stability. We hope that our study can promote the GC-MS-based metabolomics studies.