Development of data-independent acquisition workflows for metabolomic analysis on a quadrupole-orbitrap platform

Untargeted metabolomic profiling has been widely used in recent years. However, the low reproducibility of the data-dependent acquisition (DDA) strategy presents a major bottleneck that considerably limits the reliability of metabolomic studies in biological and clinical research. The data-independent acquisition (DIA) strategy is proposed to solve the above-mentioned problem, and it is gaining popularity. This paper presents a novel approach for performing metabolomic analysis using an untargeted, liquid chromatography-data independent-mass spectrometry (LC-DIA-MS) strategy on a quadrupole-Orbitrap platform. Using chemical standards and metabolites extracted from serum samples, we optimized the LC-DIA-MS parameters to analyze hydrophilic metabolites and lipids. The quantitative performance and analytical reliability were evaluated, and the performances of DIA, DDA, and all-ion fragmentation mode were compared. Finally, as a proof of concept, we applied the constructed DIA workflow to a comparative metabolomic study of papillary thyroid carcinoma (TC) serum samples. Several metabolites, including carnitine, trimethylamine N-oxide, and some amino acids, significantly changed between patients and healthy controls. This study demonstrated the feasibility and advantage of the DIA strategy on untargeted metabolomic analysis for biological study and clinical biomarker screening.