title: Optimization of large-scale pseudotargeted metabolomics method based on liquid chromatography-mass spectrometry.
abstract: Liquid chromatography-mass spectrometry (LC-MS) is now a main stream technique for large-scale metabolic phenotyping to obtain a better understanding of genomic functions. However, repeatability is still an essential issue for the LC-MS based methods, and convincing strategies for long time analysis are urgently required. Our former reported pseudotargeted method which combines nontargeted and targeted analyses, is proved to be a practical approach with high-quality and information-rich data. In this study, we developed a comprehensive strategy based on the pseudotargeted analysis by integrating blank-wash, pooled quality control (QC) sample, and post-calibration for the large-scale metabolomics study. The performance of strategy was optimized from both pre- and post-acquisition sections including the selection of QC samples, insertion frequency of QC samples, and post-calibration methods. These results imply that the pseudotargeted method is rather stable and suitable for large-scale study of metabolic profiling. As a proof of concept, the proposed strategy was applied to the combination of 3 independent batches within a time span of 5 weeks, and generated about 54% of the features with coefficient of variations (CV) below 15%. Moreover, the stability and maximal capability of a single analytical batch could be extended to at least 282 injections (about 110h) while still providing excellent stability, the CV of 63% metabolic features was less than 15%. Taken together, the improved repeatability of our strategy provides a reliable protocol for large-scale metabolomics studies.
authors.affiliation: Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
authors.forename: Ping
authors.initials: P
authors.lastname: Luo
authors.affiliation: Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
authors.forename: Peiyuan
authors.initials: P
authors.lastname: Yin
authors.affiliation: School of Computer Science and Technology, Dalian University of Technology, Dalian, China.
authors.forename: Weijian
authors.initials: W
authors.lastname: Zhang
authors.affiliation: Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
authors.forename: Lina
authors.initials: L
authors.lastname: Zhou
authors.affiliation: Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
authors.forename: Xin
authors.initials: X
authors.lastname: Lu
authors.affiliation: School of Computer Science and Technology, Dalian University of Technology, Dalian, China.
authors.forename: Xiaohui
authors.initials: X
authors.lastname: Lin
authors.affiliation: Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China. Electronic address: xugw@dicp.ac.cn.
authors.forename: Guowang
authors.initials: G
authors.lastname: Xu
mesh_terms: D002138:Calibration; D002853:Chromatography, Liquid; D013058:Mass Spectrometry; D055432:Metabolomics / Q000379:methods*; D011786:Quality Control
keywords: LC–MS; Large-scale; Metabolic profiling; Metabolomics; Pseudotargeted analysis; Quality control