Automatic Identification Approach for High-Performance Liquid Chromatography-Multiple Reaction Monitoring Fatty Acid Global Profiling

作者：Tie, Cai^*; Hu, Ting; Jia, Zhi-Xin; Zhang, Jin-Lan

来源：Analytical Chemistry, 2015, 87(16): 8181-8185.

DOI：10.1021/acs.analchem.5b00799

• MASS-SPECTROMETRY
• METABOLISM
• DISEASE
• OBESITY
• BLOOD

Fatty acids (FAs) are a group of lipid molecules that are essential to organisms. As potential biomarkers for different diseases, FAs have attracted increasing attention from both biological researchers and the pharmaceutical industry. A sensitive and accurate method for globally profiling and identifying FAs is required for biomarker discovery. The high selectivity and sensitivity of high-performance liquid chromatography-multiple reaction monitoring (HPLC-MRM) gives it great potential to fulfill the need to identify FAs from complicated matrices. This paper developed a new approach for global FA profiling and identification for HPLC-MRM FA data mining. Mathematical models for identifying FM were simulated using the isotope-induced retention time (RT) shift (IRS) and peak area ratios between parallel isotope peaks for a series of FA standards. The FA structures were predicated using another model based on the RT and molecular weight. Fully automated FA identification software was coded using the Qt platform based on these mathematical models. Different samples were used to verify the software. A high identification efficiency (greater than 75%) was observed when 96 FA species were identified in plasma. This FAs identification strategy promises to accelerate FA research and applications.

• 出版日期2015-8-18
• 单位天然药物活性物质与功能国家重点实验室; 北京协和医学院; 中国医学科学院北京协和医院