Poster Presentation 25th Annual Lorne Proteomics Symposium 2020

Mediator Lipidomics: Towards Comprehensive Metabolic Profiling of Eicosanoids and Related Fatty Acids (#148)

John Hewetson 1 , Atsuhiko 'Ash' Toyama 2 , Masaki Yamada 2 , Tatsuro Nakamura 3 , Takahisa Murata 3
  1. Shimadzu Scientific Instruments, Ermington, NSW, Australia
  2. Analytical and Measuring Instruments Division, Shimadzu Corporation, Kyoto
  3. Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, Japan

Eicosanoids, such as prostaglandins, omega-3 fatty acids and their metabolites, are a major family of bioactive lipids that mediate autocrine, paracrine and endocrine signaling in diverse pathophysiological systems. Quantitative analysis of eicosanoids is an attractive approach to increase insight into their signaling roles to better characterize a disease state and for potential contribution to biomarker development.
Using the UHPLC-MS/MS platform with established ease of compound identification, robustness and high-throughput, we sought to maximally increase the coverage of lipid mediators to develop a widely-targeted method for comprehensive metabolic profiling of eicosanoids and related fatty acids. The method was developed consisting of 326 MRM transitions acquired within 20 minutes of chromatographic separation for measuring 196 fatty acid metabolites and 18 deuterium-labeled analogs as internal standard. Identification of target signals was systematized by combining the reference ion ratio criteria with the tool-assisted retention time matching criteria at an unprecedented precision of 3 second time window. The method sensitivity evaluated as on-column LLOQ ranged from 0.1 to 1 pg for the majority of targets, which enabled quantitative detection of 67 targets from 5 μL equivalent volume of control human plasma. We used this method for a preliminary investigation of model mice undergoing inflammatory responses. Multivariate analysis of around 100 targets detected from mice serum samples resulted in characteristic profiles with notable implications.