Optimizing Oxylipin Analysis with Liquid Chromatography Mass Spectrometry through Bio-Inert Systems and Ion Funnel Adjustments
Shuster, J. T.; Wu, L.; Mill, J.; Morhaus, M. M.; Fan, N.; Tobias, F.; Baldwin, D. A.; Bruss, M. D.; Hurley, L. D.; Kimple, M.; Konopka, A. E.; Simcox, J.
Show abstract
Oxylipins are potent signaling lipids that affect inflammation, vascular tone, and metabolism, making them relevant in many diseases. Oxylipins are measured with liquid chromatography-mass spectrometry (LC-MS), but challenges in quantification arise due to low abundance and rapid degradation. In this study, we optimize LC-MS methods to improve the quantification of oxylipins in human plasma given growing interest in oxylipins and their impact on clinical research. Plasma samples were obtained from healthy participants and extracted by solid-phase extraction to concentrate the oxylipins. We then utilized a reversed phase targeted LC-MS/MS method using an Agilent 6495D triple quadrupole with transitions for 248 oxylipin species. Ion funnel voltages were set at 50 or 100 volts. Given the rapid degradation of oxylipins with bio-reactive surfaces, we compared both standard and Altura (bio-inert) columns, as well as standard and bio- inert LC setups. We observed that ion funnel parameters significantly alter detectable levels of oxylipins within LC-MS/MS analysis. By decreasing voltages applied to ions inside the ion funnel, signal was increased for most oxylipin species while peak quality was maintained. We also demonstrated that fully bio-inert setups quantify more compounds and show increased levels of some compounds, but fewer epoxyoctadecadienoic acid (EpODE) species. To explore this further, we injected analytical grade alpha-linolenic acid (ALA), the direct precursor of EpODEs, and observed formation of EpODEs within the instrumentation when using stainless steel columns. Our data shows that oxylipins benefit from fully bio-inert systems and optimized pre-mass analyzer parameters. The stainless-steel components of the column may also be contributing to epoxidation reactions of polyunsaturated fatty acids (PUFAs), generating oxylipin species during analysis. Finally, we utilized this method to perform oxylipin analysis in other human tissues including granulocytes, mononuclear cells, erythrocytes, skeletal muscle, and THP-1 cells, a human derived monocyte cell line.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Assessment of a 60-biomarker health surveillance panel (HSP) on whole blood from remote sampling devices by targeted LC/MRM-MS and discovery DIA-MS analysis 95%
- Comprehensive Metabolomic Analysis of Human Heart Tissue Enabled by Parallel Metabolite Extraction and High-Resolution Mass Spectrometry 95%
- "Organoid-in-a-column" coupled on-line with liquid chromatography-mass spectrometry 95%
Similar papers in this journal
- Development and Application of Multidimensional Lipid Libraries to Investigate Lipidomic Dysregulation Related to Smoke Inhalation Injury Severity 97%
- Development and Validation of a Novel LC-MS/MS Based Proteomics Method for Quantitation of Retinol Binding Protein 4 (RBP4) and Transthyretin (TTR) 96%
- Low-temperature HILIC provides enhanced separations and stability for LC-MS-based metabolomics 95%
Similar papers in this journal
- Optimized Mass Spectrometry Detection of Thyroid Hormones and Polar Metabolites in Rodent Cerebrospinal Fluid 95%
- High-throughput UHPLC-MS to screen metabolites in feces for gut metabolic health 95%
- An Optimised Monophasic Faecal Extraction Method for LC-MS Analysis and its Application in Gastrointestinal Disease 94%
Similar papers in this journal
Similar papers in this journal
- Quantification of esterified oxylipins following HILIC-fractionation of lipid classes 96%
- Automated preparation of plasma lipids, metabolites, and proteins for LC/MS-based analysis of a high-fat diet in mice 95%
- Quantifying acyl-chain diversity in isobaric compound lipids containing monomethyl branched-chain fatty acids 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.