Optimization of sample preparation and LC-MS analysis for high throughput untargeted lipidomics and metabolomics

Authors

• D Bennouna
• HAS Chatelaine
• K Mehta
• A Tisch
• C Beecher
• CA LeClair
• EA Mathé

Abstract

Developing a high-throughput metabolomics/ lipidomics workflow is crucial for improving data quality and reliability. By automating sample extraction and optimizing LC-MS conditions, Our goal was to minimize extraction time and human error through automated pipetting using robots and short LC-MS separation methods, ultimately enhancing signal intensities and accelerating sample analysis.
biphasic extraction protocol was first optimized manually using 20 uL of plasma before automation on 384 well plates, starting with 9 wells. The Automated protocol was carried out using an automated liquid handler with a 384ST head (Bravo, Agilent), and involved protein precipitation, lipid extraction, solvent polarity switching, and polar phase collection. Using native and labeled polar and apolar compounds, LC-MS methods for metabolomics and lipidomics were developed on short C8 and HILIC columns with 4 minutes and 5 minutes run time, respectively. The optimization of these LC-MS methods was performed on an Agilent QTOF in both positive and negative modes.
The optimized LC-MS gradient on a C8 column effectively separated major lipid classes like omega 3,6,9-fatty acids, lysophospholipids, sterols, phospholipids, ceramides, sphingomyelins, and triglycerides, reducing the separation time from 13 minutes to 2 minutes while maintaining original elution orders. The HILIC-based metabolomics LC-MS method also successfully separated polar compounds involved in key metabolic pathways such as purines, amino acids, indoles, and vitamins. Our automated biphasic extraction protocol on 384-well plates demonstrated strong reproducibility and efficiency in processing nine plasma samples. Our high-throughput approach will offer a quick and robust platform for translational research on metabolic dysregulations and biomarker discovery.

Scientific Focus Area: Molecular Biology and Biochemistry

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