Decoding Automation of Metabolite and Lipid Extraction Workflows

Technology improvements in liquid chromatography/mass spectrometry have enhanced the detection and identification of metabolites and lipids from complex biological samples. As metabolomics and lipidomics measurements become increasingly valued, there is a growing need to automate sample preparation workflows. Specifically, Agilent automation offers intuitive workflows that provide high data reproducibility and increased throughput while reducing hands-on time.
Here, we describe key learnings revealed during the automation of several workflows that extract metabolites and/or lipids from plasma and mammalian cell samples.
Learning Objectives:
- Learn about new Agilent Bravo workflows for automating metabolite and lipid extractions.
- Understand the essential steps in automated metabolite and lipid extraction workflows.
- Understand key automation developments for handling organic solvents, pipetting precipitates, employing filtration for solid phase extraction, and targeting high recovery from small samples.
Presenter: Genevieve Van de Bittner, Ph.D. (R&D Researcher, Agilent Research Laboratories, Agilent Technologies, Inc.)
Genevieve joined the Agilent Research Laboratories within Agilent Technologies in 2016 with a goal of improving technologies for metabolomic and metabolism measurements. Toward this goal, Genevieve has developed new sample preparation methods for LC/MS metabolomic and lipidomic analyses. These efforts have been informed by Genevieve’s training in chemical biology, specifically in the development of novel chemical probes to study biological systems. In her graduate work in Professor Chris Chang’s Lab at UC Berkeley, Genevieve created bioluminescent and fluorescent sensors for the in vivo measurement of reactive oxygen species and metal ions. This training led to a postdoctoral fellowship in Professor Jacob Hooker’s Lab at Harvard Medical School, during which Genevieve developed new radiotracers for imaging specific neuronal populations.
