LC-MS-Based Targeted Metabolomics for FACS-Purified Rare Cells.
Katharina SchönbergerMichael MittererKatharina GlaserManuel StecherSebastian HobitzDominik Schain-ZotaKonrad SchuldesTim LämmermannAngelika S RamboldNina Cabezas-WallscheidJoerg M BuescherPublished in: Analytical chemistry (2023)
Metabolism plays a fundamental role in regulating cellular functions and fate decisions. Liquid chromatography-mass spectrometry (LC-MS)-based targeted metabolomic approaches provide high-resolution insights into the metabolic state of a cell. However, the typical sample size is in the order of 10 5 -10 7 cells and thus not compatible with rare cell populations, especially in the case of a prior flow cytometry-based purification step. Here, we present a comprehensively optimized protocol for targeted metabolomics on rare cell types, such as hematopoietic stem cells and mast cells. Only 5000 cells per sample are required to detect up to 80 metabolites above background. The use of regular-flow liquid chromatography allows for robust data acquisition, and the omission of drying or chemical derivatization avoids potential sources of error. Cell-type-specific differences are preserved while the addition of internal standards, generation of relevant background control samples, and targeted metabolite with quantifiers and qualifiers ensure high data quality. This protocol could help numerous studies to gain thorough insights into cellular metabolic profiles and simultaneously reduce the number of laboratory animals and the time-consuming and costly experiments associated with rare cell-type purification.
Keyphrases
- mass spectrometry
- liquid chromatography
- induced apoptosis
- high resolution
- stem cells
- tandem mass spectrometry
- cell cycle arrest
- cell therapy
- high resolution mass spectrometry
- cancer therapy
- single cell
- flow cytometry
- randomized controlled trial
- high performance liquid chromatography
- gas chromatography
- ms ms
- oxidative stress
- signaling pathway
- electronic health record
- drug delivery
- mesenchymal stem cells
- ultra high performance liquid chromatography
- machine learning
- gas chromatography mass spectrometry
- risk assessment
- high speed