Achiral and chiral targeted brain metabolomics in volume-limited samples: quest for broad coverage, sensitivity and throughput using chemical derivatization and miniaturized liquid chromatography tandem mass spectrometry.

Project Details

Description

To gain more information on all metabolites in the mouse brain
extracellular fluid and their role under physiological and
pathophysiological conditions, sensitive, selective and highthroughput LC-MS/MS methods that enable the quantification of a
broad range of neurochemicals are needed. Moreover, stereospecific
analysis of chiral amino and hydroxy acids is important as also the
minor enantiomers have been shown to possess important roles in
the brain. In this project, two miniaturized LC-MS/MS methods, one
achiral and one chiral, will therefore be developed allowing the
sensitive quantification of a large panel of brain metabolites in
volume-limited microdialysis samples. Chemical derivatization of the
analytes is a promising method to enable the sensitive analysis in a
low volume biological sample of a broad range of metabolites with
distinct physicochemical properties in one run. For both methods the
derivatization reaction, the inclusion of isotope-coded derivatization
to obtain an internal standard for all compounds, the LC and mass
spectrometry parameters will be optimized using a systematic
method optimization approach. Both methods will be applied to study
fluctuations in metabolite profiles in brain microdialysis samples upon
chemogenetic modulation of astrocytes in a mouse model for
epilepsy. As these studies result in complex multivariate data sets,
chemometric tools will be used to extract relevant information.
AcronymFWOAL1076
StatusActive
Effective start/end date1/01/2331/12/26

Keywords

  • Achiral and chiral targeted brain metabolomics
  • Sensitive analysis in volume-limited biological samples
  • Chemical derivatization including isotope-coded derivatization

Flemish discipline codes in use since 2023

  • Analytical separation and detection techniques
  • Small molecules
  • Biomarker discovery
  • Chemometrics

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