Abstract

Neurochemical monitoring using targeted and untargeted metabolomic approaches can provide unique insights into changes in brain chemistry that occur normally, in response to pathology, and after therapeutic intervention. This study used an established untargeted metabolomics method (Anal. Chem., 82:3212, 2010) to identify known and unknown brain metabolites by means of ultra‐performance liquid chromatography coupled with high‐resolution mass spectrometry (UPLC‐HRMS) on an Exactive Plus Orbitrap Instrument (Thermo Fisher Scientific). To date, analyses have been performed on microdialysis samples (n=408) obtained from FrA and M1 of intact, behaving B6 mice (n=5). Microdialysis samples were collected in conformance with the FASEB Statement of Principles for the use of animals in research during electroencephalographically confirmed intervals of extended wakefulness, recovery sleep, and subsequent extended wakefulness. Partial least squares discriminant analyses showed reliable and statistically significant state‐dependent clustering of metabolites. In addition to identifying approximately 20 known molecules, analyses revealed consistent associations with the first wakefulness period (acetoacetate and lactate), sleep (valine and leucine/isoleucine), and the second wakefulness period (pyruvate and tyrosine). The results also provided a list of unidentified spectral features in FrA (n=33) and M1 (n=43) that are being subjected to additional analyses using the metabolite databases (https://metlin.scripps.edu/index.php and http://www.hmdb.ca). These spectral features may ultimately lead to the discovery of novel molecules not previously known to be associated with states of sleep and wakefulness. By integrating the dynamic sampling tool of microdialysis with the unparalleled capabilities of UPLC‐HRMS, these studies are identifying and quantifying state‐dependent and region‐specific changes in mouse brain metabolome.Support or Funding InformationNIH grants HL65252 (RL and HAB); MH099231 and 1P01NS083514 (CC and GT); and support from the UT Joint Institute for Biological Sciences.

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