4.8 Article

Combining Small-Volume Metabolomic and Transcriptomic Approaches for Assessing Brain Chemistry

期刊

ANALYTICAL CHEMISTRY
卷 85, 期 6, 页码 3136-3143

出版社

AMER CHEMICAL SOC
DOI: 10.1021/ac3032959

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资金

  1. National Institute on Drug Abuse [P30 DA081310]
  2. National Institute of Dental and Craniofacial Research [5R01 DE018866]
  3. Office of Director, National Institutes of Health
  4. NIH [F31 MH084384]
  5. National Science Foundation [IOS 05-54514]
  6. National Institute of Mental Health [R21 MH 067782]
  7. NIH National Center for Research Resources [RR018522]
  8. W.R. Wiley Environmental Molecular Science Laboratory
  9. U.S. Department of Energy's Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory
  10. Battelle Memorial Institute for the U.S. Department of Energy [DE-AC05-76RL0 1830]

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The integration of disparate data types provides a more complete picture of complex biological systems. Here we combine small-volume metabolomic and transcriptomic platforms to determine subtle chemical changes and to link metabolites and genes to biochemical pathways. Capillary electrophoresis-mass spectrometry (CE-MS) and whole-genome gene expression arrays, aided by integrative pathway analysis, were utilized to survey metabolomic/transcriptomic hippocampal neurochemistry. We measured changes in individual hippocampi from the mast cell mutant mouse strain, CS7BL/6 Kit(W-sh/W-sh). These mice have a naturally occurring mutation in the white spotting locus that causes reduced c-Kit receptor expression and an inability of mast cells to differentiate from their hematopoietic progenitors. Compared with their littermates, the mast cell-deficient mice have profound deficits in spatial learning, memory, and neurogenesis. A total of 18 distinct metabolites were identified in the hippocampus that discriminated between the CS7BL/6 KitKit(W-sh/W-sh) and control mice. The combined analysis of metabolite and gene expression changes revealed a number of altered pathways. Importantly, results from both platforms indicated that multiple pathways are impacted, including amino acid metabolism, increasing the confidence in each approach. Because the CE-MS and expression profiling are both amenable to small-volume analysis, this integrated analysis is applicable to a range of volume-limited biological systems.

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