期刊
ANALYTICAL CHEMISTRY
卷 85, 期 6, 页码 3136-3143出版社
AMER CHEMICAL SOC
DOI: 10.1021/ac3032959
关键词
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资金
- National Institute on Drug Abuse [P30 DA081310]
- National Institute of Dental and Craniofacial Research [5R01 DE018866]
- Office of Director, National Institutes of Health
- NIH [F31 MH084384]
- National Science Foundation [IOS 05-54514]
- National Institute of Mental Health [R21 MH 067782]
- NIH National Center for Research Resources [RR018522]
- W.R. Wiley Environmental Molecular Science Laboratory
- U.S. Department of Energy's Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory
- Battelle Memorial Institute for the U.S. Department of Energy [DE-AC05-76RL0 1830]
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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