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

[Image: see text] 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 el...

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Detalles Bibliográficos
Autores principales: Knolhoff, Ann M., Nautiyal, Katherine M., Nemes, Peter, Kalachikov, Sergey, Morozova, Irina, Silver, Rae, Sweedler, Jonathan V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2013
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3605826/
https://www.ncbi.nlm.nih.gov/pubmed/23409944
http://dx.doi.org/10.1021/ac3032959
Descripción
Sumario:[Image: see text] 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, C57BL/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 C57BL/6 Kit(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.