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

Abstract

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 KitW-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 KitW-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.

Role of Adult Hippocampal Neurogenesis in Cognition in Physiology and Disease: Pharmacological Targets and Biomarkers

“…Identification of hippocampal neurogenesis-specific biomarkers in blood or CSF could serve as a proxy for the rates of neurogenesis in the brain. Immature neuronal precursors in the adult brain are characterized by specific transcriptomes, cellular and membrane proteomes, secretomes, metabolomes, and lipidomes (Ramm et al 2009;Knolhoff et al 2013). Unbiased approaches to identify neurogenesisspecific transcriptomic profiles have led to the identification of several transcripts expressed during specific stages of adult neurogenesis (Miller et al 2013;Couillard-Despres et al 2006;Lim et al 2006).…”

Metabolic phenotyping and systems biology approaches to understanding neurological disorders

“…different “-omics”), which is commonly used in the field of metabolic diseases. A recent study used hierarchical clustering for the integration of metabolic and transcriptomic data to assess brain chemistry [36]; however, such an integrative approach has yet to be applied to neurological diseases. Such combined multi-omics platforms analysis should be developed using mouse models or clinical samples of neurological diseases to increase the confidence in disease prediction.…”

Review of the CE‐MS platform as a powerful alternative to conventional couplings in bio‐omics and target‐based applications

“…Samples from animal models (mice and rats) [116][117][118] or using human samples of patients [119][120][121][122][123][124][125][126] have been proposed. Samples from animal models (mice and rats) [116][117][118] or using human samples of patients [119][120][121][122][123][124][125][126] have been proposed.…”