| 2013 — 2014 |
Rubakhin, Stanislav S.
Sweedler, Jonathan V. [⬀] |
R21Activity Code Description:
To encourage the development of new research activities in categorical program areas. (Support generally is restricted in level of support and in time.) |
Glia Classification Via Single Cell Metabolomics @ University of Illinois At Urbana-Champaign
DESCRIPTION (provided by applicant): Glia comprises the majority of the cells that make up the central nervous system. These cells are integral to maintaining normal cellular activity and have been implicated in the development of many pathological conditions. The functional, positional, and biochemical heterogeneities of neurons are crucial aspects in regulating a myriad of physiological activities within the larger neuronal context; glia likely have similar localized and individual cell diversity. Here we propose to develop a unique mass spectrometry (MS)-based toolset combined with imaging to facilitate the discovery of the metabolome of thousands of individual glia. A key objective is the multifaceted investigation of multiple individual glia isolated from three specific brain regions in mouse, the hippocampus, cerebellum and brainstem, followed by transcriptional biomarker-guided glia sub-type identification. The technology allows the same cell to be characterized by its morphology, metabolic profile, and distinctive transcriptomic expression profile. Integrative analyses of the resulting data enable a unique determination of the molecular basis for glia heterogeneity. We expect to uncover characteristic metabolite biomarkers and biomarker patterns for glia subtypes. Our armamentarium includes a variety of MS technologies, including secondary ion MS and matrix-assisted laser desorption/ionization MS, as well as in-situ hybridization guided cell identificatio. Besides tool development, glia from 4- and 56-day old C57BL/6J mice will be characterized, and the results correlated to data assembled in the Allen mouse brain atlas and referenced in the Neuroscience Information Framework. This study will also reveal age- related differences in glia heterogeneity. When unknown metabolites are detected, we will characterize them via off-line approaches such as capillary electrophoresis hyphenated to MS. This innovative integration of single cell MS characterization approaches provides the capability to target individual glial cells and characterize them. These efforts are well matched to the goals of RFA-HD-12-211 Tools to Enhance Studies of Glial Cell Development, Aging, Disease and Repair. The approaches are general and adaptable to a range of glial cell types. The data obtained and the technology suite created will be used by laboratories and research groups that engage in clinical diagnostic measurements, fundamental scientific investigations, and pharmaceutical discovery.
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