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Improved Spatial Resolution of Metabolites in Tissue Biopsies Using High-Resolution Magic-Angle-Spinning Slice Localization NMR Spectroscopy
Author(s) -
Elisabeth V. Vonhof,
Martial Piotto,
Elaine Holmes,
John C. Lindon,
Jeremy K. Nicholson,
Jia V. Li
Publication year - 2020
Publication title -
analytical chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.117
H-Index - 332
eISSN - 1520-6882
pISSN - 0003-2700
DOI - 10.1021/acs.analchem.0c02377
Subject(s) - chemistry , nuclear magnetic resonance spectroscopy , medulla , magic angle spinning , cortex (anatomy) , renal cortex , metabolite , spectroscopy , nuclear magnetic resonance , proton nmr , renal medulla , kidney , anatomy , biochemistry , medicine , stereochemistry , biology , physics , quantum mechanics , neuroscience
High-resolution magic-angle-spinning 1 H NMR spectroscopy (HR-MAS NMR) is a well-established technique for assessing the biochemical composition of intact tissue samples. In this study, we utilized a method based on HR-MAS NMR spectroscopy with slice localization (SLS) to achieve spatial resolution of metabolites. The obtained 7 slice spectra from each of the model samples (i.e., chicken thigh muscle with skin and murine renal biopsy including medulla (M) and cortex (C)) showed distinct metabolite compositions. Furthermore, we analyzed previously acquired 1 H HR-MAS NMR spectra of separated cortex and medulla samples using multivariate statistical methods. Concentrations of glycerophosphocholine (GPC) were found to be significantly higher in the renal medulla compared to the cortex. Using GPC as a biomarker, we identified the tissue slices that were predominantly the cortex or medulla. This study demonstrates that HR-MAS SLS combined with multivariate statistics has the potential for identifying tissue heterogeneity and detailed biochemical characterization of complex tissue samples.

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