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Spatial Localization of Vitamin D Metabolites in Mouse Kidney by Mass Spectrometry Imaging

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Abstract

Vitamin D plays a key role in the maintenance of calcium/phosphate homeostasis and elicits biological effects that are relevant to immune function and metabolism. It is predominantly formed through UV exposure in the skin by conversion of 7-dehydrocholsterol (vitamin D3). The clinical biomarker, 25-hydroxyvitamin D (25-(OH)-D), is enzymatically generated in the liver with the active hormone 1,25-dihydroxyvitamin D then formed under classical endocrine control in the kidney. Vitamin D metabolites are measured in biomatrices by liquid chromatography-tandem mass spectrometry (LC-MS/MS). In LC-MS/MS, chemical derivatization (CD) approaches have been employed to achieve the desired limit of quantitation. Recently, matrix-assisted laser desorption/ionization (MALDI) has also been reported as an alternative method. However, these quantitative approaches do not offer any spatial information. Mass spectrometry imaging (MSI) has been proven to be a powerful tool to image the spatial distribution of molecules from the surface of biological tissue sections. On-tissue chemical derivatization (OTCD) enables MSI to image molecules with poor ionization efficiently. In this technical report, several derivatization reagents and OTCD methods were evaluated using different MSI ionization techniques. Here, a method for detection and spatial distribution of vitamin D metabolites in murine kidney tissue sections using an OTCD-MALDI-MSI platform is presented. Moreover, the suitability of using the Bruker ImagePrep for OTCD-based platforms has been demonstrated. Importantly, this method opens the door for expanding the range of other poor ionizable molecules that can be studied by OTCD-MSI by adapting existing CD methods.

Original languageEnglish
Pages (from-to)13430-13437
Number of pages8
JournalACS Omega
Volume5
Issue number22
Early online date27 May 2020
DOIs
Publication statusPublished (in print/issue) - 9 Jun 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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