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Oversampling To Improve Spatial Resolution for Liquid Extraction Mass Spectrometry Imaging
Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - BMC, Analytical Chemistry.
Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - BMC, Analytical Chemistry.
2018 (English)In: Analytical Chemistry, ISSN 0003-2700, E-ISSN 1520-6882, Vol. 90, no 4, p. 2451-2455Article in journal (Refereed) Published
Abstract [en]

Liquid extraction mass spectrometry imaging (MSI) experiments provide users with direct analysis of biological surfaces with minimal sample preparation. Until now, much of the effort to increase spatial resolution for MSI with liquid extraction techniques has focused on reducing the size of the sampling area. However, this can be experimentally challenging. Here, we present oversampling as a simple alternative to increase the spatial resolution using nanospray desorption electrospray ionization (nano-DESI) MSI. By imaging partial rat spinal cord tissue sections, two major concerns with oversampling are addressed: whether endogenous molecules are significantly depleted from repeated sampling events and whether analytes are redistributed as a result of oversampling. In depth examination of ion images for representative analytes show that depletion and redistribution do not affect analyte localization in the tissue sample. Nano-DESI MSI experiments using three times oversampling provided higher spatial resolution, allowing the observation of features not visible with undersampling. Although proper care must be taken to ensure that oversampling will work in specific applications, we envision oversampling as a simple approach to increase image quality for liquid extraction MSI techniques.

Place, publisher, year, edition, pages
AMER CHEMICAL SOC , 2018. Vol. 90, no 4, p. 2451-2455
National Category
Analytical Chemistry
Identifiers
URN: urn:nbn:se:uu:diva-348995DOI: 10.1021/acs.analchem.7b04687ISI: 000426143100011PubMedID: 29373011OAI: oai:DiVA.org:uu-348995DiVA, id: diva2:1199068
Funder
Swedish Research Council, VR 621-2013-4231Swedish Foundation for Strategic Research , SSF ICA-6Available from: 2018-04-19 Created: 2018-04-19 Last updated: 2018-04-19Bibliographically approved

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Duncan, Kyle D.Lanekoff, Ingela

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