4‑Phenyl-α-cyanocinnamic Acid Amide: Screening for a Negative Ion Matrix for MALDI-MS Imaging of Multiple Lipid Classes

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) has become a method of choice in lipid analysis, as it provides localization information for defined lipids that is not readily accessible with nonmass spectrometric methods. Most current MALDI matrices have been found...

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Bibliographic Details
Published in:Analytical chemistry (Washington) Vol. 85; no. 19; pp. 9156 - 9163
Main Authors: Fülöp, Annabelle, Porada, Martina B, Marsching, Christian, Blott, Henning, Meyer, Björn, Tambe, Suparna, Sandhoff, Roger, Junker, Hans-Dieter, Hopf, Carsten
Format: Journal Article
Language:English
Published: United States American Chemical Society 01-10-2013
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Summary:Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) has become a method of choice in lipid analysis, as it provides localization information for defined lipids that is not readily accessible with nonmass spectrometric methods. Most current MALDI matrices have been found empirically. Nevertheless, preferential matrix properties for many analyte classes are poorly understood and may differ between lipid classes. We used rational matrix design and semiautomated screening for the discovery of new matrices suitable for MALDI-IMS of lipids. Utilizing Smartbeam- and nitrogen lasers for MALDI, we systematically compared doubly substituted α-cyanocinnamic acid derivatives (R1-CCA-R2) with respect to their ability to serve as negative ion matrix for various brain lipids. We identified 4-phenyl-α-cyanocinnamic acid amide (Ph-CCA-NH2) as a novel negative ion matrix that enables analysis and imaging of various lipid classes by MALDI-MS. We demonstrate that Ph-CCA-NH2 displays superior sensitivity and reproducibility compared to matrices commonly employed for lipids. A relatively small number of background peaks and good matrix suppression effect could make Ph-CCA-NH2 a widely applicable tool for lipid analysis.
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ISSN:0003-2700
1520-6882
DOI:10.1021/ac4018154