Issue 14, 2014

Matrix effects in biological mass spectrometry imaging: identification and compensation

Abstract

Matrix effects in mass spectrometry imaging (MSI) may affect the observed molecular distribution in chemical and biological systems. In this study, we use mouse brain tissue of a middle cerebral artery occlusion (MCAO) stroke model to examine matrix effects in nanospray desorption electrospray ionization MSI (nano-DESI MSI). This is achieved by normalizing the intensity of the sodium and potassium adducts of endogenous phosphatidylcholine (PC) species to the intensity of the corresponding adduct of the PC standard supplied at a constant rate with the nano-DESI solvent. The use of MCAO model with an ischemic region localized to one hemisphere of the brain enables immediate comparison of matrix effects within one ion image. Furthermore, significant differences in sodium and potassium concentrations in the ischemic region in comparison with the healthy tissue allowed us to distinguish between two types of matrix effects. Specifically, we discuss matrix effects originating from variations in alkali metal concentrations and matrix effects originating from variations in the molecular composition of the tissue. Compensation for both types of matrix effects was achieved by normalizing the signals corresponding to endogenous PC to the signals of the standards. This approach, which does not introduce any complexity in sample preparation, efficiently compensates for signal variations resulting from differences in the local concentrations of sodium and potassium in tissue sections and from the complexity of the extracted analyte mixture derived from local variations in molecular composition.

Graphical abstract: Matrix effects in biological mass spectrometry imaging: identification and compensation

Supplementary files

Article information

Article type
Communication
Submitted
18 Mar 2014
Accepted
15 Apr 2014
First published
06 May 2014

Analyst, 2014,139, 3528-3532

Matrix effects in biological mass spectrometry imaging: identification and compensation

I. Lanekoff, S. L. Stevens, M. P. Stenzel-Poore and J. Laskin, Analyst, 2014, 139, 3528 DOI: 10.1039/C4AN00504J

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