Systematic evaluation of repeatability of IR-MALDESI-MS and normalization strategies for correcting the analytical variation and improving image quality

Abstract

Mass spectrometry imaging is a powerful tool widely used in biological, clinical, and forensic research, but its often poor repeatability limits its application for quantitative and large-scale analysis. A systematic evaluation of infrared matrix-assisted laser desorption electrospray ionization mass spectrometry (IR-MALDESI-MS) repeatability in absolute ion abundances during short- and long-term experiments was carried out on liver slices from the same rat with minimal biological variability to be expected. Results of median %RSDs ranging from 14 to 45, pooled %RMADs ranging from 11 to 33, and Pearson correlation coefficients ranging from 0.83 to 1.00 demonstrated an acceptable repeatability of IR-MALDESI-MS. Normalization is commonly applied for the purpose of accounting for analytical variability of spectra generated from different runs so as to reveal real biological differences. Nine data normalization strategies were performed on the rat liver data sets to examine their effects on reducing analytical variation, and further on a hen ovary data set containing more morphological features for the investigation of their impact on ion images. Results demonstrated that the majority of normalization approaches benefit data quality to some extent, and local normalization methods significantly outperform their global counterparts, resulting in a reduction of median %RSD up to 22. Local median normalization was found to be promisingly robust for both homogeneous and heterogeneous samples.