Matrix‐assisted laser desorption/ionization matrix incorporation evaluation algorithm for improved peak coverage and signal‐to‐noise ratio in mass spectrometry imaging
Rationale Despite decades of implementation, the selection of optimal sample preparation conditions for matrix‐assisted laser desorption/ionization (MALDI) imaging is still ambiguous due to the lack of a universal and comprehensive evaluation methodology. Thus, numerous experiments with different ma...
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Published in | Rapid communications in mass spectrometry Vol. 38; no. 15; pp. e9830 - n/a |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
Wiley Subscription Services, Inc
15.08.2024
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Subjects | |
Online Access | Get full text |
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Summary: | Rationale
Despite decades of implementation, the selection of optimal sample preparation conditions for matrix‐assisted laser desorption/ionization (MALDI) imaging is still ambiguous due to the lack of a universal and comprehensive evaluation methodology. Thus, numerous experiments with different matrix application conditions accompany a translation of the method to novel sample types and matrices.
Methods
Mouse brain tissues were covered with 9‐aminoacridine through sublimation, followed by recrystallization in vapors of 5% (v/v) methanol solution in water. The samples were analyzed by MALDI time‐of‐flight mass spectrometry, and the efficiency of lipid and small‐molecule ionization was evaluated with different metrics.
Results
We first investigate the dependency of matrix density and recrystallization conditions on the thickness of an analyte‐empty matrix layer to roughly evaluate the laser shot number required to obtain an intense signal with minimal noise. Then, we introduce metrics for the analysis of small imaging datasets (small sample regions) of model samples based on median quantity of peaks in spectra (medQP) and weighted median signal‐to‐noise ratio (wmSNR). The evaluation of small regions and taking median values for metrics help overcome the sample heterogeneity and allow for the simultaneous comparison of different acquisition parameters.
Conclusions
Here, we propose a methodology based on gradual laser ablation of small regions of sample and further implementation of weighted signal‐to‐noise ratio to assess various matrix application conditions. The proposed approach helps reduce the number of test samples required to determine optimal sample preparation conditions and improve the overall quality of images. |
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Bibliography: | Funding information Andrey A. Kuzin and Daniil I. Sobolev contributed equally. The work was supported by the Ministry of Science and Higher Education of the Russian Federation (agreement no. 075‐03‐2022‐107, project no. 0714‐2020‐0006). ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0951-4198 1097-0231 |
DOI: | 10.1002/rcm.9830 |