Acquisition of the depth profiles and reproducible mass spectra in matrix-assisted laser desorption/ionization of inhomogeneous samples

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Title
Acquisition of the depth profiles and reproducible mass spectra in matrix-assisted laser desorption/ionization of inhomogeneous samples
Author(s)
S H Ahn; K M Park; Jeong Hee Moon; S H Lee; M S Kim
Bibliographic Citation
Rapid Communications in Mass Spectrometry, vol. 29, no. 8, pp. 745-752
Publication Year
2015
Abstract
Rationale In our previous analysis of the matrix-assisted laser desorption/ionization (MALDI) spectra of peptides, we treated their depth profiles in solid samples as homogeneous. Here, we wanted to determine if the reproducible MALDI spectra and linear calibration curves reported previously would be obtained even when the depth profiles were inhomogeneous. Methods We derived a formula relating shot-number-dependent ion abundance data in temperature-controlled MALDI with the analyte depth profile in a solid sample. We prepared samples containing peptides, amino acids, and serotonin in α-cyano-4-hydroxycinnamic acid matrix by vacuum-drying and micro-spotting methods, recorded their MALDI spectra, and analyzed them with the aforementioned formula. Results For the samples prepared by vacuum-drying, the analyte depth profiles were inhomogeneous and maximized at the sample surface. Although the MALDI spectra changed as the shot continued, their sum over the entire set of spectra acquired from a spot was reproducible. Similarly, a high-quality calibration curve could be obtained with the spectral data summed over the entire set. Depth profiles were homogeneous for samples prepared by micro-spotting. Conclusions A method has been developed to obtain a reproducible MALDI spectrum and a linear calibration curve for an analyte with an inhomogeneous depth profile in a solid sample.
ISSN
0951-4198
Publisher
Wiley
DOI
http://dx.doi.org/10.1002/rcm.7157
Type
Article
Appears in Collections:
Division of Bio Technology Innovation > Core Research Facility & Analysis Center > 1. Journal Articles
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