| Literature DB >> 31093699 |
Justine Ferey1,2, Florent Marguet3,4, Annie Laquerrière3,4, Stéphane Marret3,5, Isabelle Schmitz-Afonso1, Soumeya Bekri2,3, Carlos Afonso1, Abdellah Tebani6,7.
Abstract
Ultra-high-resolution imaging mass spectrometry using matrix-assisted laser desorption ionization (MALDI) MS coupled to a Fourier transform ion cyclotron resonance (FTICR) mass analyzer is a powerful technique for the visualization of small molecule distribution within biological tissues. The FTICR MS provides ultra-high resolving power and mass accuracy that allows large molecular coverage and molecular formula assignments, both essential for untargeted metabolomics analysis. These performances require fine optimizations of the MALDI FTICR parameters. In this context, this study proposes a new strategy, using experimental design, for the optimization of ion transmission voltages and MALDI parameters, for tissue untargeted metabolomics analysis, in both positive and negative ionization modes. These experiments were conducted by assessing the effects of nine factors for ion transmission voltages and four factors for MALDI on the number of peaks, the weighted resolution, and the mean error within m/z 150-1000 mass range. For this purpose, fractional factorial designs were used with multiple linear regression (MLR) to evaluate factor effects and to optimize parameter values. The optimized values of ion transmission voltages (RF amplitude TOF, RF amplitude octopole, frequency transfer optic, RF frequency octopole, deflector plate, funnel 1, skimmer, funnel RF amplitude, time-of-flight, capillary exit), MALDI parameters (laser fluence, number of laser shots), and detection parameters (data size, number of scans) led to an increase of 32% and 18% of the number of peaks, an increase of 8% and 39% of the resolution, and a decrease of 56% and 34% of the mean error in positive and negative ionization modes, respectively. Graphical abstract.Keywords: Brain tissue; Chemometrics; Experimental design; Fourier transform ion cyclotron resonance; Mass spectrometry; Metabolomics
Mesh:
Year: 2019 PMID: 31093699 DOI: 10.1007/s00216-019-01863-6
Source DB: PubMed Journal: Anal Bioanal Chem ISSN: 1618-2642 Impact factor: 4.142