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Issue 11, 2020
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Mass spectrometry imaging of thin-layer chromatography plates using laser desorption/low-temperature plasma ionisation

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Abstract

Thin-layer chromatography (TLC) is a classic method for the separation and analysis of complex mixtures. Biological assays, chemical derivatisation and spectroscopy techniques are compatible with TLC and provide extra information about isolated compounds. However, coupling TLC to mass spectrometry is hampered by the difficulty to desorb the analytes from the silica surfaces. In this study, we used a multimodal ion source for laser desorption (LD) and low-temperature plasma (LTP) post-ionisation. Efficient desorption was reached by covering the TLC plates with activated carbon. Regions of interest can be analysed by spots, by lines or by area. We show the separation of methylxanthines from coffee, tea and cocoa preparations by TLC, with subsequent mass spectrometry imaging (MSI). Using a lateral resolution of 400 μm × 400 μm, allowed the acquisition of 21 895 spectra in 2.4 h (2.5 pixels per s). Further, we demonstrate the possibility of direct mass fragmentation studies and quantification. We mounted the system on an Open LabBot with a theoretical lateral resolution of 12.5 μm and performed the visualisation of ions of interest and the pixel-wise review of mass spectra with our free software RmsiGUI (https://bitbucket.org/lababi/rmsigui). This non-proprietary and modular platform enables the cost-efficient adaption of the system and further development by the community.

Graphical abstract: Mass spectrometry imaging of thin-layer chromatography plates using laser desorption/low-temperature plasma ionisation

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Article information


Submitted
03 Mar 2020
Accepted
01 Apr 2020
First published
07 Apr 2020

Analyst, 2020,145, 3885-3891
Article type
Paper

Mass spectrometry imaging of thin-layer chromatography plates using laser desorption/low-temperature plasma ionisation

N. S. García-Rojas, A. Moreno-Pedraza, I. Rosas-Román, E. Ramírez-Chávez, J. Molina-Torres and R. Winkler, Analyst, 2020, 145, 3885
DOI: 10.1039/D0AN00446D

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