Source attribution profiling of five species of Amanita mushrooms from four European countries by high resolution liquid chromatography-mass spectrometry combined with multivariate statistical analysis and DNA-barcoding
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Updated: Feb 10, 2026

Semi-Quantitative Analysis of Peptidoglycan by Liquid Chromatography Mass Spectrometry and Bioinformatics
Published on: October 13, 2020
Daniel Jansson1, Arthur Wolterink2, Leonie Bergwerff2
1Swedish Defence Research Agency, FOI CBRN Defence and Security, SE-901 82 Umeå, Sweden.
Abstract:
Source attribution profiling of five species of Amanita mushrooms from four European countries was performed using Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS) combined with multivariate statistical analysis. Initially, species determination was carried out morphologically and was verified by DNA-analysis. This data was then combined with chemical profiling, generated from LC-HRMS full scan analysis. The untargeted data was processed and the 720 most abundant peaks in the LC-HRMS chromatogram were used to build a multivariate PLS-DA model. The two independent methods for species determination showed 100% correlation, indicating the potential use of chemical profiling as a supporting technique to genetic methods. When specimens of one species were studied, significant variation related to the region of growth was found. The potential of the geo-positioning was shown for A. phalloides from Sweden, Denmark and UK and A. virosa from Sweden and Denmark. Additionally, A. virosa specimens could be attributed to three geographically different regions of Sweden.
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