Please use this identifier to cite or link to this item: http://dx.doi.org/10.25673/102969
Title: Untargeted metabolomics for integrative taxonomy : metabolomics, DNA marker-based sequencing, and phenotype bioimaging
Author(s): Peters, KristianLook up in the Integrated Authority File of the German National Library
Blatt-Janmaat, Kaitlyn
Tkač, Natalʹja V.Look up in the Integrated Authority File of the German National Library
van Dam, Nicole M.Look up in the Integrated Authority File of the German National Library
Neumann, SteffenLook up in the Integrated Authority File of the German National Library
Issue Date: 2023
Type: Article
Language: English
Abstract: Integrative taxonomy is a fundamental part of biodiversity and combines traditional morphology with additional methods such as DNA sequencing or biochemistry. Here, we aim to establish untargeted metabolomics for use in chemotaxonomy. We used three thallose liverwort species Riccia glauca, R. sorocarpa, and R. warnstorfii (order Marchantiales, Ricciaceae) with Lunularia cruciata (order Marchantiales, Lunulariacea) as an outgroup. Liquid chromatography highresolution mass-spectrometry (UPLC/ESI-QTOF-MS) with data-dependent acquisition (DDA-MS) were integrated with DNA marker-based sequencing of the trnL-trnF region and high-resolution bioimaging. Our untargeted chemotaxonomy methodology enables us to distinguish taxa based on chemophenetic markers at different levels of complexity: (1) molecules, (2) compound classes, (3) compound superclasses, and (4) molecular descriptors. For the investigated Riccia species, we identified 71 chemophenetic markers at the molecular level, a characteristic composition in 21 compound classes, and 21 molecular descriptors largely indicating electron state, presence of chemical motifs, and hydrogen bonds. Our untargeted approach revealed many chemophenetic markers at different complexity levels that can provide more mechanistic insight into phylogenetic delimitation of species within a clade than genetic-based methods coupled with traditional morphology-based information. However, analytical and bioinformatics analysis methods still need to be better integrated to link the chemophenetic information at multiple scales.
URI: https://opendata.uni-halle.de//handle/1981185920/104922
http://dx.doi.org/10.25673/102969
Open Access: Open access publication
License: (CC BY 4.0) Creative Commons Attribution 4.0(CC BY 4.0) Creative Commons Attribution 4.0
Journal Title: Plants
Publisher: MDPI
Publisher Place: Basel
Volume: 12
Issue: 4
Original Publication: 10.3390/plants12040881
Appears in Collections:Open Access Publikationen der MLU

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