Untargeted In Silico Compound Classification—A Novel Metabolomics Method to Assess the Chemodiversity in Bryophytes

Peters, Kristian; Balcke, Gerd Ulrich; Kleinenkuhnen, Niklas; Treutler, Hendrik; Neumann, Steffen

doi:10.3390/ijms22063251

Cited by 12 publications

(10 citation statements)

References 113 publications

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“…We also found many unique flavonoid glycosides and hydroxylated flavonoids in the Riccia profiles, which is in contrast to Marchantia spp. and Lunularia spp., which contain many unique stilbenes and (neo)lignans such as bisbibenzyls [ 27 ].…”

Section: Discussionmentioning

confidence: 99%

“…The annotation of untargeted LC/MS-MS data is still a complex task, as the natural product chemistry of bryophytes is not well known, and as a result, spectral libraries such as MassBank, GNPS, WeizMass, or Lotus only contain a few reference structures [ 24 , 38 , 60 , 61 ]. In order to unequivocally identify compounds, either authentic standards or additional elaborate analytical methods such as NMR are necessary [ 27 ]. However, in order to devise chemophenetic markers, we find that an annotation at the class level is sufficient to characterize the distinct Riccia taxa.…”

Section: Discussionmentioning

confidence: 99%

“…Recent analytical and computational developments in mass spectrometry (MS) allow for the capture of nearly all low-molecular semi-polar molecules in biological species [ 27 ]. Untargeted LC/MS-MS techniques including Data Dependent Acquisition (DDA) coupled to in silico fragmentation tools like MetFrag [ 28 ] and machine-learning tools like SIRIUS [ 29 ] now allow for the acquisition, computational annotation, and classification of the majority of acquired molecules.…”

Section: Introductionmentioning

confidence: 99%

“…Untargeted LC/MS-MS techniques including Data Dependent Acquisition (DDA) coupled to in silico fragmentation tools like MetFrag [ 28 ] and machine-learning tools like SIRIUS [ 29 ] now allow for the acquisition, computational annotation, and classification of the majority of acquired molecules. This greatly facilitates the identification of biomarkers and compound classes that distinctly describe species [ 27 , 30 ] and provides insights into the rate of chemical evolution and diversification [ 31 ], and thus may resolve the phylogeny of difficult taxonomical groups and cryptic species [ 13 ]. Therefore, untargeted metabolomics can contribute to a more ecological representation of plant systematics and the classification of certain taxa [ 13 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

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Untargeted Metabolomics for Integrative Taxonomy: Metabolomics, DNA Marker-Based Sequencing, and Phenotype Bioimaging

Peters

Blatt-Janmaat

Tkach

et al. 2023

Plants

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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 high-resolution 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.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Untargeted Metabolomics for Integrative Taxonomy: Metabolomics, DNA Marker-Based Sequencing, and Phenotype Bioimaging

Peters

Blatt-Janmaat

Tkach

et al. 2023

Plants

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“…Sample separation was visualized by conducting Principal Component Analyses (PCA) using the prcomp function. PLS analysis was conducted to select those variables that are most different between the samples [ 43 ].…”

Section: Methodsmentioning

confidence: 99%

Host Tree and Geography Induce Metabolic Shifts in the Epiphytic Liverwort Radula complanata

Blatt-Janmaat

Neumann

Ziegler

et al. 2023

Plants

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Bryophytes are prolific producers of unique, specialized metabolites that are not found in other plants. As many of these unique natural products are potentially interesting, for example, pharmacological use, variations in the production regarding ecological or environmental conditions have not often been investigated. Here, we investigate metabolic shifts in the epiphytic Radula complanata L. (Dumort) with regard to different environmental conditions and the type of phorophyte (host tree). Plant material was harvested from three different locations in Sweden, Germany, and Canada and subjected to untargeted liquid chromatography high-resolution mass-spectrometry (UPLC/ESI-QTOF-MS) and data-dependent acquisition (DDA-MS). Using multivariate statistics, variable selection methods, in silico compound identification, and compound classification, a large amount of variation (39%) in the metabolite profiles was attributed to the type of host tree and 25% to differences in environmental conditions. We identified 55 compounds to vary significantly depending on the host tree (36 on the family level) and 23 compounds to characterize R. complanata in different environments. Taken together, we found metabolic shifts mainly in primary metabolites that were associated with the drought response to different humidity levels. The metabolic shifts were highly specific to the host tree, including mostly specialized metabolites suggesting high levels of ecological interaction. As R. complanata is a widely distributed generalist species, we found it to flexibly adapt its metabolome according to different conditions. We found metabolic composition to also mirror the constitution of the habitat, which makes it interesting for conservation measures.

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Understanding the chemodiversity of plants: Quantification, variation and ecological function

Petrén,

Anaia,

Aragam

et al. 2024

Ecological Monographs

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Plants produce a great number of phytochemicals serving a variety of different functions. Recently, the chemodiversity of these compounds (i.e., the diversity of compounds produced by a plant) has been suggested to be an important aspect of the plant phenotype that may shape interactions between plants, their environment, and other organisms. However, we lack an agreement on how to quantify chemodiversity, which complicates conclusions about the functional importance of it. Here, we discuss how chemodiversity (deconstructed into components of richness, evenness and disparity) may relate to different ecologically relevant aspects of the phenotype. Then, we systematically review the literature on chemodiversity to examine methodological practices, explore patterns of variability in diversity across different levels of biological organization, and investigate the functional role of this diversity in interactions between plants and other organisms. Overall, the reviewed literature suggests that high chemodiversity is often beneficial for plants, although a heterogeneity of methodological approaches partly limits what general conclusions can be drawn. Importantly, to support future research on this topic, we provide a framework with a decision tree facilitating choices on which measures of chemodiversity are best used in different contexts and outline key questions and avenues for future research. A more thorough understanding of chemodiversity will provide insights into its evolution and functional role in ecological interactions between plants and their environment.

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Untargeted In Silico Compound Classification—A Novel Metabolomics Method to Assess the Chemodiversity in Bryophytes

Cited by 12 publications

References 113 publications

Untargeted Metabolomics for Integrative Taxonomy: Metabolomics, DNA Marker-Based Sequencing, and Phenotype Bioimaging

Untargeted Metabolomics for Integrative Taxonomy: Metabolomics, DNA Marker-Based Sequencing, and Phenotype Bioimaging

Host Tree and Geography Induce Metabolic Shifts in the Epiphytic Liverwort Radula complanata

Understanding the chemodiversity of plants: Quantification, variation and ecological function

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