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Untargeted Metabolomics Sheds Light on the Diversity of Major Classes of Secondary Metabolites in the Malpighiaceae Botanical Family
Natural products produced by plants are one of the most investigated natural sources, which substantially contributed to the development of the natural products field. Even though these compounds are widely explored, the literature still lacks comprehensive investigations aiming to explore the evolu...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9047359/ https://www.ncbi.nlm.nih.gov/pubmed/35498703 http://dx.doi.org/10.3389/fpls.2022.854842 |
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author | Mannochio-Russo, Helena de Almeida, Rafael F. Nunes, Wilhan D. G. Bueno, Paula C. P. Caraballo-Rodríguez, Andrés M. Bauermeister, Anelize Dorrestein, Pieter C. Bolzani, Vanderlan S. |
author_facet | Mannochio-Russo, Helena de Almeida, Rafael F. Nunes, Wilhan D. G. Bueno, Paula C. P. Caraballo-Rodríguez, Andrés M. Bauermeister, Anelize Dorrestein, Pieter C. Bolzani, Vanderlan S. |
author_sort | Mannochio-Russo, Helena |
collection | PubMed |
description | Natural products produced by plants are one of the most investigated natural sources, which substantially contributed to the development of the natural products field. Even though these compounds are widely explored, the literature still lacks comprehensive investigations aiming to explore the evolution of secondary metabolites produced by plants, especially if classical methodologies are employed. The development of sensitive hyphenated techniques and computational tools for data processing has enabled the study of large datasets, being valuable assets for chemosystematic studies. Here, we describe a strategy for chemotaxonomic investigations using the Malpighiaceae botanical family as a model. Our workflow was based on MS/MS untargeted metabolomics, spectral searches, and recently described in silico classification tools, which were mapped into the latest molecular phylogeny accepted for this family. The metabolomic analysis revealed that different ionization modes and extraction protocols significantly impacted the chemical profiles, influencing the chemotaxonomic results. Spectral searches within public databases revealed several clades or genera-specific molecular families, being potential chemical markers for these taxa, while the in silico classification tools were able to expand the Malpighiaceae chemical space. The classes putatively annotated were used for ancestral character reconstructions, which recovered several classes of metabolites as homoplasies (i.e., non-exclusive) or synapomorphies (i.e., exclusive) for all sampled clades and genera. Our workflow combines several approaches to perform a comprehensive evolutionary chemical study. We expect it to be used on further chemotaxonomic investigations to expand chemical knowledge and reveal biological insights for compounds classes in different biological groups. |
format | Online Article Text |
id | pubmed-9047359 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90473592022-04-29 Untargeted Metabolomics Sheds Light on the Diversity of Major Classes of Secondary Metabolites in the Malpighiaceae Botanical Family Mannochio-Russo, Helena de Almeida, Rafael F. Nunes, Wilhan D. G. Bueno, Paula C. P. Caraballo-Rodríguez, Andrés M. Bauermeister, Anelize Dorrestein, Pieter C. Bolzani, Vanderlan S. Front Plant Sci Plant Science Natural products produced by plants are one of the most investigated natural sources, which substantially contributed to the development of the natural products field. Even though these compounds are widely explored, the literature still lacks comprehensive investigations aiming to explore the evolution of secondary metabolites produced by plants, especially if classical methodologies are employed. The development of sensitive hyphenated techniques and computational tools for data processing has enabled the study of large datasets, being valuable assets for chemosystematic studies. Here, we describe a strategy for chemotaxonomic investigations using the Malpighiaceae botanical family as a model. Our workflow was based on MS/MS untargeted metabolomics, spectral searches, and recently described in silico classification tools, which were mapped into the latest molecular phylogeny accepted for this family. The metabolomic analysis revealed that different ionization modes and extraction protocols significantly impacted the chemical profiles, influencing the chemotaxonomic results. Spectral searches within public databases revealed several clades or genera-specific molecular families, being potential chemical markers for these taxa, while the in silico classification tools were able to expand the Malpighiaceae chemical space. The classes putatively annotated were used for ancestral character reconstructions, which recovered several classes of metabolites as homoplasies (i.e., non-exclusive) or synapomorphies (i.e., exclusive) for all sampled clades and genera. Our workflow combines several approaches to perform a comprehensive evolutionary chemical study. We expect it to be used on further chemotaxonomic investigations to expand chemical knowledge and reveal biological insights for compounds classes in different biological groups. Frontiers Media S.A. 2022-04-14 /pmc/articles/PMC9047359/ /pubmed/35498703 http://dx.doi.org/10.3389/fpls.2022.854842 Text en Copyright © 2022 Mannochio-Russo, de Almeida, Nunes, Bueno, Caraballo-Rodríguez, Bauermeister, Dorrestein and Bolzani. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Mannochio-Russo, Helena de Almeida, Rafael F. Nunes, Wilhan D. G. Bueno, Paula C. P. Caraballo-Rodríguez, Andrés M. Bauermeister, Anelize Dorrestein, Pieter C. Bolzani, Vanderlan S. Untargeted Metabolomics Sheds Light on the Diversity of Major Classes of Secondary Metabolites in the Malpighiaceae Botanical Family |
title | Untargeted Metabolomics Sheds Light on the Diversity of Major Classes of Secondary Metabolites in the Malpighiaceae Botanical Family |
title_full | Untargeted Metabolomics Sheds Light on the Diversity of Major Classes of Secondary Metabolites in the Malpighiaceae Botanical Family |
title_fullStr | Untargeted Metabolomics Sheds Light on the Diversity of Major Classes of Secondary Metabolites in the Malpighiaceae Botanical Family |
title_full_unstemmed | Untargeted Metabolomics Sheds Light on the Diversity of Major Classes of Secondary Metabolites in the Malpighiaceae Botanical Family |
title_short | Untargeted Metabolomics Sheds Light on the Diversity of Major Classes of Secondary Metabolites in the Malpighiaceae Botanical Family |
title_sort | untargeted metabolomics sheds light on the diversity of major classes of secondary metabolites in the malpighiaceae botanical family |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9047359/ https://www.ncbi.nlm.nih.gov/pubmed/35498703 http://dx.doi.org/10.3389/fpls.2022.854842 |
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