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Metabolites
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Integration of Metabolomics with Other Omics Technologies to Investigate Metabolism...
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Integration of Metabolomics with Other Omics Technologies to Investigate Metabolism and Signaling in Plants

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Plant Metabolism".

Deadline for manuscript submissions: closed (15 August 2021) | Viewed by 11624

Special Issue Editors

Prof. Dr. Harro J. Bouwmeester

E-Mail Website
Guest Editor
Faculty of Science, University of Amsterdam, 1012 WX Amsterdam, The Netherlands
Interests: rhizosphere signalling; strigolactones; terpenoid metabolism
Dr. Lemeng Dong

E-Mail Website
Guest Editor
Faculty of Science, University of Amsterdam, 1012 WX Amsterdam, The Netherlands
Interests: plant metabolism; metabolomics; plant-nematode-microbe interaction; stress biology; metabolic engineering
Prof. Dr. Asaph Aharoni

E-Mail Website
Guest Editor
Weizmann Institute of Science, Rehovot, Israel
Interests: plant secondary metabolites; small molecules as mediators of plant interactions and systemic signaling; metabolic pathways discovery and engineering

Special Issue Information

Dear Colleagues,

Plants constantly adapt their metabolism and signaling to survive in a highly dynamic environment. In the past few years, the integration of metabolomics and other omics technologies such as genomics, transcriptomics, proteomics, metagenomics, and metatranscriptomics has accelerated our understanding of plant metabolism and plant signaling and their role in the interaction between plants and their (a)biotic environment. This Special Issue will focus on the integration of omics technologies to elucidate metabolite biosynthesis, perception, and transport and their role in signaling within a plant and between plants and other organisms in their environment. In addition, discoveries made through the integration of omics technologies have promoted applications in the fields of biotechnology and synthetic biology. We would like to invite researchers employing metabolomics in conjunction with other (omics) tools to contribute papers on hormone metabolism and signaling in plants, systemic and local signal responses to biotic and abiotic stresses, stress-induced metabolic reprogramming, chemical communication between plants and other organisms, molecular farming, food quality improvement, and agricultural and pharmaceutical applications.

Prof. Dr. Harro J. Bouwmeester
Dr. Lemeng Dong
Prof. Dr. Asaph Aharoni
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metabolites is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Plant metabolism
  • Signaling
  • Metabolomics
  • Genomics, transcriptomics
  • Abiotic and biotic stress
  • Synthetic biology
  • Proteomics

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Published Papers (3 papers)

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Research

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17 pages, 4272 KiB  
Article
A Combination of Metabolomics and Machine Learning Results in the Identification of a New Cyst Nematode Hatching Factor
by Lieke E. Vlaar, Benjamin Thiombiano, Davar Abedini, Mario Schilder, Yuting Yang and Lemeng Dong
Metabolites 2022, 12(6), 551; https://doi.org/10.3390/metabo12060551 - 16 Jun 2022
Cited by 6 | Viewed by 3203
Abstract
Potato Cyst Nematodes (PCNs) are an economically important pest for potato growers. A crucial event in the life cycle of the nematode is hatching, after which the juvenile will move toward the host root and infect it. The hatching of PCNs is induced [...] Read more.
Potato Cyst Nematodes (PCNs) are an economically important pest for potato growers. A crucial event in the life cycle of the nematode is hatching, after which the juvenile will move toward the host root and infect it. The hatching of PCNs is induced by known and unknown compounds in the root exudates of host plant species, called hatching factors (HFs, induce hatching independently), such as solanoeclepin A (solA), or hatching stimulants (HSs, enhance hatching activity of HFs). Unraveling the identity of unknown HSs and HFs and their natural variation is important for the selection of cultivars that produce low amounts of HFs and HSs, thus contributing to more sustainable agriculture. In this study, we used a new approach aimed at the identification of new HFs and HSs for PCNs in potato. Hereto, root exudates of a series of different potato cultivars were analyzed for their PCN hatch-inducing activity and their solA content. The exudates were also analyzed using untargeted metabolomics, and subsequently the data were integrated using machine learning, specifically random forest feature selection, and Pearson’s correlation testing. As expected, solA highly correlates with hatching. Furthermore, this resulted in the discovery of a number of metabolite features present in the root exudate that correlate with hatching and solA content, and one of these is a compound of m/z 526.18 that predicts hatching even better than solA with both data methods. This compound’s involvement in hatch stimulation was confirmed by the fractionation of three representative root exudates and hatching assays with the resulting fractions. Moreover, the compound shares mass fragmentation similarity with solA, and we therefore assume it has a similar structure. With this work, we show that potato likely produces a solA analogue, and we contribute to unraveling the hatch-inducing cocktail exuded by plant roots. Full article
(This article belongs to the Special Issue Integration of Metabolomics with Other Omics Technologies to Investigate Metabolism and Signaling in Plants)
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18 pages, 2432 KiB  
Article
Differential Accumulation of Metabolites and Transcripts Related to Flavonoid, Styrylpyrone, and Galactolipid Biosynthesis in Equisetum Species and Tissue Types
by Amber N. Parrish, Iris Lange, Dunja Šamec and Bernd Markus Lange
Metabolites 2022, 12(5), 403; https://doi.org/10.3390/metabo12050403 - 29 Apr 2022
Cited by 4 | Viewed by 2876
Abstract
Three species of the genus Equisetum (E. arvense, E. hyemale, and E. telmateia) were selected for an analysis of chemical diversity in an ancient land plant lineage. Principal component analysis of metabolomics data obtained with above-ground shoot and below-ground rhizome [...] Read more.
Three species of the genus Equisetum (E. arvense, E. hyemale, and E. telmateia) were selected for an analysis of chemical diversity in an ancient land plant lineage. Principal component analysis of metabolomics data obtained with above-ground shoot and below-ground rhizome extracts enabled a separation of all sample types, indicating species- and organ-specific patterns of metabolite accumulation. Follow-up efforts indicated that galactolipids, carotenoids, and flavonoid glycosides contributed positively to the separation of shoot samples, while stryrylpyrone glycosides and phenolic glycosides were the most prominent positive contributors to the separation of rhizome samples. Consistent with metabolite data, genes coding for enzymes of flavonoid and galactolipid biosynthesis were found to be expressed at elevated levels in shoot samples, whereas a putative styrylpyrone synthase gene was expressed preferentially in rhizomes. The current study builds a foundation for future endeavors to further interrogate the organ and tissue specificity of metabolism in the last living genus of a fern family that was prevalent in the forests of the late Paleozoic era. Full article
(This article belongs to the Special Issue Integration of Metabolomics with Other Omics Technologies to Investigate Metabolism and Signaling in Plants)
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Review

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17 pages, 2157 KiB  
Review
Multi-Omics-Based Discovery of Plant Signaling Molecules
by Fei Luo, Zongjun Yu, Qian Zhou and Ancheng Huang
Metabolites 2022, 12(1), 76; https://doi.org/10.3390/metabo12010076 - 13 Jan 2022
Cited by 17 | Viewed by 4346
Abstract
Plants produce numerous structurally and functionally diverse signaling metabolites, yet only relatively small fractions of which have been discovered. Multi-omics has greatly expedited the discovery as evidenced by increasing recent works reporting new plant signaling molecules and relevant functions via integrated multi-omics techniques. [...] Read more.
Plants produce numerous structurally and functionally diverse signaling metabolites, yet only relatively small fractions of which have been discovered. Multi-omics has greatly expedited the discovery as evidenced by increasing recent works reporting new plant signaling molecules and relevant functions via integrated multi-omics techniques. The effective application of multi-omics tools is the key to uncovering unknown plant signaling molecules. This review covers the features of multi-omics in the context of plant signaling metabolite discovery, highlighting how multi-omics addresses relevant aspects of the challenges as follows: (a) unknown functions of known metabolites; (b) unknown metabolites with known functions; (c) unknown metabolites and unknown functions. Based on the problem-oriented overview of the theoretical and application aspects of multi-omics, current limitations and future development of multi-omics in discovering plant signaling metabolites are also discussed. Full article
(This article belongs to the Special Issue Integration of Metabolomics with Other Omics Technologies to Investigate Metabolism and Signaling in Plants)
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