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GigaScience2017; 6(7); 1-20; doi: 10.1093/gigascience/gix037

From chromatogram to analyte to metabolite. How to pick horses for courses from the massive web resources for mass spectral plant metabolomics.

Abstract: The grand challenge currently facing metabolomics is the expansion of the coverage of the metabolome from a minor percentage of the metabolic complement of the cell toward the level of coverage afforded by other post-genomic technologies such as transcriptomics and proteomics. In plants, this problem is exacerbated by the sheer diversity of chemicals that constitute the metabolome, with the number of metabolites in the plant kingdom generally considered to be in excess of 200 000. In this review, we focus on web resources that can be exploited in order to improve analyte and ultimately metabolite identification and quantification. There is a wide range of available software that not only aids in this but also in the related area of peak alignment; however, for the uninitiated, choosing which program to use is a daunting task. For this reason, we provide an overview of the pros and cons of the software as well as comments regarding the level of programing skills required to effectively exploit their basic functions. In addition, the torrent of available genome and transcriptome sequences that followed the advent of next-generation sequencing has opened up further valuable resources for metabolite identification. All things considered, we posit that only via a continued communal sharing of information such as that deposited in the databases described within the article are we likely to be able to make significant headway toward improving our coverage of the plant metabolome.
© The Authors 2017. Published by Oxford University Press.
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Publication Date: 2017-05-19 PubMed ID: 28520864PubMed Central: PMC5499862DOI: 10.1093/gigascience/gix037Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The research article focuses on the current challenges in plant metabolomics and explores various web resources that can aid in better identifying and quantifying metabolites. It also discusses the complexity of choosing appropriate software for analysing large volumes of data generated by next-generation sequencing technologies.

Metabolomics and Its Challenges

  • Metabolomics is a key discipline used to study and understand complex biological systems. Its goal is to expand the coverage of the metabolome – the complete set of metabolites in a biological cell.
  • However, the sheer diversity of chemicals in plants, augmenting to more than 200,000 metabolites, makes this a significant challenge. Extending metabolome coverage to a level comparable to transcriptomics and proteomics is an ongoing quest in this field.

Web Resources as Solutions

  • This research article emphasizes exploring the potential of various web resources to enhance analyte and metabolite identification and quantification.
  • Several software solutions are available to help with metabolite identification and peak alignment, but choosing the right one can be a daunting task for beginners in the field.
  • The paper reviews these software options, discussing their pros and cons, and providing insights about the level of programming skills required to effectively utilize them.

Next-Generation Sequencing and Metabolomics

  • The advent of next-generation sequencing (NGS) has created a vast repository of genome and transcriptome sequences. This data provides invaluable resources for metabolite identification.
  • The unleashing of such huge amounts of data can significantly improve metabolite detection and identification, provided the right software and data interpretation methods are employed.

Communal Sharing for Metabolome Coverage

  • A critical take-home message from this article is the importance of continuous communal sharing of information, such as that contained in the databases discussed in the research.
  • This communal effort is considered essential for making significant progress towards achieving better coverage of the plant metabolome, leading to more in-depth understanding of plant metabolomics.

Cite This Article

APA
Perez de Souza L, Naake T, Tohge T, Fernie AR. (2017). From chromatogram to analyte to metabolite. How to pick horses for courses from the massive web resources for mass spectral plant metabolomics. Gigascience, 6(7), 1-20. https://doi.org/10.1093/gigascience/gix037

Publication

GigaScience
ISSN: 2047-217X
NlmUniqueID: 101596872
Country: United States
Language: English
Volume: 6
Issue: 7
Pages: 1-20

Researcher Affiliations

Perez de Souza, Leonardo
  • Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Germany.
Naake, Thomas
  • Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Germany.
Tohge, Takayuki
  • Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Germany.
Fernie, Alisdair R
  • Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Potsdam-Golm, Germany.

MeSH Terms

  • Gas Chromatography-Mass Spectrometry / methods
  • Gas Chromatography-Mass Spectrometry / standards
  • Metabolome
  • Metabolomics / methods
  • Metabolomics / standards
  • Plants / chemistry
  • Plants / metabolism

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