Plants Metabolome Study: Emerging Tools and Techniques

Overview

Journal Plants (Basel)

Date 2021 Nov 27

PMID 34834772

Citations 30

Authors

Manish Kumar Patel

Sonika Pandey

Manoj Kumar

Md Intesaful Haque

Sikander Pal

Narendra Singh Yadav

Affiliations

Soon will be listed here.

Abstract

Metabolomics is now considered a wide-ranging, sensitive and practical approach to acquire useful information on the composition of a metabolite pool present in any organism, including plants. Investigating metabolomic regulation in plants is essential to understand their adaptation, acclimation and defense responses to environmental stresses through the production of numerous metabolites. Moreover, metabolomics can be easily applied for the phenotyping of plants; and thus, it has great potential to be used in genome editing programs to develop superior next-generation crops. This review describes the recent analytical tools and techniques available to study plants metabolome, along with their significance of sample preparation using targeted and non-targeted methods. Advanced analytical tools, like gas chromatography-mass spectrometry (GC-MS), liquid chromatography mass-spectroscopy (LC-MS), capillary electrophoresis-mass spectrometry (CE-MS), fourier transform ion cyclotron resonance-mass spectrometry (FTICR-MS) matrix-assisted laser desorption/ionization (MALDI), ion mobility spectrometry (IMS) and nuclear magnetic resonance (NMR) have speed up precise metabolic profiling in plants. Further, we provide a complete overview of bioinformatics tools and plant metabolome database that can be utilized to advance our knowledge to plant biology.

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References

Ruttkies C, Schymanski E, Wolf S, Hollender J, Neumann S . MetFrag relaunched: incorporating strategies beyond in silico fragmentation. J Cheminform. 2016; 8:3. PMC: 4732001. DOI: 10.1186/s13321-016-0115-9. View

Daly R, Rogers S, Wandy J, Jankevics A, Burgess K, Breitling R . MetAssign: probabilistic annotation of metabolites from LC-MS data using a Bayesian clustering approach. Bioinformatics. 2014; 30(19):2764-71. PMC: 4173012. DOI: 10.1093/bioinformatics/btu370. View

Hofmann J, Pagel K . Glycan Analysis by Ion Mobility-Mass Spectrometry. Angew Chem Int Ed Engl. 2017; 56(29):8342-8349. DOI: 10.1002/anie.201701309. View

Foroutan A, Goldansaz S, Lipfert M, Wishart D . Protocols for NMR Analysis in Livestock Metabolomics. Methods Mol Biol. 2019; 1996:311-324. DOI: 10.1007/978-1-4939-9488-5_23. View

Xia J, Psychogios N, Young N, Wishart D . MetaboAnalyst: a web server for metabolomic data analysis and interpretation. Nucleic Acids Res. 2009; 37(Web Server issue):W652-60. PMC: 2703878. DOI: 10.1093/nar/gkp356. View

Zhou J, Ma C, Xu H, Yuan K, Lu X, Zhu Z . Metabolic profiling of transgenic rice with cryIAc and sck genes: an evaluation of unintended effects at metabolic level by using GC-FID and GC-MS. J Chromatogr B Analyt Technol Biomed Life Sci. 2009; 877(8-9):725-32. DOI: 10.1016/j.jchromb.2009.01.040. View

Guo B, Chen B, Liu A, Zhu W, Yao S . Liquid chromatography-mass spectrometric multiple reaction monitoring-based strategies for expanding targeted profiling towards quantitative metabolomics. Curr Drug Metab. 2012; 13(9):1226-43. DOI: 10.2174/138920012803341401. View

Smoot M, Ono K, Ruscheinski J, Wang P, Ideker T . Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics. 2010; 27(3):431-2. PMC: 3031041. DOI: 10.1093/bioinformatics/btq675. View

Mastrangelo A, Ferrarini A, Rey-Stolle F, Garcia A, Barbas C . From sample treatment to biomarker discovery: A tutorial for untargeted metabolomics based on GC-(EI)-Q-MS. Anal Chim Acta. 2015; 900:21-35. DOI: 10.1016/j.aca.2015.10.001. View

10.

Tohge T, de Souza L, Fernie A . Genome-enabled plant metabolomics. J Chromatogr B Analyt Technol Biomed Life Sci. 2014; 966:7-20. DOI: 10.1016/j.jchromb.2014.04.003. View

11.

Hong J, Yang L, Zhang D, Shi J . Plant Metabolomics: An Indispensable System Biology Tool for Plant Science. Int J Mol Sci. 2016; 17(6). PMC: 4926328. DOI: 10.3390/ijms17060767. View

12.

Yuliana N, Khatib A, Verpoorte R, Choi Y . Comprehensive extraction method integrated with NMR metabolomics: a new bioactivity screening method for plants, adenosine A1 receptor binding compounds in Orthosiphon stamineus Benth. Anal Chem. 2011; 83(17):6902-6. DOI: 10.1021/ac201458n. View

13.

Zhou J, Liu H, Liu Y, Liu J, Zhao X, Yin Y . Development and Evaluation of a Parallel Reaction Monitoring Strategy for Large-Scale Targeted Metabolomics Quantification. Anal Chem. 2016; 88(8):4478-86. DOI: 10.1021/acs.analchem.6b00355. View

14.

Viant M . Improved methods for the acquisition and interpretation of NMR metabolomic data. Biochem Biophys Res Commun. 2003; 310(3):943-8. DOI: 10.1016/j.bbrc.2003.09.092. View

15.

Garcia-Alcalde F, Garcia-Lopez F, Dopazo J, Conesa A . Paintomics: a web based tool for the joint visualization of transcriptomics and metabolomics data. Bioinformatics. 2010; 27(1):137-9. PMC: 3008637. DOI: 10.1093/bioinformatics/btq594. View

16.

Sobolev A, Testone G, Santoro F, Nicolodi C, Iannelli M, Amato M . Quality traits of conventional and transgenic lettuce (Lactuca sativa L.) at harvesting by NMR metabolic profiling. J Agric Food Chem. 2010; 58(11):6928-36. DOI: 10.1021/jf904439y. View

17.

Menikarachchi L, Cawley S, Hill D, Hall L, Hall L, Lai S . MolFind: a software package enabling HPLC/MS-based identification of unknown chemical structures. Anal Chem. 2012; 84(21):9388-94. PMC: 3523192. DOI: 10.1021/ac302048x. View

18.

TKindt R, Morreel K, Deforce D, Boerjan W, Van Bocxlaer J . Joint GC-MS and LC-MS platforms for comprehensive plant metabolomics: repeatability and sample pre-treatment. J Chromatogr B Analyt Technol Biomed Life Sci. 2009; 877(29):3572-80. DOI: 10.1016/j.jchromb.2009.08.041. View

19.

Lin L, Huang X, Lv Z . Isolation and identification of flavonoids components from L. Springerplus. 2016; 5(1):1649. PMC: 5033795. DOI: 10.1186/s40064-016-3308-9. View

20.

Silva-Navas J, Moreno-Risueno M, Manzano C, Tellez-Robledo B, Navarro-Neila S, Carrasco V . Flavonols Mediate Root Phototropism and Growth through Regulation of Proliferation-to-Differentiation Transition. Plant Cell. 2015; 28(6):1372-87. PMC: 4944400. DOI: 10.1105/tpc.15.00857. View