The study of plant metabolomics occupies an important place in the overall study of metabolomics. As a class of sequestered organisms, plants can produce a great variety of metabolites, with a total number of between 200,000 and 1 million species. Plant metabolites can be broadly classified into two major groups: primary metabolites and secondary metabolites. Primary metabolites are necessary to sustain plant life and growth and development. Secondary metabolites are more involved in environmental responses such as disease resistance and stress resistance in plants.
General schematic representation of techniques utilised in plant metabolomics (Sangwan et al., 2015)
The wide variety of plant metabolites with different structures and widely varying contents makes plants, on the one hand, ideal materials for studying metabolite biosynthesis and its regulation. The complexity of plant metabolites also poses a serious challenge to plant metabolomics research.
With the development of metabolomics analysis technology, the content of metabolomics research has been expanded. Through the integration of metabolomics with other histological techniques (e.g. transcriptomics, genomics), it is more useful for studies such as identification of functional genes, metabolic pathway elucidation and genetic analysis of natural variation in plants.
The most commonly used technique for plant metabolome studies is chromatography coupled with mass spectrometry.
The metabolomics platform based on gas chromatography-mass spectrometry (GC-MS) technology is mainly used to analyze small molecules metabolites that are thermally stable, volatile and can be vaporized, with high separation efficiency and high resolution and sensitivity. GC-MS detection results can be compared with standard spectral libraries to obtain metabolite structure information, which is easy to characterize metabolites. The development of full 2D chromatography-mass spectrometry techniques using multidimensional chromatography, such as full 2D gas chromatography-time-of-flight mass spectrometry (GC×GC-TOF/MS) can further improve chromatographic separation and peak capacity, while increasing the detection of metabolites by improving sensitivity and focusing effect, demonstrating superior performance for the analysis of complex biological samples.
Liquid chromatography-mass spectrometry (LC-MS) based metabolite detection methods have wide detection limits and high sensitivity, and do not require volatility or thermal stability of the components to be measured. The detection of various metabolites, especially various secondary metabolites, from polar to non-polar can be achieved by selecting different types of columns. Complex pre-treatments for derivatization are generally not required. The application of new liquid chromatography techniques such as ultra performance liquid chromatography (UPLC) and ultra high pressure systems (pressure >105 kPa) can significantly improve chromatographic separation, reduce matrix interference when coupled with mass spectrometry, and greatly reduce the analysis cycle time while improving detection sensitivity.
Metabolomic Approaches in Plant Research (Tahir et al., 2019)
Metabolomics allows not only for the analysis of known metabolites, but also for the qualitative and quantitative detection of unknown metabolites. The use of time-of-flight mass spectrometry, Fourier transform mass spectrometry and orbital trap mass (orbi⁃trap) spectroscopy can provide precise masses of metabolites. Multiplex mass spectrometry (MSn) can provide complete fragment ion information of metabolites. By analyzing and processing these information, structural information such as relative molecular mass, elemental composition and functional groups of metabolites can be obtained, and then bioinformatics can be used to annotate metabolite structures.
- Sangwan, N. S., Tiwari, P., et al. (2015). Plant metabolomics: An overview of technology platforms for applications in metabolism. PlantOmics: The omics of plant science, 257-298.
- Tahir, A. T., Fatmi, Q., Nosheen, A., Imtiaz, M., & Khan, S. (2019). Metabolomic approaches in plant research. In Essentials of Bioinformatics, Volume III (pp. 109-140). Springer, Cham.
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