With the important developments in analytical methods and data mining that have occurred in recent years, metabolomics has rapidly evolved and provides a global picture of plant molecular organisation at the metabolite level. A very significant increase in studies related to plant metabolomics has been recorded over the last decade . While this approach has been used for various biological systems in conjunction with other omics approaches (e.g., genomics, transcriptomics and proteomics), metabolomics has recently become a key approach for studying plant responses to stress phenomena  and plant-host interactions .
However, this analytical approach is still very challenging because there is no single extraction or analysis technique that is suitable for all low molecular weight metabolites . Among the different techniques enlisted for metabolomic analysis are mass spectrometry (MS) and nuclear magnetic resonance (NMR); different advantages and disadvantages are associated with each analytical system. Chromatographic metabolite separation combined with detection by MS (GC-MS or LC-MS) constitutes a powerful means of generating multivariate metabolic data. In all cases, however, further development is required to achieve a complete quantitative survey of all metabolites over a significant dynamic range in a complex plant or fungal extract.
Currently, two main complementary approaches are used for metabolomic investigations, metabolic profiling and metabolic fingerprinting. For the latter, the intention is not to identify each observed metabolite, but to compare patterns or "fingerprints" of metabolites that change in response to disease, toxin exposure, environmental changes or genetic alterations. On the other hand, metabolic profiling focuses on the analysis of a group of metabolites related to either a specific metabolic pathway or a class of compounds. When a putative biomarker cannot be directly matched in a database, a dedicated procedure (target analysis) can be performed for identification. Furthermore, target analysis can be used when accurate quantification is required.
MS provides sensitive detection and the ability to identify metabolites based on MS or MS/MS spectra when libraries are available. MS can be used to profile extracts directly or in conjunction with HPLC (LC-MS). Because the MS response is compound dependent, absolute quantification in metabolic profiling studies is currently not feasible. NMR, on the other hand, is a non-destructive high throughput method that allows metabolite identification and quantification . It is, however, significantly less sensitive than MS . NMR is considered more reproducible than MS, especially in long-term studies where samples collected and analysed over different time period have to be compared. For short-term studies or for studies in which all of the samples can be analysed simultaneously, MS-based metabolomics represents a good alternative. It has been used in numerous plant stress response studies where the biomarkers of interest require a high sensitivity of detection. Today, the most powerful studies combine the advantages of MS and NMR spectroscopy .
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