Metabolomics

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What is Metabolomics ?

  • Metabolomics is the scientific study of chemical processes involving metabolites. Specifically, metabolomics is the "systematic study of the unique chemical fingerprints that specific cellular processes leave behind", the study of their small-molecule metabolite profiles.[1] The metabolome represents the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes.[2] mRNA gene expression data and proteomic analyses reveal the set of gene products being produced in the cell, data that represents one aspect of cellular function. Conversely, metabolic profiling can give an instantaneous snapshot of the physiology of that cell. One of the challenges of systems biology and functional genomics is to integrate proteomic, transcriptomic, and metabolomic information to provide a better understanding of cellular biology.

Figure 1. Integrated functional genomics. The effects of gene perturbations are evaluated at multiple levels including the transcriptome, proteome, and metabolome. Changes in the metabolome occur as a consequence of those changes in the transcriptome that result in changes in the levels or catalytic activities of enzymes. Therefore, metabolome analysis is a valuable tool for inferring gene function.

  • Advances in mass spectrometry have enabled the analysis of cellular proteins and metabolites (proteome and metabolome respectively) on a scale previously unimaginable. The cumulative utilization of these technologies has advanced the fields of functional genomics (Holtorf et al., 2002; Oliver et al., 2002; Somerville and Somerville, 1999) and systems biology (Ideker et al., 2001; Kitano, 2000). Both fields comprise traditional molecular biology, enzymology and bio- chemistry; however, the predominant difference from previous approaches is the significantly larger scale upon which they are conducted.

Limitations of metabolomics

  • The major limitation of metabolomics is its current inability to comprehensively profile all of the metabolome. This inability is directly related to the chemical complexity of the metabolome, the biological variance inherent in most living organisms, and the dynamic range limitations of most instrumental approaches. In many ways, this is similar to the situation of the Human Genome Project in 1990, when the technological means to sequence genomes were not yet available.

Metabolome technologies

  • It is generally accepted that a single analytical technique will not provide sufficient visualization of the metabolome and, therefore, multiple technologies are needed for a comprehensive view (Hall et al., 2002; Sumner et al., 2002). Accordingly, many analytical technologies have been enlisted to profile the metabolome. Methods based on infrared spectroscopy (IR) (Oliver et al., 1998), nuclear magnetic resonance (NMR(Bligny and Douce, 2001; Ratcliffe and Shachar-Hill,2001; Roberts, 2000), thin layer chromatography (TLC) (Tweeddale et al., 1998), HPLC with ultraviolet and photodiode array detection (LC/UV/PDA) (Fraser et al., 2000), capillary electrophoresis coupled to ultravio- let absorbance detection (CE/UV) (Baggett et al., 2002), capillary electrophoresis coupled to laser induced fluorescence detection (CE/LIF) (Arlt et al., 2001), capillary electrophoresis coupled to mass spectrometry (CE/MS) (Soga et al., 2002), gas chromatography-mass spectrometry (GC/MS), liquid chromatography-mass spectro- metry (LC/MS) (Huhman and Sumner, 2002), liquid chromatography tandem mass spectrometry (LC/MS/ MS) (Huhman and Sumner, 2002), Fourier transform ion cyclotron mass spectrometry (FTMS) (Aharoni et al., 2002), HPLC coupled with both mass spectrometry and nuclear magnetic resonance detection (LC/NMR/ MS) (Bailey et al., 2000a), and LC/NMR/MS/MS (Bai- ley et al., 2000b) have all been used.

Projects List

Project Title Species Published years Academic Journal RiceWiki Project ID
Genetic analysis of the metabolome exemplified using a rice population Oryza sativa 2013 Proceedings of the National Academy of Sciences IC4R001-Metabolomics-2013-24259710
Folate fortification of rice by metabolic engineering Oryza sativa L. ssp. Japnoica 2007 Nature Biotechnology IC4R002-Metabolomics-2007-17934451
Characterization of Volatile Aroma Compounds in Cooked Black Rice Oryza sativa 2007 Journal of Agricultural and Food Chemistry IC4R003-Metabolomics-2007-18081248
A targeted metabolomics approach toward understanding metabolic variations in rice under pesticide stress Oryza sativa 2015 Analytical Biochemistry IC4R004-Metabolomics-2015-25766578
Metabolomic screening applied to rice FOX Arabidopsis lines leads to the identification of a gene-changing nitrogen metabolism. Oryza sativa L. ssp. japonica 2010 Molecular Plant IC4R005-Metabolomics-2010-20085895
Application of a metabolomic method combining one-dimensional and two-dimensional gas chromatography-time-of-flight/mass spectrometry to metabolic phenotyping of natural variants in rice Oryza sativa L. 2007 Journal of Chromatography B IC4R006-Metabolomics-2007-17556050
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 Oryza sativa L. 2009 Journal of Chromatography B IC4R007-Metabolomics-2009-19233746
Toward better annotation in plant metabolomics: isolation and structure elucidation of 36 specialized metabolites from Oryza sativa (rice) by using MS/MS and NMR analyses Oryza sativa 2014 Metabolomics IC4R008-Metabolomics-2014-25057267
Comparative metabolic profiling of pigmented rice (Oryza sativa L.) cultivars reveals primary metabolites are correlated with secondary metabolites Oryza sativa L. 2013 Journal of Cereal Science IC4R009-Metabolomics-2013-25056584
Using metabolomic approaches to explore chemical diversity in rice Oryza sativa 2015 Plant Molecular Biology Reporter IC4R010-Metabolomics-2015-25578272
Metabolome-genome-wide association study dissects genetic architecture for generating natural variation in rice secondary metabolism Oryza sativa 2015 Plant Journal IC4R011-Metabolomics-2015-25267402
Dissection of genotype-phenotype associations in rice grains using metabolome quantitative trait loci analysis Oryza sativa 2012 Plant Journal IC4R012-Metabolomics-2012-22229385

References