The ultimate starting point of a metabolomic experiment is to quantify all of the metabolites in a cellular system (i.e. the cell or tissue in a given state at a given point in time). The main challenges are the chemical complexity and heterogeneity of metabolites, the dynamic range of the measuring technique, the throughput of the measurements, and the extraction protocols.
Metabolites are chemical entities and can be analysed by the standard tools of chemical analysis such as molecular spectroscopy and MS. The resolution, sensitivity and selectivity of these technologies can be enhanced or modified by coupling them to gas chromatograpy (GC) or liquid chromatography (LC) steps NMR spectroscopy has been shown to provide valuable information on metabolites, typically directly from biofluids with little or no sample preparation steps
Gas-chromatography-mass-spectrometry (GC-MS), gas- chromatography- time-of-flight-mass-spectrometry (GC-TOF-MS).GC- MS technologies enable the identification and robust quantification of a few hundred primary metabolites within a single extract. However, only volatile compounds (boiling point below 3008C) like ketones and alcohols can be examined directly by GC–MS. Analysis of Semi-volatile compounds such as amino acids and lipids require additional chemical derivatization processes (typically silylation or alkylation) Liquid-chromatography-mass-spectrometry (LC-MS) are currently the standard mass-spectrometry methods for metabolite analyses. LC-MS offers several distinct advantages, chiefly its adaptability to measure a far broader range of metabolites encompassing both primary and secondary metabolites. With the „„soft‟‟ ionization method of ESI, seamless interfacing of LC–MS can be achieved. Thus, even non-volatile metabolites can be directly subjected to mass analysis in this method
Compared to the genome, transcriptome and proteome, the metabolome is of much more complexity, since a large diversity of molecules are produced through metabolism and many of which may participate in several different metabolic or regulatory Pathways Two strategies for metabolomic studies, that is, target analysis involves identification and quantification of specific analytes while metabolite profiling focuses on the characterization of a large number of molecules either intracellularly (metabolic fingerprinting) or extracellularly (metabolic footprinting) (Allen et al., 2003, 2004) serving as an unambiguous marker correlated to certain cellular status
Common and envisaged technologies in metaboliteprofiling
Wang et al 2006 Integrating metabolomics into systems biologyframeworkto exploit metabolic complexity: strategies and applications inmicroorganisms.Appl Microbiol Biotechnol 70: 151–161
Wang et al 2006 Integrating metabolomics into systems biologyframeworkto exploit metabolic complexity: strategies and applications in
Pathway viewers KEGG (http://www.genome.ad.jp/kegg/ ), Atomic Reconstruction of Metabolism database (http:// www.metabolome.jp/), BioCyc (http://biocyc.org) (Paleyand Karp 2006), MetaCyc (http://metacyc.org/) (Caspiet al. 2006), AraCyc (http://www.Arabidopsis.org/tools/ aracyc/) (Zhang et al. 2005), MapMan (http://gabi.rzpd. de/projects/MapMan/) (Thimm et al. 2004), KaPPA-View (http://kpv.kazusa.or.jp/kappa-view/) (Tokimatsu et al.2005) and BioPathAT (http://www.ibc.wsu.edu/research/ lange/public%5Ffolder/) (Lange and Ghassemian 2005), the data model for plant metabolomics experiments ArMet (http://www.armet.org/)
A clear difference between the metabolome patterns (NMR-based study) of chamomile tea drinkers before and after dosing was demonstrated, and the results suggested that the effects of tea drinking lasted for at least two weeks post-dosing. population and toxicogenomic studies should benefit from the combination of “omics”, by allowing connections to be drawn between environmental factors in terms of diet and exposure to toxicity and environmental induced diseases
One significant challenge for plant metabolomics is the lack of a fully described and annotated metabolome for any plant species. Estimates are that the plant kingdom produce 90 000–200 000 different metabolites Owing to technical limitations, researchers traditionally focused on a single or, at most, a handful of metabolic traits that were of greatest importance either for industrial or nutritional value. Prime examples of these targeted approaches include carotenoid content of tomato, protein content of maize and starch content of potato and rice
Metabolomics in systems biology mainly focus on quantifying metabolite levels and flows in primary metabolism. By relying on predefined connections between genetic sequences and metabolites, the information observed by acquiring a snapshot of the cellular metabolic composition is upgraded The use of LC-MS, for example, has been exploited to map metabolic activity and flexibility through dynamic analysis of intracellular metabolites during the yeast cell-cycle (Wittmann et al. 2005) and the effect of culture age on metabolite pools To quantify metabolites containing an amino or carboxylic acid group, Villas-Bôas et al. (2005) applied a sensitive GC-MS method coupled to a statistical data-mining strategy for the integrated analysis of clearly identified and quantified intra- and extracellular metabolites in S. cerevisiae
In yeast, the intracellular metabolites were used to identify the phenotypes of several silent mutants (Raamsdonk et al. 2001). Comparative comprehensive metabolite studies were also used in authentication of other strains (de Nijs et al. 1997).
This level of qualification and quantification is of increasing importance, as the significance of more biosynthetic pathways is elucidated. GC-MS applications have benefited from large databases such as the NIST database. For LC-MS these databases are still in their infancy plant metabolomic experiments this will be more problematic, since the metabolite number and the structural diversity of the metabolites that plants produce is much greater Identification of specific metabolites in complex mixtures by NMR is also problematic. However, it has been demonstrated that many common metabolites can be identified by the application of 2D NMR experiments Data analysis and integration remains problematic.Simone Rochfort,2005 Metabolomics Reviewed: A New “Omics” Platform TechnoloBiology and Implications for Natural Products Research J. Nat. Prod. 68, 1813-182