Recent Applications of Metabolomics Toward Cyanobacteria
AbstractOur knowledge on cyanobacterial molecular biology increased tremendously by the application of the “omics” techniques. Only recently, metabolomics was applied systematically to model cyanobacteria. Metabolomics, the quantitative estimation of ideally the complete set of cellular metabolites, is particularly well suited to mirror cellular metabolism and its flexibility under diverse conditions. Traditionally, small sets of metabolites are quantified in targeted metabolome approaches. The development of separation technologies coupled to mass-spectroscopy- or nuclear-magnetic-resonance-based identification of low molecular mass molecules presently allows the profiling of hundreds of metabolites of diverse chemical nature. Metabolome analysis was applied to characterize changes in the cyanobacterial primary metabolism under diverse environmental conditions or in defined mutants. The resulting lists of metabolites and their steady state concentrations in combination with transcriptomics can be used in system biology approaches. The application of stable isotopes in fluxomics, i.e. the quantitative estimation of carbon and nitrogen fluxes through the biochemical network, has only rarely been applied to cyanobacteria, but particularly this technique will allow the making of kinetic models of cyanobacterial systems. The further application of metabolomics in the concert of other “omics” technologies will not only broaden our knowledge, but will also certainly strengthen the base for the biotechnological application of cyanobacteria.
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Schwarz, D.; Orf, I.; Kopka, J.; Hagemann, M. Recent Applications of Metabolomics Toward Cyanobacteria. Metabolites 2013, 3, 72-100.
Schwarz D, Orf I, Kopka J, Hagemann M. Recent Applications of Metabolomics Toward Cyanobacteria. Metabolites. 2013; 3(1):72-100.Chicago/Turabian Style
Schwarz, Doreen; Orf, Isabel; Kopka, Joachim; Hagemann, Martin. 2013. "Recent Applications of Metabolomics Toward Cyanobacteria." Metabolites 3, no. 1: 72-100.