Gas chromatography mass spectrometry–based metabolite profiling in plants

By J. Lisec, Nicolas Schauer, Joachim Kopka, Lothar Willmitzer, Alisdair R. Fernie. Nature Protocols, 2006

2,070 citations recorded by the source corpus.

Subfields: Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/8c5f3954781fd9728e186589918f82c4a3b2cb62

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Citations in the corpus

Metabolomics for functional genomics, systems biology, and biotechnology. (2010, methodology): “The GC-MS method has been one of the most popular metabolomics techniques because the method is able to determine the levels of primary metabolites such as amino acids, organic acids, and sugars by employing a chemical derivatization of these hydrophilic metabolites (107, 114, 156).”
Metabolomics demonstrates divergent responses of two Eucalyptus species to water stress (2012, methodology): “Methoximated TMS derivatives were prepared essentially as described previously (Lisec et al. 2006).”
Quality control for plant metabolomics: reporting MSI-compliant studies. (2008, background): “that need to be carefully avoided, and detailed guidelines and practice protocols have been published previously (Fiehn, 2006; Lisec et al., 2006).”
Root exudation of sugars, amino acids, and organic acids by maize as affected by nitrogen, phosphorus, potassium, and iron deficiency (2011, positive): “Sugars were determined by GC-TOF-MS (Lisec et al., 2006).”
The use of metabolomics to dissect plant responses to abiotic stresses (2012, methodology): “The crucial advantage of this technology is that it has long been used for metabolite profiling, and thus there are stable protocols for machine setup and maintenance, and chromatogram evaluation and interpretation [9–11].”
Ascophyllum nodosum-based algal extracts act as enhancers of growth, fruit quality, and adaptation to stress in salinized tomato plants (2018, methodology): “GC-MS analysis of algal extracts Derivatization of metabolites and GC-MS analysis was performed as described in Lisec et al. (2006), using half of the volume of the solutions for derivatization.”
Comparative metabolomics and transcriptomics of plant response to Tomato yellow leaf curl virus infection in resistant and susceptible tomato cultivars (2014, methodology): “GC–MS analysis was performed as described previously (Lisec et al. 2006).”
Decision tree supported substructure prediction of metabolites from GC-MS profiles (2010, methodology): “Firstly, as GC-MS inherently requires volatile analytes, metabolites of interest need to be chemically modiﬁed, for example by methoxyamination and silylation reagents (Kopka 2006, Lisec et al. 2006).”