SE139:/MS1
From Metabolonote
Sample Set Information
| ID | TSE1240 |
|---|---|
| Title | Comparative metabolomics charts the impact of genotype-dependent methionine accumulation in Arabidopsis thaliana. |
| Description | Methionine (Met) is an essential amino acid for all organisms. In plants, Met also functions as a precursor of plant hormones, polyamines, and defense metabolites. The regulatory mechanism of Met biosynthesis is highly complex and, despite its great importance, remains unclear. To investigate how accumulation of Met influences metabolism as a whole in Arabidopsis, three methionine over-accumulation (mto) mutants were examined using a gas chromatography–mass spectrometry-based metabolomics approach. Multivariate statistical analyses of the three mto mutants (mto1, mto2, and mto3) revealed distinct metabolomic phenotypes. Orthogonal projection to latent structures–discriminant analysis highlighted discriminative metabolites contributing to the separation of each mutant and the corresponding control samples. Though Met accumulation in mto1 had no dramatic effect on other metabolic pathways except for the aspartate family, metabolite profiles of mto2 and mto3 indicated that several extensive pathways were affected in addition to over-accumulation of Met. The pronounced changes in metabolic pathways in both mto2 and mto3 were associated with polyamines. The findings suggest that our metabolomics approach not only can reveal the impact of Met over-accumulation on metabolism, but also may provide clues to identify crucial pathways for regulation of metabolism in plants. |
| Authors | Kusano M, Fukushima A, Redestig H, Kobayashi M, Otsuki H, Onouchi H, Naito S, Hirai MY, Saito K. |
| Reference | Amino Acids. 2010 Oct;39(4):1013-21. doi: 10.1007/s00726-010-0562-y. Epub 2010 Mar 31. |
| Comment |
Analytical Method Details Information
| ID | MS1 |
|---|---|
| Title | GC-TOF MS |
| Instrument | GC:Agilent 6890N MS:LECO Pegasus III TOF |
| Instrument Type | |
| Ionization | EI |
| Ion Mode | Positive |
| Description | Plants may show differences in terms of metabolite profiles, so-called ‘metabotypes’, even when no visible phenotypic changes can be observed (Hall 2006). To achieve a broad coverage of primary metabolites, GC-TOF/MS-based metabolite profiling was used in this study. As described previously (Kusano et al. 2007), each sample was extracted, derivatized, and analyzed using GC-TOF/MS. Five milligrams fresh weight of plant tissues was used for GC-TOF/MS analysis. The derivatized extracts, equivalent to 55.6 μg fresh weight of plant material, were injected into the GC-TOF/MS instrument. All raw data were pre-processed using a MATLAB script (version 7.0.4, The MathWorks, Natick, MA) implemented by Jonsson et al. (2005, 2006) to perform baseline correction, alignment, and peak deconvolution. Metabolite identifications were performed by comparing their mass spectra and retention time indices to those generated for authentic compounds analyzed on our instrumentation as well as those in the mass spectra and retention index libraries in the Golm Metabolome Database (Kopka et al. 2005; Schauer et al. 2005). To correct the interference, or cross-contribution, between the internal standards and native metabolites because of problems such as insufficient chromatographic resolution, the data were normalized using cross-contribution compensating multiple standard normalization (CCMN) (Redestig et al. 2009). |
| Comment_of_details |
