Difference between revisions of "IC4R006-Metabolomics-2007-17556050"
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==Project Title== | ==Project Title== | ||
'''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''' | '''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''' | ||
| + | ==The Background of This Projec== | ||
| + | |||
| + | * Two-dimensional gas chromatography GC × GC-TOF/MS is a novel approach for enhancing the GC resolution, and it has great advantages in increasing the resolution and peak capacity over the one dimensional separation method. The GC × GC-TOF/MS for metabolomics has been applied for com- plex metabolite profiles from mouse spleen [21]. This is the first report for the use of a technique which significantly enhances metabolite resolution. Currently, the GC × GC-TOF/MS technique has been applied in the analysis of volatile compounds [22,23] and also in the analysis of metabolite mixtures from mouse tissue, yeast cells, and human urine and serum as the comprehensive GC × GC-TOF/MS analysis [24–27]. | ||
| + | * When non-targeted metabolic profiling data are subjected to multivariate statistical analysis such as principal component analysis (PCA) and partial least square-discriminate analysis (PLS-DA) toward the obtained data, a high throughput and high accuracy can be achieved for clustering according to the vectors of numerous metabolites. | ||
==Labs working on this Project== | ==Labs working on this Project== | ||
Revision as of 02:17, 22 June 2016
Contents
Project Title
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
The Background of This Projec
- Two-dimensional gas chromatography GC × GC-TOF/MS is a novel approach for enhancing the GC resolution, and it has great advantages in increasing the resolution and peak capacity over the one dimensional separation method. The GC × GC-TOF/MS for metabolomics has been applied for com- plex metabolite profiles from mouse spleen [21]. This is the first report for the use of a technique which significantly enhances metabolite resolution. Currently, the GC × GC-TOF/MS technique has been applied in the analysis of volatile compounds [22,23] and also in the analysis of metabolite mixtures from mouse tissue, yeast cells, and human urine and serum as the comprehensive GC × GC-TOF/MS analysis [24–27].
- When non-targeted metabolic profiling data are subjected to multivariate statistical analysis such as principal component analysis (PCA) and partial least square-discriminate analysis (PLS-DA) toward the obtained data, a high throughput and high accuracy can be achieved for clustering according to the vectors of numerous metabolites.
Labs working on this Project
- RIKEN Plant Science Center, 1-7-22 Yokohama, Kanagawa 230-0045, Japan
- Group for Chemometrics, Organic Chemistry, Department of Chemistry, Umeå University, SE-901 87 Umeå, Sweden
- Umeå Plant Science Centre, Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, SE-901 87 Umeå, Sweden
- National Institute of Agrobiological Sciences, 2-1-2 Kannondai, Tsukuba, Ibaraki 305-8602, Japan
- Department of Molecular Biology and Biotechnology, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba 263-8522, Japan
Corresponding Author
Miyako Kusano (E-mail:mkusano005@psc.riken.jp)
