Rice full-length cDNA over-expressed Arabidopsis mutant database
Research Contents
Metabolite phenotyping by GC-TOF/MS

A strategy for finding "metabolotypes" by using the FOX hunting system

- Metabolite profiling of rice full-length cDNA overexpressed (FOX) Arabidopsis lines by gas chromatography - time-of-flight mass spectrometry (GC-TOF/MS)

Metabolomics allows comprehensive phenotyping, filling a niche between systems biology and functional genomics. It thus contributes strongly to integrated functional genomics. Metabolite profiling is one of the strategies used to study the metabolome. This approach can be used for in-depth investigations of metabolite responses. Gas chromatography - time-of-flight mass spectrometry (GC-TOF/MS) is one of the most widely used techniques and a key technology in metabolite profiling because of its long history in analyzing low-molecular-weight compounds. To screen aerial parts of rice FOX Arabidopsis lines, we performed GC-TOF/MS analysis as shown in Figure 1. We investigated 352 three-week-old independent lines of the T2 generation for changes in their metabolite profiles. We re-profiled candidate lines that showed specific metabolite profiles in the first screen, because metabolites often show fluctuations even when plants are grown under strictly controlled conditions.

Metabolite phenotyping by FT-NIR spectroscopy

A strategy for finding "metabolotypes" by using the FOX hunting system

- Nondestructive metabolite fingerprinting of rice full-length cDNA overexpressed (FOX) Arabidopsis lines by Fourier transform - near-infrared (FT-NIR) spectroscopy.

Metabolomics allows comprehensive phenotyping, filling a niche between systems biology and functional genomics. It thus contributes strongly to integrated functional genomics. Metabolite fingerprinting is used in metabolomics because it enables rapid, high-throughput analysis and provides information from spectra of total compositions of metabolites. Fourier transform - near-infrared (FT-NIR) spectroscopy has great potential for metabolite fingerprinting because its operation is simple, and various types of samples (liquid, solid, and powder) can be analyzed nondestructively. In addition, the spectral traits can be systematically extracted by multivariate statistical analysis. Therefore, we used FT-NIR for metabolic screening of rice FOX Arabidopsis lines.

We screened approximately 3000 lines of Arabidopsis seeds of the T2 generation showing no visible aberrations in seed morphology. For the screening of FOX lines, 200 seeds were placed in a glass tube for each line, and the FT-NIR spectra were directly measured. Candidate lines were selected for their unique metabolic footprints by principal components analysis.

Equipment
Nicolet 6700 FT-IR equipped with a Smart Near-IR UpDRIFT (Thermo Electron Corporation)
Software: OMNIC 7.2a
Beamsplitter: CaF2
Detector: TEC InGaAs 2.6um
The mirror velocity: 1.2659 cm/s
Resolution: 4 cm-1
Background: spectralon (LabSphere, Inc.)

Supplemental material
Raw spectral data (Zip file 160MB)
Seed list (Excel file 140KB)


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