SE52:/SS01

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Sample Set Information

ID SE52
Title Mass spectra-based framework for automated structural elucidation of metabolome data to explore phytochemical diversity
Description A novel framework for automated elucidation of metabolite structures in liquid chromatography–mass spectrometer metabolome data was constructed by integrating databases. High-resolution tandem mass spectra data automatically acquired from each metabolite signal were used for database searches. Three distinct databases, KNApSAcK, ReSpect, and the PRIMe standard compound database, were employed for the structural elucidation. The outputs were retrieved using the CAS metabolite identifier for identification and putative annotation. A simple metabolite ontology system was also introduced to attain putative characterization of the metabolite signals.The automated method was applied for the metabolome data sets obtained from the rosette leaves of 20 Arabidopsis accessions. Phenotypic variations in novel Arabidopsis metabolites among these accessions could be investigated using this method.
Authors Fumio Matsuda, Ryo Nakabayashi, Yuji Sawada, Makoto Suzuki, Masami Yokota Hirai, Shigehiko Kanaya, Kazuki Saito
Reference Matsuda F et al. (2011) Front. Plant Sci. 2:40. doi: 10.3389/fpls.2011.00040
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The raw data files are available at DROP Met web site in PRIMe database of RIKEN.

Sample Preparation Details Information

ID SS01
Title Sample Preparation
Description The seeds were soaked on MS agar plates and then incubated at 22°C under 16 h day and 8 h night conditions. At 18 days after germination, the aerial parts of the seedlings were harvested.
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