SE52:/DS01
From Metabolonote
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 |
| Comment |
The raw data files are available at DROP Met web site in PRIMe database of RIKEN.
Data Analysis Details Information
| ID | DS01 |
|---|---|
| Title | Databases similarity search |
| Description | The ReSpect (RIKEN MS/MS spectra database for phytochemicals; 2011 January version), KNApSAcK (2010.12.24 version; Shinbo et al., 2006; Takahashi et al., 2008), and PRIMe standard compound database (2009 November version) were used in this study. The genetic polymorphism data from 20 Arabidopsis accessions were downloaded from the TAIR web site (Clark et al., 2007; Poole, 2007). All data processing procedures were conducted using the in-house script written with Perl. Structural elucidation work was performed in-batch search for all metabolite signals.
In the automated structural elucidation procedure, several thresholds were required to conduct the database searches. The thresholds used in this study are described in Figures 2 and 3. To search the MS/MS spectra, the similarity scores were determined by employing dot product method with mass tolerance at 0.5 Da (Stein and Scott, 1994). The two spectra were considered to be the similar when the similarity score was greater than 0.6. For hierarchical clustering analysis, log2-transformed Z-scored signal intensity data were processed using MEV version 4.4 (Saeed et al., 2003, 2006). |
| Comment_of_details |
