SE51:/MS01
Sample Set Information
| ID | SE51 |
|---|---|
| Title | RIKEN tandem mass spectral database (ReSpect) for phytochemicals: A plant-specific MS/MS-based data resource and database |
| Description | The fragment pattern analysis of tandem mass spectrometry (MS/MS) has long been used for the structural characterization of metabolites. The construction of a plant-specific MS/MS data resource and database will enable complex phytochemical structures to be narrowed down to candidate structures. Therefore, a web-based database of MS/MS data pertaining to phytochemicals was developed and named ReSpect (RIKEN tandem mass spectral database). Of the 3595 metabolites in ReSpect, 76% were derived from 163 literature reports, whereas the rest was obtained from authentic standards. As a main web application of ReSpect, a fragment search was established based on only the m/z values of query data and records. The confidence levels of the annotations were managed using the MS/MS fragmentation association rule, which is an algorithm for discovering common fragmentations in MS/MS data. Using this data resource and database, a case study was conducted for the annotation of untargeted MS/MS data that were selected after quantitative trait locus analysis of the accessions (Gifu and Miyakojima) of a model legume Lotus japonicus. In the case study, unknown metabolites were successfully narrowed down to putative structures in the website. |
| Authors | Yuji Sawada, Ryo Nakabayashi, Yutaka Yamada, Makoto Suzuki, Muneo Sato, Akane Sakata, Kenji Akiyama, Tetsuya Sakurai, Fumio Matsuda, Toshio Aoki, Masami Yokota Hirai, Kazuki Saito |
| Reference | Sawada Y et al. (2012) Phytochemistry 82: 38-45 |
| Comment |
The raw data files are available at DROP Met web site in PRIMe database of RIKEN.
Analytical Method Details Information
| ID | MS01 |
|---|---|
| Title | Metabolic profiling and mQTL analysis |
| Instrument | UPLC-QTOF Premier (Waters) and UPLC-TQS (Waters) |
| Instrument Type | UPLC-QTOF-MS |
| Ionization | ESI |
| Ion Mode | Positive and Negative |
| Description | <Metabolic profiling>
A seed was disrupted using a multi beads shocker (Shake Master NEO, BMS, Tokyo, Japan), and the seed powder was extracted with 1 mL of extraction buffer (0.1% HCO2H, MeOH–H2O (4:1 v/v), and 33.6 nM lidocaine and 840 nM camphor sulfonic acid as internal standards of positive mode and negative mode, respectively) using a multi beads shocker. After centrifugation (4 °C, 10,000 rpm, 5 min), the sample tubes were subjected to sample preparation (buffer transfer, 250 μL of seed extract; dried up, resolution, 250 μL of LC-MS grade H2O; filtration, 384 well formatted filter (0.45 μm PVDF, Whatman, NJ, USA) with a liquid handling system (Microlab Star Plus, Hamilton, Ontario, Canada) (Sawada et al., 2009a). The metabolites were analyzed using a liquid chromatography quadrupole time of flight mass spectrometer and tandem quadruple mass spectrometer system (UPLC-QTOF Premier and UPLC-TQS, Waters Co., MA, USA) (Matsuda et al., 2009; Sawada et al., 2009a). The metabolites were analyzed using a liquid chromatography quadrupole time of flight mass spectrometer and tandem quadruple mass spectrometer system (UPLC-QTOF Premier and UPLC-TQS, Waters Co., MA, USA) (Matsuda et al., 2009; Sawada et al., 2009a). After cutting off the low intensity data of MS2Ts, 702 MS2Ts were used for a selected reaction monitoring (SRM) assay of UPLC-TQS. To determine the optimal collision energy for MS2Ts, collision induced dissociation fragmentation analyses at six energy steps (10–60 eV) were conducted using the same seed extracts. As a result, 4212 SRMs were used for analysis. The SRM condition that gave the highest signal intensity among the six energy steps was defined as the optimal SRM. The optimal SRM conditions were further selected based on the following criterion: the relative standard deviation of UPLC-TQS peak area values must be less than 10% (analytical replicates = 3). Finally, 342 SRM conditions for MS2Ts were successfully assigned to the seed extract of L. japonicus. Based on the natural variations in the metabolite accumulation patterns among the accessions (MG-20 and B-129), 88 SRM conditions were used for mQTL analysis.
Metabolic profiling data of 129 RILs were processed as follows: the peak area values of 88 SRMs were divided by the peak area values of the internal standards, which were lidocaine and camphor sulfonic acid for the positive and negative ion modes, respectively. The divided values were then converted into z-scores of binary logarithms after missing values were replaced with 0.1. The genotype data of each RIL were obtained from KDRI (http://www.kazusa.or.jp/lotus/). Using processed metabolic profiling data and gene marker data of RILs, mQTL analysis was carried out using R/qtl (Broman et al., 2003) (Supplementary Data). |
| Comment_of_details |
