Development of RIKEN Plant Metabolome MetaDatabase. (17th December 2021)

• Record Type: Journal Article
• Authors: Fukushima, Atsushi; Takahashi, Mikiko; Nagasaki, Hideki; Aono, Yusuke; Kobayashi, Makoto; Kusano, Miyako; Saito, Kazuki; Kobayashi, Norio; Arita, Masanori
• Is Part Of: Plant & cell physiology. Volume 63:Number 3(2022)
• Page Start: 433
• Page End: 440
• Publication Date: 2021-12-17
• Subjects: Data sharing -- Metabolite profiling -- Metabolomics -- Plant metabolism -- Semantic web; Plant physiology -- Periodicals; Microbiology -- Periodicals; Cytology -- Periodicals; Cell Physiology -- Periodicals; Plant Physiological Phenomena -- Periodicals; Cytology; Microbiology; Plant physiology; Periodicals; 571.205
• DOI: 10.1093/pcp/pcab173
• Languages: English
• ISSNs: 0032-0781

Abstract

Abstract: The advancement of metabolomics in terms of techniques for measuring small molecules has enabled the rapid detection and quantification of numerous cellular metabolites. Metabolomic data provide new opportunities to gain a deeper understanding of plant metabolism that can improve the health of both plants and humans that consume them. Although major public repositories for general metabolomic data have been established, the community still has shortcomings related to data sharing, especially in terms of data reanalysis, reusability and reproducibility. To address these issues, we developed the RIKEN Plant Metabolome MetaDatabase (RIKEN PMM, http://metabobank.riken.jp/pmm/db/plantMetabolomics ), which stores mass spectrometry-based (e.g. gas chromatography–MS-based) metabolite profiling data of plants together with their detailed, structured experimental metadata, including sampling and experimental procedures. Our metadata are described as Linked Open Data based on the Resource Description Framework using standardized and controlled vocabularies, such as the Metabolomics Standards Initiative Ontology, which are to be integrated with various life and biomedical science data using the World Wide Web. RIKEN PMM implements intuitive and interactive operations for plant metabolome data, including raw data (netCDF format), mass spectra (NIST MSP format) and metabolite annotations. The feature is suitable not only for biologists who are interested in metabolomic phenotypes, but also for researchers who would like to investigate life science in general through plant metabolomic approaches.