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Poster Presentations
Day 2, June 23（Mon.）
Room P (Maesato East, Foyer, Ocean Wing)
- 2P-AM-18
Semi-automated detection and identification of multiplex-labeled metabolomics data
(1MKI, 2Taiyo Nippon Sanso, 3Lipidome Lab)
oNoritaka Masaki1, Akari Ikeda2, Mei Tanabe2, Yasuto Yokoi1, Takayo Ohto3, Hiroki Nakanishi3
Metabolomics study covers wide variety of analytes including lipids, sugars, drugs, artificially synthesized chemicals, and so on. To evaluate these metabolites, mass spectrometry (MS) is popularly used as it can detect large number of metabolites at once. On the other hand, it is difficult to identify large number of MS signals only from the information of their mass. Although tandem mass spectrometry provides their structural information, it is not enough to distinguish molecular species larger than 1,000. In addition, their quantification is also a task to understand metabolism as it must be discussed based on their reaction kinetics. These issues are also important in the proteomics study and multiplex analysis plays a key to address these issues. In combination with derivatizations and isotope labeling, molecules with their specific motif are determined more precisely.
Here, we make an approach to introduce multiplex analysis for metabolomic study. For this purpose, we will demonstrate the semi-automated detection and identification of metabolites derivatized with a multiplex reagent.