Discovering unexplored metabolomes with novel metabolomics techniques

November 28, 2017

Epimetabolite identifications by using mass spectrometry cheminformatics

Many studies have reported that metabolites themselves are deeply involved in the physiological functions and homeostasis of living organisms. While the technique of mass spectrometry (MS) based untargeted metabolomics has been expected as a great tool to discover such metabolites, a lot of the computational works for the data analysis of enormous MS data are needed with the expert knowledge of mass spectrometry and biology.

Therefore, new metabolomics technique using “mass spectrometry cheminformatics” was developed by the research collaboration between RIKEN CSRS and UC Davis (US) to efficiently identify “epimetabolites”, which are defined as modified metabolites distinct from classical biochemical pathways, with the accumulated metabolome database over the past 13 years (BinBase).

It uses three cheminformatics tools: 1) BinVestigate, a program to extract epimetabolite candidates from the BinBase metabolome database, 2) MS-DIAL 2.0, a universal metabolomics software for gas chromatography–mass spectrometry (GC-MS) and liquid chromatography–mass spectrometry (LC-MS) and 3) MS-FINDER 2.0, a structure elucidation software for predicting the molecular structure of unknowns by means of the technique of computational mass fragmentation.

The integrated method enabled us to identify five epimetabolites including N-methyl-uridine monophosphate (upregulated in breast cancer cells) and N-methyl-alanine (thought to be a product from gut flora).

The method can be applied not only for medical sciences but also for many biological fields such as microbiome- and plant biology. Our research will be contributed to the further understanding of metabolisms.


Original article
Nature Methods doi:10.1038/nmeth.4512
Z. Lai, H. Tsugawa, G. Wohlgemuth, S. Mehta, M. Mueller, Y. Zheng, A. Ogiwara, M. Showalter, J. Meissen, K. Takeuchi, T. Kind, P. Beal, M. Arita, O. Fiehn,
"Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics".

Hiroshi Tsugawa
Research Scientist
Metabolome Informatics Research Team