- Project ID
- Project Name
- Unknown annotation in different biological samples with KGMN
- Liquid chromatography - mass spectrometry (LC-MS) based untargeted metabolomics allows to measure both known and unknown metabolites in the metabolome. However, unknown metabolite annotation is a grand challenge in untargeted metabolomics. Here, we developed an approach, namely, knowledge-guided multi-layer network (KGMN), to enable global metabolite annotation from knowns to unknowns in untargeted metabolomics. The KGMN approach integrated three-layer networks, including knowledge-based metabolic reaction network, knowledge-guided MS/MS similarity network, and global peak correlation network. To demonstrate the principle, we applied KGMN in an in-vitro enzymatic reaction system and different biological samples, with ~100-300 putative unknowns annotated in each data set. Among them, >80% unknown metabolites were validated with in-silico MS/MS tools. Finally, we successfully validated 5 unknown metabolites through the repository-mining and the syntheses of chemical standards. Together, the KGMN approach enables efficient unknown annotations, and substantially advances the discovery of recurrent unknown metabolites towards deciphering dark matters in untargeted metabolomics.
Metabolite annotation from knowns to unknowns through knowledge-guided multi-layer metabolic networking
Zhou Z, Luo M, Zhang H, Yin Y, Cai Y, Zhu ZJ. Metabolite annotation from knowns to unknowns through knowledge-guided multi-layer metabolic networking. Nat Commun. 2022;13(1):6656.
(PMID: 36333358) (DOI: 10.1038/s41467-022-34537-6)
Experiment ID Experiment name Experiment type Create Date OEX015818 OEX_Zheng-Jiang_2202161911 Metabolomic 2022-02-16
Sample ID Sample Name Sample Subject Type Organism Tissue Create Date OES134293 Human urine, plasma and BV2 cell Human Homo sapiens Human urine, plasma and BV2 cell 2022-02-16
Run ID Run Name Experiment Sample Data Num Create Date OER247095 OER_Zheng-Jiang_2202161916 OEX015818 OES134293 64 2022-02-16
- Create Date
- Last Modified
- Zheng-Jiang Zhu
- Interdisciplinary Research Center on Biology and Chemistry (IRCBC), Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences