Project Summary/Abstract
The human metabolome remains mostly unknown, presenting a major bottleneck in the discovery of new
biological mechanisms because structures are needed to predict function. There is a critical need for
high-throughput, experimental strategies to characterize these unknowns. The overall goal of this project is to
characterize unknown small molecules in humans using a combination of organic synthesis, mass
spectrometry and public data mining. This proposal focuses on the synthesis and detection of two classes of
small molecules critical to human physiology – neurotransmitter derivatives and sphingolipids.
For the proposed projects, a strategy called reverse metabolomics will be used. Typically, in an untargeted
metabolomics experiment, compounds are detected first, prioritized based on biological significance, then
structurally identified. In the proposed reverse metabolomics experiments, however, the process is flipped.
Compound classes of interest are first identified and synthesized, then their spectra are searched for in public
metabolomics data to see if they are found in humans and if so, where.
The proposed work will generate large MS/MS libraries of previously unidentified metabolites and all data will
be made public. Additionally, a novel catalytic method for the one-step divergent synthesis of sphingolipids will
be developed. While the proposed studies focus on two specific types of molecules, this strategy can be
readily adapted to study other classes of biological molecules. Ultimately, this research enables the
identification of new potential biomarkers, therapeutic targets, and pathogenic mechanisms.