MetaTag: A Biochemical Reaction-Guided Design Strategy for New Metabolite Discovery.

Abstract

Most small-molecule features detected in untargeted metabolomics remain unannotated, representing the dark matter of the metabolome. Here, we introduce MetaTag, a biochemical-reaction-guided framework that generates high-probability novel metabolites by combining abundant endogenous metabolites with common enzymatic transformations derived from KEGG pathways. In this proof-of-concept implementation, we focused on N-acylation and N-alkylation reactions. We synthesized and characterized a physical library of 1068 compounds, creating a public MS/MS database (https://mtdb-website.vercel.app). Screening against 27 rat tissues matched 180 previously unreported metabolites with 6 at level 1 (confirmed by RT, formula, MS/MS) and 174 at level 2 (confirmed by RT, formula). These metabolites exhibited tissue-specific distributions and participated in the interorgan exchange during fasting. Functional interrogation of one such metabolite, N-propionyltaurine, demonstrated its role as a redox-sensitive regulator in brown adipocytes. This biochemistry-guided strategy provides a scalable platform for the discovery of previously uncharacterized bioactive metabolites.