METLIN: A Technology Platform for Identifying Knowns and Unknowns

TLDR

METLIN began as a database for known metabolites and has evolved into a platform for identifying both known and unknown metabolites and other chemical entities. METLIN is designed to address the characterization of known and unknown molecules using its informatic and experimental data features. METLIN’s high‑resolution tandem mass spectrometry database, built from reference standards, labeled isotope analogues, and in‑silico predictions, is coupled with a fragment‑similarity search that operates independently of precursor mass and uses isotopic m/z shifts to identify structures. The platform now contains over one million molecules across diverse classes and has successfully identified four previously unknown metabolites.

Abstract

METLIN originated as a database to characterize known metabolites and has since expanded into a technology platform for the identification of known and unknown metabolites and other chemical entities. Through this effort it has become a comprehensive resource containing over 1 million molecules including lipids, amino acids, carbohydrates, toxins, small peptides, and natural products, among other classes. METLIN's high-resolution tandem mass spectrometry (MS/MS) database, which plays a key role in the identification process, has data generated from both reference standards and their labeled stable isotope analogues, facilitated by METLIN-guided analysis of isotope-labeled microorganisms. The MS/MS data, coupled with the fragment similarity search function, expand the tool's capabilities into the identification of unknowns. Fragment similarity search is performed independent of the precursor mass, relying solely on the fragment ions to identify similar structures within the database. Stable isotope data also facilitate characterization by coupling the similarity search output with the isotopic m/ z shifts. Examples of both are demonstrated here with the characterization of four previously unknown metabolites. METLIN also now features in silico MS/MS data, which has been made possible through the creation of algorithms trained on METLIN's MS/MS data from both standards and their isotope analogues. With these informatic and experimental data features, METLIN is being designed to address the characterization of known and unknown molecules.