InSourcerer: a high-throughput method to search for unknown metabolite modifications by mass spectrometry

Area of Science:

• Metabolomics
• Analytical Chemistry
• Biochemistry

Background:

• High-throughput mass spectrometry enables analysis of known metabolites.
• Identification of unknown metabolite structures and modifications remains a significant challenge.
• Unexpected modifications of known molecules contribute to unidentified variants.

Purpose of the Study:

• To present a novel method for high-throughput discovery of unknown metabolite modifications.
• To identify conjugate metabolite isoforms.
• To address the challenge of identifying previously unknown structures in mass spectrometry.

Main Methods:

• Utilizes user-controlled in-source fragmentation to induce loss of weakly bound modifications.
• Compares product ions from in-source fragmentation and collision-induced dissociation (CID).
• Employs diagonal MS^2-MS^3 matching for detecting unknown modifications and substructure similarities.

Main Results:

• Evaluated using 15 cytokinin standards, demonstrating successful identification of modifications.
• Hierarchical clustering confirmed that common substructures lead to good matches.
• Successfully detected standards in a complex plant leaf extract and identified endogenous compounds.

Conclusions:

• Presents a method integrating LC/MS, fragmentation models, and computational algorithms.
• Validates the use of in-source fragmentation for pinpointing structural similarities.
• Demonstrates in-source fragmentation's utility in indicating the occurrence of metabolite modifications.