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Updated: Oct 3, 2025
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An Integrated Workflow of Identification and Quantification on FDR Control-Based Untargeted Metabolome
Published on: September 20, 2022
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Novel Real-Time Library Search Driven Data Acquisition Strategy for Identification and Characterization of
Brandon Bills1, William D Barshop1, Seema Sharma1
1Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States.
Analytical Chemistry
|February 21, 2022
Summary
A new Met-IQ strategy enhances metabolite identification by using real-time spectral matching for targeted MS3 analysis, increasing data acquisition efficiency for drug discovery and metabolomics. This method improves the detection of novel compounds and potential metabolites.
Area of Science:
- Analytical Chemistry
- Metabolomics
- Drug Discovery
Background:
- Structural characterization of novel metabolites is crucial but challenging in drug discovery and metabolomics.
- Current multilevel fragmentation (MSn) methods face limitations due to instrument cycle times, necessitating complex data acquisition strategies for complex samples.
- Targeting low-concentration analytes often requires splitting data acquisition across multiple experiments.
Purpose of the Study:
- To introduce Met-IQ, a novel LC/MS data acquisition strategy for enhanced structural characterization of unknown compounds.
- To improve the efficiency of MSn experiments by making real-time, data-dependent decisions for MS3 acquisition.
- To increase the identification rate of novel metabolites and related compounds in complex biological samples.
Main Methods:
- Developed Met-IQ, a strategy employing real-time spectral library matching to trigger MS3 acquisitions.
- Implemented a decision-dependent event system where MS3 is initiated based on MS2 spectral similarity to a reference library.
- Applied Met-IQ to Amprenavir incubated with human liver microsomes, focusing MS2 fragment selection on higher mass ions.
Main Results:
- Met-IQ significantly increased the MS2 instrument sampling rate compared to traditional data-dependent acquisition.
- A 2-fold increase in MS2 spectra was observed, leading to the identification of 14-34% more unique potential metabolites.
- The strategy effectively focused MS3 acquisition on structurally relevant fragments, aiding in compound identification.
Conclusions:
- Met-IQ offers a more efficient approach to metabolite identification and structural characterization in LC/MS-based studies.
- The strategy enhances the ability to detect and identify novel compounds, particularly those related to known analytes.
- Met-IQ is broadly applicable to various analytical challenges beyond metabolism studies where structural elucidation of unknown related compounds is desired.
