A complete workflow for improved untargeted metabolome annotation and identification using ultra high- resolution accurate mass and LC-MSn Orbitrap-based mass spectrometry

Importance of the Topic

The reliable and comprehensive annotation of metabolites in complex biological samples is critical for various applications in biomedical research, clinical diagnostics and pharmaceutical development. Improved workflows that combine untargeted and semi targeted strategies enable deeper metabolome coverage and greater annotation confidence.

Objectives and Study Overview

This study demonstrates a global semi targeted metabolomics workflow that integrates ultra high resolution accurate mass data and data dependent MS2 spectra acquired on an Orbitrap ID X tribrid mass spectrometer. The aim was to annotate unknown metabolites in NIST SRM1950 human plasma with high confidence by spiking reference standards and performing spectral library searches.

Methodology

Key steps include:

• Sample preparation via methanol precipitation of human plasma followed by reconstitution in aqueous methanol
• Spiking of 58 authentic reference compounds into plasma extracts
• UHPLC separation on a Hypersil GOLD C18 column using a Vanquish UHPLC system
• Mass spectrometry in positive and negative ion modes at 120000 resolution for MS1 and 30000 for MS2 with stepped collision energy
• AcquireX driven inclusion list to prioritize targeted compounds for fragmentation
• Data processing with Compound Discoverer version 3.1 including formula search against ChemSpider and Metabolika databases
• Spectral matching against local mzVault and online mzCloud libraries for MS2 based identification

Used Instrumentation

• Vanquish UHPLC system
• Hypersil GOLD C18 column (2.1 x 150 mm, 1.9 μm)
• Orbitrap ID X tribrid mass spectrometer
• Compound Discoverer software version 3.1

Results and Discussion

The workflow detected over 5000 features and returned 349 identity matches from the mzCloud library. Targeted analysis of the 58 spiked reference standards in SRM1950 plasma achieved confident identification of 56 compounds with mass measurement errors below 0.1 ppm. Spectral match scores exceeded 85 percent in both mzVault and mzCloud searches. One isomer of levulinic acid could not be distinguished based on retention time differences.

Benefits and Practical Applications

• Enhanced metabolome coverage through combined untargeted and semi targeted analysis
• High confidence in metabolite annotation with cross validation by retention time and MS2 spectra
• Single platform workflow suitable for biomarker discovery and quality control laboratories
• Relative quantitation and identity confirmation of targeted metabolites in a single experiment

Future Trends and Potential Applications

Metabolomics workflows will benefit from further automation and integration of machine learning for spectral annotation. Advances in instrument resolution and acquisition speed will enable deeper coverage of low abundance metabolites. Combined omics integration will expand applications in precision medicine and systems biology.

Conclusion

A combined untargeted and semi targeted metabolomics workflow using ultra high resolution LC MS and tribrid instrumentation provides robust, high confidence metabolite annotation in human plasma. The approach supports comprehensive profiling and reliable identification in a single analysis.

Reference

• Sumner LW et al 2007 Proposed minimum reporting standards for chemical analysis Metabolomics 3 231–241 doi 10.1007/s11306-007-0082-2