Enhanced Structure-guided Molecular Networking Annotation Method for Untargeted Metabolomics Data from Orbitrap...

Area of Science:

• Metabolomics
• Analytical Chemistry
• Bioinformatics

Background:

• Metabolomics research faces challenges in rapid, accurate compound annotation within complex samples.
• Existing annotation methods do not fully utilize the capabilities of advanced mass spectrometers like the Orbitrap Astral.
• The Orbitrap Astral mass spectrometer offers enhanced speed and sensitivity for metabolomic analyses.

Purpose of the Study:

• To develop an enhanced structure-guided molecular networking (E-SGMN) method tailored for the Orbitrap Astral mass spectrometer.
• To improve the efficiency, accuracy, and coverage of metabolite annotation in complex biological samples.
• To exploit the advanced capabilities of the Astral mass analyzer for comprehensive metabolomic profiling.

Main Methods:

• Developed an enhanced structure-guided molecular networking (E-SGMN) method.
• Integrated metabolite data from both previously detected and potentially detected compounds using structural similarity.
• Utilized the Orbitrap Astral mass spectrometer for high-speed, high-sensitivity MS/MS scanning.

Main Results:

• Astral-E-SGMN achieved 76.84% annotation coverage and 78.08% accuracy on spiked plasma, outperforming previous methods.
• Annotated 5440 metabolite features in human plasma, a 3.6-fold increase compared to QE HF-SGMN.
• Demonstrated 3.7-44.2 times enhanced metabolite annotation coverage across six biological sample types.

Conclusions:

• The E-SGMN method, optimized for the Orbitrap Astral MS, significantly expands metabolite annotation coverage and accuracy.
• This approach offers a transformative tool for understanding complex biological systems in life science and clinical medicine.
• The developed method balances annotation scale with accuracy, minimizing irrelevant compound inclusion.