Enhanced Structure-guided Molecular Networking Annotation Method for Untargeted Metabolomics Data from Orbitrap Astral Mass Spectrometer

The rapid, efficient, and accurate annotation of compounds
in complex
samples remains a significant challenge in metabolomics. The recently
developed Orbitrap Astral mass spectrometer (MS) integrates a traditional
quadrupole Orbitrap with a novel Astral mass analyzer, providing fast
MS/MS scanning speed and high sensitivity. However, existing metabolomics
annotation methods have not fully exploited the advanced capabilities
of Astral MS. In this study, an enhanced structure-guided molecular
networking (E-SGMN) method was developed, which is specifically tailored
for the Orbitrap Astral mass spectrometer (MS). Unlike previous network
annotation methods, E-SGMN extracted both previously detected metabolites
and those potentially detected by Astral from the metabolome database,
enabling more efficient and accurate network construction through
structural similarity. E-SGMN expands annotation coverage by accurately
improving network size, while minimizing the inclusion of irrelevant
compounds, achieving a balance between annotation scale and accuracy.
Validation results revealed that Astral-E-SGMN achieved an annotation
coverage and accuracy of 76.84% and 78.08%, respectively, for a spiked
plasma, significantly outperforming E-SGMN-Q Exactive HF (E-SGMN-QE
HF). Notably, 5440 metabolite features from NIST SRM 1950 human plasma
were annotated by Astral-E-SGMN, a 3.6-fold increase over QE HF-SGMN.
Comparative analyses for six types of typical biological samples demonstrate
that E-SGMN-Astral enhanced metabolite annotations by 3.7–44.2
times compared to conventional annotation methods, highlighting E-SGMN’s
wider metabolite annotation coverage. This method not only enhances
annotation coverage, but also provides a transformative tool for understanding
complex biological systems, holding significant potential for life
science and clinical medicine.