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.