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bioRxiv · 10.1101/2025.03.12.642824

SMART: an approach for accurate formula assignment in spatially-resolved metabolomics

Cao, Y.·Li, S.·Liu, Z.·Jia, Z.·Zhuang, W.·Pan, X.·Zhou, J.·Yang, L.·Wang, L.
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Abstract

Spatially-resolved metabolomics plays a critical role in unraveling tissue-specific metabolic complexities. Despite its significance, this profound technology generates thousands of features, yet accurate annotation significantly lags behind LC-MS-based approaches. To bridge this gap, we introduce SMART, an open-source platform designed for precise formula assignment in mass spectrometry imaging. SMART constructs a KnownSet database containing 2.8 million formulas linked by DBEdges derived from repositories such as HMDB, ChEMBL, PubChem, and BioEdges from KEGG biological reactant pairs. Using a multiple linear regression model, SMART extracts formula networks associated with the m/z of interest and scores potential candidates based on several criteria, including linked formulas, DBEdges/BioEdges, and ppm values. Benchmarking against reference datasets demonstrates that SMART achieves prediction accuracy rates of up to 92.4%. Applied to mass spectrometry imaging, SMART successfully annotated 986 formulas in developing mouse embryos. This robust platform enables systematic formula annotation within tissues, enhancing our understanding of metabolic heterogeneity.

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Cao, Y., Li, S., Liu, Z., Jia, Z., Zhuang, W., Pan, X., Zhou, J., Yang, L., Wang, L.. 2025-03-14. SMART: an approach for accurate formula assignment in spatially-resolved metabolomics. https://doi.org/10.1101/2025.03.12.642824

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