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Background Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) is widely used in metabolomics because it enables high-resolution spatial characterization of molecular distributions directly from tissue. Nevertheless, comprehensive analysis of small, polar metabolites remains difficult due to limited ionization efficiencies and diverse chemical structures. On-tissue chemical derivatization (OTCD) has emerged as an effective strategy to improve ionization efficiency, sensitivity, and selectivity for these analytes. Methods In this study, we established and systematically optimized an OTCD approach for spatial analysis of carbonyl- and carboxyl-containing metabolites in murine tissues using 4-APEBA in combination with carbodiimide crosslinker EDC. Reagent concentrations, solvent composition, and spray parameters were optimized to achieve reproducible derivatization across multiple tissue types. Results The optimized protocol enabled reproducible and confident detection of carbonyl- and carboxyl-containing metabolites in positive ion mode through the characteristic bromine isotopic signature of 4-APEBA. Application to metastatic liver and lung tissue demonstrated the method’s performance in biologically complex environments. Pronounced metabolic heterogeneity correlated with histopathological features in tumor-rich liver sections, and clear tumor-specific localizations were obtained in lung tissue with only small metastatic foci. Metabolic differences between tumor and adjacent healthy regions were consistent with established cancer metabolism pathways, including glycolytic reprogramming. Conclusion This study is the first to optimize and investigate sample preparation conditions for mouse tissue application of a reliable OTCD workflow using EDC and 4-APEBA for MALDI-MSI-based spatial metabolomics, with localized OTCD-MSI of melanoma metastases. By utilizing this combination of reagents, carbonyl and carboxyl moiety containing molecules are confidently annotated based on isotopic signatures in positive mode ionization. The application is capable of interrogating metabolic heterogeneity in clinically relevant tumor models and demonstrates its value for future investigations of tumor metabolism.
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Fecke et al. (2026) studied this question.
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