Optimization of Pseudotargeted Metabolomics: Fully Integrating the Advantages of Both Targeted and Untargeted Approaches

Introduction: This study aimed to address persistent challenges in pseudotargeted metabolomics, particularly the limited compatibility with diverse sample types, by developing an enhanced method integrating the strengths of targeted and untargeted approaches. Methods: An upgraded pseudotargeted metabolomics method was developed, incorporating a sample- specific MS-RI library (SSMSRIL) to identify novel metabolites in new samples. Newly discovered metabolites were dynamically added to a pseudotargeted MRM list. Additionally, MRM transitions for 227 target metabolites were integrated, resulting in a final method monitoring >500 metabolites. This design facilitates the extraction and addition of new metabolites to the monitoring list. The method was established and evaluated using gas chromatography-tandem mass spectrometry (GCMS/ MS). Results: Evaluation with new samples revealed that 33-40% of all detected metabolites were identified exclusively through the integrated targeted MRM transitions. This demonstrated their significant role in expanding metabolite coverage. Furthermore, 23-54% of metabolites detected in new sample types were absent from the initial SSMSRIL list. Discussion: The substantial proportion (23-54%) of metabolites detected in new sample types missing from the original library underscores the critical necessity of dynamically updating the pseudotargeted MRM list when applying the method to new samples. This update mechanism is vital for maintaining broad metabolite coverage and method applicability across diverse sample matrices. result: The new method monitors over 500 metabolites, allowing for easy extraction and addition of new metabolites to the monitoring list. Evaluation with new samples revealed that 33-40% of all detected metabolites were identified solely through the targeted MRM transitions, indicating a significant expansion of metabolite coverage. Furthermore, 23-54% of detected metabolites from new sample types were not in the initial SSMSRIL list, highlighting the importance of updating the pseudotargeted MRM list for different sample types. Conclusion: The enhanced pseudotargeted method significantly improves metabolite coverage and adaptability to new sample types through dynamic MRM list updating and the integration of targeted MRM transitions. While developed using GC-MS/MS, the core concept is readily transferable to liquid chromatography (LC)-based full-scan and MRM methodologies, broadening its potential impact.