Streamlined MRM method transfer between instruments assisted with HRMS matching and retention-time prediction.
1School of Civil and Environmental Engineering, Nanyang Technological University, 639798, Singapore; Environmental Chemistry and Materials Centre, Nanyang Environment and Water Research Institute, Nanyang Technological University, 637141, Singapore.
This study presents a new platform for transferring multiple reaction monitoring (MRM) methods between mass spectrometry instruments. This approach enhances small molecule analysis without costly authentic standards.
Area of Science:
- Analytical Chemistry
- Mass Spectrometry
- Environmental Science
Background:
- Multiple reaction monitoring (MRM) using liquid-chromatography tandem mass spectrometry (LC-QqQ-MS/MS) offers high sensitivity for trace small molecule analysis in complex matrices.
- The reliance on costly and often unavailable authentic standards limits the widespread adoption of MRM methods.
- A need exists for practical solutions to enable MRM method transfer and facilitate small molecule quantification without direct standard use.
Purpose of the Study:
- To develop a practical platform for transferring MRM methods between different LC-QqQ-MS/MS instruments.
- To enable confident small molecule identification and quantification without the need for authentic standards.
- To leverage high-resolution mass spectrometry (LC-HRMS) and retention time prediction for method transfer.
Main Methods:
- Developed a platform integrating LC-HRMS and retention time (RT) prediction for MRM method transfer.
- Utilized accurate mass measurements from LC-HRMS and MS/MS fragments from literature.
- Employed retention time matching, peak matching, and a quantitative structure retention relationship (QSRR) model for compound identification.
- Validated the platform's robustness using spiked environmental chemicals in various complex matrices (sludge water, urine, cell extracts).
Main Results:
- The platform successfully transfers MRM methods between different LC-QqQ-MS/MS instruments.
- Integration of LC-HRMS and RT prediction allows for confident small molecule identification without authentic standards.
- The QSRR model, based on random forest feature selection, achieved a Pearson r² of 0.63 for RT prediction.
- Robustness was demonstrated across diverse sample types, including environmental, biological, and cellular matrices.
Conclusions:
- The developed platform provides a practical and cost-effective solution for MRM method transfer.
- This approach significantly reduces the dependency on expensive and scarce authentic standards for small molecule analysis.
- The validated platform enhances the reliability and accessibility of trace-level small molecule quantification in complex samples.
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