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Isotopic Distribution Calibration for Mass Spectrometry.
Anthony D Maus1, Jennifer V Kemp1, Todd J Hoffmann1
1Department of Laboratory Medicine and Pathology, Divisions of Clinical Biochemistry and Immunology, Mayo Clinic, Rochester, Minnesota 55905, United States.
A new internal calibration method for mass spectrometry (MS) uses an analyte's natural isotope distribution. This simplifies complex quantification, enabling more efficient and accurate measurements, especially for multiple analytes.
Area of Science:
- Analytical Chemistry
- Mass Spectrometry
Background:
- Mass spectrometry (MS) is crucial for sensitive and specific analyte detection and quantification.
- Current MS quantification relies on complex, resource-intensive external calibration curves and internal standards (IS).
- Existing methods are particularly challenging for multi-analyte measurements due to variability across instruments, samples, and runs.
Purpose of the Study:
- To develop a simplified and more efficient internal calibration method for mass spectrometry.
- To enable accurate quantification of multiple analytes simultaneously.
- To provide mathematical correction for suboptimal experimental conditions in MS.
Main Methods:
- Developed an internal calibration method using the natural isotope distribution of an analyte's internal standard (IS).
- Utilized multiple isotope distribution calibrators for multiplex quantification within the same sample.
- Applied the method to high resolution, accurate mass MS for various analytes, including lower molecular weight compounds.
Main Results:
- The internal calibration method effectively uses natural isotope distributions for multipoint calibration.
- Demonstrated successful multiplex quantification of different targets in a single sample.
- Showed that the approach allows mathematical correction for suboptimal experimental conditions and can potentially quantify difficult targets.
Conclusions:
- The developed isotope distribution calibration method offers a simplified, resource-efficient alternative to traditional MS quantification.
- This approach facilitates accurate multiplex quantification and improves robustness against experimental variability.
- The method holds promise for enhancing the capabilities of automated MS platforms and quantifying challenging analytes.
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