Combining NMR and MS with Chemical Derivatization for Absolute Quantification with Reduced Matrix Effects

Area of Science:

• Metabolomics
• Analytical Chemistry
• Biochemistry

Background:

• Absolute quantitation of metabolites is crucial but challenging in metabolomics.
• Previous NMR-guided MS methods did not fully address matrix effects.
• Matrix effects in mass spectrometry can compromise quantitative accuracy.

Purpose of the Study:

• To develop a novel method for absolute metabolite quantitation using mass spectrometry (MS).
• To overcome matrix effects inherent in MS-based quantitation.
• To establish a cost-efficient and highly quantitative approach for metabolite analysis.

Main Methods:

• Developed the qNMR-MS method combining Nuclear Magnetic Resonance (NMR) spectroscopy and chemical derivatization.
• Utilized isotope-labeled and unlabeled reagents for derivatizing reference and study samples, respectively.
• Mixed derivatized reference samples with study samples for MS analysis and compared paired peaks.

Main Results:

• Achieved high accuracy for amino acid quantitation in standards (R² > 0.99) using propyl-chloroformate derivatization.
• Demonstrated comparable results to conventional isotope-labeled internal standard (iSTD) methods for human serum (R² ≥ 0.99).
• Reported an average median coefficient of variation (CV) of 5.45% for the qNMR-MS method in serum samples.

Conclusions:

• The qNMR-MS method provides a simple, highly quantitative, and cost-effective solution for absolute metabolite quantitation.
• This method effectively eliminates matrix effects, offering improved accuracy in MS measurements.
• The qNMR-MS approach shows promise for routine quantitation of amino acids and can be extended to other metabolites in various biological samples.