AQuA: An Automated Quantification Algorithm for High-Throughput NMR-Based Metabolomics and Its Application in Human...

Area of Science:

• Analytical Chemistry
• Biochemistry
• Metabolomics

Background:

• High-throughput NMR-based metabolomics is limited by the absence of rapid, accurate metabolite quantification tools.
• Absolute quantification of numerous metabolites from complex spectra remains a challenge.

Purpose of the Study:

• To develop and evaluate the Automated Quantification Algorithm (AQuA) for targeted absolute metabolite quantification from 1H NMR spectra.
• To provide a rapid and accurate method for analyzing complex NMR data in metabolomics.

Main Methods:

• AQuA utilizes spectral data from a library of standard calibration spectra for each metabolite.
• It employs a single preselected NMR signal per metabolite, accounting for interferences.
• The algorithm was validated using experimental 1H NMR spectra from human plasma.

Main Results:

• AQuA demonstrated high accuracy, with 61 out of 67 quantified metabolites in human plasma spectra showing an r² ≥ 0.9 compared to manual spectral fitting.
• Three quality indicators (occurrence, interference, positional deviation) were developed for result evaluation.
• The algorithm achieved high efficiency, quantifying 67 metabolites in 1342 human plasma spectra in under 1 second.

Conclusions:

• AQuA is a rapid, accurate, and efficient algorithm for targeted absolute metabolite quantification from 1H NMR spectra.
• The developed quality indicators aid in assessing the reliability of the quantification results.
• AQuA significantly advances high-throughput metabolomics capabilities.