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

Abstract

A key limiting step for high-throughput NMR-based metabolomics is the lack of rapid and accurate tools for absolute quantification of many metabolites. We developed, implemented, and evaluated an algorithm, AQUA (Automated Quantification Algorithm), for targeted metabolite quantification from complex H-1 NMR spectra. AQUA operates based on spectral data extracted from a library consisting of one standard calibration spectrum for each metabolite. It uses one preselected NMR signal per metabolite for determining absolute concentrations and does so by effectively accounting for interferences caused by other metabolites. AQUA was implemented and evaluated using experimental NMR spectra from human plasma. The accuracy of AQUA was tested and confirmed in comparison with a manual spectral fitting approach using the ChenomX software, in which 61 out of 67 metabolites quantified in 30 human plasma spectra showed a goodness-of-fit (r(2)) close to or exceeding 0.9 between the two approaches. In addition, three quality indicators generated by AQUA, namely, occurrence, interference, and positional deviation, were studied. These quality indicators permit evaluation of the results each time the algorithm is operated. The efficiency was tested and confirmed by implementing AQUA for quantification of 67 metabolites in a large data set comprising 1342 experimental spectra from human plasma, in which the whole computation took less than 1 s.

Published in

Analytical Chemistry
2018, volume: 90, number: 3, pages: 2095-2102
Publisher: AMER CHEMICAL SOC

SLU Authors

• Eriksson Röhnisch, Hanna

  • Department of Molecular Sciences, Swedish University of Agricultural Sciences
    

• Eriksson, Jan

  • Department of Molecular Sciences, Swedish University of Agricultural Sciences
    

• Müllner, Elisabeth

  • Department of Molecular Sciences, Swedish University of Agricultural Sciences
    

• Agback, Peter

  • Department of Molecular Sciences, Swedish University of Agricultural Sciences
    

• Sandström, Corine

  • Department of Molecular Sciences, Swedish University of Agricultural Sciences
    

• Moazzami, Ali

  • Department of Molecular Sciences, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Analytical Chemistry

Publication identifier

• DOI: https://doi.org/10.1021/acs.analchem.7b04324

Permanent link to this page (URI)

https://res.slu.se/id/publ/94459