A Real-Life Reproducibility Assessment for NMR Metabolomics

Nuclear magnetic resonance (NMR) metabolomics is currently popular enough to attract both specialized and non-specialized NMR groups involving both analytical trained personnel and newcomers, including undergraduate students. Recent interlaboratory studies performed by established NMR metabolomics g...

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Bibliographic Details
Main Authors: Cristina Stavarache, Alina Nicolescu, Cătălin Duduianu, Gabriela Liliana Ailiesei, Mihaela Balan-Porcăraşu, Mihaela Cristea, Ana-Maria Macsim, Oana Popa, Carmen Stavarache, Anca Hîrtopeanu, Lucica Barbeş, Raluca Stan, Horia Iovu, Calin Deleanu
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Diagnostics
Subjects:
Online Access:https://www.mdpi.com/2075-4418/12/3/559
Description
Summary:Nuclear magnetic resonance (NMR) metabolomics is currently popular enough to attract both specialized and non-specialized NMR groups involving both analytical trained personnel and newcomers, including undergraduate students. Recent interlaboratory studies performed by established NMR metabolomics groups demonstrated high reproducibility of the state-of-the-art NMR equipment and SOPs. There is, however, no assessment of NMR reproducibility when mixing both analytical experts and newcomers. An interlaboratory assessment of NMR quantitation reproducibility was performed using two NMR instruments belonging to different laboratories and involving several operators with different backgrounds and metabolomics expertise for the purpose of assessing the limiting factors for data reproducibility in a multipurpose NMR environment. The variability induced by the operator, automatic pipettes, NMR tubes and NMR instruments was evaluated in order to assess the limiting factors for quantitation reproducibility. The results estimated the expected reproducibility data in a real-life multipurpose NMR laboratory to a maximum 4% variability, demonstrating that the current NMR equipment and SOPs may compensate some of the operator-induced variability.
ISSN:2075-4418