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Volume 218, 2019
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An integrated approach for mixture analysis using MS and NMR techniques

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We suggest an improved software pipeline for mixture analysis. The improvements include combining tandem MS and 2D NMR data for a reliable identification of the constituents in an algorithm based on network analysis aiming for a robust and reliable identification routine. An important part of this pipeline is the use of open-data repositories, although it is not totally reliant on them. The NMR identification step emphasizes robustness and is less sensitive towards changes in data acquisition and processing than existing methods. The process starts with LC-ESI-MSMS based molecular network dereplication using data from the GNPS collaborative collection. We identify closely related structures by propagating structure elucidation through edges in the network. Those identified compounds are added on top of a candidate list for the following NMR filtering method that predicts HSQC and HMBC NMR data. The similarity of the predicted spectra of the set of closely related structures to the measured spectra of the mixture sample is taken as one indication of the most likely candidates for its compounds. The other indication is the match of the spectra to clusters built by a network analysis from the spectra of the mixture. The sensitivity gap between NMR and MS is anticipated and it will be reflected naturally by the eventual identification of fewer compounds, but with a higher confidence level, after the NMR analysis step. The contributions of the paper are an algorithm combining MS and NMR spectroscopy and a robust nJCH network analysis to explore the complementary aspects of both techniques. This delivers good results, even if a perfect computational separation of the compounds in the mixture is not possible. All of the scripts are freely available to aid studies such as with plants, marine organisms, and microorganism natural product chemistry and metabolomics, as those are the driving forces for this project.

Graphical abstract: An integrated approach for mixture analysis using MS and NMR techniques

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Publication details

The article was received on 04 Dec 2018, accepted on 07 Feb 2019 and first published on 08 Feb 2019

Article type: Paper
DOI: 10.1039/C8FD00227D
Faraday Discuss., 2019,218, 339-353

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    An integrated approach for mixture analysis using MS and NMR techniques

    S. Kuhn, S. Colreavy-Donnelly, J. Santana de Souza and R. M. Borges, Faraday Discuss., 2019, 218, 339
    DOI: 10.1039/C8FD00227D

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