Improving the chemical profiling of complex natural extracts by joint 13C NMR and LC-HRMS2 analysis and the querying of in silico generated chemical databases - Anses - Agence nationale de sécurité sanitaire de l’alimentation, de l’environnement et du travail Access content directly
Preprints, Working Papers, ... Year : 2024

Improving the chemical profiling of complex natural extracts by joint 13C NMR and LC-HRMS2 analysis and the querying of in silico generated chemical databases

Simon Remy
Alexis Kotland
  • Function : Author
Jane Hubert
  • Function : Author

Abstract

The chemical profiling of complex natural mixtures emerges as a pivotal avenue of investigation for the discovery of new bioactive compounds. It requires a dereplication step generally based either on liquid chromatography-high resolution tandem mass spectrometry (LC-HRMS2) or on nuclear magnetic resonance (NMR) to quickly identify known compounds. The high sensitivity of MS results in numerous but sometimes incorrect candidate compounds, whereas the greater universality of NMR leads to fewer but more accurate annotations. These two analytical techniques are rarely used in combination despite their complementarity. This study focuses on the chemical profiling of Larix decidua (Pinaceae) bark by joint LC-HRMS2 and 13C NMR data analysis and by querying custom in silico-generated chemical databases. MS-based dereplication allowed the annotation of 135 MS2 spectra with at least two different annotation tools. Twenty-five compounds were annotated in parallel by NMR spectra analysis, including two previously undescribed myrtenic acid derivatives. Sixteen of these compounds were already reported in the Pinaceae family. Twelve compounds were jointly annotated with a high confidence level by comparing LC-HRMS2 and 13C NMR dereplication results, including compounds not reported to date in Larix decidua. Our results show the benefits brought by combining LC-HRMS2 and 13C NMR data and by querying custom in silico chemical databases to enhance the confidence level of data annotation during the chemical profiling of complex natural extracts.
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Dates and versions

hal-04485136 , version 1 (01-03-2024)

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Julien Cordonnier, Simon Remy, Alexis Kotland, Ritchy Leroy, Pierre Darme, et al.. Improving the chemical profiling of complex natural extracts by joint 13C NMR and LC-HRMS2 analysis and the querying of in silico generated chemical databases. 2024. ⟨hal-04485136⟩
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