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Ultrahigh-Resolution NMR with Water Signal Suppression for a Deeper Understanding of the Action of Antimetabolic Drugs on Diffuse Large B-Cell Lymphoma

  • Gildas Bertho
  • , Leonardo Lordello
  • , Xi Chen
  • , Covadonga Lucas-Torres
  • , Imed Eddine Oumezziane
  • , Cédric Caradeuc
  • , Mathieu Baudin
  • , Stéphanie Nuan-Aliman
  • , Catherine Thieblemont
  • , Véronique Baud
  • , Nicolas Giraud

Research output: Contribution to journalArticlepeer-review

Abstract

Ultrahigh-resolution NMR has recently attracted considerable attention in the field of complex samples analysis. Indeed, the implementation of broadband homonuclear decoupling techniques has allowed us to greatly simplify crowded 1H spectra, yielding singlets for almost every proton site from the analyzed molecules. Pure shift methods have notably shown to be particularly suitable for deciphering mixtures of metabolites in biological samples. Here, we have successfully implemented a new pure shift pulse sequence based on the PSYCHE method, which incorporates a block for solvent suppression that is suitable for metabolomics analysis. The resulting experiment allows us to record ultrahigh-resolution 1D NOESY 1H spectra of biofluids with suppression of the water signal, which is a crucial step for highlighting metabolite mixtures in an aqueous phase. We have successfully recorded pure shift spectra on extracellular media of diffuse large B-cell lymphoma (DLBCL) cells. Despite a lower sensitivity, the resolution of pure shift data was found to be better than that of the standard approach, which provides a more detailed vision of the exo-metabolome. The statistical analyses carried out on the resulting metabolic profiles allow us to successfully highlight several metabolic pathways affected by these drugs. Notably, we show that Kidrolase plays a major role in the metabolic pathways of this DLBCL cell line.

Original languageEnglish
Pages (from-to)1041-1051
Number of pages11
JournalJournal of Proteome Research
Volume21
Issue number4
DOIs
Publication statusPublished - 1 Apr 2022
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • DLBCL
  • Kidrolase
  • antimetabolic drugs
  • cancer cells
  • lymphoma
  • metabolomics analysis
  • metformin
  • pure shift NMR
  • water signal suppression

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