Abstract

Robust annotation of metabolites is a challenging task in metabolomics. Among available applications, 13C NMR experiment INADEQUATE determines direct 13C-13C connectivity unambiguously, offering indispensable information on molecular structure. Despite its great utility, it is not always practical to collect INADEQUATE data on every sample in a large metabolomics study because of its relatively long experiment time. Here, we propose an alternative approach that maintains the quality of information but saves experiment time. In this approach, individual samples in a study are first screened by 13C homonuclear J-resolved experiment (JRES). Next, JRES data are processed by statistical total correlation spectroscopy (STOCSY) to extract peaks that behave similarly among samples. Finally, INADEQUATE is collected on one internal pooled sample to select STOCSY peaks that originate from the same compound. We tested this concept using the 13C-labeled endometabolome of a model marine diatom strain incu-bated under various settings, intending to cover a range of metabolites produced under different external conditions. This scheme was able to extract known diatom metabolites proline, 2,3-dihydroxypropane-1-sulfonate (DHPS), b-1,3-glucan, choline, and glutamate. This pipeline also detected unknown compounds with structural information, which is valuable in metabolomics where a priori knowledge of metabolites is not always available. The ability of this scheme was seen even in sugar regions, which are usually chal-lenging in 1H NMR due to severe peak overlap. JRES and INADEQUATE were highly complementary; INADEQUATE provided directly-bonded 13C networks, whereas JRES linked INADEQUATE networks within the same compound but broken by nitrogen or sulfur atoms, highlighting the advantage of this integrated approach.(c) 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Keywords

Metabolomics; 13C; J-resolved; STOCSY; INADEQUATE; Phytoplankton

Published in

Journal of Magnetic Resonance
2023, Volume: 347, article number: 107365
Publisher: ACADEMIC PRESS INC ELSEVIER SCIENCE

SLU Authors

• Olofsson, Malin

  • Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences
    
  • University of Georgia

UKÄ Subject classification

Bioinformatics (Computational Biology)
Analytical Chemistry


Publication identifier

DOI: https://doi.org/10.1016/j.jmr.2022.107365

Permanent link to this page (URI)

https://res.slu.se/id/publ/121460