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Metabolomics with multi-block modelling of mass spectrometry and nuclear magnetic resonance in order to discriminate Haplosclerida marine sponges

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Abstract

A comprehensive metabolomic strategy, integrating 1H NMR and MS-based multi-block modelling in conjunction with multi-informational molecular networking, has been developed to discriminate sponges of the order Haplosclerida, well known for being taxonomically contentious. An in-house collection of 33 marine sponge samples belonging to three families (Callyspongiidae, Chalinidae, Petrosiidae) and four different genera (Callyspongia, Haliclona, Petrosia, Xestospongia) was investigated using LC–MS/MS, molecular networking, and the annotations processes combined with NMR data and multivariate statistical modelling. The combination of MS and NMR data into supervised multivariate models led to the discrimination of, out of the four genera, three groups based on the presence of metabolites, not necessarily previously described in the Haplosclerida order. Although these metabolomic methods have already been applied separately, it is the first time that a multi-block untargeted approach using MS and NMR has been combined with molecular networking and statistically analyzed, pointing out the pros and cons of this strategy.

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Data availability

The raw data files and preprocessed peak lists related to the LC–MS/MS analysis were deposited on the public MassIVE repository under the accession number: MSV000088423. The molecular network could be accessed on this link: https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=3012a113c5544344a8e31a156259234f.

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Acknowledgements

We thank Professor Jean-Claude Braekman for using his sponge extract collection given to the Museum National d’Histoire Naturelle.

Funding

This study received financial support from the Muséum National d’Histoire Naturelle de Paris (ATM) and CNRS-LIA FVLC-TEL.

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Authors and Affiliations

  1. Équipe “Chimie des Substances Naturelles” BioCIS, CNRS, Université Paris-Saclay, 5 rue J.-B. Clément, 92290, Châtenay-Malabry, France

    Mehdi A. Beniddir

  2. Muséum National d’Histoire Naturelle, Unité Molécules de Communication Et Adaptation des Micro-Organismes (MCAM-UMR 7245 MNHN-CNRS, Sorbonne Université), 57 rue Cuvier (CP54), 75005, Paris, France

    Laurence Le Moyec, Arlette Longeon, Alexandre Deville, Alain Blond & Marie-Lise Bourguet-Kondracki

  3. Université d’Evry Val d’Essonne-Université Paris-Saclay, Boulevard François Mitterrand, 91360, Evry, France

    Laurence Le Moyec

  4. Laboratoire CSPBAT, UMR7244 UFR Santé, Médecine et Biologie Humaine, Université Paris 13, 74 rue Marcel Cachin, 93017, Bobigny, France

    Mohamed N. Triba

  5. Institute of Marine Biochemistry (IMBC), Vietnam Academy of Science and Technology (VAST), 18 Hoang Quoc Viet, Caugiay, Hanoi, Vietnam

    Van Cuong Pham

  6. Naturalis Biodiversity Center, PO Box 9517, 2300 RA, Leiden, The Netherlands

    Nicole J. de Voogd

  7. Institute of Environmental Sciences, Leiden University, Einsteinweg 2, 2333 CC, Leiden, The Netherlands

    Nicole J. de Voogd

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  1. Mehdi A. Beniddir
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  2. Laurence Le Moyec
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  9. Marie-Lise Bourguet-Kondracki
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Correspondence to Mehdi A. Beniddir, Laurence Le Moyec or Marie-Lise Bourguet-Kondracki.

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Beniddir, M.A., Le Moyec, L., Triba, M.N. et al. Metabolomics with multi-block modelling of mass spectrometry and nuclear magnetic resonance in order to discriminate Haplosclerida marine sponges. Anal Bioanal Chem 414, 5929–5942 (2022). https://doi.org/10.1007/s00216-022-04158-5

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