Taxonomically informed metabolite annotation and data organization in natural products research

A Rutz; S Ollivier; D Olivier; J Bisson; M Dounoue-Kubo; A Gaudry; LM Quiros Guerrero; B David; J Boustie; J-L Wolfender; P-M Allard

doi:10.1055/s-0039-3399846

Planta Medica, Table of Contents

Planta Med 2019; 85(18): 1468
DOI: 10.1055/s-0039-3399846

Main Congress Poster

Poster Session 1

Taxonomically informed metabolite annotation and data organization in natural products research

A Rutz

¹School of Pharmaceutical Sciences, University of Geneva, University of Lausanne,, Rue Michel-Servet 1, 1211 Geneva, Switzerland

,

S Ollivier

¹School of Pharmaceutical Sciences, University of Geneva, University of Lausanne,, Rue Michel-Servet 1, 1211 Geneva, Switzerland

²CNRS, ISCR (Institut des Sciences Chimiques de Rennes), UMR 6226, Université de Rennes,, Rennes, France

,

D Olivier

¹School of Pharmaceutical Sciences, University of Geneva, University of Lausanne,, Rue Michel-Servet 1, 1211 Geneva, Switzerland

²CNRS, ISCR (Institut des Sciences Chimiques de Rennes), UMR 6226, Université de Rennes,, Rennes, France

,

J Bisson

³Center for Natural Product Technologies, Program for Collaborative Research in the Pharmaceutical Sciences (PCRPS) and Department of Medicinal Chemistry and Pharmacognosy, College of Pharmacy, University of Illinois at Chicago,, 833 South Wood Street, Chicago, Illinois 60612, United States

,

M Dounoue-Kubo

¹School of Pharmaceutical Sciences, University of Geneva, University of Lausanne,, Rue Michel-Servet 1, 1211 Geneva, Switzerland

,

A Gaudry

¹School of Pharmaceutical Sciences, University of Geneva, University of Lausanne,, Rue Michel-Servet 1, 1211 Geneva, Switzerland

,

LM Quiros Guerrero

¹School of Pharmaceutical Sciences, University of Geneva, University of Lausanne,, Rue Michel-Servet 1, 1211 Geneva, Switzerland

,

B David

⁴Green Mission Pierre Fabre, Branche Phytochimie et Biodiversité, Institut de Recherche Pierre FABRE,, 3, Avenue Hubert Curien - BP 31562 Toulouse, France

,

J Boustie

²CNRS, ISCR (Institut des Sciences Chimiques de Rennes), UMR 6226, Université de Rennes,, Rennes, France

,

J-L Wolfender

¹School of Pharmaceutical Sciences, University of Geneva, University of Lausanne,, Rue Michel-Servet 1, 1211 Geneva, Switzerland

,

P-M Allard

¹School of Pharmaceutical Sciences, University of Geneva, University of Lausanne,, Rue Michel-Servet 1, 1211 Geneva, Switzerland

› Author Affiliations

Abstract

Full Text

Natural products, more precisely defined as specialized metabolites, are by definition strongly linked to the taxonomical position of the producing organisms. Considering taxonomy when exploring natural products thus appears as an evidence. Such principles were already formulated in 1816 by De Candolle who postulated that 1) Plant taxonomy would be the most useful guide to man in his search for new industrial and medicinal plants and 2) Chemical characteristics of plants will be most valuable to plant taxonomy in the future. [1] We adhere to De Candolle’s postulate and aim to establish their validity using computational approaches.

Regarding the first postulate, we show that the consideration of taxonomic position is beneficial in the metabolite annotation process leading to a systematic improvement (> 50% of correct annotation at rank 1) of current in silico metabolite annotation solution (Sirius, MSFinder, CFM+Tremolo). [2] This increased confidence in metabolite annotation efficiently improves the natural products drug discovery process and should complement orthogonal information already shown to strengthen classical spectral scoring systems. [3],[4] Regarding the second postulate, we demonstrate the interest of considering the chemical dimension (structural or spectral relationships) when seeking to organize plants or lichens extracts. We present a novel metric, Spectral and Substructural Similarity- Informed Distance (SSS-ID) for such classification and compare it to classically established taxonomies (genetic material or morphological character-based organizations), demonstrating its interest. The principles and implementation as well as practical applications of such approaches will be discussed.

References

References
1 Candolle AP de. Essai sur les propriétées médicales des plantes, comparées avec leurs formes extérieures et leur classification naturelle. Paris: Chez Crochard, Libraire,; 1816. On Internet: http://www.biodiversitylibrary.org/bibliography/112422
2 Dounoue-Kubo M, Rutz A, Bisson J, Saesong T, Bagherri M, Ebrahimi SN. et al. Taxonomically informed scoring enhances confidence in natural products annotation. Front Plant Sci. 2019 (in preparation).
3 da Silva RR, Wang M, Nothias LF, JJJ van der Hooft, Caraballo-Rodríguez AM, Fox E. et al. Propagating annotations of molecular networks using in silico fragmentation. PLoS Comput Biol 2018; 14: 1-26.
4 Bach E, Szedmak S, Brouard C, Böcker S, Rousu J. Liquid-chromatography retention order prediction for metabolite identification. Bioinf 2018; 34: i875-i883. On Internet: https://academic.oup.com/bioinformatics/article/34/17/i875/5093227