Planta Medica International Open 2017; 4(S 01): S1-S202
DOI: 10.1055/s-0037-1608247
Poster Session
Georg Thieme Verlag KG Stuttgart · New York

Multi informative molecular network to explore the chemodiversity and bioactivity of an atypical natural resource: entomopathogenic microrganisms

L Pellissier
1   School of Pharmaceutical Sciences, EPGL, University of Geneva, University of Lausanne, Rue Michel Servet 1, CH-1211, Geneva, Switzerland
,
S Toure
2   CNRS, Institut de Chimie des Substances Naturelles UPR 2301, University Paris-Saclay, 1 Avenue de la Terrasse,91198, Gif-sur-Yvette, France
,
PM Allard
1   School of Pharmaceutical Sciences, EPGL, University of Geneva, University of Lausanne, Rue Michel Servet 1, CH-1211, Geneva, Switzerland
,
V Eparvier
2   CNRS, Institut de Chimie des Substances Naturelles UPR 2301, University Paris-Saclay, 1 Avenue de la Terrasse,91198, Gif-sur-Yvette, France
,
JL Wolfender
1   School of Pharmaceutical Sciences, EPGL, University of Geneva, University of Lausanne, Rue Michel Servet 1, CH-1211, Geneva, Switzerland
› Author Affiliations
Further Information

Publication History

Publication Date:
24 October 2017 (online)

 

Entomopathogenic microorganisms (principally fungi and bacteria) are natural pathogens of insects involved in the regulation of host populations, representing an underexplored field of natural products (NPs) research. They have been shown to produce a wide range of bioactive secondary metabolites and thus appear as a promising source of new agents of biological, pharmaceutical and ecological interests (1). Our objective was to explore the chemodiversity and simultaneously investigate antimicrobial and insecticidal compounds within a unique collection of 57 enthomopathogenic strains collected on living infected insects. Recently, molecular networking (MN) has been established as a useful tool for the chemical exploration of complex extracts, since it enables the clustering of detected metabolites as structural families according to the similarity of their fragmentation patterns (tandem MS2 spectra) (2). Here, a multi-informative MN was built by overlaying different information layers (taxonomy, bioactivity) on top of the MN generated from the full collection of entomopathogenic fungi. This method allowed the organisation of 203'928 MS2 spectra into 821 clusters containing 5'784 nodes. By annotating the constructed MN against experimental and in silico spectral NPs databases (3), we could identify molecular families previously described in those organisms like beauveriolides or eniatins. Additionally, the exploration of the MN via the bioactivity mapping allowed to highlight clusters containing nodes from bioactive extracts. Compounds found in some of these clusters could be linked to previously isolated larvicidal and antibiotic secondary metabolites. The approach permitted to easily pinpoint unknown analogues of those compounds that are likely to be bioactive and the data generated will be used to target their isolation.

[1] Beemelmanns et al. Beilstein J Org Chem. 2016;12:314 – 27.

[2] Wang M et al. Nat Biotech. 2016;34:828 – 37.

[3] Allard PM et al. Anal Chem. 2016;88:3317 – 23.

Photo credits: ©Andreas Kay, 2016, https://www.flickr.com/photos/andreaskay/31115643631 (accessed March 2017)