The development of new drugs will certainly benefit from an ever improving knowledge of the living beings chemistry. However, identification of drugable molecules within the immense biodiversity of forests, soils or oceans still requires considerable investments in technical equipments, time and human resources. An important part of this process is the quick identification of known substances in order to concentrate the efforts on the discovery of new ones. A range of "dereplication" procedures are currently emerging to meet this challenge as key strategies to improve the performance of natural product screening programs. Initially defined in 1990 as "a process of quickly identifying known chemotypes", dereplication is today a not so univocal concept and has evolved over the last years in different ways. The present review covers all dereplication-related sudies in natural product research from 1990 to 2014.Its writing brought to light five distinct dereplication workflows that can be characterized by the nature of starting materials, by the key analytical technique, and above all by the final objective. Dereplication can be used as an untargeted workflow for the rapid identification of the major compounds whatever their chemical class in a single sample or for the acceleration of bioactivity-guided fractionation procedures. In other cases dereplication is fully integrated in metabolomic studies for the untargeted chemical profiling of natural extract collections or for the targeted identification of a predetermined class of metabolites. Finally a quite distinct dereplication approach mainly based on gene-sequence analyses is frequently used for the taxonomic identification of microbial strains.

Rhamnolipids produced by the bacteria Pseudomonas aeruginosa are known as very efficient biosurfactant molecules. They are used for a wide range of industrial applications, especially in food, cosmetics and pharmaceutical formulations as well as in bioremediation of pollutants. In this paper, the role of rhamnolipids as novel molecules triggering defence responses and protection against the fungus Botrytis cinerea in grapevine is presented. The effect of rhamnolipids was assessed in grapevine using cell suspension cultures and vitro-plantlets. Ca 2+ influx, mitogenactivated protein kinase activation and reactive oxygen species production form part of early signalling events leading from perception of rhamnolipids to the induction of plant defences that include expression of a wide range of defence genes and a hypersensitive response (HR)-like response. In addition, rhamnolipids potentiated defence responses induced by the chitosan elicitor and by the culture filtrate of B. cinerea. We also demonstrated that rhamnolipids have direct antifungal properties by inhibiting spore germination and mycelium growth of B. cinerea. Ultimately, rhamnolipids efficiently protected grapevine against the fungus.We propose that rhamnolipids are acting as microbeassociated molecular patterns (MAMPs) in grapevine and that the combination of rhamnolipid effects could participate in grapevine protection against grey mould disease.

Because of their highly complex metabolite profile, the chemical characterization of bioactive natural extracts usually requires time-consuming multistep purification procedures to achieve the structural elucidation of pure individual metabolites. The aim of the present work was to develop a dereplication strategy for the identification of natural metabolites directly within mixtures. Exploiting the polarity range of metabolites, the principle was to rapidly fractionate a multigram quantity of a crude extract by centrifugal partition extraction (CPE). The obtained fractions of simplified chemical composition were subsequently analyzed by (13)C NMR. After automatic collection and alignment of (13)C signals across spectra, hierarchical clustering analysis (HCA) was performed for pattern recognition. As a result, strong correlations between (13)C signals of a single structure within the mixtures of the fraction series were visualized as chemical shift clusters. Each cluster was finally assigned to a molecular structure with the help of a locally built (13)C NMR chemical shift database. The proof of principle of this strategy was achieved on a simple model mixture of commercially available plant secondary metabolites and then applied to a bark extract of the African tree Anogeissus leiocarpus Guill. & Perr. (Combretaceae). Starting from 5 g of this genuine extract, the fraction series was generated by CPE in only 95 min. (13)C NMR analyses of all fractions followed by pattern recognition of (13)C chemical shifts resulted in the unambiguous identification of seven major compounds, namely, sericoside, trachelosperogenin E, ellagic acid, an epimer mixture of (+)-gallocatechin and (-)-epigallocatechin, 3,3'-di-O-methylellagic acid 4'-O-xylopyranoside, and 3,4,3'-tri-O-methylflavellagic acid 4'-O-glucopyranoside.