Jane Hubert
email: jane.hubert@univ-reims.fr

Jean-Marc Nuzillard

Jean-Hugues Renault

Dereplication strategies in natural product research: How many tools and methodologies behind the same concept?

Keywords: Dereplication, natural products, metabolomics, drug discovery, taxonomic classification

Dereplication strategies in natural product research: How many tools and methodologies behind the same concept?

Introduction

Living beings provide a unique diversity of secondary metabolites that are still waiting to be investigated and exploited for the discovery of new drugs, cosmetic ingredients, nutraceutics or bio-sourced materials. The performance of natural product screening programs remains however strongly limited by the equipment, labor and time investments required for isolation and structural elucidation of novel metabolites with potent biological properties. Significant advances have been made over the last decades to improve the resolution and sensitivity of analytical methods for the study of small molecules in natural extracts. Very efficient hyphenation systems between separation and spectroscopic instruments now enable the identification of highly complex molecular structures even within complex mixtures of compounds. Despite these efforts, very serious issues, such as the frequent rediscovery of known compounds after time consuming purification and identification steps, the redundant investigation of taxonomically ambiguous microbial strains or the investigation of irrelevant crude materials regarding a selected biological application, still result in a considerable waste of time. Consequently, many pharmaceutical companies have considerably slowed down or even terminated their natural product research activities.

Nevertheless, the search for novel chemical structures within natural resources continues to be a crucial strategy for the discovery of novel therapeutic drugs. Moreover, remembering that more than 300 000 secondary metabolites have been identified so far from the biodiversity, it is obvious that new biological activities of known metabolites can be still put to light . Some of these known metabolites have only been structurally elucidated but never evaluated biologically. Among those that have already been engaged in one or even more specific bioassays, it is certain that a wide majority have not yet revealed all their biological potential, just because it remains impossible to test every compound on every known target in a reasonable amount of time. Furthermore, most in vitro bioassays are not relevant to in vivo or clinical conditions regarding either the activity or bioavailability of the compound under examination, not to mention that a metabolite with a specific activity in the pure state may show a different activity when present within a mixture Innovative strategies are therefore needed to significantly reduce the timeline of bioactive natural product discovery.

All evidence suggests that the most promising workflows for the chemical profiling of natural products should involve, at least in part, a dereplication procedure. Historically, the first definition of the term "dereplication" was given by [START_REF] Beutler | Dereplication of phorbol bioactives -Lyngbya majuscula and Croton cuneatus[END_REF] as "a process of quickly identifying known chemotypes" [START_REF] Beutler | Dereplication of phorbol bioactives -Lyngbya majuscula and Croton cuneatus[END_REF]. Their goal was to evaluate the activity of a range of terrestrial and marine plant extracts by using a simple phorbol dibutyrate (PDBu) receptor binding assay and to rapidly identify compounds responsible for this activity without investing time in traditional bioassay-guided fractionation or full structure elucidation procedures.

But what exactly lies behind the term "dereplication" more than twenty years later? Is this definition still relevant today within the context of natural product research? What does a dereplication process involve in terms of methods and techniques? For what purpose is such a strategy really useful? On which natural ressources is it currently applied? How much progress has been made in dereplication workflows over the last years?

In the present review, we would like to address these points by presenting a state-of-the-art report on the various dereplication approaches that have been used until now for the chemical profiling of natural products. A literature survey, covering the period 1990-2014, for the topic "dereplication" or "de-replication" in the Web of Science database revealed 358 hits. Upon closer examination, it emerged that the research areas covered by the matching studies not only include pharmacology/pharmacy, chemistry, or plant sciences, but also molecular biology, biotechnology, microbiology, and food science technology. Another important fact is the huge increase of published items every year, particularly since 2012, as well as the exponential growth of annual citations (Fig. 1). The literature survey was rigorously scrutinized in order to assess the function and usefulness of modern dereplication strategies for bioactive natural product discovery. Of course, the goal of this review is not to impose a definition or a specific way to perform natural product dereplication, but to highlight as objectively as possible that, depending on the natural resources under examination and on the final objectives, dereplication does not correspond to a single, clearly defined step-by-step procedure. In the 358 references found, 14 not dealing with natural products and 30 meeting abstracts were not taken into account. After a brief outline of the most common separation and analytical tools used for natural product dereplication, the critical role of natural metabolite databases and microbial strain libraries will be discussed. The studies covered by the literature survey have been organized in five distinct dereplication categories (annotated from DEREP1 to DEREP5), all involved in the search for novel bioactive substances of natural origin, but each following a particular workflow based on different starting materials, different separation and/or analytical procedures and different structural elucidation approaches.

A comparison chart summarizing these five categories (Table 1) shows that natural product dereplication can be performed as an untargeted workflow for the rapid identification of the major compounds whatever their chemical class in a single natural sample (DEREP1).

Frequently, this first strategy is also directly combined with biological assays to accelerate bioactivity-guided fractionation procedures (DEREP2). In other cases dereplication is fully embedded in untargeted metabolomic studies for the chemical profiling of natural extract collections (DEREP3) or for the targeted identification of predetermined compounds (desired or undesired) in natural samples (DEREP4). Finally a distinct dereplication category mainly based on gene-sequence analyses is increasingly used for the taxonomic identification of microbial strains (DEREP5).

Technical considerations

As dereplication refers to the rapid identification of known secondary metabolites, it is obvious that reliable, robust, rapid and sensitive analytical methods are required to perform an efficient dereplication procedure. With the remarkable developments of separation sciences, spectroscopic techniques, and high-throughput analytical technologies, valuable resources now exist to structurally characterize natural products, not only as pure compounds, but also within complex mixtures such as crude plant extracts or microbial culture media. This review will start by presenting the most common analytical tools used for the dereplication of natural products.

Since many detailed reviews are available for each technique, we will only briefly describe their strengths and weaknesses and focus on their benefits when applied to natural product dereplication.

Analytical chromatographic systems and hyphenation possibilities

High performance liquid chromatography (HPLC) remains by far the most commonly used technique to separate natural compounds at the analytical scale. HPLC is robust, easy-to-use, and applicable to a wide diversity of compounds, even starting from materials of complex chemical composition. More recently, ultra-high pressure liquid chromatography (UHPLC) has enabled a remarkable decrease of separation times while improving sensitivity, resolution, and reproducibility as compared to conventional HPLC. Both techniques, referred to as "LC" in the present paper, are currently applied to natural product analysis for various purposes including quality control, chemical characterization of crude plant extracts or high throughput fingerprinting (Wolfender et al. 2010[START_REF] Eugster | Combination of LC retention, high resolution TOF-MS information and web database search as dereplication tools in a chemotaxonomic study of Lippia spp[END_REF]. Thin layer chromatography (TLC or HPTLC) is another chromatographic technique frequently used for the preliminary analysis of natural extracts or for the rapid identification of known compounds within simplified mixtures obtained after the prefractionation of a crude natural sample [START_REF] Hook | Approaches to automating the dereplication of bioactive natural products -The key step in high throughput screening of bioactive materials from natural sources[END_REF][START_REF] Hook | Approaches to automating the dereplication of bioactive natural products -The key step in high throughput screening of bioactive materials from natural sources[END_REF][START_REF] Tan | Identification of the major constituents of Hypericum perforatum by LC/SPE/NMR and/or LC/MS[END_REF]. TLC-based bioautographic methods also enable the rapid localization of biologically active metabolites directly on TLC plates [START_REF] Hostettmann | Strategy in the search for new lead compounds and drugs from plants[END_REF][START_REF] Adhami | Combination of Bioautography with HPTLC-MS/NMR: A fast identification of acetylcholinesterase inhibitors from galbanum dagger[END_REF]) High speed counter current chromatography (HSCCC), centrifugal partition chromatography (CPC), supercritical fluid chromatography (SFC) or capillary electrophoresis (CE) are less commonly used analytical-scale separation system, and therefore will not be detailed here.

Among post-chromatographic hyphenation possibilities, simple ultraviolet (UV) or photodiode array (DAD) detectors remain limited to the interpretation of peak retention times or UV spectral fingerprints, but can nevertheless be employed in dereplication strategies for both identification and quantification purposes by using standard molecules as references [START_REF] Wolfender | HPLC in Natural Product Analysis: The Detection Issue[END_REF]. With the help of chemometric tools, LC/UV-DAD data can be processed by chromatographic band deconvolution, resulting in a significant improvement of chromatographic resolution. This method was recently used to identify several Cglycosylflavone isomers in the traditional herbal medicine Jatropha gossypifolia [START_REF] Pilon | Interval Multivariate Curve Resolution in the Dereplication of HPLC-DAD Data from Jatropha gossypifolia[END_REF]. However, due to the very limited structural information recovered from simple UV or DAD detection systems, other more powerful instruments are generally required to assess the structural diversity of natural products. Among them, mass spectrometry (MS) and nuclear magnetic resonance (NMR) described in the next section remain by far the favourites.

MS and NMR-based detection in natural product dereplication workflows

Mass spectrometry is a sensitive, rapid and accurate high throughput detection technique frequently used for the dereplication of natural products. The characterization of natural metabolites is established on the basis of exact mass, elemental composition, adducts and fragmentation patterns. Due to their high sensitivity, MS-based methods also enable the rapid detection of trace-level compounds, meaning that only small amounts of materials is required for successful analyses. LC coupled to high-resolution mass spectrometers such as Time-of-Flight (TOF), Fourier Transform (FT) or Orbitrap devices currently constitute the most powerful "high-throughpout screening" platforms for the on-line identification of metabolites in natural resources [START_REF] Strege | High-performance liquid chromatographic electrospray ionization mass spectrometric analyses for the integration of natural products with modern highthroughput screening[END_REF], Wolfender et al. 2000[START_REF] Shin | Analysis and screening of combinatorial libraries using mass spectrometry[END_REF][START_REF] Harrigan | Chemical and biological integrity in natural products screening[END_REF][START_REF] Bitzer | Accelerated dereplication of natural products, supported by reference libraries[END_REF][START_REF] Moss | Efficient structure elucidation of natural products in the pharmaceutical industry[END_REF][START_REF] Sashidhara | Various dereplication strategies using LC-MS for rapid natural product lead identification and drug discovery[END_REF][START_REF] Nielsen | Dereplication of Microbial Natural Products by LC-DAD-TOFMS[END_REF][START_REF] Sarker | Hyphenated techniques and their applications in natural products analysis[END_REF], Smyth et al. 2012[START_REF] Carter | NP/MS since 1970: from the basement to the bench top[END_REF]. Regarding hydrophobic or volatile small molecules, GC/MS is a more appropriate coupling, as demonstrated for instance for the dereplication of fatty acids [START_REF] Stavri | The antimycobacterial components of hops (Humulus lupulus) and their dereplication[END_REF] or flavor and aroma constituents [START_REF] Molyneux | Compound identification: A Journal of Agricultural and Food Chemistry perspective[END_REF].

Although MS is recognized as a key technology for the identification of natural products, some pitfalls still exist and these problems have to be solved to make MS-based dereplication methods more efficient [START_REF] Cech | Mass Spectrometry for Natural Products Research: Challenges, Pitfalls, and Opportunities[END_REF]. The major drawback arises from the important variabilities in the raw datasets obtained from one mass analyzer to another, which strongly hampers the creation of exchangeable MS/MS databases. The ionization processes taking place at the input of MS systems to desolvate and charge the analytes are also particularly critical because they vary with the type of ion source (electrospray or atmospheric pressure chemical ionization, for example), and may also vary through ionization suppression or enhancement under matrix effects. A high heterogeneity has been reported after the construction of a Collision-Induced-Dissociation MS/MS spectral library of ubiquitous flavonoids using either hybrid quadrupole time of flight (Q-TOF) or Ion Trap (IT) under various CID energy conditions (Wolfender et al. 2000). Perfect control of the parameters used to generate informative MS/MS spectra is thus needed for an efficient use of MS detection in the dereplication of natural products.

The interpretation of MS data is another critical issue that limits the speed of dereplication Molecular networking is also a promising computer-based approach to visualize and organize tandem mass spectrometry datasets and to automate database search for metabolite identification within complex mixtures [START_REF] Garg | Mass spectral similarity for untargeted metabolomics data analysis of complex mixtures[END_REF]. Such a tool relies on the observation that structurally similar metabolites share similar MS/MS fragmentation patterns. After collection of MS/MS spectra from a natural sample, the method consists in the construction of a molecular network by measuring the correlations within the produced dataset and establishing a Cytoscape visual representation of the chemical similarities between metabolites. Because structurally similar metabolites share similar fragmentation patterns, molecular families tend to cluster together within a network [START_REF] Nguyen | MS/MS networking guided analysis of molecule and gene cluster families[END_REF], Yang, Sanchez et al. 2013). The chemical investigation of natural resources by molecular networking has already proven to be a very useful complement to current MS-based dereplication strategies, for instance to highlight the chemical diversity among marine cyanobacteria (Winnikoff, Glukhov et al. 2014), to automatically detect structurally related nonribosomal peptides in filamentous fungi [START_REF] Klitgaard | Combining stable isotope labeling and Molecular networking for biosynthetic pathway characterization[END_REF], or to investigate interkingdom molecular interactions and metabolic exchange processes within microbial communities [START_REF] Moree | Interkingdom metabolic transformations captured by microbial imaging mass spectrometry[END_REF].

Another promising data mining workflow based on MS 2 precursor lists and targeting only signals related to bacterial metabolism was recently developed to characterize myxobacterial secondary metabolites [START_REF] Hoffmann | Improving Natural Products Identification through Targeted LC-MS/MS in an Untargeted Secondary Metabolomics Workflow[END_REF]. Even direct MS infusion can be used for natural product dereplication if assisted by computer tools. Such an approach was applied to the chemotyping of filamentous fungi strains from culture collections, and to subsequently classify unknown samples, thus avoiding redundancies in the selection of samples to be further investigated (Larsen 2005).

Nuclear Magnetic Resonance (NMR) is the other predominant detection technique used for the dereplication of natural products. It remains by far the most efficient to unambiguously elucidate complex structures of individual small molecules. With the advent of high field magnets, capillary and cryogenic probes, the lower sensitivity of NMR as compared to MSbased analytical methods has been progressively counterbalanced, and even the structure elucidation of minor compounds within mixtures becomes possible [START_REF] Hu | High-throughput natural product Chem methods and the application of the capillary NMR probe[END_REF]). In addition, sophisticated hardware and software products have been introduced in recent years to promote high-throughput NMR analyses, such as NMRbot Python scripts [START_REF] Clos | NMRbot: Python scripts enable high-throughput data collection on current Bruker BioSpin NMR spectrometers[END_REF]. As described in a recent review, these technical improvements along with hyphenation possibilities and their combination with computational treatments is progressively bringing NMR to the front of the powerful resources used in natural product dereplication strategies [START_REF] Halabalaki | Recent advances and new strategies in the NMR-based identification of natural products[END_REF].

It should nevertheless be emphasized that solvent and pH effects induce significant chemical shift variations across samples and are important drawbacks of NMR-based methods. These effects can strongly influence the efficiency of natural product dereplication procedures, as demonstrated for instance in a study investigating the molecular structures of caffeoyl quinic acid derivatives [START_REF] Pauli | Solvent effects in the structure dereplication of caffeoyl quinic acids[END_REF]. The limited spectral dispersion and the complexity of signal patterns, particularly in 1 H NMR spectra are also a major NMR challenge. In this sense it was pointed out in a recent paper that unambiguous 1 H NMR analyses for dereplication purposes require adequate precision when reporting chemical shifts or 1 H-1 H coupling constants from 1 H spectra, what is not so that easy when working with spectra of natural product mixtures (Pauli 2014). Diffusion ordered spectroscopy (DOSY) was proposed as an efficient alternative to simplify interpretation of NMR spectra of natural mixtures [START_REF] Williamson | New diffusion-edited NMR experiments to expedite the dereplication of known compounds from natural product mixtures[END_REF][START_REF] Stessman | Employing dereplication and gradient 1D NMR methods to rapidly characterize sponge-derived sesterterpenes[END_REF]. It has been shown for instance that 1D-DOSY when combined with 1D or 2D NMR experiments enables the acquisition of full spectral data of high molecular weight polysaccharides directly from crude hot water extracts of mushroom species without the need of any purification step [START_REF] Politi | Useful applications of DOSY experiments for the study of mushroom polysaccharides[END_REF]) Although natural organic compounds also contain carbon atoms, the use of 13 C NMR for the analysis of natural extracts remains largely underutilised, mainly because the low abundance of the 13 C isotope (1 %) and its low gyromagnetic ratio (25 % of that of 1 H) considerably reduce its detection sensitivity. Yet 13 C NMR presents several strong advantages for the analysis of natural mixtures: carbon atoms constitute a significant part of all organic molecules, and each 13 C position in a molecular structure corresponds to a single resonance on a broadband 1 H decoupled 13 C NMR spectrum.

In addition, the 13 C NMR spectral width is significantly higher than that of 1 H (220 ppm for 13 C and 12 ppm for 1 H), what also significantly reduces the occurrence of signal overlaps. Here again with the technical improvements of NMR spectrometers and the emergence of promising methodologies such as dynamic nuclear polarisation, it becomes possible to acquire 13 C spectra of metabolite mixtures with high resolution, good sensitivity, and in a reasonable time. In fact, an increasing amount of work using 13 C NMR for the analysis of natural products is emerging [START_REF] Clendinen | C-13 NMR Metabolomics: Applications at Natural Abundance[END_REF], Hubert et al. 2014[START_REF] Yona | 13C NMR detection of metabolic mixtures enhanced by dynamic nuclear polarization[END_REF].

Particular attention must also be paid to LC/NMR or LC/SPE/NMR methods, which combine the separation performance of liquid chromatography, the concentration effect of SPE, and the structural information provided by NMR. In the case of LC/SPE/NMR, the main advantage is that peak trapping on SPE cartridges significantly increases analyte concentration and thus provides access to 2D NMR data in a short time. The use of LC/NMR has rapidly expanded over the last years for the dereplication of natural products, especially for the direct comparison of metabolite profiles in small extracts using 1 H NMR before further investing in more laborious preparative-scale isolation processes. Such strategy greatly helps to avoid re-isolation of already known extract constituents. Several reviews published since the mid 1990s have detailed LC/NMR technical developments and their applications in the field of natural product research (Bobzin et al. 2000, Bobzin et al. 2000, Wolfender et al. 2001[START_REF] Wolfender | Liquid chromatography with ultraviolet absorbance-mass spectrometric detection and with nuclear magnetic resonance spectroscopy: a powerful combination for the on-line structural investigation of plant metabolites[END_REF], Jaroszewski 2005, Jaroszewski 2005, Wolfender et al. 2005[START_REF] Wolfender | The importance of hyphenated techniques in the discovery of new lead compounds from nature[END_REF][START_REF] Queiroz | Modern approaches in the search for new lead antiparasitic compounds from higher plants[END_REF][START_REF] Brkljaca | Recent advancements in HPLC-NMR and applications for natural product profiling and identification[END_REF][START_REF] Van Der Hooft | Structural elucidation of low abundant metabolites in complex sample matrices[END_REF].

The crucial role of natural product databases and computer tools

The success of a dereplication procedure to achieve the rapid characterization of known compounds greatly depends on the availability and quality of natural product databases or strain libraries. Many commercial or public databases of low molecular weight metabolites have been developed over the last 20 years [START_REF] Corley | Strategies for database dereplication of natural products[END_REF][START_REF] Lopez-Perez | NAPROC-13: a database for the dereplication of natural product mixtures in bioassay-guided protocols[END_REF][START_REF] Blunt | Data, H-1-NMR databases, data manipulation[END_REF][START_REF] Valli | Development of a Natural Products Database from the Biodiversity of Brazil[END_REF] Metabolite databases dedicated to marine and/or microbial molecular structures. This is not to mention all the locally-built libraries fragmented and scattered in many laboratories worldwide.

There is a crucial need today to expand and standardize these natural products databases.

A number of studies found in the literature survey were performed with the sole objective of database construction and implementation. Many of them were based on molecular structures, while others were focused on MS fragmentation patterns, bioactivity or taxonomic data [START_REF] Fredenhagen | An MS/MS library on an ion-trap instrument for efficient dereplication of natural products. Different fragmentation patterns for [M+H](+) and [M+Na](+) ions[END_REF][START_REF] Konishi | Molecular formula analysis by an MS/MS/MS technique to expedite dereplication of natural products[END_REF][START_REF] Liu | A method for the production and characterization of fractionated libraries from Chinese herbal formulas[END_REF][START_REF] Overy | Explanatory signal interpretation and metabolite identification strategies for nominal mass FIE-MS metabolite fingerprints[END_REF], Rojas-Cherto et al. 2012).

In addition to databases, computer tools and multivariate statistics have considerably improved the automation of analytical data processing and have substantially contributed to the current enhancement of natural product dereplication strategies [START_REF] Hansen | X-hitting: An algorithm for novelty detection and dereplication by UV spectra of complex mixtures of natural products[END_REF], Wolf and Siems 2007[START_REF] Jarussophon | Automated molecular formula determination by tandem mass spectrometry[END_REF][START_REF] Ng | Dereplication and de novo sequencing of nonribosomal peptides[END_REF][START_REF] Khosrokhavar | 2D Quantitative Structure-Property Relationship Study of Mycotoxins by Multiple Linear Regression and Support Vector Machine[END_REF], Wolfender et al. 2010[START_REF] Chlipala | CYANOS: A Data Management System for Natural Product Drug Discovery Efforts Using Cultured Microorganisms[END_REF][START_REF] Eugster | Retention time prediction for dereplication of natural products (CxHyOz) in LC-MS metabolite profiling[END_REF][START_REF] Kokkotou | An integrated approach using UHPLC-PDA-HRMS and 2D HSQC NMR for the metabolic profiling of the red alga Laurencia: Dereplication and tracing of natural products[END_REF]. Strong advances in the area of Computer-Assisted Structure Elucidation (CASE) systems, which combine artificial intelligence software with spectroscopic data to automatically generate molecular structures, have also dramatically accelerated structure elucidation procedures and have improved the reliability of dereplication results [START_REF] Jaspars | Computer assisted structure elucidation of natural products using twodimensional NMR spectroscopy[END_REF][START_REF] Steinbeck | Recent developments in automated structure elucidation of natural products[END_REF][START_REF] Elyashberg | Computer-assisted methods for molecular structure elucidation: realizing a spectroscopist's dream[END_REF].

Finally, spectral pattern recognition strategies based on the organization of spectral data according to chemical similarities are also powerful complements to natural product dereplication workflows. In this case spectroscopic data of metabolite mixtures are required along with spectra obtained from known standards, well-characterized organisms or prediction tools, preferably organized into databases. The utility of pattern recognition tools for natural product dereplication was for instance demonstrated for the chemical characterization of a diverse array of marine and terrestrial microbial samples using a MS-based method (Yang et al. 2013), or for the chemical characterization of plant extracts using 13 C NMR combined to hierarchical clustering analysis [START_REF] Hubert | Identification of natural metabolites in mixture: A pattern recognition strategy based on C-13 NMR[END_REF].

Dereplication and metabolomics: Where to draw the line?

Before entering the literature survey, some thought should be given to the term "chemical profiling" as well as to the obvious connection between dereplication and "metabolomics". Of course each of these two terms alone deserves detailed discussion, as their use can be ambigous depending on the context. For the sake of clarity, we would like to define the meaning of "chemical profiling" within the context of the present review, and also to highlight that a range of metabolomic studies are fully associated with natural metabolite dereplication workflows.

The term "chemical profiling" will be defined here in a very broad sense as the systematic detection and/or identification and/or quantification of a range of natural compounds.

Depending on the final purpose and on the analytical technique available, chemical profiling can be performed as a fingerprint analysis or as a targeted profile. A fingerprint analysis represents a global analysis where all detected metabolites are not necessarily identified. In a targeted chemical profiling approach, a predefined number of compounds or a particular chemical class of compounds is investigated and the molecular structures are identified.

Metabolomics, which is defined as the qualitative and quantitative analysis of the whole set of low molecular weight metabolites present in a biological system [START_REF] Fiehn | Metabolomics -the link between genotypes and phenotypes[END_REF], Zhang et al. 2012), also falls within the scope of a chemical profiling. However, more specifically, metabolomics is an interdisciplinary field that combines high resolution analytical systems, multivariate statistics and data mining tools, chemical and biological knowledge, and sometimes metabolic network modeling in an attempt to understand metabolic pathways, genefunction relationships, or states of an organism in response to environmental changes, drug perturbations, phylogeny, genotypic or phenotypic variabilities. Metabolomics workflows are strongly context-dependent and have been used over the last years in so many different fields that a range of experimental design methodologies have been developed with specific lines regarding sample preparation, data analysis or metabolite identification strategies. To keep it simple, we will only distinguish "targeted" from "untargeted" metabolomics studies. Typically, a targeted metabolomic approach is used to analyze a set of defined metabolites in a sample, while a much more comprehensive "untargeted" metabolomics approach consists of the detection and/or quantification of as many metabolites as possible without a priori knowledge of metabolite targets. In this latter case, samples and metabolites are generally classified according to spectral patterns. In the field of natural product research, both targeted and untargeted metabolomic approaches have already demonstrated strong potentialities, mainly for the quality control of herbal medicines, for the determination of chemical markers in plant species, or to assess the correlations between bioactivity and composition [START_REF] Fiehn | Metabolomics -the link between genotypes and phenotypes[END_REF][START_REF] Yuliana | Comprehensive Extraction Method Integrated with NMR Metabolomics: A New Bioactivity Screening Method for Plants, Adenosine A1 Receptor Binding Compounds in Orthosiphon stamineus Benth[END_REF][START_REF] Sheridan | The potential of metabolic fingerprinting as a tool for the modernisation of TCM preparations[END_REF], Zhang et al. 2012[START_REF] Cox | The utility of metabolomics in natural product and biomarker characterization[END_REF][START_REF] Seiber | Targeted Metabolomics: a New Section in the J of Agricultural and Food Chem[END_REF]. Of course the use of metabolite databases for the identification of the metabolites was a key aspect of all of these studies, and although not commented on explicitly, a dereplication process was in fact involved in the metabolomics study every time that a known metabolite was identified with the help of a database. It must be mentioned here that in dereplication, metabolite identification is often only a putative identification. Several articles have suggested ways to evaluate the level of confidence in metabolite identification [START_REF] Dunn | Mass appeal: metabolite identification in mass spectrometry-focused untargeted metabolomics[END_REF]. For instance the Chemical Analysis Working Group of the Metabolomics Standards Initiative (http://msi-workgroups.sourceforge.net) has defined four different confidence levels, with level 1 corresponding to confidently identified compounds by comparing multiple physicochemical properties of a pure standard to those of the metabolite of interest, level 2 corresponding to putatively annotated compounds, level 3 corresponding to putatively annotated compound classes and level 4 corresponding to unknown compounds [START_REF] Sumner | Proposed minimum reporting standards for chemical analysis[END_REF][START_REF] Creek | Metabolite identification: are you sure? And how do your peers gauge your confidence?[END_REF]. Implementation of such levels, mainly in the field of metabolomics, would also be useful for the natural product research community.

Dereplication of natural products: one concept involved in different strategies

Rapid identification of the major compounds in a single natural extract regardless of chemical class (DEREP1)

A very common way to perform dereplication of natural products today is to establish the chemical profile of a single natural resource using a hyphenated analytical system and to directly compare the obtained spectroscopic data with libraries of natural metabolites. This dereplication approach will be annotated "DEREP1" in the present review and is illustrated in Fig. 2. The starting natural resource is most often fractionated before the analytical step and the dereplication procedure can be achieved independently from bioassay experiments. In this way, a global view of the main chemical classes present in a natural species can be easily obtained and theoretically the major known compounds rapidly identified. Among the published works mentioning the term "dereplication" between 1990 and 2014, 50 studies summarized in Table 2 were based on a DEREP1 workflow (16 % of the total examined articles). More than two-thirds of these studies were carried out on plant extracts, while a minority delt with marine sponges, brown algae and cyanobacteria extracts. This distribution is logical considering that databases containing spectroscopic data of plant-derived metabolites are substantially more developed than those related to less explored marine or microbial species. The analytical tools involved in these studies were mainly based on high resolution LC/MS or NMR, and molecular structure assignments were usually performed by directly entering spectral data (exact mass or molecular formula in MS, chemical shifts in NMR, UV spectra or log P-based estimation of the chromatographic retention time in LC/DAD) into a database for automatic search. In several studies the strength of the procedure was reinforced by combining the analytical step with computational treatments in order to detect spectral patterns before searching molecular structures into metabolite databases [START_REF] Boudreau | Spectroscopic networking based dereplication applied to a strain of Moorea producens affords a fuller picture of its metabolome[END_REF], Hubert et al. 2014).

It can also be noted from Table 2 that, even if flavonoids and phenolic acids remain by far the most investigated compounds, a diversity of other chemical classes including anthrones, iridoids, terpenoids or fatty acids have also been successfully identified in these DEREP1

studies. Another advantage is that although dereplication does not provide original information on novel chemical structures, previously known compounds can still be identified in genus or species in which they are not a priori expected. For instance, flavonoid glycosides already known in a range of plant species were identified for the first time in the genus Lasiopetolum by using a LC/NMR-based DEREP1 procedure [START_REF] Timmers | On-line (HPLC-NMR) and Off-line Phytochemical Profiling of the Australian Plant, Lasiopetalum macrophyllum[END_REF]. Of course, the efficiency of such dereplication approach strongly depends on the quality of spectral libraries.

As mentioned above, significant efforts are currently being to develop and especially to standardize comprehensive databases containing structures and spectroscopic data (MS or NMR) of natural products.

Table 2. Dereplication strategies published from 1990 to 2014 using a DEREP1 workflow (from oldest to most recent).

Identified chemical classes and natural sources Analytical technique Reference

Representative set of 46 plant and microbe-derived metabolites

ESI-MS, API-MS Zhou and

Hamburger 1996 An alkaloid and a sesquiterpene previously purified NMR, computerassisted identification using the DNP However, the identification of new compounds by bioactivity-guided fractionation procedures requires a multi-step workflow, and often a great deal of work is done to purify the bioactive fractions and finally discover previously known compounds (Agarwal et al. 2014).

Consequently, dereplication also constitutes a key approach to overcome this frequent issue of known compound rediscovery in bioactivity-guided fractionation procedures.

In the literature survey, 52 studies (17 % of the total examined articles) were dedicated to the identification of natural metabolites on the basis of bioactivity-guided fractionation procedures.

These approaches will be annotated DEREP2 in the present paper. It is obvious that DEREP1 and DEREP2 workflows are not that different, except that DEREP2 ones are systematically focused on active natural samples as determined by biological assays. These studies are summarized in Table 3 and their common global workflow is illustrated in Fig. 3. dereplication was also reported useful when combined with bioactivity-guided fractionation procedures to rapidly set aside undesired constituents. For instance, the dereplication of sulphated polysaccharides was achieved in two studies investigating new potent anti-HIV compounds, because many of them were already extensively described in the literature as having an anti-HIV activity and thus were not considered as interesting compounds (Beutler et al. 1993[START_REF] Harnett | Anti-HIV activities of organic and aqueous extracts of Sutherlandia frutescens and Lobostemon trigonus[END_REF]. In this way, the tedious isolation of undesired constituents could be avoided, so that isolation, structure determination, and pharmacological investigations could be carried out only on bioactive and novel compounds.

It must be pointed out that most bioactivity-guided fractionation procedures are based on the theory that the activity shown by a mixture of metabolites results directly from the sum of activities of individual metabolites. However, it is becoming evident that the biological effects of a natural extract most likely result from a multi-component synergism [START_REF] Pavana | Effects of tephrosia purpurea aqueous seed extract on blood glucose and antioxidant enzyme activities in streptozotocin induced diabetic rats[END_REF][START_REF] Wagner | Synergy research: Approaching a new generation of phytopharmaceuticals[END_REF][START_REF] Yuliana | Metabolomics for the rapid dereplication of bioactive compounds from natural sources[END_REF]. Another limitation reported for bioactivity-guided fractionation is the irrelevance of most in vitro bioassays as compared to in vivo or clinical conditions regarding the efficacy and bioavailability of the samples under examination [START_REF] Houghton | Uses and abuses of in vitro tests in ethnopharmacology: visualizing an elephant[END_REF]. Potentially interesting compounds may also be missed just because they are not active on the selected biological assays. Research strategies for the discovery of novel bioactive molecules among natural products are thus progressively re-evaluated to consider more than one active constituent within natural resources [START_REF] Wang | Strategies and Techniques for Multi-Component Drug Design from Medicinal Herbs and Traditional Chinese Medicine[END_REF].

Dereplication procedures directly applied to crude extract collections (DEREP3)

The ability to directly identify molecular structures within crude extracts of natural products has become a critical step, either to cope with potent synergistic effects between constituents during biological evaluation, or even just to ensure that the material under examination presents an interest before going further with fractionation or purification steps. Here again, at the earliest stage of natural resource analysis, dereplication strategies have proved their value. It is obvious that the quick identification of known compounds directly in crude extracts is very ambitious because of the highly complex mixtures of non-fractionated samples. However, with the recent analytical advances, mainly in terms of resolution improvement and hyphenation capabilities, a range of efficient analytical systems are available today for the detailed analysis of complex mixtures [START_REF] Funari | Metabolomics, an optimized approach for the rational exploitation of Brazilian biodiversity: state of the art, new scenarios, and challenges[END_REF][START_REF] Michel | New Concepts, Experimental Approaches, and Dereplication Strategies for the Discovery of Novel Phytoestrogens from Natural Sources[END_REF][START_REF] Carter | NP/MS since 1970: from the basement to the bench top[END_REF][START_REF] Halabalaki | Recent advances and new strategies in the NMR-based identification of natural products[END_REF]). We will note as "DEREP3" all studies (n=50, 16 % of the total examined articles) found in the literature survey in which natural product dereplication consisted of the direct analysis of crude extract collections, either in combination with bioassays or not, but in all cases without fractionation or isolation of individual constituents. These studies are summarized in Table 4 and their workflow is illustrated in Fig. 4. hierarchical clustering analysis of GC/MS data obtained from 500 bacterial isolates allowed the selection of samples with a high probability of containing unknown natural products while avoiding the unnecessary analysis of samples of similar composition [START_REF] Boroczky | Cluster analysis as selection and dereplication tool for the identification of new natural compounds from large sample sets[END_REF]). In another interesting study, a collection of 30 New Zealand algae extracts were analyzed by a 2D

NMR method based on the addition of HSQC spectra to construct a "stacked HSQC digital mask" displaying strong similarities between spectra as intense peaks [START_REF] Popplewell | Colensolide A: a new nitrogenous bromophenol from the New Zealand marine red alga Osmundaria colensoi[END_REF]. In order to enhance the unique signals present, implying potentially novel compounds, the mask was substracted from each individual HSQC spectrum. In this way a new bromophenol, colensolide A, was isolated from the red algae Osmundaria colensoi together with the known lanosol (2,3-dibromo-4,5-dihydroxybenzyl alcohol) and four of its derivatives.

A range of untargeted metabolomic studies fit perfectly with DEREP3 strategies and provide interesting perspectives especially in the chemical profiling of underexplored marine or microbial extracts. Investigation of marine species and microbes are indeed developing at an exponential rate, mainly based on phylogenetic analyses for drug lead discovery, but the vast array of available species and strains together with their unusual metabolite profiles as compared to plant species make it difficult to evaluate their metabolite composition (Rocha- Martin et al. 2014). It was reported in 2012 that the investigation of filamentous fungi for anticancer drug leads resulted in the isolation and characterization of only 140 compounds over the four previous years, and that only 30% of these represented new chemical entities [START_REF] El-Elimat | De-inventing the wheel: Dereplication tools for natural products research[END_REF]. Dereplication of microbial culture collections using DEREP3-based metabolomic procedures can therefore be helpful to classify strain collections via a chemotyping approach.

Moreover, DEREP3-based strategies should accelerate the evaluation of metabolite diversity, mainly by avoiding redundancy in the identification of metabolites produced by the species under examination and by maximizing microbial natural product libraries that can be generated from collections of microorganisms [START_REF] Berdy | Bioactive microbial metabolites -A personal view[END_REF], Larsen et al. 2005[START_REF] Silver | Natural product screening for antibacterial agents[END_REF], Liu et al. 2012[START_REF] Tawfike | Metabolomics and Dereplication Strategies in Natural Products[END_REF][START_REF] Ito | Dereplication of microbial extracts and related analytical technologies[END_REF]. The direct analysis of fungi directly in fermentation extracts using LC/MS, pattern recognition tools and databases was reported in several papers as an efficient alternative to discover novel molecules with unknown activities [START_REF] Martin | Applying LC-MS de-replication strategies for the discovery of new natural products[END_REF][START_REF] El-Elimat | High-Resolution MS, MS/MS, and UV Database of Fungal Secondary Metabolites as a Dereplication Protocol for Bioactive Natural Products[END_REF]. In another example, a metabolomic approach combining HR-FTMS and NMR spectral data to PCA, HCA and OPLS-DA statistical treatments was used for the dereplication of metabolites in antitrypanosomally active spongeassociated bacterium Actinokineospora sp. obtained from four different fermentation conditions, the main objective being to identify the best culture one-strain-many-compounds condition for the isolation of novel bioactive metabolites (Abdelmohsen 2014).

Other interesting studies performing "co-cultures" of microorganisms to enhance the diversity of metabolite production via the activation of silent genes have followed a DEREP3 workflow to rapidly determine the presence of novel compounds while leaving aside those already known [START_REF] Butler | Identification of aluminium dioxalate in fungal cultures grown on vermiculite[END_REF], Bertrand et al. 2013). For example, ten known compounds were identified by dereplication in a crude extract of the sponge-derived actinomycetes Actinokineospora sp.

while three unexpected natural products not detected in the single culture were identified when Actinokineospora sp. was grown in co-culture with Nocardiopsis sp. (Dashti, Grkvic et al. 2014).

Another interesting aspect of DEREP3 strategies arises from the possibility to directly correlate biological properties to chromatographic and spectroscopic features of the crude analyzed samples. In this case, the purpose is to link the chemical characteristics of natural compounds to a specific biological activity. With the help of the ChemGPS-natural product database, it was shown that the inhibition of cyclooxygenase enzymes involved in inflammatory processes is frequently correlated with the presence of at least one ring in the metabolite structure.

Fragments exhibit structural rigidity, and compounds have a relatively large molecular volume [START_REF] Larsson | Expanding the ChemGPS chemical space with natural products[END_REF]. In another example, a screening technology combining on-line biological analysis with the resolution of LC/MS for structure elucidation was developed to directly analyze estrogen-receptor binding compounds in complex mixtures of a large plant extract library [START_REF] Schobel | High resolution screening of plant natural product extracts for estrogen receptor alpha and beta binding activity using an online HPLC-MS biochemical detection system[END_REF]. LC/MS signals of compounds from 22 phenolic extracts of extra virgin olive oil showing an activity against a breast cancer cell line were also identified by applying a correlation analysis between particular spectral features and the observed activity.

From this method a model was estimated to predict the activity of new samples [START_REF] Roldan | Identification of active compounds in vegetal extracts based on correlation between activity and HPLC-MS data[END_REF]. Optimization of such strategies in future research efforts could significantly accelerate the discovery of novel active substances and help our understanding of natural products with respect to structure-activity relationships.

Dereplication and targeted chemical profiling: two terms coming down to the same approach (DEREP4)

As mentioned above, in a targeted metabolite profiling approach a predefined number of compounds or a particular chemical class of compounds is investigated and the molecular structures are identified. Remembering that the literal definition of dereplication is "the rapid identification of known compounds", and assuming that the range of compounds investigated in targeted chemical profiling studies can also be known, it can be considered that both concepts are quite similar in many cases and that a targeted chemical profiling is necessarily a kind of dereplication, even if in contrast dereplication does not always correspond to a targeted chemical profiling approach.

In the literature survey, 57 studies (18 % of the total examined articles) involving dereplication were used a targeted chemical profiling approach. These studies are summarized in Table 5 and are noted as DEREP4 strategies. Their global workflow is given in Fig. 5. The main objective of DEREP4-based studies is either to analyze a particular group of molecules presenting a biological interest or on the contrary to identify potentially toxic or undesired constituents of crude natural extracts. For example, the dereplication of free sugars and polyols was performed by GC/MS in a study investigating novel natural sweeteners.

Among the sweet-tasting species analysed, the extracts containing high levels of these compounds were regarded as lower priority leads and thus directly removed from further consideration, enabling a significant time gain [START_REF] Chung | Dereplication of saccharide and polyol constituents of candidate sweet-tasting plants: Isolation of the sesquiterpene glycoside mukurozioside IIb as a sweet principle of Sapindus rarak[END_REF]. DEREP4 approaches are also commonly used to assess the quality of botanical drugs that must be checked for authentication, contamination, and identification of active substances or safety validation. Such procedures are based on the fact that all natural extracts, although highly complex, contain secondary metabolites which are specific to the species under study. During analytical data capture, the set of signals corresponding to these specific metabolites becomes a chemical fingerprint and the most characteristic signals are called "chemical markers". For instance three major concentrated stilbenoids quickly identified by a HPTLC/MS-based dereplication approach and exhibiting skin-anti-ageing properties were reported as relevant markers of a range of orchid species (Williams et al. 2012). Of course, concentration variability of these chemical markers in natural raw materials is inevitable due to inherent factors such as genotype variability, growing conditions, and climate or soil type. By tracking chemical markers over different steps of the manufacturing processes, the DEREP4 approach can assess this variability and minimize the potential composition heterogeneity of the final ingredient from one batch to another. This procedure forms an integral part of the standardization of botanical drugs, a major task which is necessary to adjust the concentration of the active substances and ensure a reproducible quality of the final products.

In the vast majority of targeted chemical profiling studies, natural metabolites were analyzed by mass spectrometry. This can be explained by the fact that a group of targeted compounds generally comprises structurally related molecules, consequently exhibiting very similar fragmentation patterns. The use of MS-based libraries containing fragmentation spectra and substructure data of the targeted compounds is thus very useful in the case of such dereplication approaches. For instance, a range of taxoids were successfully identified in a crude extract of Taxus wallichiana with the help of a MS library containing fragmentation spectra of 3 taxoid standards and substructure spectra of 139 previously reported toxoids [START_REF] Stefanowicz | Detection and partial structure elucidation of basic taxoids from Taxus wallichiana by electrospray ionization tandem mass spectrometry[END_REF]).

Similarly, it was found that retro-Diels-Alder rearrangement occurring during the MS fragmentation of a xanthone skeleton produce characteristic fragment ions which could be used to target prenylated xanthones in plant extracts such as Garcinia plants [START_REF] Zhou | Characterization of polyprenylated xanthones in Garcinia xipshuanbannaensis using liquid chromatography coupled with electrospray ionization quadrupole time-of-flight tandem mass spectrometry[END_REF]. The fragmentation pattern of flavonoids and their glycoside derivatives is also commonly used to dereplicate this class of compounds in crude natural extracts through targeted chemical profiling approaches [START_REF] Constant | A general method for the dereplication of flavonoid glycosides utilizing high performance liquid chromatography mass spectrometric analysis[END_REF][START_REF] Waridel | Evaluation of quadrupole time-of-flight tandem mass spectrometry and ion-trap multiple-stage mass spectrometry for the differentiation of C-glycosidic flavonoid isomers[END_REF][START_REF] Tchoumtchoua | Structureoriented UHPLC-LTQ Orbitrap-based approach as a dereplication strategy for the identification of isoflavonoids from Amphimas pterocarpoides crude extract[END_REF]. Mass accuracy and isotopic patterns are other data recovered from MS and MS n acquisition that can be used to build up libraries of natural metabolites for dereplication purposes [START_REF] Gomez-Romero | Automated identification of phenolics in plant-derived foods by using library search approach[END_REF].

It can be supposed that NMR-based metabolite profiling strategies are less efficient to perform the targeted chemical profiling of a predefined set of compounds, mainly because of the strong NMR signal overlaps observed when analysing a group of structurally related molecules.

However, several studies have demonstrated that this issue can be overcome by focusing on specific NMR signals of the targeted molecules. The screening of several brominated tyrosine derivatives named bastadins in a crude extract of the marine sponge Lanthella basta was performed for instance by 1 H NMR detection of their characteristic methoxy signals [START_REF] Franklin | Bastadin 20 and bastadin O-sulfate esters from Ianthella basta: Novel modulators of the Ry(1)R FKBP12 receptor complex[END_REF]. In the same way, diagnostic 1 H NMR signals of epoxide and conjugated diene moieties have been used to dereplicate macrocyclic trichothecenes in filamentous fungal species in the context of new anticancer lead discovery [START_REF] Sy-Cordero | Dereplication of macrocyclic trichothecenes from extracts of filamentous fungi through UV and NMR profiles[END_REF]).

Finally, it should be mentioned that targeted chemical profiling approaches not only enable the identification of previously known compounds, but also promote the discovery of additional novel metabolites, often corresponding to structural analogs of the predefined class of targeted compounds.

Molecular genetics and taxonomic dereplication of microbial strains (DEREP5)

Microbial natural products are a major resource for the development of novel drugs in pharmaceutical industry. However, the chemical characterization of microbial secondary metabolites is currently hampered by the laborious isolation processes when working with culture broths, and by the limited availability of structural and spectral libraries for microbial metabolites. In addition, microbial culture collections are extremely diverse, and thus a major challenge in their rational exploitation is the reduction of unnecessary or redundant testing of strains. In this sense, a range of dereplication tools mainly based on phenotypic characteristics or genetic differences have been developed to select microbial isolates at the species level.

Genetics and metabolic engineering are currently an integral part of these dereplication strategies. In recent years, the exploration of new taxa or ecological niches through metagenomic approaches have provided access to a large number of gene sequences that can now be investigated not only in well-studied bacteria but also in microorganisms that were previously neglected as natural ressources. The metagenome can be defined as a "collective genome" including isolated microbial DNA of all microorganisms present in a particular habitat [START_REF] Handelsman | Molecular biological access to the Chem of unknown soil microbes: A new frontier for natural products[END_REF]. "DEREP5" will thus denote all studies (n=22, 7 % of the total examined articles) found in the literature survey that involved a genetic approach for the dereplication of microbial strains. These studies are all included in Table 6 and their workflow is illustrated in Fig. 6. It must be specified that many DEREP5 studies were performed on microbial strains or isolates "as a whole" and did not systematically include a detailed analysis of the metabolites produced by the selected microorganisms. Nevertheless, such approaches have already led to the construction of extensive taxonomy-guided microbial natural product libraries, and thus enables for instance biodiversity surveys, strain prioritization, spatial distribution characterization, biosynthetic pathway elucidation, discovery of untapped sources of natural products, and detection of uncommon genera or species among microbes. Most of the current protocols for the taxonomic dereplication of microbial strains involve 16S rDNA gene sequencing or PCRfingerprinting of large collections of isolates followed by clustering analysis in order to correlate phylogenic similarities or to highlight discriminating strains. Once microorganisms have been taxonomically identified and revealed as promising leads, more sensitive analytical tools can be implemented to investigate metabolite profiles and potentially identify novel bioactive compounds. Strategies for in silico-guided identification of secondary metabolites by genome mining have been highlighted in several reviews [START_REF] Zerikly | Strategies for the discovery of new natural products by genome mining[END_REF], Helfrich et al. 2014, Helfrich 2014). Such strategies seem promising, but although novel compounds have been revealed in activity-driven screening of gene libraries, the frequency of the identified compounds is relatively low [START_REF] Novakova | Bioprospecting microbial metagenome for natural products[END_REF]. Research efforts are currently being reinforced to better understand microbial and chemical ecology, improve microbial culture conditions, high-throughput cultivation and performance of large-scale biological screening assays [START_REF] Ashforth | Bioprospecting for antituberculosis leads from microbial metabolites[END_REF][START_REF] Baltz | Streptomyces and Saccharopolyspora hosts for heterologous expression of secondary metabolite gene clusters[END_REF][START_REF] Penesyan | Development of Novel Drugs from Marine Surface Associated Microorganisms[END_REF]. Improvements in sequencing capabilities would also contribute to this area, particularly regarding primer design, increase of insert sizes and diversification of library hosts (alternative to Escherichia coli-based libraries).

It must finally be mentioned that the large majority of DEREP5 studies are aimed at screening novel antibacterial metabolites. Pathogen resistance to currently available antibiotics has indeed reached a very critical level. Over the last twenty years, most pharmaceutical companies have abandoned natural product chemical profiling investments in favor of large and cost-effective libraries of synthetic molecules. However, it is obvious that further improvements in genome sequencing technologies, together with the use of modern analytical systems, computer tools and application of reliable and pertinent biological assays will progressively solve the speedlimiting dereplication obstacles and lead these companies to refocus on natural product candidates [START_REF] Kirst | Developing new antibacterials through natural product research[END_REF]. Several reviews addressing the value and uses of molecular geneticsbased dereplication procedures applied to natural microbial metabolites are available in the literature [START_REF] Strobel | Useful products from rainforest microorganisms. Part 2. Unique bioactive molecules from endophytes[END_REF][START_REF] Knight | Diversifying microbial natural products for drug discovery[END_REF][START_REF] Leeds | Recent developments in antibacterial drug discovery: microbe-derived natural products -from collection to the clinic[END_REF], Liu et al. 2010[START_REF] Genilloud | Current approaches to exploit actinomycetes as a source of novel natural products[END_REF], Roemer 2011[START_REF] Genilloud | The re-emerging role of microbial natural products in antibiotic discovery[END_REF][START_REF] Sandiford | Advances in the arsenal of tools available enabling the discovery of novel lantibiotics with therapeutic potential[END_REF].

Conclusion

Dereplication procedures now play a prominant role in the field of natural product research.

The examination of all bibliographic references published from 1990 to 2014 which involve the concept of dereplication clearly reveals that five different dereplication strategies have been gradually developed to meet specific objectives. The common denominator between these studies is the willingness to accelerate the discovery of biologically active substances by improving characterization methods of natural resources. Most dereplication workflows have addressed this issue by using targeted or untargeted chemical profiling strategies, often in combination with biological assays and computer tools to assess the presence of active metabolites in natural samples, while others have used a taxonomic approach mainly based on genetic analyses for the classification and prioritization of samples. It is quite clear that the quality and completeness of small metabolite databases and microbial strain libraries remain the major impediments to high performance dereplication workflows. Consequently, the author can only stress the importance of finding a way to link collected spectral data between laboratories and finally homogenize these databases.

Fig. 1 .

 1 Fig. 1. Citation report obtained with the topic "dereplication" or "de-replication" from Thomson Reuters Web of Science. The latest 20 years up to December 2014 are displayed. (c) Thomson Reuters. All rights reserved

  strategies. Efforts are currently underway to develop the computerized treatment of mass spectral data. Software dedicated to the pre-processing of LC-MS data are now available and very useful for peak picking, ion extraction, organization and classification of data. They include for instance Bruker1 Data Analysis and Bruker1 Profile Analysis for Bruker, MassHunter for Agilent, MarkerLynx for Waters or publicly available software such as XCMS, MZmine, and METIDEA which can handle data from different instruments. Among the computer tools that assist metabolite identification, four data mining software are for instance described in a recent review[START_REF] Hufsky | New kids on the block: novel informatics methods for natural product discovery[END_REF]: MetFusion which uses substructures to assess spectral and chemical similarities, ISIS which is based on the prediction of fragmentation patterns for spectra comparison, FingerID which compares molecular structures after prediction of structural features, and FT-BLAST which is based on the use of a fragmentation tree database.

Fig. 2 .

 2 Fig. 2. DEREP1: an untargeted dereplication workflow aiming at the rapid identification of the major known compounds whatever their chemical class in a single natural sample

Fig. 3 .

 3 Fig. 3. DEREP2: A dereplication workflow for the acceleration of bioactivity-guided fractionation procedures

Fig. 4 .

 4 Fig. 4. DEREP3: a dereplication approach fully embedded in untargeted metabolomic analyses of natural extract collections

Fig. 5 .

 5 Fig. 5. DEREP4: a targeted dereplication workflow focused on the identification of a predefined group of known molecules

Fig. 6 .

 6 Fig. 6. DEREP5: A taxonomic dereplication workflow based on gene-sequence analyses of collection of microbial strains

Table 1 .

 1 Summary of the particular features distinguishing from DEREP1 to DEREP5 dereplication workflows.

		DEREP 1	DEREP 2	DEREP 3	DEREP 4	DEREP 5
		Identification
		of the major
	Goal	compounds in
		a single
		extract

  The more comprehensive databases include the Dictionary of

	organisms, the ACD/Labs NMR and ACD/Spectrus databases providing structural and spectral
	data of many thousands of synthetic and natural compounds, the UCSD Natural Products
	Database containing a large repository of microorganisms and exosymbionts, the Human
	Metabolome Database, Napralert, the NuBBE database dedicated to the Brasilian biodiversity,
	the UniProtKB/Swiss-Prot protein sequence database, KnapSack which is a comprehensive
	plant species-metabolite relationship database, and MarinLit, AntiMarin, AntiBase or Seaweed
	Natural Products (DNP) containing over 260,000 molecular structures, the Dictionary of
	Marine Natural Products containing around 48,000 molecular structures drawn from marine

Table 3 .

 3 Dereplication strategies published from 1990 to 2014 using a DEREP2 workflow (from oldest to most recent)

	Natural materials	Biological assays	Compounds	Analytical	Ref
			identified	technique(
				s)
	Lyngbya majuscula	Phorbol dibutyrate (PDBu)	Debromoaplysiatoxin	HPLC/UV	Beutler et al.
	(filamentous	receptor binding assay	in Lyngbya majuscula		1990
	cyanobacteria) and		and a complex of
	Croton cuneatus		potent phorbol esters
	(plant)		in Croton cuneatus
	Marine invertebrates	HIV inhibition test	Sulphated	Precipitatio	Beutler et al.
			polysaccharides (for	n method	1993
			removal)
	Thevetia ahouia	Cytotoxicity against a panel of	Cardenolide	UV, IR,	Decosterd et
	(wood)	human cancer cell lines	glycosides	MS, NMR	al. 1994
	Marine sponge Agelas	In vitro radioreceptor binding	Agelasines	NMR	deVries et al.
	axifera	assay on protein kinase C			1997
	Azadirachta excels	Cytotoxicity against KB cell	Meliacin-type	LC/ESI-	Cui et al.
	(stem bark)	lines	limonoids	MS	1998
	Semecarpus	Cytotoxicity against a panel of	Alkenyl catechols	HPLC/ESI-	Shin et al.
	anacardium	human cancer cell lines		MS	1999
	Five crude plant	Radioligand Receptor Binding	Galanthamine,	CPC, TLC Ingkaninan et
	extracts	Assays; AChE Inhibitory	theobromine, caffeine,		al. 2000
		Activity; in vitro anti-	fatty acids, phenolic
		asthmatic assay	acids and flavonoids
	Acnistus arborescens	Cytotoxicity against a panel of	Withanolides	NMR, MS	Minguzzi et
	(leaves)	human cancer cell lines			al. 2002
	Kielmeyera	Cytotoxicity against KB cell	Coumarins	LC/MS	Scio et al.
	albopunctata (bark)	lines			2003
	Plant extract spiked	Continuous-flow enzymatic	Phosphodiesterase	LC/fluoresc	Schenk et al.
	with 2 naturally	assay	(PDE) inhibitors	ence	2003
	occurring PDE
	inhibitors
	Artocarpus kemando	Cytotoxicity against KB cell	Prenylated flavonoids	HPLC/ESI-	Seo et al.
	(stem bark)	lines and DNA strand-scission		MS	2003
		activity
	Plant extract spiked	Continuous-flow enzymatic	Phosphatase inhibitors LC/MS	Schenk et al.
	with tetramisole	assay		(on-line)	2003
	In vitro marine culture	Antifungal activity against	Griseofulvin	ESI-IT/MS	Petit et al.
	of the strain	Candida albicans		and MSn	2004

Table 4 .

 4 Dereplication strategies published from 1990 to 2014 using a DEREP3 workflow (from oldest to most recent)

	Natural sources and strategy	Goal	Ref
	Screening of a collection of 116 marine sponges, ascidians, and	Extract prioritization	(Antonio and
	cnidarians for their antifungal activity against Candida albicans		Molinski
			1993)
	Screening of a collection of aqueous extracts of terrestrial plants,	Extract prioritization	(Cardellina
	cyanobacteria, and marine invertebrates for their AIDS-antiviral		et al. 1993)
	activity
	Screening of 38,000 extracts from plants and microorganisms for	Early identification and	(Ramakrishn
	antibacterial activity. Four promising extracts were retained after	elimination of known	a et al. 1999)
	chemical dereplication	compounds
	LC/MS analysis of a plant extract library combined on-line to an	Acceleration of bioactive	(Schobel et
	estrogen receptor binding assay	compound characterization	al. 2001)
	Curie-point pyrolysis MS and numerical taxonomic analysis of	Taxonomic classification	(Colquhoun
	44 deep-sea Rhodococci, clustering according to PyMS		et al. 2000)
	fingerprints and comparison with conventional microbial
	systematic classifications
	Single quadrupole LC/MS discrimination of novel from known	Early identification and	(Gilbert et al.
	compounds in crude biologically active extracts	elimination of known	2003)
		compounds
	Screening of fungal metabolites and mycotoxins in cultured	Early identification and	(Nielsen and
	extracts using a LC/UV/MS micro-scale method and a MS-	elimination of known	Smedsgaard
	library	compounds	2003)
	Screening of 16 Penicillium species grown in different matrixes,	Evaluation of strain chemical	(Nielsen et
	and evaluation of produced metabolites via a chemo-diversity	diversity	al. 2004)
	index
	Use of the ChemGPS database for a set of natural products	Investigation of correlations	(Larsson et
	exhibiting cyclooxygenase-1 and/or -2 (COX-1/2) inhibition	between structural features	al. 2005)
		and bioactivity
	Screening of 456 bacterial isolates from marine sponges by	Rapid selection of strains	(Dieckmann
	using Intact-Cell MALDI-TOF-MS and proteometric clustering	representing rare species for	et al. 2005)
	of the strains into 11 groups corresponding to particular species	subsequent chemical
		characterization
	Analysis of four different collections of the sponge genus Zyzzya	Search for anticancer	(Dijoux et al.
	and comparative testing of these compounds in the National	compounds	2005)
	Cancer Institute's 60 human tumor cell lines
	Analysis of 500 bacterial isolates by GC/MS combined to HCA	Early identification of known	(Boroczky et
		compounds	al. 2006)

Table 5 .

 5 Dereplication strategies published from 1990 to 2014 using a DEREP4 workflow (from oldest to most recent)

	Targeted compounds and natural sources	Analytical technique(s)	Ref
	Cucurbitacins in Iberis amara, Begonia plebeja and	Computer-Assisted	(Fuller et al. 1994)
	Gonystylus keithii	recognition of cytotoxicity
		profiles
	Elaiophylin and geldanamycin in a range of microbial	CPC/DAD, LC-MS	(Alvi et al. 1995)
	broths
	Two known antibiotics teicoplanin and phenelfamycin	LC/UV/ESI-MS/MALDI-	(Ackermann et al.
	in several microbial crude extracts	MS	1996)
	Bastadins from Lanthella basta	1 H NMR	(Franklin et al.
			1996)
	Free sugars and polyols in six sweet-tasting plant	GC/MS	(Chung et al.
	extracts		1997)
	Flavonoids and flavonoid glycosides using an aqueous	LC/MS and CID for	(Constant and
	extract of Eugenia jambos as a model	fragmentation patterns	Beecher 1995,
			Constant et al.
			1997)
	Potentially interfering polyphenols during the biological	LC/UV/MS	(Kinghorn et al.
	screening on in vitro cytotoxicity bioassays of 3000		1995, Cordell and
	plant extracts from tropical rainforests against a panel		Shin 1999,
	of human cancer cell lines.		Kinghorn et al.
			1999)
	Seven destruxins in the fungus Metarrhizium anisopliae HPLC/ESI-TOF-MS	(Potterat et al.
			2000)
	Taxoids from Taxus wallichiana	MS n	(Stefanowicz et al.
			2001)
	C-glycosidic flavonoids	LC/MS/MS using Q-TOF	(Waridel et al.
		and IT under various CID	2001)
		energy conditions
	Sesquiterpenes from two Indo Pacific sponges	NMR	(Stessman et al.
	Lendenfeldia frondosa and Hyrtios sp.		2002)
	Trichothecenes from seven microbial Trichoderma	LC/UV/vis and ESI-MS	(Nielsen et al.
	species grown on several solid and liquid media		2005)
	Betaxanthins from yellow-orange cactus pear fruits and	13 C NMR	(Stintzing et al.
	yellow Swiss chard petioles		2006)
	High molecular weight polysaccharides from several	DOSY-based NMR	(Politi et al. 2006)
	mushroom extracts
	Pentacyclic triterpenoids as their methyl esters	GC/ESI-MS	(Gu et al. 2006)
	(oleanolic acid, betulinic acid and ursolic acid) with
	potent anti-tubercular activity
	Saponins and acyclic sesquiterpene oligoglycosides in	LC/UV/ESI-MS, MS/MS	(Murgu and
	the fruits of Sapindus saponaria		Rodrigues 2006)
	Anti-inflammatory compound vicenin-2 in Leucopogon	LC/ESI-MS n	(de Moraes et al.
	ericoides		2007)

Table 6 .

 6 Molecular genetic-based strategies developed for the taxonomic dereplication of microbial natural products (DEREP5) Evaluation of the antimicrobial activity and sub-grouping of 217 streptomycetes isolates from the water surface microlayer in Norway by phylogenetic analysis and 16S rDNAs sequencing. 7 isolates with identical 16S rDNA sequences were further studied for the presence of PKS type I genes rRNA gene sequencing and whole cell MALDI-TOF-MS analysis DNA expression array analysis of Aspergillus nidulans in combination with legacy data to form a comprehensive gene expression compendium and data clustering to identify cross-chemistry between physically separate gene clusters Investigation of a collection of Aspergillus nomius strains from Brazil nuts including morphological characters, RAPD and AFLP profiles, partial β-tubulin and calmodulin nucleotide sequences, aflatoxin patterns, as well as tolerance to low water activity in cultured media

	Strategy	General goal	Ref
	Investigation of unusual strains of actinomycetes and	Detection of uncommon	(Donadio et al.
	filamentous fungi by reconstruction of gene clusters from	genera of soil microbes	2002)
	small segment of cloned DNA and preparation of large-
	insert libraries
	Identification of 26 closely related Streptomyces soil	Discrimination between	(Ritacco et al.
	isolates using rDNA sequencing, MIDI fatty acid analysis,	morphologically similar	2003)
	and LC-MS profiling of fermentation extract	strains
	Screening of 20 Micromonospora isolates from UK coastal	Investigation of strain	(Zhao et al.
	sediments, taxonomic classification by rDNA sequencing,	diversity	2004)
	fluorescent amplified fragment length polymorphism
	(AFLP), and Fourier transform infrared spectroscopy (FT-
	IR)
	Targeted analysis of polyketide synthases and	Characterization approach	(Ayuso et al.
	nonribosomal peptide synthetases amplified sequences in a	for Actinomycetes	2005)
	collection of wild-type Actinomycetes isolated from
	tropical soil samples evaluated for the production of
	antimicrobial activities
	Dereplication of microorganisms collected in 12	Investigation of biodiversity	(Huys et al.
	aquaculture sites in Southeast Asian and using PCR	and environmental	2007)
	fingerprinting	distribution of
		chloramphenicol-resistant
		(CmR) mesophilic
		heterotrophs

Ramakrishna NVS, Nadkarni SR, Bhat RG, Naker SD, Kumar E, Lal B (1999)