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

A major goal in natural product discovery programs is to rapidly dereplicate known entities from complex biological extracts. We demonstrate here that molecular networking, an approach that organizes MS/MS data based on chemical similarity, is a powerful complement to traditional dereplication strategies. Successful dereplication with molecular networks requires MS/MS spectra of the natural product mixture along with MS/MS spectra of known standards, synthetic compounds, or well-characterized organisms, preferably organized into robust databases. This approach can accommodate different ionization platforms, enabling cross correlations of MS/MS data from ambient ionization, direct infusion, and LC-based methods. Molecular networking not only dereplicates known molecules from complex mixtures, it also captures related analogues, a challenge for many other dereplication strategies. To illustrate its utility as a dereplication tool, we apply mass spectrometry-based molecular networking to a diverse array of marine and terrestrial microbial samples, illustrating the dereplication of 58 molecules including analogues.

The longstanding, successful use of herbal drug combinations in traditional medicine demands that we find a rationale for their comparative pharmacological and therapeutic superiority to isolated single constituents. The synergistic efficacy of these combinations can be evaluated and verified by Berenbaum's isobole method, followed by clinical studies performed in comparison with synthetic standard drugs. There are many examples of mono- and multi-extract combinations used presently, which exhibit synergistic efficiency based on multi-target mechanisms of action. Among the natural products, gallocatechins of green tea and curcuminoids of ginger are the presently favoured polyphenols for a possible future use in co-medication with antibiotics and standard anticancer drugs. The main targets were found to be COX 1+2, NF-κB, and membrane glycoproteins that belong to the ATP-binding cassette (ABC) transporter family. Copyright © 2010 Elsevier B.V. All rights reserved.

In polymicrobial infections, microbes can interact with both the host immune system and one another through direct contact or the secretion of metabolites, affecting disease progression and treatment options. The thick mucus in the lungs of patients with cystic fibrosis is highly susceptible to polymicrobial infections by opportunistic pathogens, including the bacterium Pseudomonas aeruginosa and the fungus Aspergillus fumigatus. Unravelling the hidden molecular interactions within such polymicrobial communities and their metabolic exchange processes will require effective enabling technologies applied to model systems. In the present study, MALDI-TOF and MALDI-FT-ICR imaging mass spectrometry (MALDI-IMS) combined with MS/MS networking were used to provide insight into the interkingdom interaction between P. aeruginosa and A. fumigatus at the molecular level. The combination of these technologies enabled the visualization and identification of metabolites secreted by these microorganisms grown on agar. A complex molecular interplay was revealed involving suppression, increased production, and biotransformation of a range of metabolites. Of particular interest is the observation that P. aeruginosa phenazine metabolites were converted by A. fumigatus into other chemical entities with alternative properties, including enhanced toxicities and the ability to induce fungal siderophores. This work highlights the capabilities of MALDI-IMS and MS/MS network analysis to study interkingdom interactions and provides insight into the complex nature of polymicrobial metabolic exchange and biotransformations.