Antimicrobial screening, genome mining and molecular networkingbased metabolomics guided the discovery of novel bioactive compounds from actinomycetes derived from a marine polluted environment

Résumé

The discovery of new pharmaceutical products remains a major challenge for researchers. Natural products derived from microorganisms are known for their potent bioactivities and high structural diversity, which makes their identification complex, expensive and time-consuming. Notably, those derived from marine microorganisms provide a rich source of natural products of biological interest and marine actinobacteria in particular have been described as widely biodiverse and able to produce biologically active compounds. The marine environments of Algeria are microbiologically unexploited, and, therefore, we believe they could be an interesting source of bioactive microorganisms. In this matter, the Coast of Bejaia City is polluted, a factor that could affect the metabolic capabilities of its endogenous microorganisms. For these reasons, this biotope was explored for this work. Natural products are mostly isolated via conventional methods (e.g. HPLC purification, mass spectrometry, NMR spectrometry, etc.), a strategy that mostly leads to the rediscovery of known compounds, which represents a waste of time and resources. However, in recent years, huge progress has been made in metabolomics, genomic approaches and bioinformatic processing, which could help to identify already known compounds, allowing dereplication at an early stage of the discovery process, and improving the discovery process to guide toward novel molecules. In this context, my thesis focused on the investigation of antibacterial actinobacteria strains isolated from polluted marine environments using metabolomics,molecular networking and genome mining-based approaches. Overall, the present investigation indicates that the Coast of Bejaia could be a source of promising antagonistic actinobacteria, but the number of isolates was low, likely related to the pollution level in the samples. Statistical analysis has determined the best procedure to uncover actinobacteria in such environments. The obtained isolates were screened for their antimicrobial activities, and c.a. 10% showed activity against Gram-positive bacteria. Furthermore, the most interesting strain (Streptomyces RO-S4 strain) was explored via an integrated combination of metabolomic, molecular networking and genome mining-based approaches, and the results show that this strain generates only tricyclic fridamycin-like angucyclines. Further analyses were performed to explain the ring-opening and lactonization processes, and several hypotheses were generated. Hence, based on these findings, the combination of untargeted metabolomics and genomic approaches seems very promising to uncover new natural products and understand biosynthetic gene clusters involved in the expression of bioactive compounds.

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