Mining Indonesian Microbial Biodiversity for Novel Natural Compounds by a Combined Genome Mining and Molecular Networking Approach

• Main Authors: Ira Handayani, Hamada Saad, Shanti Ratnakomala, Puspita Lisdiyanti, Wien Kusharyoto, Janina Krause, Andreas Kulik, Wolfgang Wohlleben, Saefuddin Aziz, Harald Gross, Athina Gavriilidou, Nadine Ziemert, Yvonne Mast
• Format: Article
• Language: English
• Published: MDPI AG 2021-05-01
• Series: Marine Drugs
• Subjects: Indonesia; biodiversity; novel antibiotics; drug screening; bioactivity; gene cluster networking
• Online Access: https://www.mdpi.com/1660-3397/19/6/316

Indonesia is one of the most biodiverse countries in the world and a promising resource for novel natural compound producers. Actinomycetes produce about two thirds of all clinically used antibiotics. Thus, exploiting Indonesia’s microbial diversity for actinomycetes may lead to the discovery of novel antibiotics. A total of 422 actinomycete strains were isolated from three different unique areas in Indonesia and tested for their antimicrobial activity. Nine potent bioactive strains were prioritized for further drug screening approaches. The nine strains were cultivated in different solid and liquid media, and a combination of genome mining analysis and mass spectrometry (MS)-based molecular networking was employed to identify potential novel compounds. By correlating secondary metabolite gene cluster data with MS-based molecular networking results, we identified several gene cluster-encoded biosynthetic products from the nine strains, including naphthyridinomycin, amicetin, echinomycin, tirandamycin, antimycin, and desferrioxamine B. Moreover, 16 putative ion clusters and numerous gene clusters were detected that could not be associated with any known compound, indicating that the strains can produce novel secondary metabolites. Our results demonstrate that sampling of actinomycetes from unique and biodiversity-rich habitats, such as Indonesia, along with a combination of gene cluster networking and molecular networking approaches, accelerates natural product identification.