Effective approaches to discover new microbial metabolites in a large strain library
Author(s) -
Mitja M. Zdouc,
Marianna Iorio,
Kristiina Vind,
Matteo Simone,
Stefania Serina,
Cristina Brunati,
Paolo Monciardini,
Arianna Tocchetti,
Guadalupe S. Zarazúa,
Max Crüsemann,
Sonia I. Maffioli,
Margherita Sosio,
Stefano Donadio
Publication year - 2021
Publication title -
journal of industrial microbiology and biotechnology
Language(s) - English
Resource type - Journals
eISSN - 1476-5535
pISSN - 1367-5435
DOI - 10.1093/jimb/kuab017
Subject(s) - streptomyces , computational biology , metabolite , strain (injury) , selection (genetic algorithm) , small molecule , biology , secondary metabolite , microbiology and biotechnology , biochemical engineering , bacteria , computer science , biochemistry , genetics , engineering , gene , artificial intelligence , anatomy
Natural products have provided many molecules to treat and prevent illnesses in humans, animals and plants. While only a small fraction of the existing microbial diversity has been explored for bioactive metabolites, tens of thousands of molecules have been reported in the literature over the past 80 years. Thus, the main challenge in microbial metabolite screening is to avoid the re-discovery of known metabolites in a cost-effective manner. In this perspective, we report and discuss different approaches used in our laboratory over the past few years, ranging from bioactivity-based screening to looking for metabolic rarity in different datasets to deeply investigating a single Streptomyces strain. Our results show that it is possible to find novel chemistry through a limited screening effort, provided that appropriate selection criteria are in place.
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