Nature offered mankind the first golden era of discovery of novel antimicrobials based on
the ability of eukaryotes or micro-organisms to produce such compounds. The microbial world proved
to be a huge reservoir of such antimicrobial compounds which play important functional roles in every
environment. However, most of those organisms are still uncultivable in a classical way, and therefore,
the use of extended culture or DNA based methods (metagenomics) to discover novel compounds
promises usefulness. In the past decades, the advances in next-generation sequencing and bioinformatics
revealed the enormous diversity of the microbial worlds and the functional repertoire available for
studies. Thus, data-mining becomes of particular interest in the context of the increased need for new
antibiotics due to antimicrobial resistance and the rush in antimicrobial discovery. In this review, an
overview of principles will be presented to discover new natural compounds from the microbiome. We
describe culture-based and culture-independent (metagenomic) approaches that have been developed to
identify new antimicrobials and the input of those methods in the field as well as their limitations.
Keywords: Antimicrobial peptides, Metagenomics, Data mining, Bioinformatics, Microbiome, Antimicrobials agents.
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