Actinobacteria have attracted the attention of researchers in the most diverse fields of research, including medical and agrarian sciences. In particular, in the agricultural area, these bacteria stand out due to their potential as biological control agents and as producers of compounds with fungicidal and herbicidal properties. In fact, more than 65% of all compounds of microbial origin come from the phylum Actinobacteria. However, the rate of discovery of new chemical molecules is on a steep decline and some compounds of interest are produced in small quantities, making chemical analysis more difficult. Since 2002 when the first genome of an actinobacterium was published, there has been a growing use of genomic tools in an attempt to increase the rate of discovery of new bioactive compounds. In practice, these studies have shown that some secondary metabolites, coded in genomes, remain to be discovered, probably because these genes are not transcribed under conditions of conventional fermentations in the laboratory, being them, therefore, designated "silenced genes". As alternative, several strategies have been applied for the activation of silenced microbial pathways or overproduction of target compounds, such as modifications of the culture medium, heterologous and homologous expression, co-culture and ribosomal engineering. Among them, ribosomal engineering seems more viable due to the simplicity of the method and the fact that it does not require the global knowledge of the bacterial genome. In this sense, the objective of this project is to apply the ribosomal engineering strategy to activate or induce the expression of genes that may be involved in the synthesis of antibiotics.For this purpose, a candidate strain for a new species, Streptomyces sp. CAAT 7-52, that presents a discrete production of albocycline will be used as a model to obtain mutant strains overproductive of antibiotics. In addition, this study opens up unprecedented possibilities for the agro-technological exploration of this new lineage of Streptomyces with the identification of possible cryptic secondary metabolites through LC-MS / MS analysis of the generated mutants.
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