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The Two-Component System (TCS) AbrA1/A2 from Streptomyces coelicolor M145 is a negative regulator of antibiotic production and morphological differentiation. In this work we show that it is able to auto-regulate its expression, exerting a positive induction of its own operon promoter, and that its activation is dependent on the presence of iron. The overexpression of the abrA2 response regulator (RR) gene in the mutant DabrA1/A2 results in a toxic phenotype. The reason is an excess of phosphorylated AbrA2, as shown by phosphoablative and phosphomimetic AbrA2 mutants. Therefore, non-cognate histidine kinases (HKs) or small phospho-donors may be responsible for AbrA2 phosphorylation in vivo. The results suggest that in the parent strain S. coelicolor M145 the correct amount of phosphorylated AbrA2 is adjusted through the phosphorylation-dephosphorylation activity rate of the HK AbrA1. Furthermore, the ABC transporter system, which is part of the four-gene operon comprising AbrA1/A2, is necessary to de-repress antibiotic production in the TCS null mutant. Finally, in order to test the possible biotechnological applications of the DabrA1/A2 strain, we demonstrate that the production of the antitumoral antibiotic oviedomycin is duplicated in this strain as compared with the production obtained in the wild type, showing that this strain is a good host for heterologous antibiotic production. Thus, this genetically modified strain could be interesting for the biotechnology industry.
Noncoding RNAs are integral to a wide range of biological processes, including translation, gene regulation, host-pathogen interactions and environmental sensing. While genomics is now a mature field, our capacity to identify noncoding RNA elements in bacterial and archaeal genomes is hampered by the difficulty of de novo identification. The emergence of new technologies for characterizing transcriptome outputs, notably RNA-seq, are improving noncoding RNA identification and expression quantification. However, a major challenge is to robustly distinguish functional outputs from transcriptional noise. To establish whether annotation of existing transcriptome data has effectively captured all functional outputs, we analysed over 400 publicly available RNA-seq datasets spanning 37 different Archaea and Bacteria. Using comparative tools, we identify close to a thousand highly-expressed candidate noncoding RNAs. However, our analyses reveal that capacity to identify noncoding RNA outputs is strongly dependent on phylogenetic sampling. Surprisingly, and in stark contrast to protein-coding genes, the phylogenetic window for effective use of comparative methods is perversely narrow: aggregating public datasets only produced one phylogenetic cluster where these tools could be used to robustly separate unannotated noncoding RNAs from a null hypothesis of transcriptional noise. Our results show that for the full potential of transcriptomics data to be realized, a change in experimental design is paramount: effective transcriptomics requires phylogeny-aware sampling.