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ИСТИНА ЦЭМИ РАН |
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Bacteria of class Mollicutes and in particular mycoplasmas represent good approximation of minimal cell due to the severe reduction of genome. Previous studies revealed that mycoplasmas feature very limited repertoire of transcriptional regulators and poorly react to different stimuli in perturbation models. These findings led to conclusion that the systems of gene expression regulation degraded in mycoplasmas along with the general reduction of genome. We applied a highthroughput method of the identification of transcription start sites and the quantitation of their activity with machine learning to construct the quantitative model of bacterial promoter on the model of Mycoplasma gallisepticum. The model was able to predict promoter strength from its sequence. Further we identified promoters, which predicted strength deviated from their measured activity. Thus we identified candidate promoters, which activity was putatively regulated. This group included the targets of few known regulators as well. Surprisingly we identified numerous regulated promoters. Further using genetic engineering we identified novel DNA sites and RNA structures, responsible for the activator or repressor effect on the promoters. We conclude that the gene expression regulation in mycoplasmas is complex. The regulated genes code for both stressresponse proteins and housekeeping proteins. The latter is of particular interest for synthetic biology since the control of housekeeping genes may be an essential function of cell. This work was funded by RSF grant 142400159.