10.3389/fmicb.2018.01637.s012 Mathias Weyder Mathias Weyder Marc Prudhomme Marc Prudhomme Mathieu Bergé Mathieu Bergé Patrice Polard Patrice Polard Gwennaele Fichant Gwennaele Fichant Image_8_Dynamic Modeling of Streptococcus pneumoniae Competence Provides Regulatory Mechanistic Insights Into Its Tight Temporal Regulation.PDF Frontiers 2018 bacterial competence negative and positive feedback loops dynamic modeling ordinary differential equations transcriptional network 2018-07-24 08:18:56 Figure https://frontiersin.figshare.com/articles/figure/Image_8_Dynamic_Modeling_of_Streptococcus_pneumoniae_Competence_Provides_Regulatory_Mechanistic_Insights_Into_Its_Tight_Temporal_Regulation_PDF/6854105 <p>In the human pathogen Streptococcus pneumoniae, the gene regulatory circuit leading to the transient state of competence for natural transformation is based on production of an auto-inducer that activates a positive feedback loop. About 100 genes are activated in two successive waves linked by a central alternative sigma factor ComX. This mechanism appears to be fundamental to the biological fitness of S. pneumoniae. We have developed a knowledge-based model of the competence cycle that describes average cell behavior. It reveals that the expression rates of the two competence operons, comAB and comCDE, involved in the positive feedback loop must be coordinated to elicit spontaneous competence. Simulations revealed the requirement for an unknown late com gene product that shuts of competence by impairing ComX activity. Further simulations led to the predictions that the membrane protein ComD bound to CSP reacts directly to pH change of the medium and that blindness to CSP during the post-competence phase is controlled by late DprA protein. Both predictions were confirmed experimentally.</p>