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Dynamic Modeling of Streptococcus pneumoniae Competence Provides Regulatory Mechanistic Insights Into Its Tight Temporal Regulation

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 cen...

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Autores principales: Weyder, Mathias, Prudhomme, Marc, Bergé, Mathieu, Polard, Patrice, Fichant, Gwennaele
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6066662/
https://www.ncbi.nlm.nih.gov/pubmed/30087661
http://dx.doi.org/10.3389/fmicb.2018.01637
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author Weyder, Mathias
Prudhomme, Marc
Bergé, Mathieu
Polard, Patrice
Fichant, Gwennaele
author_facet Weyder, Mathias
Prudhomme, Marc
Bergé, Mathieu
Polard, Patrice
Fichant, Gwennaele
author_sort Weyder, Mathias
collection PubMed
description 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.
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spelling pubmed-60666622018-08-07 Dynamic Modeling of Streptococcus pneumoniae Competence Provides Regulatory Mechanistic Insights Into Its Tight Temporal Regulation Weyder, Mathias Prudhomme, Marc Bergé, Mathieu Polard, Patrice Fichant, Gwennaele Front Microbiol Microbiology 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. Frontiers Media S.A. 2018-07-24 /pmc/articles/PMC6066662/ /pubmed/30087661 http://dx.doi.org/10.3389/fmicb.2018.01637 Text en Copyright © 2018 Weyder, Prudhomme, Bergé, Polard and Fichant. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Microbiology
Weyder, Mathias
Prudhomme, Marc
Bergé, Mathieu
Polard, Patrice
Fichant, Gwennaele
Dynamic Modeling of Streptococcus pneumoniae Competence Provides Regulatory Mechanistic Insights Into Its Tight Temporal Regulation
title Dynamic Modeling of Streptococcus pneumoniae Competence Provides Regulatory Mechanistic Insights Into Its Tight Temporal Regulation
title_full Dynamic Modeling of Streptococcus pneumoniae Competence Provides Regulatory Mechanistic Insights Into Its Tight Temporal Regulation
title_fullStr Dynamic Modeling of Streptococcus pneumoniae Competence Provides Regulatory Mechanistic Insights Into Its Tight Temporal Regulation
title_full_unstemmed Dynamic Modeling of Streptococcus pneumoniae Competence Provides Regulatory Mechanistic Insights Into Its Tight Temporal Regulation
title_short Dynamic Modeling of Streptococcus pneumoniae Competence Provides Regulatory Mechanistic Insights Into Its Tight Temporal Regulation
title_sort dynamic modeling of streptococcus pneumoniae competence provides regulatory mechanistic insights into its tight temporal regulation
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6066662/
https://www.ncbi.nlm.nih.gov/pubmed/30087661
http://dx.doi.org/10.3389/fmicb.2018.01637
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