Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Weyder M

PROVIDER: S-EPMC6066662 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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

Weyder Mathias M Prudhomme Marc M Bergé Mathieu M Polard Patrice P Fichant Gwennaele G

Frontiers in microbiology 20180724

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 ...[more]

PMID: 30087661

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Project description:Pneumococcal bacteriocins (pneumocins) are antibacterial toxins that mediate intra-species competition within the human host. However, the triggers of pneumocin expression are poorly understood. Using RNA-sequencing, we mapped the regulon of the pneumocin cluster (blp) of Streptococcus pneumoniae D39. Furthermore, by analogy with pneumococcal competence, we show that several antibiotics activate the blp-genes. Using real-time gene expression measurements we show that while the promoter driving expression of the two-component regulatory system blpR/H is constitutive, the remaining blp-promoters that control pneumocin expression, immunity and the inducer peptide BlpC, are pH-dependent and induced in the late exponential phase. Intriguingly, competence for genetic transformation, mediated by the paralogous ComD/E two-component quorum system, is induced by the same environmental cues. To test for interplay between these regulatory systems, we quantified the regulatory response to the addition of synthetic BlpC and competence-stimulating peptide (CSP). Supporting the idea of such interplay, we found that immediately upon addition of CSP, the blp-promoters were activated in a comD/E-dependent manner. After a delay, blp-expression was highly induced and was strictly dependent on blpRH and blpC. This raised the question of the mechanism of BlpC export, since bioinformatic analysis showed that the genes encoding the putative exporter for BlpC, blpAB, are not intact in strain D39 and most other strains. By contrast, all sequenced pneumococcal strains contain intact comAB genes, encoding the transport system for CSP. Consistent with the idea that comAB mediate BlpC export, we finally show that high-level expression of the blp-genes requires comAB. Together, our results demonstrate that regulation of pneumocin expression is intertwined with competence, explaining why certain antibiotics induce blp-expression. Antibiotic-induced pneumocin expression might therefore have unpredictable consequences on pneumococcal colonization dynamics by activating genes that mediate intra-specific interference competition.

Project description:Streptococcus thermophilus is a lactic acid bacterium adapted toward growth in milk and is a vital component of starter cultures for milk fermentation. Here, we combine genome-scale metabolic modeling and transcriptome profiling to obtain novel metabolic insights into this bacterium. Notably, a refined genome-scale metabolic model (GEM) accurately representing S. thermophilus CH8 metabolism was developed. Modeling the utilization of casein as a nitrogen source revealed an imbalance in amino acid supply and demand, resulting in growth limitation due to the scarcity of specific amino acids, in particular sulfur amino acids. Growth experiments in milk corroborated this finding. A subtle interdependency of the redox balance and the secretion levels of the key metabolites lactate, formate, acetoin, and acetaldehyde was furthermore identified with the modeling approach, providing a mechanistic understanding of the factors governing the secretion product profile. As a potential effect of high expression of arginine biosynthesis genes, a moderate secretion of ornithine was observed experimentally, augmenting the proposed hypothesis of ornithine/putrescine exchange as part of the protocooperative interaction between S. thermophilus and Lactobacillus delbrueckii subsp. bulgaricus in yogurt. This study provides a foundation for future community modeling of food fermentations and rational development of starter strains with improved functionality. IMPORTANCE Streptococcus thermophilus is one the main organisms involved in the fermentation of milk and, increasingly, also in the fermentation of plant-based foods. The construction of a functional high-quality genome-scale metabolic model, in conjunction with in-depth transcriptome profiling with a focus on metabolism, provides a valuable resource for the improved understanding of S. thermophilus physiology. An example is the model-based prediction of the most significant route of synthesis for the characteristic yogurt flavor compound acetaldehyde and identification of metabolic principles governing the synthesis of other flavor compounds. Moreover, the systematic assessment of amino acid supply and demand during growth in milk provides insights into the key challenges related to nitrogen metabolism that is imposed on S. thermophilus and any other organism associated with the milk niche.

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Dataset Information

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

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Dynamic Modeling of <i>Streptococcus pneumoniae</i> Competence Provides Regulatory Mechanistic Insights Into Its Tight Temporal Regulation.

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