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Temporal controls of the asymmetric cell division cycle in Caulobacter crescentus.

Li S, Brazhnik P, Sobral B, Tyson JJ - PLoS Comput. Biol. (2009)

Bottom Line: The asymmetric cell division cycle of Caulobacter crescentus is orchestrated by an elaborate gene-protein regulatory network, centered on three major control proteins, DnaA, GcrA and CtrA.The model is validated against observed phenotypes of wild-type cells and relevant mutants, and it predicts the phenotypes of novel mutants and of known mutants under novel experimental conditions.Because the cell cycle control proteins of Caulobacter are conserved across many species of alpha-proteobacteria, the model we are proposing here may be applicable to other genera of importance to agriculture and medicine (e.g., Rhizobium, Brucella).

View Article: PubMed Central - PubMed

Affiliation: Department of Biological Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.

ABSTRACT
The asymmetric cell division cycle of Caulobacter crescentus is orchestrated by an elaborate gene-protein regulatory network, centered on three major control proteins, DnaA, GcrA and CtrA. The regulatory network is cast into a quantitative computational model to investigate in a systematic fashion how these three proteins control the relevant genetic, biochemical and physiological properties of proliferating bacteria. Different controls for both swarmer and stalked cell cycles are represented in the mathematical scheme. The model is validated against observed phenotypes of wild-type cells and relevant mutants, and it predicts the phenotypes of novel mutants and of known mutants under novel experimental conditions. Because the cell cycle control proteins of Caulobacter are conserved across many species of alpha-proteobacteria, the model we are proposing here may be applicable to other genera of importance to agriculture and medicine (e.g., Rhizobium, Brucella).

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Simulation of ctrAD51E mutant.ks,ctrA-P1 = ks,ctrA-P2 = 0, ktrans,CtrA∼P = 0, k ′ = 0.064 (40% of WT) was added to [CtrA∼P] equation. The vertical column of open circles here and on subsequent figures indicates the time at which the mutation is introduced. For earlier times the simulation is run with wild-type values of all parameters.
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pcbi-1000463-g005: Simulation of ctrAD51E mutant.ks,ctrA-P1 = ks,ctrA-P2 = 0, ktrans,CtrA∼P = 0, k ′ = 0.064 (40% of WT) was added to [CtrA∼P] equation. The vertical column of open circles here and on subsequent figures indicates the time at which the mutation is introduced. For earlier times the simulation is run with wild-type values of all parameters.

Mentions: Since in this mutant the constitutively expressed CtrA is active all the time, we simulated the mutant by turning off CtrA production from the original gene and by producing the active form of CtrA (phophorylated form in our model) constitutively. Our simulation shows (Figure 5) that an elevated level of CtrA∼P does not block progression of cells through the cell cycle. The CtrA degradation machinery is able to lower the level of CtrA∼P enough that the necessary conditions for DNA replication are satisfied, while the components for the Z-ring assembly and constriction are also available when needed. Elevated CtrA∼P reduces to some extent GcrA, PodJL/PleC, FtsZ and Zring, and accelerates DNA methylation, but these changes do not have lethal effects on cell cycle progression.


Temporal controls of the asymmetric cell division cycle in Caulobacter crescentus.

Li S, Brazhnik P, Sobral B, Tyson JJ - PLoS Comput. Biol. (2009)

Simulation of ctrAD51E mutant.ks,ctrA-P1 = ks,ctrA-P2 = 0, ktrans,CtrA∼P = 0, k ′ = 0.064 (40% of WT) was added to [CtrA∼P] equation. The vertical column of open circles here and on subsequent figures indicates the time at which the mutation is introduced. For earlier times the simulation is run with wild-type values of all parameters.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2714070&req=5

pcbi-1000463-g005: Simulation of ctrAD51E mutant.ks,ctrA-P1 = ks,ctrA-P2 = 0, ktrans,CtrA∼P = 0, k ′ = 0.064 (40% of WT) was added to [CtrA∼P] equation. The vertical column of open circles here and on subsequent figures indicates the time at which the mutation is introduced. For earlier times the simulation is run with wild-type values of all parameters.
Mentions: Since in this mutant the constitutively expressed CtrA is active all the time, we simulated the mutant by turning off CtrA production from the original gene and by producing the active form of CtrA (phophorylated form in our model) constitutively. Our simulation shows (Figure 5) that an elevated level of CtrA∼P does not block progression of cells through the cell cycle. The CtrA degradation machinery is able to lower the level of CtrA∼P enough that the necessary conditions for DNA replication are satisfied, while the components for the Z-ring assembly and constriction are also available when needed. Elevated CtrA∼P reduces to some extent GcrA, PodJL/PleC, FtsZ and Zring, and accelerates DNA methylation, but these changes do not have lethal effects on cell cycle progression.

Bottom Line: The asymmetric cell division cycle of Caulobacter crescentus is orchestrated by an elaborate gene-protein regulatory network, centered on three major control proteins, DnaA, GcrA and CtrA.The model is validated against observed phenotypes of wild-type cells and relevant mutants, and it predicts the phenotypes of novel mutants and of known mutants under novel experimental conditions.Because the cell cycle control proteins of Caulobacter are conserved across many species of alpha-proteobacteria, the model we are proposing here may be applicable to other genera of importance to agriculture and medicine (e.g., Rhizobium, Brucella).

View Article: PubMed Central - PubMed

Affiliation: Department of Biological Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA.

ABSTRACT
The asymmetric cell division cycle of Caulobacter crescentus is orchestrated by an elaborate gene-protein regulatory network, centered on three major control proteins, DnaA, GcrA and CtrA. The regulatory network is cast into a quantitative computational model to investigate in a systematic fashion how these three proteins control the relevant genetic, biochemical and physiological properties of proliferating bacteria. Different controls for both swarmer and stalked cell cycles are represented in the mathematical scheme. The model is validated against observed phenotypes of wild-type cells and relevant mutants, and it predicts the phenotypes of novel mutants and of known mutants under novel experimental conditions. Because the cell cycle control proteins of Caulobacter are conserved across many species of alpha-proteobacteria, the model we are proposing here may be applicable to other genera of importance to agriculture and medicine (e.g., Rhizobium, Brucella).

Show MeSH