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Stochastic simulations of the tetracycline operon.

Biliouris K, Daoutidis P, Kaznessis YN - BMC Syst Biol (2011)

Bottom Line: The results of the simulations agree well with experimental observations such as tight repression, fast gene expression, induction with tetracycline, and small intracellular TetR2 amounts.Computer simulations of the tetracycline operon afford augmented insight into the interplay between its molecular components.Therefore, simulations may assist in designing novel gene network architectures consisting of tetracycline operon components.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Chemical Engineering and Materials Science, University of Minnesota, 421 Washington Ave SE, Minneapolis, MN 55455, USA.

ABSTRACT

Background: The tetracycline operon is a self-regulated system. It is found naturally in bacteria where it confers resistance to antibiotic tetracycline. Because of the performance of the molecular elements of the tetracycline operon, these elements are widely used as parts of synthetic gene networks where the protein production can be efficiently turned on and off in response to the presence or the absence of tetracycline. In this paper, we investigate the dynamics of the tetracycline operon. To this end, we develop a mathematical model guided by experimental findings. Our model consists of biochemical reactions that capture the biomolecular interactions of this intriguing system. Having in mind that small biological systems are subjects to stochasticity, we use a stochastic algorithm to simulate the tetracycline operon behavior. A sensitivity analysis of two critical parameters embodied this system is also performed providing a useful understanding of the function of this system.

Results: Simulations generate a timeline of biomolecular events that confer resistance to bacteria against tetracycline. We monitor the amounts of intracellular TetR2 and TetA proteins, the two important regulatory and resistance molecules, as a function of intrecellular tetracycline. We find that lack of one of the promoters of the tetracycline operon has no influence on the total behavior of this system inferring that this promoter is not essential for Escherichia coli. Sensitivity analysis with respect to the binding strength of tetracycline to repressor and of repressor to operators suggests that these two parameters play a predominant role in the behavior of the system. The results of the simulations agree well with experimental observations such as tight repression, fast gene expression, induction with tetracycline, and small intracellular TetR2 amounts.

Conclusions: Computer simulations of the tetracycline operon afford augmented insight into the interplay between its molecular components. They provide useful explanations of how the components and their interactions have evolved to best serve bacteria carrying this operon. Therefore, simulations may assist in designing novel gene network architectures consisting of tetracycline operon components.

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Impact of changing the affinity of TetR2 for the operators on Tc and TetA amounts. Average maximum number of TetA (Figure 10a) and Tc (Figure 10b) molecules for a range of administered Tc in the wild type (wt) system, as well as in systems where the affinity of TetR2 for the operators is 10, 50 and 100 times lower than the nominal value. Decreased affinity of TetR2 for the operator sites leads to high TetA and low Tc amounts in the cell.
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Figure 10: Impact of changing the affinity of TetR2 for the operators on Tc and TetA amounts. Average maximum number of TetA (Figure 10a) and Tc (Figure 10b) molecules for a range of administered Tc in the wild type (wt) system, as well as in systems where the affinity of TetR2 for the operators is 10, 50 and 100 times lower than the nominal value. Decreased affinity of TetR2 for the operator sites leads to high TetA and low Tc amounts in the cell.

Mentions: Here, we explore the significance of the high binding strength (Keq ≃ 1012M-1) [31] of TetR2 to the operator sites, tetO1 and tetO2. This feature enables the repressor to bind quickly and tightly to the operator sites in the absence of Tc, making this operon a thoroughly tuned biological switch. The importance of this feature is investigated through a set of simulations in which the binding strength of the repressor for the operators is 10, 50 and 100 times lower than the wild type value. This could be experimentally achieved by either introducing amino acid changes on the TetR protein or mutating the operator sites [61]. In our simulations, this is attained by decreasing all the corresponding kinetic parameters (k3, k5, k19, k25, k64, k65, k66, k67) 10, 50 and 100 times. We decrease the rate that TetR2 binds to the operators when it is either free (k3, k5, k64, k65) or bound on Tc (k19, k25, k66, k67), causing a decrease to the binding strength. In contrast to the previous case, in which the affinity of Tc for the repressor is investigated, we only consider a decrease and not an increase to the binding affinity. The binding affinity value is already very high and a possible increase would not be experimentally meaningful due to diffusion limitations. The results of the simulations are shown in Figure 10 and they represent the average maximum TetA and Tc amounts in the cells.


Stochastic simulations of the tetracycline operon.

Biliouris K, Daoutidis P, Kaznessis YN - BMC Syst Biol (2011)

Impact of changing the affinity of TetR2 for the operators on Tc and TetA amounts. Average maximum number of TetA (Figure 10a) and Tc (Figure 10b) molecules for a range of administered Tc in the wild type (wt) system, as well as in systems where the affinity of TetR2 for the operators is 10, 50 and 100 times lower than the nominal value. Decreased affinity of TetR2 for the operator sites leads to high TetA and low Tc amounts in the cell.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3037858&req=5

Figure 10: Impact of changing the affinity of TetR2 for the operators on Tc and TetA amounts. Average maximum number of TetA (Figure 10a) and Tc (Figure 10b) molecules for a range of administered Tc in the wild type (wt) system, as well as in systems where the affinity of TetR2 for the operators is 10, 50 and 100 times lower than the nominal value. Decreased affinity of TetR2 for the operator sites leads to high TetA and low Tc amounts in the cell.
Mentions: Here, we explore the significance of the high binding strength (Keq ≃ 1012M-1) [31] of TetR2 to the operator sites, tetO1 and tetO2. This feature enables the repressor to bind quickly and tightly to the operator sites in the absence of Tc, making this operon a thoroughly tuned biological switch. The importance of this feature is investigated through a set of simulations in which the binding strength of the repressor for the operators is 10, 50 and 100 times lower than the wild type value. This could be experimentally achieved by either introducing amino acid changes on the TetR protein or mutating the operator sites [61]. In our simulations, this is attained by decreasing all the corresponding kinetic parameters (k3, k5, k19, k25, k64, k65, k66, k67) 10, 50 and 100 times. We decrease the rate that TetR2 binds to the operators when it is either free (k3, k5, k64, k65) or bound on Tc (k19, k25, k66, k67), causing a decrease to the binding strength. In contrast to the previous case, in which the affinity of Tc for the repressor is investigated, we only consider a decrease and not an increase to the binding affinity. The binding affinity value is already very high and a possible increase would not be experimentally meaningful due to diffusion limitations. The results of the simulations are shown in Figure 10 and they represent the average maximum TetA and Tc amounts in the cells.

Bottom Line: The results of the simulations agree well with experimental observations such as tight repression, fast gene expression, induction with tetracycline, and small intracellular TetR2 amounts.Computer simulations of the tetracycline operon afford augmented insight into the interplay between its molecular components.Therefore, simulations may assist in designing novel gene network architectures consisting of tetracycline operon components.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Chemical Engineering and Materials Science, University of Minnesota, 421 Washington Ave SE, Minneapolis, MN 55455, USA.

ABSTRACT

Background: The tetracycline operon is a self-regulated system. It is found naturally in bacteria where it confers resistance to antibiotic tetracycline. Because of the performance of the molecular elements of the tetracycline operon, these elements are widely used as parts of synthetic gene networks where the protein production can be efficiently turned on and off in response to the presence or the absence of tetracycline. In this paper, we investigate the dynamics of the tetracycline operon. To this end, we develop a mathematical model guided by experimental findings. Our model consists of biochemical reactions that capture the biomolecular interactions of this intriguing system. Having in mind that small biological systems are subjects to stochasticity, we use a stochastic algorithm to simulate the tetracycline operon behavior. A sensitivity analysis of two critical parameters embodied this system is also performed providing a useful understanding of the function of this system.

Results: Simulations generate a timeline of biomolecular events that confer resistance to bacteria against tetracycline. We monitor the amounts of intracellular TetR2 and TetA proteins, the two important regulatory and resistance molecules, as a function of intrecellular tetracycline. We find that lack of one of the promoters of the tetracycline operon has no influence on the total behavior of this system inferring that this promoter is not essential for Escherichia coli. Sensitivity analysis with respect to the binding strength of tetracycline to repressor and of repressor to operators suggests that these two parameters play a predominant role in the behavior of the system. The results of the simulations agree well with experimental observations such as tight repression, fast gene expression, induction with tetracycline, and small intracellular TetR2 amounts.

Conclusions: Computer simulations of the tetracycline operon afford augmented insight into the interplay between its molecular components. They provide useful explanations of how the components and their interactions have evolved to best serve bacteria carrying this operon. Therefore, simulations may assist in designing novel gene network architectures consisting of tetracycline operon components.

Show MeSH
Related in: MedlinePlus