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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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Schematic representation of the tet operon without (off state) and with (on state) Tc. When Tc is absent, the cells save energy by repressing the expression of tetA and tetR. When Tc is present, TetA is produced and pumps Tc out of the cell. More TetR is also produced to shut down expression again when it is no longer necessary [16].
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Figure 1: Schematic representation of the tet operon without (off state) and with (on state) Tc. When Tc is absent, the cells save energy by repressing the expression of tetA and tetR. When Tc is present, TetA is produced and pumps Tc out of the cell. More TetR is also produced to shut down expression again when it is no longer necessary [16].

Mentions: Already in 1964, there was evidence that Escherichia coli (E. coli) bacteria had developed resistance to Tc, but the exact resistance mechanism was not clear [12]. To date, four resistance mechanisms have been identified [13]. These mechanisms are associated with a) active efflux of Tc out of the cell, b) Rib protection from Tc, c) rRNA mutation and d) Tc inactivation. In the present work, we investigate the mechanism of active transport of Tc out of the cell, whereby bacteria under attack by Tc, quickly produce a membrane protein that pumps Tc out of the cell. This resistance mechanism relies on the tet operon [14]. Several Tc resistance determinants have evolved [13,15]. This work refers to class B (or Tn10-type) Tc resistance determinant. A qualitative model of the tet operon is shown in Figure 1.


Stochastic simulations of the tetracycline operon.

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

Schematic representation of the tet operon without (off state) and with (on state) Tc. When Tc is absent, the cells save energy by repressing the expression of tetA and tetR. When Tc is present, TetA is produced and pumps Tc out of the cell. More TetR is also produced to shut down expression again when it is no longer necessary [16].
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 1: Schematic representation of the tet operon without (off state) and with (on state) Tc. When Tc is absent, the cells save energy by repressing the expression of tetA and tetR. When Tc is present, TetA is produced and pumps Tc out of the cell. More TetR is also produced to shut down expression again when it is no longer necessary [16].
Mentions: Already in 1964, there was evidence that Escherichia coli (E. coli) bacteria had developed resistance to Tc, but the exact resistance mechanism was not clear [12]. To date, four resistance mechanisms have been identified [13]. These mechanisms are associated with a) active efflux of Tc out of the cell, b) Rib protection from Tc, c) rRNA mutation and d) Tc inactivation. In the present work, we investigate the mechanism of active transport of Tc out of the cell, whereby bacteria under attack by Tc, quickly produce a membrane protein that pumps Tc out of the cell. This resistance mechanism relies on the tet operon [14]. Several Tc resistance determinants have evolved [13,15]. This work refers to class B (or Tn10-type) Tc resistance determinant. A qualitative model of the tet operon is shown in Figure 1.

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