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Effector device in timed suicide switch

Usage and Biology

2022 SZU-China plans to design a timed suicide switch mediated by a classical synthetic gene oscillator. Effector is the device performing suicide. The MazEF system is an important component of the subtilisin-antitoxin system, which leads to programmed cell death. MazF is an mRNA endonuclease that specifically cleaves a five-base UACAU sequence on RNA. In the presence of MazE, MazF has a higher affinity for MazE than its RNA substrate. MazE combines with MazF at a ratio of 1:1 to occupy its active site and make it lose its toxicity.

The core of the effector is the MazEF toxin-antitoxin system, in which the antitoxin MazE is controlled by the Promoter tetR , and the antitoxin MazF is controlled by the constitutive promoter PJ23110. The effector is encoded in the high-copy plasmid colE1.

Assembly

The oscillator and the effector form a timed suicide switch.

The engineered bacteria with a timed suicide switch were placed in an IPTG-rich medium or in a dormant state before being applied in fields. The purpose of being placed in IPTG is to continuously activate the PlacI and make the oscillator unbalanced and stagnant， in which circumstance MazF does not express.

After being applied to the field, the oscillator is re-activated with the release of IPTG and the resuscitation of the engineering bacteria. The contents of three repressor proteins changed cyclically: lacI inhibited the expression of tetR, tetR inhibited the expression of λ cI, and λ cI inhibited lacI expression. That is, the three promoters PlacI, PtetR, and PλcI were alternately activated.

As for the effector, MazE was constitutively expressed and maintained at a certain concentration in the cytoplasm, while the expression of MazF was inhibited by tetR and showed a fluctuating increase. In a simplified model, MazE and MazF bind at the ratio of 1:1, resulting in toxin inactivation. When the concentration of toxin MazF is higher than that of antitoxin MazE, the extra toxin MazF plays the role of endonuclease to cut mRNA and kill the engineered microorganisms.

Model

Assumption

In order to establish the oscillator model, the following assumptions are necessary for the model:

Assumption 1: The amount of DNA in the same cell is constant and the physiological behavior is same. The DNA in the same cell can be expressed at the corresponding gene fragment.

Assumption 2: Transcription and translation processes are carried out under saturation conditions. In the process of transcription and translation, polymerases, ribosomes, amino acids and nucleotides are present in large amounts.

Assumption 3: Degradation of protein and mRNA as well as reactive degradation. That is, proteins and mRNA can be degraded directly without intermediate products.

Assumption 4: Transcription rate can be modelled by Hill equation. That is because the transcription rate of each gene is determined by the concentration of its protein product, and the repressor protein binds to the regulatory region of the gene faster than transcription and translation.

Assumption 5: The Hill coefficient approximates the number of cooperative ligand binding sites on the receptor, and ligand molecules bind to a receptor simultaneously.

Assumption 6: The translation rate of each gene is equal.

Modeling on the osillator

The expression processes of the 3 genes lacI,tetR and cI are described as follows:

For the transcription process, the ODE for transcription rate is described as follows:

Hill equation：

To carry out dimension reduction and simplify the analysis of this system, we normalize the ODEs

Results

We set the oscillator model parameters as:

First, we set the initial number of mRNA molecules and the number of protein molecules to be both 0. The oscillator model was simulated for 1000 minutes. Note that only the curve representing the number of cI protein molecules is visible, as all plotted concentrations are identical and overlap. From the simulation results, it can be seen that the peak value is 288 molecules at 8 minutes, and the steady state is reached at 28 minutes, where the number of protein molecules is maintained at 210 molecules.

We set the initial mRNA molecules and protein molecules to mlacI= 0, mtetR = 0m, cIt = 0, ptetR = 10, placI= 0, pcI 0, The oscillator model was then simulated for 1000 minutes, and the simulation results are shown in Figure 3. It is clear that after a period of time in the oscillator system, the system reaches a steady state with the peak value is 3000 molecules of the 3 proteins and the peak-to-peak period is 175 min.

It is clear that after a period of time in the oscillator system, the system reaches a steady state with the peak value is 3000 molecules of the 3 proteins and the peak-to-peak period is 175 min.

In order to change the peak amplitude of the oscillator model and the peak when the steady state is reached, we also explored the effect of different initial conditions on the oscillator model. In addition, we used 3D representation that plotted the simulation of the oscillator system for 1000 minutes (Figure 5), to fully understand the behavior of the oscillator system. Figure 5(a). shows that the system will rapidly reach the steady state under different initial protein numbers for 1000 minutes, unless all concentrations are the same, the system will begin to approach the limit cycle, and the steady state simulation is shown in red. Figure 5(b). shows the changes in TetR and LacI protein concentrations during the simulation. Figure 5(c). shows the curve of the region near the steady state near the limit cycle of Figure 5(b). Figure 5(d). shows that when the oscillator system is greater than 800 minutes, except for the steady state (indicated in red), it is related to the limit cycle. Figure 5(e). shows that for more than 200 minutes, the closer the initial conditions are to the same, the longer it takes for the system to reach the limit cycle.

Modeling on the effector

After exploring the behavior of the oscillator with different parameters, we explore the dynamics of the MazEF system. MazEF is a toxin-antitoxin module located on the Escherichia coli chromosome and that of some other bacteria, including pathogens. MazF is a stable toxin that is capable of exerting toxic effects to kill cells. MazE is an unstable antitoxin that binds to MazF to form MazEF to keep cells alive, and its cellular concentration drops more rapidly than that of MazF, leaving MazF to exert its toxic effect, leading to cell death. The oscillator is coupled to the MazEF system.

We set different initial parameters of mRNA molecules and protein molecules for 1000 minutes of simulation, as shown in Figure 2. We set k1=0.03 per minute, k2=10.0 per minute, K=40 per minute, d1 =0.25 per minute, d2=1.155E-2 per minute and Kas=2.0\E-3 per minute.

Modeling on the timed suicide switch

The oscillator model simulates oscillations in the number of repressor, MazE and MazF protein molecules. Notably, the MazF minimum amplitude corresponds to the cI protein minimum amplitude, which is due to the fact that both are controlled by the tetR operon. In addition, it can be seen that the number of MazF protein molecules does not decrease to 0 like other genes, because MazF protein has a long half-life and is more stable in cells. In the simulation, it can be seen that after a period of time, the content of MazF exceeds the content of MazE, and the toxin in the cells gradually plays a role, thus causing cell death. For example, in Figure 6(b), the cells will accumulate toxin proteins in the cells at 437 minutes, 626 minutes, 735 minutes and 806 minutes, thus causing cell death.

Sequencing

Sequence and Features

References

[1]Elowitz MB, Leibler S. A synthetic oscillatory network of transcriptional regulators. Nature. 2000 Jan 20;403(6767):335-8. doi: 10.1038/35002125. PMID: 10659856.

[2]Purcell O, di Bernardo M, Grierson CS, Savery NJ. A multi-functional synthetic gene network: a frequency multiplier, oscillator and switch. PLoS One. 2011 Feb 17;6(2):e16140. doi: 10.1371/journal.pone.0016140. PMID: 21359152; PMCID: PMC3040778.

[3]Potvin-Trottier L, Lord ND, Vinnicombe G, Paulsson J. Synchronous long-term oscillations in a synthetic gene circuit. Nature. 2016 Oct 27;538(7626):514-517. doi: 10.1038/nature19841. Epub 2016 Oct 12. PMID: 27732583; PMCID: PMC5637407.

[4]Hoseini S, Kalani BS, Ghafourian S, Maleki A, Asadollahi P, Badakhsh B, Pakzad I. In Vitro and In Silico Investigation of some Type II TA Genes in H. Pylori. Clin Lab. 2022 Aug 1;68(8). doi: 10.7754/Clin.Lab.2021.211002. PMID: 35975492.

[5]Nigam A, Ziv T, Oron-Gottesman A, Engelberg-Kulka H. Stress-Induced MazF-Mediated Proteins in Escherichia coli. mBio. 2019 Mar 26;10(2):e00340-19. doi: 10.1128/mBio.00340-19. PMID: 30914510; PMCID: PMC6437054.