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Balagaddé et al., (2008). A synthetic Escherichia coli predator-prey ecosystem.

May 2011, model of the month by Michele Mattioni
Original models: BIOMD0000000296


The Lokta-Volterra model is one of the best known predator-prey models , commonly used in biology classes to introduce differential equations. The considered ecosystem consists of a population of prey (rabbits) and a population of predators (foxes). The model reproduces the dynamic oscillation of the system, explaining how an increase in the prey's population can trigger an increase in the predators' population which decreases as soon as the prey population can no longer sustain the number of predators. When the predators' population is of small size, the prey can start to reproduce and increase their numbers to the point where the predators start to catch up again. The predators, however, should not over-exploit the prey, or else they starve themselves to death.

In this paper, Balagaddé et al. [1, BIOMD0000000296] have investigated the predator-prey system using two different genetically modified E. Coli, that act as 'predator' and 'prey', which communicate using a two way Quorum Sensing mechanism, as shown in Figure 1.

Figure 1

Figure 1: Engineered strains of E. Coli, using Quorum Sensing as system to influence each other. (Figure taken from Box1A of [1])


Figure 2

Figure 2: Individual test of the prey and predator response to external stimuli. (Figure taken from [1]).

The predator is able to endogenously produce ccdB, a toxic protein which directs the cell to death. To stay alive it needs active LuxR which activates the expression of ccdA that in turn inhibits the transcription of ccdB. LuxR is active only if there is enough 3OC6HSL in the culture - an acyl-homoserine lactone produced by the 'prey'. The prey will thrive without the predator, but will die as soon as another acyl-homoserine lactone, 3OC12HSL, that is produced by the predator exceeds a certain threshold. This lactone binds the LasR protein, which is able to activate the luxI promoter and start the transcription of ccdB, killing the prey. This synthetic circuit is activated by IPTG, which enhances transcription from the ccdB promoter in the predator, thereby activation the Quorum Sensing mechanism in the prey.

This system is different from the classic predator-prey system, because of the competition on the same vital resources, shared by the predator and the prey.


To test the activation of the circuit, the predator and the prey have been tested under controlled experimental conditions (Figure 2), where the two exogenous hormones are added to the culture externally.

In the OFF condition, the predator is able to grow to the maximal density allowed by culture resources. However, with the addition of IPTG to the culture, the number of live cells is reduced due to the toxic action of ccdB. When the prey-lactone is added to the culture the ccdA protein is transcribed, inhibiting ccdB, thus rescuing the predator-cells. Similarly the prey cells are able to proliferate and live in the the OFF condition. With the addition of IPTG, the cells start to produce the ccdA protein. After addition of the predator-hormone the prey-cells express the toxic ccdB protein leading to cell death.

Figure 3

Figure 3: Bifurcation analysis and timecourse of the predator-prey system (Figure taken from Box 1B of [1]).


Figure 4

Figure 4: Oscillatory behaviour of predator and prey in a 180h cycle. (Figure taken from [1]).

It has to be noted that, when the circuit is switched ON with the IPTG addition, the engineered circuit drains some resources from the normal metabolism of the cell, causing a decrease in the growth even if no toxic protein is produced at all.

From the bifurcation analysis of the model (Figure 3), three different scenarios are possible, which are chosen according to the death rate of the predator-cell: (i) prey dominant, (ii) oscillating system and (iii) predator dominant.

Using microchemostat reactors, the system has been tested and an oscillatory behaviour has been recorded with an IPTG concentration of 5 µM and a dilution rate of 0.1125 h-1 (Figure 4).


In Figure 5 shows the influence of IPTG concentration on the dynamic behaviour of the system, which is then compared to experimental data. At low IPTG concentrations the predator is able to dominate due to their higher growth rate, consuming nutrients faster than the prey, which consequently is wiped out. However, as soon the Hopf bifurcation point is passed, the system enters an oscillating state.

Another insight from the model is the reduction of oscillation frequencies with increasing dilution factor (D), for which the system exhibits three different behaviours: (i) stable and, (ii) damped oscillations as well as (iii) population collapse (Figure 6).

Figure 5

Figure 5: Different scenario obtained by varying the IPTG concentration, from prey dominant to oscillating system. (Figure taken from [1]).


Figure 6

Figure 6: Dependence of systems dynamics on dilution rate (D). (Figure taken from [1]).

Modeling in Synthetic Biology is a powerful tool, which permits to design and predict, in silico, the evolution of complex interactions. In 2000, Elowitz et al. [2 , BIOMD0000000012], have demonstrated the oscillating ability of 3 genes, whose transcription products are able to inhibit one of the other genes, creating a loop of inhibition proteins, bringing the system to an oscillatory state.

In this paper, Balagaddé et al (2008) have demonstrated how to model and verify by experiment, a complex interaction of the prey-predator ecosystem, involving two different cells and creating a two way communication system which could be used as framework to test other complex systems, involving several genes in different cells.



Bibliographic References

  1. Balagaddé FK, Song H, Ozaki J, Collins CH, Barnet M, Arnold FH, Quake SR, You L. A synthetic Escherichia coli predator-prey ecosystem. Mol Syst Biol , 4: 187, 2008. [CiteXplore]
  2. Elowitz MB, Leibler S. A synthetic oscillatory network of transcriptional regulators. Nature , Jan;403(6767): 335-8, 2000. [CiteXplore]
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