Team:Toulouse France/Model

iGEM Toulouse 2016

Modelling

Toward the cave

At the end of our summer work, our strain Paleolitis is not complete yet. Anyway, using such a GMO in the cave environment is a very risky challenge and we decided to anticipate and conceptualize how it could be used in the safest way.

Context

Even if Paleolitis was finalized, there is no way we use it in the cave without long and accurate testing phases. The step before Lascaux should be its validation in a laboratory cave (figure 1). There are experts in such approaches and we decided to focus on the step between the completion of our strain and this laboratory validation.

Figure 1: Description of our strategy to anticipate the use of Paleolitis in the Lascaux cave.


An iterative strategy

We conceived this step as an iterative strategy (figure 1). To predict how the strain will behave in the cave environment, we decided to use a modelling strategy and created a Prey-Predator model. Such approach will provide accurate prediction only with accurate data. It means using the strain to treat mould patches as it should be done in the cave. We feel that we should use all the solution available for the confinement and we designed a device to physically contain our strain during the treatment. With this device, we could perform tests on stones to mimic the cave situation. Data from these tests will be used to implement our model with real data to obtain better predictions that will be tested again, and hence the iterative approach. Once satisfactory prediction are obtained, the next step toward laboratory cave could be initiated.

Modeling

We designed a prey predator model to predict how Paleolitis and the fungi will behave. Indeed, these are living entities, with a capacity to multiply but also with a death rate. This means that how the system evolved (i.e, toward fungal or bacterial domination) depends on the growth and death rates of the strains, but also on their initial numbers. The cave is very poor in growth substrates and the production of toxin should also make the bacteria unstable. We therefore assumed that the Paleolitis strain should not maintain in this environment. Therefore the simulation should help us to know how much bacteria should be used to treat the mould patches, when the job is finished, and when the bacteria should have disappeared.

The model was conceived using Netlogo.

It was designed has a simple interface (figure 2) and is totally open to the iGEM community and beyond (Click here to see our program).

Figure 2: image of the prey-predator model interface.


Figure 3: simulation from the model.



Confinement Device

The confinement device (figure 4) was designed has a transparent glass bell (5) mounted on a soft sucking pad (6) to stick to the cave wall. This sucking pad can be depressurized (4) to allow tight and airproof contact to the stone. Bacterial suspension at the concentration indicated by the model is placed in the chamber (1). The device is placed on top of the mould patch and bacterial suspension is sprayed on the confined surface (figure 5) using the sprinkler inside the bell (3). Optionally, a UV ramp could be mounted inside the chamber, either to reveal the bacteria if they express a fluorescent marker, or to ensure killing of the recA- Bacillus strain (this background allows reducing the risk of recombination – see the design part-, and is therefore very sensitive to UV).

Figure 4: Technical diagram of the device


Figure 5: Simulation of the device utilization



Test on stones

The device will have to be used during test on stone in laboratory condition. As a very preliminary work, limestone rocks were sterilized by autoclaving and used to perform a series of tests. We deposited on the stones several mixes including ochre, substrates, Bacillus subtilis expressing the antifungal AF_A operon, and fungi (figure 6). However, it appears that fungal growth in such conditions is very slow and it was difficult to obtain sound results in the few days left to perform the tests. Anyway, such a test could be easily adapted to test the model predictions and the device functionality. Sampling during and after the predicted time could be done and qRT-PCR performed to measure how the fungal and bacterial populations evolved. These numbers will be implemented in the model to refine its prediction and hence optimize the approach until the results are satisfying enough to start test in laboratory caves.

Figure 6: example of test on stones.



Perspectives: the laboratory cave and other applications

The described iterative approach will help to settle the best conditions to apply our project in the Lascaux cave. The cave has a very unstable ecosystem and microbiologists that work on Lascaux treat it with extreme caution and care. They also do not act on the cave until they know the exact consequences of the treatments they plan on applying. They therefore use laboratory caves where various treatments are performed and fully analysed before deciding to use them directly on the cave. Moreover, the study of the laboratory caves enables the microbiologists to understand better which characteristics lead to certain ecosystems that were identified in the caves. This could help build a referential on the microorganisms that develop underground. These caves are all located in France, and have similarities with the Lascaux cave in terms of bacterial and fungal population. However, each cave is unique and the microbiologists that work on the cave decided to develop a network of laboratory caves. Each one of them could help respond to a particular issue of the Lascaux cave and all of them combined would tackle all the aspect of the Lascaux cave’s situation.

The concept of our project could be used for other applications as well. Indeed, in hospitals, fungi cause a lot of sanitary issues. The fungus settles on the pipes and may cause infections to patients that require extreme care and sterile healing conditions. A Paleotilis-like solution would be a great way to get rid of the microorganisms that threaten the health of the convalescents.




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