Team:Dundee/Project

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iGEM Dundee 2013 · ToxiMop

Algae are photosynthetic organisms which live in aquatic environments. Cyanobacteria are also known as blue-green algae and they are prokaryotes that are responsible for the majority of photosynthesis on Earth. During the hot and sunny summer months we experience a phenomenon known as an algal bloom. This is a spectacular increase in the size of the algal population in a water body as the algae take advantage of the seasonal spike in light and warmth. With increased amounts of nutrients leaching into water due to agriculture, blooms are becoming more and more common. Aside from affecting the environment they occur in, algae can also be dangerous for humans as many species produce toxins. We have decided to focus on one hepatotoxin called microcystin, a cyclic non-ribosomal peptide that binds covalently and irreversibly to protein phosphatases in mammalian bodies, inactivating them.

The study of biochemical processes in human cells is one of the most heavily-researched scientific fields. However, it is not often that scientists exploit the biochemical potential that our bodies offer in order to create new technologies for environmental remediation. We have decided to exploit the human protein phosphatase 1 (PP1)–microcystin interaction to create a bacterium that will sequester microcystin and prevent its toxic action.

We engineered the chassis organism Eschericha coli to export human protein phosphatase 1 (PP1) to its periplasmic compartment. By doing this we have created a biological mop for microcystin that we call the ToxiMop.

Detection and Monitoring

The current procedures for detecting algal toxins involve HPLC analysis of contaminated water bodies, and takes approximately 24 hours. Bacterial populations are so dynamic that in the interim between taking a sample for testing and getting a result the amount of toxin present or even its presence may have changed dramatically. In addition, this kind of analysis is expensive, so often water bodies will not be tested unless there is already some evidence of algal growth.

Based on the protein – toxin interaction explained above we also constructed a toxin detection system. E. coli’s membrane-bound osmolarity sensor, EnvZ, was modified to include the PP1 protein. The idea was that upon binding to the microcystin, EnvZ is activated and triggers luminescence by upregulating expression of a fluorescent reporter gene. This light will be then recognised by a modular hardware device (Moptopus) that contains a light meter, thus detecting the toxin. The Moptopus contains a pH meter, dissolved oxygen meter, thermometer, humidity meter and a microscope, which will calculate the possibility of an algal bloom occurring and will provide data on demand for potential algal bloom forecasts. The Moptopus is designed to permanently inhabit a water body, providing real-time information on many of the parameters that control algal growth.

Mathematical Modelling

Mathematical modelling was fundamental to the project in understanding and informing the progression of the wet work.

Initially the team was working with two bacterial chassis, E. coli and B. subtilis. We planned to anchor PP1 to the outer surface of B. subtilis or have the protein free flowing in the periplasm of E. coli. If the efficiency of these bacterial chassis as mops depended only upon the number of PP1 they can accommodate, the E. coli chassis has the potential for greater efficiency. This analysis allowed the Wet team to tailor their time and resources accordingly.

Modelling of Tat transport, which we used to transport the PP1 molecules to the periplasm of E. coli, produced ordinary differential equations able to mathematically explain the processes being carried out in the ToxiMop bacteria and what the limiting factors were. Using this modelling, future improvements to increase the efficiency of the bacterial mop were suggested to the Wet team.

The migration of microcystin into the periplasm of a cell and its binding with PP1 are crucial events to the successful application of the ToxiMop. Visualisation of production and export alongside these events was achieved via the creation of a virtual cell environment in Netlogo (a multi-agent programming language). This virtualisation allowed the dynamic alteration of key properties returning immediate feedback to help analyse the corresponding effects.