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Team:Dundee/Project/SoftwareTheory
From 2013.igem.org
Toxi Mop - Splash and the toxin's gone!
The Microcystin Monster
Algal blooms are an ever-growing problem in freshwater systems. At the Beijing Olympics 2008, 10,000 people were hired to clean up the extensive algal bloom in time for the sailing regatta. The main concern is the level of a toxin called microcystin, which is released by cyanobacteria when they die and lyse.
Currently, the method of detection takes a day to produce results, so our aim as a team is to develop a 60 minute microcystin detection system, as well as a method to combat the rising levels of the toxin in lakes, ponds, etc. The iGEM Dundee team were inspired to act on this problem due to not only its effect on the local freshwater reservoirs, but worldwide.
Save the Janitor, Save the world!
Microcystin, a toxin released by Microcystis aeruginosa, is harmful to mammals due to its ability to latch on to the human protein PP1, thus ceasing its operation.
We are exploiting the ability of the human protein phosphatase (PP1) to covalently bind to microcystin, in order to develop a biological mop ‘janitor’ to rid algal bloom water of the toxin.
By changing domains on receptors on the cell surface of e.coli and b.subtilis, we plan to develop a method of microcystin detection. Thirdly, iGEM Dundee are creating ‘Moptopus’; a remote environmental monitoring device which is designed to detect pH, temperature, light, dissolved oxygen in H2O and even has a robotic eye. Moptopus can be controlled online and can even send tweets to alert the public whenever an algal bloom is imminent.
Unmasking the Monster
The public generally considers synthetic biology as an immoral concept, although if you imagine it as an episode of Scooby Doo, it doesn’t seem so bad; everyone is scared of this unknown monster, but underneath this mask is just a janitor. In the case of our project ToxiMop, we are using a ‘janitor bacterium’ to mop up the microcystin toxin from freshwater reservoirs!
The Universe's Lego Kit
What comes to people's mind when they hear the term 'synthetic biology'? Many people don't know what it is, or have an ambiguous idea that it is something dangerous, potentially immoral. It can be thought of as playing with the universe's lego kit. Building with what is already here, naturally, biologists attempt to create better biological systems and machinery to advance life on earth.
Toxi-Mop
We are using cloning techniques to genetically engineer B. subtilis and E. coli to express PP1 so that they can inhibit the toxin microcystin in algal blooms, therefore reducing harm to freshwater ecosystems. ”
Project Mop-topus
A remotly accessed electronic environmental sensor that detects and monitors the state of a lake and its susceptibility to algal blooms by measuring light, temperature, pH, and dissolved oxygen variables.
The Detector
We are making 2 different microcystin detectors by substituting domains of bacterial cell surface receptors involved with gene regulation, with PP1 molecules.
Our Team
The team is consists of biologists, a mathematician, a math biologist, a physicist and a software engineer. By bringing together students with different expertise, we strive to maintain and improve upon previous iGEM teams' achievements.
Contents |
Insight to the Mop-topus and Toxi-Tweet
Aims:
Using mathematical tools to allow us to predict the limiting factors in the production of PP1 and its mopping applications. Working alongside the biologists to produce models which are relevant and can predict what is expected to happen during the synthetic engineering of the mop and detection bacteria.
Development of Moptopus:
The current method for detecting toxic levels of microcystin is to take a sample of water from different regions of the site being investigated and then to carry out high performance liquid chromatography (HPLC). This process currently takes approximately 24 hours, we hope to reduce this to a more suitable 1 hour.
Assuming the cyanobacteria undergo binary fission and grow unbounded we were able to determine how the problem increases over 24 hours in comparison to 1 hour detection. where MC(t) is the number of microcystin at time t b0 is the initial number of algae
The ratio for time t=24:1 is 8.4million:1. To put this into perspective this is the same as the height of the empire state building compared with the length of 7 E.coli bacterium. This model therefore emphasises that the 1 hour detection period is much more efficient and worth pursuing.
<img id="image-6" src="http://placehold.it/600x300/8066DB/000000&text=Mop-topus">
The Toxi-Tweet System:
We considered different limiting factors of our mop bacteria. The factor discussed in this section is the maximum number of PP1 which can fit either on the surface of B.subtilis, or in the periplasm of E.coli. We considered the volumes of the bacteria and PP1 and used a cube approximation that took into account volume which was wasted, in packing, by the spherical shape of the protein. For this model we assumed there were no other surface proteins and protein production was not limited by any factors.
Calculations show the maximum number of PP1 which can fit on the surface of B.subtilis is between 60 000 -70 000. From the average we can calculate that the number of bacterial mops required to clean a toxic level of microcystin in a litre of water is 1.40x1010.
In E.coli, PP1 which would bind microcystin is free-flowing in the periplasm. The volume of the periplasm is much greater than the surface of B.subtilis. Therefore E.coli has the capacitive potential to be a more efficient mop. The maximum number of PP1 which can be packed into the periplasm is between 150 000 -200 000. Consequently, less bacterial mops are required to clean the same level of microcystin: 0.52x1010.
When we have accurate numbers from the biology team on how many PP1 are attached to the surface or in the periplasm for B.subtilis and E.coli respectively, we can compare these numbers and compute the efficiency of our PP1 expressing bacteria.
Progress and Future Plans
An Ordinary Differential Equation (ODE) uses a function f(t) to describe how the output changes as a result of changing the input dx(t)/dt. For example how PP1 concentration changes with time in a single cell. In order to model transcription and translation of PP1 we used a system of ODEs , which is more than one ODE where the outputs are coupled.
We used law of mass action to obtain a system of ODEs to describe the production of mRNA to PP1. mRNA and PP1 are coupled in the sense we need mRNA before we can produce any PP1. Also, the mRNA is not used up. We also took into consideration the degradation rates of mRNA and PP1 which are denoted as .
- k1 – rate mRNA production - 4.98x10-9
- kd1 – rate mRNA degradation – 1x10-2
- k2 – rate PP1 production – 4x10-2
- kd2 – rate PP1 degradation – 4x10-4
<img id="image-6" src="http://placehold.it/600x300/8066DB/000000&text=Figure 1">
Figure 1. How mRNA and PP1 are produced over 20 minute cell division time. Note scaling on PP1 compared to mRNA.
<img id="image-6" src="http://placehold.it/600x300/8066DB/000000&text=Figure 2">
Figure 2. A steady state is when the quantities describing a system are independent of time – they reach an equilibrium i.e dx/dt = 0. The steady state for (mRNA, PP1) is (0.04, 0.04) corresponding to a non-dimensionalised system. This plot demonstrates that during a 20 minute cell division period mRNA reaches the steady state but PP1 does not.
<img id="image-6" src="http://placehold.it/600x300/8066DB/000000&text=Figure 3">
Figure 3. This plot shows that given a time longer than cell division time both the mRNA and PP1 eventually reach their steady states.
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