Team:ITB Indonesia/Modeling/Model Integration

After all mathematical representation of our phenomena has been successfully constructed, we build a biological system model in Simbiology. It help us to achieve whole cell simulation to predict analysis time, analysis performance of our device, and even helped us to construct a standard protocol to use this device.

Our complete biological system model :

How we simulate our whole cell biosensor?
There is some guideline to helped us simulate our system :

• Simulate device sensitivity. We want our device to report aflatoxin presence as low as Indonesia’s regulation on food safety (BPOM RI No. Hk.00.05.1.4057 stated that aflatoxin safety threshold in Indonesia is 20 ppb).
• We imagine our device would be shaped like small syringe with our dried cell inside it. So user can measure accurately how much medium and sample needed to enter our device.

With that in mind, we run our simulation with following parameters :

Using Simbiology, we simulate all step at once and variate all parameters that matter to device and protocol design. Then, we observe the result to find a good estimation about our design and protocol.

Simulation result
We try to simulate whole system with different sample concentration using scan parameter. Logically, GFP production rate will increase along with increasing aflatoxin concentration in sample. The result of green protein synthesized versus time for each number of aflatoxin molecule on sample is showed in curve below (bottom line is no aflatoxin presence in device, aflatoxin molecule increasing 6,4e-10 mole every run) :

Assume that sample volume is the same, so increasing volume of medium will make aflatoxin concentration inside our device more dillute. More dillute the aflatoxin concentration, the green fluorescent protein concentration will be lower.
This curve can guide us to estimate the time needed for analysis. We simulate the first 3600 seconds of our device and we can see that fluorescent concentration for different aflatoxin concentration can be distinguished clearly after 2500 second (approximately 40 minute).

Further development
There is still a lot of task to do to improve our modelling. Finding better parameter value that really close to our project may be our first step. Rewrite and remove some redundant expression and rule may be our next step. But our big obstacle is learning the concept of modelling itself for the first time. Actually, we really amazed about how a software can save a lot of money and other resources in research process. It really bring an interesting discussion between engineer and science student to look at the same project with whole new perspective, and it really important to solve our world’s problem. This is really motivates us to share our modelling progress as much as we can through “Open Source Modelling” spirit. We believe that it will drive the synthetic biology development, especially for modelling and in silico experiment, faster by positive two-way discussion and constructive improvement between iGEM team all over the world.