Team:UT-Tokyo-Software/Project/GeneNetworkGame

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UT-Tokyo-Software
Gene Network Game

Overview

Gene Network Game is an educational puzzle game. Players aim to create proper gene networks from given promoters and genes. Through this game, the player can learn basic knowledge of gene networks and can be helpful when trying to understand other team's constructs and eventually to create their own construct. This game is also usable as a tutorial for modeling & simulation.

  At the beginning of the stage, the player has some promoters and genes in his inventory. Using this inventory, he/she aims at creating a network capable of reaching a certain output protein concentration (Left). A stage is completed when the player aligns genes in the correct order and the outputs level is achieved (Right). Completing successive stages, the player will learn ideas from "What are promoters and genes?" to "Genetic oscillators and toggle switches".

 

  The game is also implemented with a stage editor. In the editor, you can assign promoters and genes, adjust parameters (copy rate, degradiation rate etc.) and create your own stage. The editor is designed so that you not only to enjoy your own stage but it can also be used as a simple modeling tool which enables you to obtain preliminary knowledge about conducting modeling and creating simulations. It will be a first step towards using more technical modelig software such as Matlab.


Background

Planning Biobrick construction is perhaps the most important iGEM activities. To do this, participants have to be able to understand constructs designed by other teams and go on to design their own. This includes knowledge on what will happen when a specific BioBrick promoter is connected to a gene, and further when such complex parts are combined.

In addition, in order to reach a full understanding of how a developed construct may behave, we believe it is important for one to be able to create an image of how protein concentrations may evolve in time. We have found that this is often especially difficult for students getting started with iGEM, at which time many seem to have a fuzzy image of how protein production could be 'on' or 'off.' As the project proceeds, students may need to assess the feasibility of the constructs they intend to create (for have already created). Many teams do not get around to doing this or in some cases attempt this at a stage when construction has already ended and it is too late to turn back. If you open a textbook on systems biology to learn the dynamics, students may find themselves put off by the mathematical knowledge required or the volume of the text, often unnecessary for a simple iGEM project. So it would be helpful if there is a tutorial from which beginners can learn sufficient information about gene network dynamics for an iGEM project. Such aid should result in more teams being able to predict and to test the behavior of their constructs, leading to improvement of the quality of the parts submitted.

We have also created a tutorial for the purpose of helping users understanding what modeling is and what sort of information can be gained from it, as well as creating their own model. We have noticed that many iGEM participants want to make models for their project, and also that iGEM HQ is recommending modeling. However, large number of students do not even know what modeling is, and tend to leave it up to members who have technical skills, if present. We wanted to make a tutorial for such people to learn what can be achieved by modeling. This basic program will hopefully be a sufficient stepping stone before beginners move on to more advance software such as Matlab.


Result

    With Gene Network Game, beginners
  • learn to be able to understand functions and the dynamics of expression from their constructs.
  • -> Beginners will understand other teams' projects smoothly.
  • are trained to design their own constructs.
  • -> They can begin considering their projects efficiently.
  • can learn basic skills to conduct modeling.
  • -> Team members can work together in modeling.

Future

  • Improving stage editor
    • Add Quorum sensing
    • Edit and register stages via the internet
  • New past project based stages
  • Improving modeling tools
    • Add pattern of usable chemical reactions
    • Add Parameter database of actual promoters and genes

Method

System

  • Programming language: processing
  • GUI library: ControlP5
  • Developing environment: eclipse

Method of simulation

  • Regulation model by transcription factor: Hill equation
  • Ordinary differential equation solver: 4th order Runge-Kutta method

Demo