Team:Tokyo Tech/Collaborations

1. Collaboration with Kanagawa Institute of Technology

1-1. Overview

Our team collaborated with iGEM 2016 team KAIT_Japan and other teams, as we were asked to help them with the modeling in an early stage. From iGEM 2016 team KAIT_Japan we were asked to help them create a mathematical model for their project.

1-2. Project

Team KAIT planned on increasing the production of Bacterial Cellulose (BC) produced by the bacteria A. xylinum. To do so, we have to take into account the cellulose synthesis pathway.

Fig. 8-1-1. Cellulose synthesis pathway of an Acetobacter

Based on the mechanisms of this pathway, iGEM 2016 team KAIT_Japan planned to increase the amount of cellulose production by diminishing the amount of G6PDH and PGI enzymes by the antisense method.

1-3. Mathematical Model

Cellulose is produced basically by a series of enzymatic reactions, so in order to create a mathematical model for this project, we have to take into account the principal reactions taking place in this production. By doing this we obtain the following equations.

$$ \displaystyle \frac{d[Glc]}{dt} = - \frac{V_{max_1}[Glc]}{K_{m_1} + [Glc]} $$

$$ \displaystyle \frac{d[Frc]}{dt} = - \frac{V_{max_5}[Frc]}{K_{m_5} + [Frc]} - \frac{V_{max_6}[Frc]}{K_{m_6} + [Frc]} $$

$$ \displaystyle \frac{d[G6P]}{dt} = - \frac{V_{max_1}[Glc]}{K_{m_1} + [Glc]} - \frac{V_{max_2}[G6P]}{K_{m_2} + [G6P]} - \frac{V_{f_3} \frac{[G6P]}{K_{s_3}} - V_{s_3} \frac{[F6P]}{K_{P_3}}}{1 + \frac{[G6P]}{K_{s_3}} + \frac{[F6P]}{K_{P_3}}} - \frac{V_{max_4}[G6P]}{K_{m_4} + [G6P]} $$

$$ \displaystyle \frac{d[F6P]}{dt} = \frac{V_{max_5} [Frc]}{K_{m_5} + [Frc]} + \frac{V_{max_8} [FDP]}{K_{m_8} + [FDP]} + \frac{V_{f_3} \frac{[G6P]}{K_{s_3} - V_{s_3} \frac{[F6P]}{K_{P_3}}}}{1 + \frac{[G6P]}{K_{s_3}} + \frac{[F6P]}{K_{P_3}}} $$

$$ \displaystyle \frac{[F1P]}{dt} = \frac{V_{max_6}[Frc]}{K_{m_6} + [Frc]} - \frac{V_{max_7} [F1P]}{K_{m_7} + [F1P]} $$

$$ \displaystyle \frac{d[FDP]}{dt} = \frac{V_{max_7} [F1P]}{K_{m_7} + [F1P]} - \frac{V_{max_8} [FDP]}{K_{m_8} + [FDP]} $$

$$ \displaystyle \frac{d[PGA]}{dt} = \frac{V_{max_2} [G6P]}{K_{m_2} + [G6P]} - \frac{V_{max_{11}}[PGA]}{K_{m_{11}} + [PGA]} $$

$$ \displaystyle \frac{d[G1P]}{dt} = \frac{V_{max_4} [G6P]}{K_{m_4} + [G6P]} - \frac{V_{max_9} [G1P]}{K_{m_9} + [G1P]} $$

$$ \frac{[UDP - Glc]}{dt} = \frac{V_{max_9}[G1P]}{K_{m_9} + [G1P]} - \frac{V_{max_{10}}[UDP-Glc]}{K_{m_{10}} + [UDP-Glc]} $$

$$ \frac{d[Cell]}{dt} = \frac{V_{max_{10}}[UDP-Glc]}{K_{m_{10}} + [UDP - Glc]} $$

Where each equation represents the concentration of each molecule. \( V_{max_n} \) and \( K_{m_n} \) represent the maximum velocity and the Michaelis constant of reaction respectively. In regards of the concentration of G6P and F6P, we had to consider the reversibility of the reaction.

However in this case, since it was considered to only use glucose and not fructose, we can simplify the equations to the following ones.

$$ \frac{d[Glc]}{dt} = - \frac{V_{max_1} [Glc]}{K_{m_1} + [Glc]} $$

$$ \displaystyle \frac{d[G6P]}{dt} = - \frac{V_{max_1}[Glc]}{K_{m_1} + [Glc]} - \frac{V_{max_2}[G6P]}{K_{m_2} + [G6P]} - \frac{V_{f_3} \frac{[G6P]}{K_{s_3}} - V_{s_3} \frac{[F6P]}{K_{P_3}}}{1 + \frac{[G6P]}{K_{s_3}} + \frac{[F6P]}{K_{P_3}}} - \frac{V_{max_4}[G6P]}{K_{m_4} + [G6P]} $$

$$ \frac{d[F6P]}{dt} = \frac{V_{f_3} \frac{[G6P]}{K_{s_3}}}{ 1 + \frac{[G6P]}{K_{s_3}} + \frac{[F6P]}{K_{P_3}}} $$

$$ \frac{d[PGA]}{dt} = \frac{V_{max_2} [G6P]}{K_{m_2} + [G6P]} $$

$$ \frac{d[G1P]}{dt} = \frac{V_{max_4} [G6P]}{K_{m_4} + [G6P]} - \frac{V_{max_9} [G1P]}{K_{m_9} + [G1P]} $$

$$ \frac{d[UDP- Glc]}{dt} = \frac{V_{max_{9}} [G1P]}{K_{m_{9}} + [G1P]} - \frac{V_{max_{10}} [UDP-Glc]}{K_{m_{10}} + [UDP-Glc]} $$

$$ \frac{d[Cell]}{dt} = \frac{V_{max_{10}} [UDP-Glc]}{K_{m_{10}} + [UDP-Glc]} $$

1-4. Antisense Method

The antisense method consists in inhibiting the production of certain proteins by using an antisense RNA that is perfectly complementary to the target nucleotide sequence, thus preventing its transcription.

In this case we are using the antisense method to prevent the production of the enzymes G6PD and PGI so by representing the binding of the antisense mRNA to the nucleotide sequence with a Hill equation we got the following equations.

$$ \frac{d[G6P]}{dt} = \frac{V_{max_1} [Glc]}{K_{m_1} + [Glc]} - \left(1 - \frac{\alpha_1[mRNA_1]^{n_1}}{K_1^{n_1} + [mRNA_1]^{n_1}} \right) * \frac{V_{max_2}[G6P]}{K_{m_2} + [G6P]} \\ - \left(1 - \frac{\alpha_2[mRNA_2]^{n_2}}{K_2^{n_2} + [mRNA_2]^{n_2}} \right) * \frac{V_{f_3} \frac{[G6P]}{K_{s_3}} - V_{s_3} \frac{[F6P]}{K_{P_3}}}{1 + \frac{[G6P]}{K_{s_3}} + \frac{[F6P]}{K_{P_3}}} - \frac{V_{max_4}[G6P]}{K_{m_4} + [G6P]} $$

$$ \frac{d[F6P]}{dt} = \left( 1 - \frac{alpha_2[mRNA_2]^{n_2}}{K_2^{n_2} + [mRNA_2]^{n_2}} \right) * \frac{V_{f_3} \frac{[G6P]}{K_{s_3}} - V_{s_3} \frac{[F6P]}{K_{P_3}}}{1 + \frac{[G6P]}{K_{s_3}} + \frac{[F6P]}{K_{P_3}}} $$

$$ \frac{[PGA]}{dt} = \left(1 - \frac{\alpha_1[mRNA_1]^{n_1}}{K_1^{n_1} + [mRNA_1]^{n_1}} \right) * \frac{V_{max_2}[G6P]}{K_{m_2} + [G6P]} $$

Where \( \alpha_{n} \), \( K_{n} \) and \( n_{n} \) are constants from the Hill equation, And the concentration of the mRNA depend on the conditions of the experiment.

1-5. Results

Applying this mathematical model we got the following graphs.

(a) (b) (c) (d) (e)

Fig. 8-1-2. (a) Concentrations without applying the antisense method, (b) Concentration while inhibiting G6PD enzyme, (c) Concentrations inhibiting PGI enzyme, (d) Concentrations inhibiting both G6PD and PGI enzymes, (e) Concentrations strongly inhibiting both enzymes

We can see that the more we inhibit the enzymes G6PD and PGI, the production of BC increases; so we can assume this model is correct. However, we cannot say it is the most appropriate to our case since it has not been corroborated with the experiments. We managed, though, to create the basis for a future more precise model.



Fig.8-1-3 logo of KAIT_Japan

2. A workshop of modeling

On August 16th, we hosted a workshop of dry teams. The participating universities were Gifu University, Tokyo University of Agriculture and Technology, University of Tokyo and Kanazawa Institute of Technology. The iGEM team Tokyo_Tech and the iGEM team UT-Tokyo taught modeling methods to the other iGEM teams present. We exchanged our ideas, and thereby we gained new knowledge of modeling.


Fig.8-1-4 logo of UT-Tokyo(left), Tokyo-NoKoGen(center),iGEM Gifu(right)

3. Helping a New iGEM High School Team

We visited The American School in Japan on September 14th and gave a modeling lecture. We explained our project's overview and taught modeling methods. We also talked about what iGEM is because the American School is a new iGEM team. The iGEM Tokyo Tech team had collaborated with many universities so far. This visit enabled us to collaborate with a high school.


Fig.8-1-5 logo of The American School in Japan

4. Developing an application

4-1. Abstract

We developed an Android application based on the suggestion from iGEM 2016 team UT-Tokyo of turning E. coli cultivation and genetic modification into an application so that more people can know synthetic biology.

4-2. Explanation of the Application

When a player taps the main screen, E. coli in a medium increases. Additionally, the more E. coli increases, the more experience points a player gains, which increases the player’s level. Leveling up also gives the player access to gene ligation techniques.

This application is distributed on Google Play. Here is the URL.

At present, players can only increase the number of E. coli. However, in the future, we aim to upgrade the application so that players can do genetic modification in the application.

5. May Festival

The Japanese iGEM teams took part in the school festival at the University of Tokyo. Our team shared ideas and gave each other feedback. We introduced iGEM and synthetic biology to the public.

See the Human Practice page for further information.

Participants

iGEM 2016 team Gifu
https://2016.igem.org/Team:Gifu

iGEM 2016 team KAIT_Japan
https://2016.igem.org/Team:KAIT_Japan

iGEM 2016 team Kyoto
https://2016.igem.org/Team:Kyoto_Japan

iGEM 2016 team UT-Tokyo
https://2016.igem.org/Team:UT-Tokyo

team Tokyo-NoKoGen
http://tokyonokogen.wixsite.com/tokyo-noko-gen

6. Writing International iGEM Protocols with iGEM 2016 team METU HS Ankara

iGEM 2016 team METU HS Ankara asked our team to write International iGEM Protocols as a collaboration this year, and we decided to translate them into Japanese.
Since they are basic protocols, we can’t make any successful experiments without them . We are sure that their activities will be able to help other iGEM teams. We are so grateful to be able to help in such activities.

    

Fig.8-1-6 team METU HS Ankara's member   Fig.8-1-7 logo of team METU HS Ankara

7. Published on iGEM news of iGEM EPFL

This year, our team was introduced on the page of iGEM EPFL, “iGEMnews”, where it is written about other teams or their projects.
We appreciate having such an opportunity because there are only a few chances for us to let people know about our team.




Fig.8-1-4 logo of iGEM.TODAY
> iGEM EPFL's iGEM News link!!<

8. Meetup at Boston University

On October 26th, our team is going to host a meetup in Boston University. We are looking forward to sharing ideas with other iGEM teams. Teams will have the opportunity to present their projects and exchange their ideas in details with other iGEM teams and faculty advisors right before the Giant Jamboree.

see Community/Meetups page