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Modelling
Overview
In iGEM history, many teams including Tokyo_Tech tried information processing between bacteria. This year we tried to establish an artificial inter-kingdom communication between human cell and bacteria then enable their co-culture. We call this new artificial human-bacteria co-culture living system “Coli Sapiens.” Many factors like growth rate of human cells and bacterial cells are quite different and it is difficult to consider the all parameters to the model. In complex systems, only essential parameters were selected and an abstract model was designed. To evaluate this model, drylab comprehensively simulated the property of the system using data from the experiments. As a result, our simulation contributed to the suggestion of part improvement to wetlab. This part improvement increased the feasibility of the model and it indicated that concentration of E. coli could be controlled by human cells and the condition for co-culture. Thus, we succeeded in engineering a new living system of co-existence between human cells and E. coli. This could be a progress for iGEM.
![](https://static.igem.org/mediawiki/2017/3/35/Modeling_full10.png)
Simulation
We developed our models with two main goals. 1. In wetlab, a lot of noise will affect to the results because co-culture between human cells and E. coli is very complicated. Constructing the model containing only essential mechanism and integrating the data from wetlab, we improve the genetic circuits and engineer the model which enables co-culture. 2. Calculate the condition of co-existence between the human cells and E. coli changing the value of variable parameters.
2-1 Introduction
In our project, we use two signaling molecules, 3OC8HSL and isopentenyl adenine, to establish an artificial inter-kingdom communication between human cells and bacteria and MazF to control cell growth of E. coli. The details are described below.
Signaling Molecules
- 3OC8HSL (C8)
Quorum Sensing is cell-to-cell communication system used by variety of microorganism. Signal molecular used in Quorum sensing has variety of chemical structure. LuxI is synthesis gene of 3OC6HSL and TraI is synthesis gene of 3OC8HSL. Chemical structures of these molecules are shown in Fig. 1.
![](https://static.igem.org/mediawiki/2017/f/fd/T--TokyoTech--TraI1.jpg)
LuxR gene express intracellular LuxR receptor. Signal molecular and this receptor form complex. This complex interacts with responsive promoters, Plux and regulates transcription of downstream genes. The concentration of signal molecular increase with cell density. By using this system, microorganism assess their local density and regulates gene expression.
In previous study, a novel, inducible, eukaryotic gene expression system based on the quorum-sensing transcription factor TraR was developed (Read TraI Assay page). In this system, expression of downstream genes of CMV minimal promoter is induced in the presence of signal molecular 3OC8HSL. Therefore, we chose 3OC8HSL as a signal molecule and tried to make E.coli to produce 3OC8HSL.
- Isopentenyl adenine (iP)
Isopentenyl adenine (iP) is a kind of cytokinin and we use it as a signal molecule from human cells to E. coli in the inter-kingdom communication. Cytokinins are the signaling molecules (or Phytohormones) that plants produce and play important roles in cell growth and differentiation. In the case of Arabidopsis thaliana, extracellular iP is received by a transmembrane receptor, AHK4. AHK4 has a histidine kinase activity, and binding of iP to AHK4 triggers auto-phosphorylation of AHK4 and the following histidine-to-aspartate phosphorelay. As a consequence, transcription from target genes is induced and/or repressed so that physiological states of plants are changed. The histidine kinase activity of AHK4 has shown to be activated depending on iP even in E. coli cells (Suzuki et al. 2001, Lukáš Spíchal et al. 2004). This fact encouraged us to use iP as a signaling molecule in our project (See AHK4 Assay page).
Growth Inhibition Molecule
- Toxin-antitoxin system
A toxin-antitoxin system is composed of two or more cognate genes that encode toxins and antitoxins. Toxins are proteins, whereas antitoxins are either proteins or non-coding RNAs. Many prokaryotes harbor toxin-antitoxin systems on the genomes, typically in multiple copies. Changes in the physiological conditions, such as stress conditions or viral infection trigger antitoxin degradation by cytosolic proteases. Unleashed toxin proteins impede or alter cellular processes including translation, cell division, DNA replication, ATP synthesis, mRNA stability, or cell wall synthesis and lead to dormancy. This dormant state probably enables bacteria to survive in unfavorable conditions. In general, toxin proteins are more stable than antitoxin proteins, but antitoxins are expressed at a higher level in cells.
- MazF
MazF is a toxin protein. MazF is a ribosome-independent endoribonuclease whose activity leads to bacterial growth arrest. MazF dimer cleaves mRNAs at ACA sequences.
2-2 Mathematical model
In order to simulate our gene circuits, we developed an ordinary differential equation model. The equations and parameters to simulate our genetic circuits are shown below.
![](https://static.igem.org/mediawiki/2017/e/e0/Modeling_parameter.png)
![](https://static.igem.org/mediawiki/2017/a/a0/Modeling1_v6_tokyotech.png)
![](https://static.igem.org/mediawiki/2017/4/46/Fomula1_v3.png)
![](https://static.igem.org/mediawiki/2017/e/eb/Modeling2_v2.png)
![](https://static.igem.org/mediawiki/2017/3/3f/Fomula2_v3.png)
![](https://static.igem.org/mediawiki/2017/9/91/Modeling3_v3.png)
![](https://static.igem.org/mediawiki/2017/3/3f/Fomula2_v3.png)
![](https://static.igem.org/mediawiki/2017/9/93/Modeling4_v4.png)
![](https://static.igem.org/mediawiki/2017/2/20/Fomula4_v3.png)
2-3 Analysis
We obtained the result that E. coli grow excessively because of the concentration of C8 was low and enough expression of MazF was not induced.
![](https://static.igem.org/mediawiki/2017/a/a1/T--TokyoTech--normal_model.png)
This result indicated that C8 synthetic quantity was needed to increase. Thus, we proposed improvement of traI coding C8 synthetic enzyme to wetlab. In wetlab, the C8 synthetic quantity was improved by introducing a single point mutation to traI (Read TraI Improvement page). Using this experiment data, the excessive E. coli growth was suppressed. We confirmed the desirable behavior of the whole system by modifying and improving a part.
![](https://static.igem.org/mediawiki/2017/5/5d/T--TokyoTech--improved_model.png)
2-4 Explore the condition of co-existence
We confirm that the human cell and the E. coli can co-exist in our model, but the condition to become co-existence is supposed to be severe. And that to clarify the condition will make a substantial contribution to application of our co-culture system. Therefore, we investigate the values of variable parameters in our model, flow(x axis, f in Fig. 9) and the concentration of human cells(y axis, u in Fig. 9), to co-exist. The result graph was shown in the below, Fig. 9. The yellow area means failure of co-existence due to excessive growth of E. coli. The purple are means that failure of co-existence due to E. coli extermination. The green area means that success of co-existence. When we apply the co-culture system (Read Project page), we can choose the best condition to satisfy co-existence for the application.
![](https://static.igem.org/mediawiki/2017/f/f4/T--TokyoTech--oveall.png)
Reference
[2] The protocol of β-Gal ELISA kit
[3] Optimal tuning of bacterial sensing potential, 2009 Anand Pai et al
[4] Cytokinin Oxidase and the Regulation of Cytokinin Degradation, Donald J. Armstrong
Hajime Fujita: All Rights Reserved