OVERVIEW

Modelling was heavily utilised to obtain a better understanding of our systems, as well as, shaping our experimental designs which helped us save unnecessary wastage of resources and time. We constructed models that allowed us to achieve the following:

1. Preliminary study of our intended biochemical pathway
2. Optimal genetic circuit design
3. Proof that optogenetics can work in our systems and improve upon existing inducible/repressible light systems
4. Simulation and optimisation of our entire experimental process

Our MATLAB scripts can be found here.

Our team started with the intention to produce dyes consisting of the primary colours, red, yellow and blue, that can be easily mixed to create a plethora of colours for the textile industry. However, we have decided to produce namely, Chrysanthemin (red) and Luteolin (yellow) instead. This decision was due in part to our interview with Mr Holger Schlaefke (link to our interview here), Global Marketing Manager of DyStar Pte Ltd, that advised us to produce vibrant colours, and how numerous past iGEM teams have attempted to produce Indigo (a colour similar to blue).

PART 1: THE BIOCHEMICAL PATHWAY

Goal of model

Thus, Wet Lab needs to verify the feasibility of producing these two flavone compounds in E.Coli from the starting substrate, Naringenin, by considering only the biochemical reactions using mathematical modelling in-silico (refer to the biochemical pathway in Fig 1.). In addition to this, we explore how enzyme concentrations affect our system in hopes that it may aid us in our experimental design.

Fig. 1 Biochemical Pathway from starting substrate Naringenin

Considerations

Since there was a competing biochemical pathway which produces Callistephin – an undesired product – for the production pathway of Chrysanthemin, it had to be considered in our model as well.

Methods

Using the ODE15s solver on MATLAB, we solved for the following ordinary differential equations (ODEs) with respect to time. The following parameters were obtained from literature1 and the ODEs were derived from the mass balancing of the Michaelis-Menten equation2. Initial enzyme concentrations were set to high (in excess) amounts to create a simplified model for our initial study of our biochemical system.

The chemical and differential equations for the model are shown below:

Therefore, in order to obtain the maximal velocity, V_m, of the enzyme acting on a particular substrate, the concentration of the enzyme is multiplied by its turnover rate, k_cat.

Table 1. Parameters for preliminary study model

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