This years iGEM team has undertaken two separate modeling projects to help us carry out and understand our project.

Contents 1 Metabolic Modeling 1.1 Why Metabolic Modeling 1.2 The Model 1.3 The Questions/Answers 2 Homology Modeling 2.1 Optimization

Metabolic Modeling

Why Metabolic Modeling

The majority of degredation pathways for oilsands contaminants convert various organic compounds into catechol. Our project this year in the incorporation of the gene xylE into E. coli. The xylE gene encodes catechol-2,3,-dioxygenase, which converts catechol into 2-hydroxymuconate semialdehyde. This semialdehyde can be metabilized by E. coli by means of the glycolysis / Krebbs cycle.

However, little is known about how the effect of increased flux of these metabolites into cell (such as intermediate concentrations and metabolite fluxes). Thus to asses the viability of specialized bioremediation and metabolic engineering it is very important to understand what is happening within the cell. By using computer modeling of metabolism pathways and using kintetic data, we can asses the robustness of the system and what we can do to improve the efficiency of the system.

The Model

The proposed model will include the entire glycolysis / Krebbs cycle and the entry of catecol and 2-hydroxymuconate semialdehyde into it alongside normal metabolites. Databases (such as BRENDA) have detailed all the pathways and should have most if not all the kinetic parameters required.

The Questions/Answers

1) What is the maximal rate of catechol degradation by the cell by this pathway?

2) What are the rate limiting steps and what can be done to increase throughput (i.e. the effect of increasing the expression of one or two proteins)?

3) At excessively high levels of catechol, what is the effect on the system (robustness of the system)?

These a very important questions as many iGEM projects use catechol as their entry point into bacterial metabolism. To enable metabolic engineering an understanding of what is occurring within the cell is crucial.

Homology Modeling

Optimization