Team:UGA-Georgia/Modeling

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Metabolic Modeling of Methanococcus maripaludis

Previously…

Our 2014 UGA-Georgia iGEM team mapped out the isoprenoid biosynthesis pathway for Methanococcus maripaludis, as we can take of this pathway’s production of high-carbon compounds. Additionally we adopted and adapted the M. maripaludis S2 metabolic model (iMM518) to contain exchange and formation reactions for geraniol synthase (Table 1). By incorporating the geraniol synthase gene, were able to calculate the rate of production of geraniol in a M. maripaludis cell using flux balance analysis.

Table 1. The geraniol synthase metabolites and reactions added to the original M. maripaludis metabolic model (iMM518) from BioModels Database.

This year, our 2015 UGA-Georgia iGEM team used our modified model to observe the rate of geraniol production after altering specific growth substrates, carbon dioxide (CO₂) and ammonium (NH₄). Shown below is the progression of flux balance analyses.

Target Growth Substrates:

Carbon source: CO₂

Nitrogen Source: NH₄

These two common growth substrates for M. maripaludis were chosen as our constraints, as they can be easily manipulated for in vivo experiments.

Target Products:

Biomass production

Geraniol production

The production of biomass for cells is essential and is significantly from isoprenoids. Geraniol is an isoprenoid derivative, so when targeting geraniol, we must also consider a reasonable biomass production rate.

Preliminary Observation:

Changes in CO₂/NH₄ ratio result in influenced biomass and geraniol production.

Exploring the Evidence:

Upon observing the relationship between the CO₂/NH₄ ratio and the production of our target products, biomass and geraniol, we began to specifically explore the ratio of these substrates. We explored two different options, (1) limiting nitrogen and (2) excess carbon.

1. Reducing NH₄ + maintaining CO₂ and observing change in geraniol production: (with same specific growth rate*)

1. Increasing CO₂ + maintaining NH₄ and observing change in geraniol production (with corresponding change in specific growth rate*)

2. Increasing CO₂ + maintaining NH₄ and observing change in geraniol production (with same specific growth rate*)

Results:

1. Although CO₂/NH₄ ratio is increased by decreasing NH₄, there was no change in geraniol production (no change in specific growth rate* as well)
2. The increase in CO₂/NH₄ by increasing CO₂
1. with corresponding increase in specific growth rate* resulted in decreased geraniol production
2. with same specific growth rate* resulted in increased geraniol production.

*The constraints for specific growth rate were obtained from simulating the original iMM518 model to represent the specific growth rate of wild-type M. maripaludis.

In addition to metabolic modeling, we used UTR Designer to determine if their model for predicting prokaryotic translational efficiency worked for M. maripaludis. More information about UTR designer can be found on our Software page.

Legend: Correlation between predicted and experimental mCherry expression levels for different RBS mutants. Delta G values for mRNA folding were predicted by UTR designer, and the lower the values are, the more efficient the translation usually is for Bacteria. However, as shown in this graph, the delta G values are not correlated at all with our experimental results obtained from M. maripaludis, an archaeon. Therefore, further studies are needed to validate a prediction model for archaeal RBS.