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2A Viral Tag Modeling for Biosynthesis

        Building a 2A eukaryotic biochemical network can be hard, and these viral tags are not without a drawback. Previous research (Beekwilder 2014) has shown there was a decreased level of expression of enzymes downstream of the promoter. This can certainly affect the overall yield of the pathway, but we can certainly minimize this effect!

        We have designed a computation tool to combinatorically test all available rearrangements of your biochemical network and display the ideal ordering of your network to optimize reaction efficiency. The model utilizes the heavily studied kinetics of enzymes and implements their behavior in a differential equations model. This is nested within a permutation loop to test all possible orderings.

To prove how easy it is to use, we even redesigned three 2014 iGEM teams circuits for how they would be optimally arranged in eukaryotic 2A systems!

2014 Arizona State Pyruvate to Fatty Acid Ethyl Esters

Promoter -> pyruvate dehydrogenase (1st)-> Long-chain acyl-ACP reductase (2nd) -> Alcohol dehydrogenase (3rd) -> Long-chain-fatty-acid-CoA ligase EC (4th)

2014 BYU Denitrification

Promoter -> Nitrite reductase (1st) -> Nitrous-oxide reductase (2nd) -> Nitric Oxide reductase (3rd) >

2014UIUC caffeine degradation for dogs

Promoter -> 7-methylxanthine demethylase (1st)-> Methylxanthine N1-demethylase (2nd) -> Methylxanthine N1-demethylase (3rd) >

        To emphasize the portability of this tool, the system was designed in MATLAB and embedded in a graphical user interface (GUI). If you want to test this tool out or use it to optimize your own experiments, head on over to:

or contact:

Patrick V. Holec
University of Minnesota