Team:Calgary/Notebook/Future Directions


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Future Directions


The protein expression detection kit is designed such that one can clone in their gene of interest (GOI) into the kit using a simple biobrick cloning method and the system will give a simple visual output that would indicate the point of protein expression that is failing. For example: if the output is red that indicates that the protein is misfolding in the periplasm, if there is green flouroscent protein expressed, it indicates that protein is misfolding in the cytoplasm.

This kit employs existing reporter coupling methods to make a compact kit which detects problems in one step. To take this kit a step further, the team will be working on adding more promoters in the system so that misfolding stress can be detected at different levels both high and low. This would allow the system to be more sensitive to different levels of protein folding stress. We also plan on including different coloured reporters to indicate which system got activated. For example: currently we are using GFP for the sigma32 system which detects cytoplasmic stress and RFP for the Cpx regulon which detects periplasmic stress. In the future, we can couple the Lol system which monitors outer membrane lipoprotein with YFP, the Ppi system which targets outer membrane Beta-barrels with CFP and so on. This allows the system to be more diverse and specific, because systems like Lol and Ppi have very specific target substrates.

Another interesting future direction with this project is building an auto-tuner with the stress detector. Literature has established that proteins at low levels fold properly, however at high levels, which are used during recombinant protein production, they misfold due to high protein concentration. The autotuner would be included in the current system to help control the level of protein expression such that if the protein misfolds, the stress promoter turns on which in turns represses the expression of the GOI until it does not misfolds or form inclusion bodies. This would essentially allow the cell to find its own optimal protein expression levels of a certain protein in order to optimize protein production.

auto tuner

Schematic of the auto-tuner 1. Constitutive production of the GOI using a TetR promoter. 2. Activation of Stress promoter due to overproduction of GOI and misfolding of GOI. 3. Production of Tet product and the repression of the TetR promoter as a result.


The modeling project currently consists of examining different parameters such as temperature, pH and hydrophobic content of a protein in order to generate a ratio of inclusion body compared to folded proteins. Future directions for the modeling project would be incorporate more variables. One of the interesting variables to include would be protein motifs such as protease domains. This approach would make the model more diverse because it would account for the fact that every protein is different. However, this would also be a generalization about certain stretches of amino acids and be further criticized by proteomics expert as it is too vague and might not always hold. Another interesting future direction would be to create software or a user interphase that is much easier to operate than MATLAB, where the parameters could be changed easily and the input that would be required would be pI (isoelectric point) of the protein and the amino acid sequence of the protein. This could contribute to a software entry for iGEM next year if the project is continued and successfully finished.

Currently, the model uses previously established models in order to contribute to the algorithm that generates the ratio. In the future, we would like to incorporate the use of Markov models which would account for the random chance of events happening and probabilities a lot better than the current algorithms that are being used.