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Engineering

Design, Process, and Innovation.

Engineering

Overview

The three main types of genetic circuits we have created are the "Detection unit", the "Secretion unit", and the "Amplification unit". First, our system just consists of MESA and a transcriptional system. However, the insight from Dry Lab, IHP, and consultation with our advisor have dramatically changed our project. Concretely, Human Practice told us the essentiality of speed to deal with CRS. Dry Lab showed the superiority of the Secretion unit over the transcriptional-based MESA system in terms of speed. Also, they questioned the amount of protease secreted by the Secretion unit and modeled its amplification. Also, we got recommendations from IHP about Amplification unit and the types of proteases that are useful for our system.

Overview_of_Our_Engineering_FlowFigure 0: Overview of Engineering Flow

For each of these units, we have been improving them efficiently by repeating the cycle of "Design"⇨"Build"⇨"Test"⇨"Learn."

However, this is not always the case, as we also changed the design through papers and dialogues ("Counsel") without experimentation, and changed the experimental method without changing the design itself based on the results of the experiments.

Engineering_Cycle_for_Our_ProjectFigure 1: Engineering Cycle for Our Project

As we proceeded with the experiments, the following flowchart was created in order to conduct the experiments efficiently. Of course, not all experiments could be performed. However, this flowchart will be useful for future experiments after the project as iGEM.

Flowchart_on_the_Construction_of_ExperimentsFigure 2: Flowchart on The Construction of Experiments(The figures in this chart were obtained from 1)

Detection Unit

Cycle 1

Cycle1.1

Enhancements in MESA Cycle: Addressing Speed Requirements with a New Unit Proposal

In MESA_cycle 1 & 1.1, MESA which releases TF (tTA) was proposed and endeavored to be realized. However, there were concerns about its adequacy for meeting the speed requirements to deal with CRS. To address this, a new unit was proposed, involving the secretion of POI without transcription and translation processes.

This unit was modeled, and feedback from the Dry Lab was utilized to enhance

If you want to see the order as in the experiment, go to Secretion Cycle 1

Cycle 2

Counsel

Through discussions with the advisor, it was suggested that the protein may not be able to penetrate and exist on the membrane without the signaling peptide.

Cycle 3

Cycle 4

Secretion Unit

Counsel

Human Practice (Dr. Kagoya) suggested that the transcription-based system is too slow to deal with CRS. This was proven also by the Dry Lab. See Human Practice Page for more information. See Modeling Page for more information on Secretion unit.

Cycle 1

Counsel

Dry Lab suggested that the Secretion unit alone may not be sufficient for the secretion of proteases, and we compared the expression levels of target substances with and without the Amplification unit using the ODE model to confirm the superiority of the Amplification unit, and also confirmed that the absolute expression level was sufficient. To see this, go to Amplification

Amplification Unit

Counsel

In the course of our project, the fear that the amount of secreted protease by MESA is not enough to realize a swift response. Here, there is the need for the Amplification unit, enhancing system performance by amplifying the output from MESA and ensuring an ample input supply to Secretion. Through Human Practice and Dry Lab work, it was demonstrated that the amplification module successfully amplified input as expected, and it was also shown that the amplification factor could be adjusted by selecting the appropriate protease.

Amp

Cycle 1

References

  1. Praznik, A., Fink, T., Franko, N., Lonzarić, J., Benčina, M., Jerala, N., Plaper, T., Roškar, S., & Jerala, R. (2022). Regulation of protein secretion through chemical regulation of endoplasmic reticulum retention signal cleavage. Nature Communications, 13(1), 1323-1323. https://doi.org/10.1038/s41467-022-28971-9 ↩ ↩2

  2. Munich iGEM Team. (n.d.). Approach 2: Proximity Activation, Description. SpecifiCar. https://2022.igem.wiki/munich/description ↩

  3. Daringer, N. M., Dudek, R. M., Schwarz, K. A., & Leonard, J. N. (2014). Modular extracellular sensor architecture for engineering mammalian cell-based devices. ACS Synthetic Biology, 3(12), 892-902. https://doi.org/10.1021/sb400128g ↩ ↩2

  4. Schwarz, K. A., Daringer, N. M., Dolberg, T. B., & Leonard, J. N. (2017). Rewiring human cellular input-output using modular extracellular sensors. Nature Chemical Biology, 13(2), 202-209. https://doi.org/10.1038/NCHEMBIO.2253 ↩ ↩2

  5. Stein, V., & Alexandrov, K. (2014). Protease-based synthetic sensing and signal amplification. Proceedings of the National Academy of Sciences, 111(45), 15934-15939. https://doi.org/10.1073/pnas.1405220111 ↩

  6. Goryashchenko, A. S., Khrenova, M. G., & Savitsky, A. P. (2018). Detection of protease activity by fluorescent protein FRET sensors: from computer simulation to live cells. Methods and applications in fluorescence, 6(2), 022001. ↩